**ATTENTION, PREDICTIONS AND EXPECTATIONS, AND THEIR VIOLATION: ATTENTIONAL CONTROL IN THE HUMAN BRAIN**

**Topic Editors Simone Vossel, Joy J. Geng and Karl J. Friston**

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**ISSN** 1664-8714 **ISBN** 978-2-88919-367-7 **DOI** 10.3389/978-2-88919-367-7

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# **ATTENTION, PREDICTIONS AND EXPECTATIONS, AND THEIR VIOLATION: ATTENTIONAL CONTROL IN THE HUMAN BRAIN**

Topic Editors:

**Simone Vossel,** University College London, United Kingdom & Research Centre Jülich, Germany **Joy J. Geng,** University of California Davis, USA **Karl J. Friston,** University College London, United Kingdom

Rethinking the role of the rTPJ in attention and social cognition in light of the opposing domains hypothesis: findings from an ALE-based meta-analysis and resting-state functional connectivity; Benjamin Kubit and Anthony Ian Jack; doi: 10.3389/fnhum.2013.00323

# Table of Contents

Jocelyn L. Sy, James C. Elliott and Barry Giesbrecht

*133 Paired-Pulse Transcranial Magnetic Stimulation Reveals Probability-Dependent Changes in Functional Connectivity Between Right Inferior Frontal Cortex and Primary Motor Cortex During Go/No-Go Performance*

A. Dilene van Campen, Franz-Xaver Neubert, Wery P. M. Van Den Wildenberg, K. Richard Ridderinkhof and Rogier B. Mars

## Attention, predictions and expectations, and their violation: attentional control in the human brain

## *Simone Vossel 1,2\*, Joy J. Geng3 and Karl J. Friston1*

*1 Wellcome Trust Centre for Neuroimaging, University College London, London, UK*

*2 Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany*

*3 Department of Psychology, Center for Mind and Brain, University of California Davis, Davis, USA*

*\*Correspondence<EMAIL_ADDRESS>
#### *Edited and reviewed by:*

*John J. Foxe, Albert Einstein College of Medicine, USA*

**Keywords: attentional networks, predictions, trial history, reward, emotions, neuroimaging, TMS, EEG**

In the complex scenes of everyday life, our brains must select from among many competing inputs for perceptual synthesis so that only the most relevant are fully processed and irrelevant (distracting) information is suppressed. At the same time, we must remain responsive to salient events outside our current focus of attention—and balancing these two processing modes is a fundamental task our brain constantly needs to solve.

This Research Topic examines how attentional control is guided by sensory predictions, prior knowledge, reward, task sets, and emotional factors. Moreover, the neural signatures of these mechanisms are investigated in Original Research Articles or summarized in Review, Perspective and Hypothesis and Theory Articles. Findings from a wide range of state-of-the-art complementary neuroscientific methods such as fMRI, M/EEG, TMS, and ALE-based meta-analysis are presented.

The collection of papers of this Research Topic provides an overview over our current knowledge in the field and also presents novel stimulating hypotheses on how attention is controlled in the human brain. It moreover bridges the gap to other disciplines such as decision-making and social and affective neuroscience.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 15 May 2014; accepted: 17 June 2014; published online: 02 July 2014. Citation: Vossel S, Geng JJ and Friston KJ (2014) Attention, predictions and expectations, and their violation: attentional control in the human brain. Front. Hum. Neurosci. 8:490. doi: 10.3389/fnhum.2014.00490*

*This article was submitted to the journal Frontiers in Human Neuroscience. Copyright © 2014 Vossel, Geng and Friston. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## Attention and predictions: control of spatial attention beyond the endogenous-exogenous dichotomy

## *Emiliano Macaluso1\* and Fabrizio Doricchi 1,2*

*1 Neuroimaging Laboratory, Fondazione Santa Lucia, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy 2 Dipartimento di Psicologia, Università degli Studi "La Sapienza", Rome, Italy*

#### *Edited by:*

*Simone Vossel, University College London, UK*

#### *Reviewed by:*

*Ralph Weidner, Forschungszentrum Jülich, Germany Klaartje Heinen, Institute of Cognitive Neuroscience, UK*

#### *\*Correspondence:*

*Emiliano Macaluso, Neuroimaging Laboratory, Fondazione Santa Lucia, Via Ardeatina 306 00179, Rome, Italy e-mail<EMAIL_ADDRESS>
The mechanisms of attention control have been extensively studied with a variety of methodologies in animals and in humans. Human studies using non-invasive imaging techniques highlighted a remarkable difference between the pattern of responses in dorsal fronto-parietal regions vs. ventral fronto-parietal (vFP) regions, primarily lateralized to the right hemisphere. Initially, this distinction at the neuro-physiological level has been related to the distinction between cognitive processes associated with strategic/endogenous vs. stimulus-driven/exogenous of attention control. Nonetheless, quite soon it has become evident that, in almost any situation, attention control entails a complex combination of factors related to both the current sensory input and endogenous aspects associated with the experimental context. Here, we review several of these aspects first discussing the joint contribution of endogenous and stimulus-driven factors during spatial orienting in complex environments and, then, turning to the role of expectations and predictions in spatial re-orienting. We emphasize that strategic factors play a pivotal role for the activation of the ventral system during stimulus-driven control, and that the dorsal system makes use of stimulus-driven signals for top-down control. We conclude that both the dorsal and the vFP networks integrate endogenous and exogenous signals during spatial attention control and that future investigations should manipulate both these factors concurrently, so as to reveal to full extent of these interactions.

**Keywords: endogenous, exogenous, salience, prediction, parietal cortex**

## **INTRODUCTION**

The ability to suitably allocate processing resources is fundamental for the efficient processing of incoming sensory signals and for the generation of appropriate behavior in complex environments. The brain continuously receives a large amount of sensory signals that cannot be fully processed. Attention selection allows preferential processing of some signals and filtering out of other inputs. What are the constraints that govern this selection process, thus determining what signals should gain access to in-depth processing?

Traditionally, attention research has distinguished between two types of mechanisms that contribute to the selection process. On one hand there are endogenous, top-down factors that primarily relate to the subject's "internal" goals and intentions. On the other hand, there are exogenous, bottom-up effects that primarily relate to the characteristics "external" stimuli. Endogenous factors are associated with top-down voluntary control, while exogenous factors are associated with stimulus-driven control that is thought to take place automatically. The distinction between these two types of control can be rather intuitive: when searching for a friend in a crowd, we will voluntary shift attention from one face to another until the external input (i.e., what we see) matches our internal knowledge about the physical appearance of our friend. By contrast, in a crowd of people all dressed with dark cloths, we will quickly notice a person dressed in bright red, who will catch attention automatically. Experimentally, the impact of endogenous and exogenous factors for selection have been studied with a variety of paradigms. Somewhat related to the "real-life" examples above, visual search tasks can be used to highlight endogenous vs. exogenous factors for the allocation of spatial attention. Search tasks including a target-item "similar" to the distracters (e.g., look for a vertical red bar presented among vertical green bars and tilted red bars) will be slow and inefficient. The search time will depend on the number of competing distracters thus indicating that search proceeds serially with attention shifted voluntarily from one item to another item. By contrast, when the target item stands out (e.g., look for a red bar presented among green bars) the search is rapid and efficient, with the red target capturing attention in an automatic manner irrespective of the number of distracters.

Another way to investigate endogenous and exogenous control of spatial attention includes using variants of the Posner spatial cueing paradigm (Posner, 1980). Rather than presenting distracters during the search of a target, the target is presented in isolation but it is preceded by a spatial cue. In the endogenous version of the task, the cue is presented centrally (e.g., a leftward or rightward pointing arrow) and it predicts the target location on most of the trials (e.g., 75–80% "valid" trials). In the remaining trials the cue is "invalid" (25–20%) and the target is presented at a different position compared to the location initially signaled by the cue. Behaviorally, targets proceeded by a valid cue are detected/discriminated more rapidly/accurately than targets proceeded by invalid cues. The reason for this is that subjects can strategically use the central cue to voluntarily shift attention towards the cued location. This leads to enhanced processing when the target is presented there (valid trials), while additional re-orienting operations are needed when the target is presented somewhere else (invalid trials). In the exogenous version of this paradigm, the cue is presented peripherically (e.g., a box is flashed in the left or right visual hemifield), again followed by a target either at the same (valid) or different (invalid) location. Unlike the endogenous version, now the cue does not predict the target location (i.e., 1:1 ratio of valid and invalid trials) and the subject has no strategic reason to use the cue to voluntarily direct attention. Nonetheless, the detection of the target is faster and more accurate at the cued/valid location compared with the opposite/invalid location, provided that the interval between cue and target is short (e.g., Klein, 2000). In this case, the interpretation is that the sudden appearance of the box on one side attracts attention automatically, triggering exogenous mechanisms spatial orienting.

Many functional imaging and Event Related Potentials (ERPs) studies have investigated the neural basis of endogenous and exogenous visuo-spatial attention control. These highlighted the central role of the frontal and parietal lobes, with a notable distinction between the response patterns in dorsal and ventral regions. A variety of tasks requiring endogenous control of spatial attention highlighted the activation of dorsal fronto-parietal regions (e.g., Corbetta et al., 1993; Gitelman et al., 1999; Yantis et al., 2002). The activation pattern typically includes the intraparietal sulcus (IPS) and/or the posterior parietal cortex (PPC) plus the frontal eye-field (FEF) in the premotor cortex. These areas are found in serial search tasks (Gitelman et al., 2002; Himmelbach et al., 2006; Fairhall et al., 2009), plus many other non-spatial attention tasks also requiring the voluntary allocation of processing resources (e.g., see Wojciulik and Kanwisher, 1999). Accordingly, the "dorsal attention network" is commonly accepted to be involved in the endogenous control of attention (Corbetta and Shulman, 2002). Furthermore, specific experimental designs allowed segregating brain activity associated with the different phases of attention tasks, which often comprise multiple control processes. In spatial cueing tasks, the dorsal attention network has been found to activate upon the presentation of the predictive cue (e.g., Hopfinger et al., 2000; Doricchi et al., 2010) and to show sustained activity in the cue-to-target delay (Kastner et al., 1999, see also Hahn et al., 2006). These preparatory effects, and the sustained activity in the absence of any external stimulus, are consistent with the "internal"/endogenous nature of the responses in the dorsal attention system. Analogous preparatory effects have been also found within the occipital visual areas that represent the attended/cued location (e.g., see also Chawla et al., 1999, Kastner et al., 1999, for related effects in non-spatial selective attention tasks). These findings support the proposal that attention selection entails top-down signals that originate in the dorsal system and modulate activity in sensory areas that represent the currently relevant location (e.g., Simpson et al., 2011). This, in turns, would yield to greater responses when visual stimuli appear at the attended location, particularly so when the display also contains other distracting visual stimuli (Desimone and Duncan, 1995; Kastner et al., 1999; Geng et al., 2006; see also Moore, 2006, for review).

On the other hand, areas in the ventral parietal and frontal cortex activate when a behaviorally relevant stimulus is presented outside the current focus of attention, for example a visual target that follows and invalid predictive cue in spatial cueing paradigms (Arrington et al., 2000). These targets stimuli are thought to capture attention in a stimulus-driven manner and the "ventral attention network" has been associated with the control of exogenous attention (Arrington et al., 2000; Corbetta and Shulman, 2002; Macaluso et al., 2002; Corbetta et al., 2008, for review). This network comprises the temporo-parietal junction (TPJ) and the inferior frontal gyrus (IFG) and is considered to be typically lateralized in the right hemisphere (Shulman et al., 2010). Nonetheless, quite soon, it has become evident that the conditions typically associated with activation of the ventral fronto-parietal (vFP) entail not only spatial aspects of attention control (i.e., the visual target triggering a shift of attention from one position to another), but they also produce some breach of expectation (e.g., the subject expects the target at one location, but this appears at a different position) and/or require some task-related judgment of the stimulus at a previously unattended location.

In the following sections we discuss recent evidence that, on one hand, highlighted the role of bottom-up signals for attention control in the dorsal fronto-parietal system and, on the other hand, demonstrated that the ventral system combines stimulusdriven aspects of spatial reorienting with endogenous signals related to expectation and the representation of task-related contextual information (predictions). These data challenge the traditional dichotomy linking the dorsal system with endogenous attention and the ventral system with exogenous attention, and indicate a novel perspective to understand the multifaceted mechanisms underlying the control of spatial attention.

## **STIMULUS-DRIVEN EFFECTS IN THE DORSAL ATTENTION SYSTEM**

As noted above, a wealth of imaging evidence has associated activation of the dorsal fronto-parietal network with endogenous/voluntary attention control (Wojciulik and Kanwisher, 1999; Corbetta and Shulman, 2002). Nonetheless, sensory aspects of the incoming signals may also play an important role, particularly so in posterior parietal regions. Indeed, while showing increased activation even in the absence of any sensory input (Kastner et al., 1999; Hopfinger et al., 2000), the parietal cortex shows some residual spatially-specific responses also to unattended stimuli (Saygin and Sereno, 2008). The co-occurrence of sensory-driven responses and top-down internally-controlled activity, also associated with motor planning, has triggered an intense debate about the format of the spatial representations in parietal cortex (e.g., Andersen et al., 1993; Colby and Goldberg, 1999). Among the many hypotheses, the concept of "saliency map" has recently gained much interest. Saliency maps are topographical representations of the visual space and code for the relative relevance of different locations. Depending on definition, these account for bottom-up interactions between multiple sensory input/features (Itti and Koch, 2001, see also Borji and Itti, 2013) or integrate bottomup effects with top-down goals (Gottlieb et al., 1998; Treue, 2003, for review; and Gottlieb, 2007; see also "priority maps", Ptak, 2012). Saliency maps have been associated with neuronal responses in dorsal parietal (Gottlieb et al., 1998; Kusunoki et al., 2000; Constantinidis and Steinmetz, 2001) and dorsal pre-motor regions (Thompson et al., 2005), as well as visual areas in occipital cortex (Mazer and Gallant, 2003). In most of these regions, the patterns of response reflect both bottom-up as well as top-down factors that jointly contribute to make a region of space relevant.

In a series of imaging studies we made use of saliency maps to investigate attentional selection using naturalistic stimuli (i.e., complex pictures and videos). In order to explicitly characterize the effect of bottom-up signals, we considered the saliency model proposed by Itti and Koch (2001). This decomposes complex images into a set of conspicuity maps, representing local contrast in intensity, orientation and color, plus motion and flicker for dynamic visual stimuli (i.e., videos). These maps are then combined in a single map that represents the bottom-up salience of each location in the image, irrespective of the feature dimension making the location salient. The final saliency map reflects only sensory-driven aspects (i.e., competition between locations in the image) and can predict fixation patterns during the viewing of complex visual stimuli (Carmi and Itti, 2006; Elazary and Itti, 2008). Nonetheless, eye-movement studies have highlighted that factors other than pure bottom-up signals influence spatial orienting in complex environments (Navalpakkam and Itti, 2005; Einhauser et al., 2007; see also Borji and Itti, 2013). Accordingly, in our studies we combined saliency-related bottom-up indexes with measures derived from overt eye-movements recorded during free viewing of the stimuli. With this we sought to track the influence of bottom-up and top-down factors, and the interaction between the two, during selective processing of complex and naturalistic stimuli (see also Seidl et al., 2012).

In a first study, we investigated the impact of visual salience on spatial orienting using a virtual visual environment (Nardo et al., 2011). We computed the mean salience of each visual frame and used this as a covariate for the analysis of the imaging data. This revealed that activity in the occipital visual cortex and the PPC increased with increasing salience of the visual input (see also Bordier et al., 2013, who separated the effect of salience vs. single visual features). Notably, when we combined saliency data and patterns of eye-movements we found that activity in the entire dorsal fronto-parietal network (i.e., including both parietal and frontal nodes) increased specifically when the salient bottom-up signals successfully/efficaciously attracted the subjects' gaze. These activations were found also when we asked subjects to maintain central fixation (i.e., now indexing the efficacy of the bottom-up signals in one session, and using these indexes to analyze the fMRI data in a different session), consistent with an interpretation based on spatial attention/selection rather than mere oculomotor control. Related results were also obtained by Bogler et al. (2011), who used multivariate pattern recognition to reveal that PPC represents "selected" saliency signals following a winner-takes-all mechanism.

Previous studies considered the role of the dorsal frontoparietal cortex for the processing of bottom-up signals within two main frameworks. On one hand, it has been proposed that activation of the dorsal system "follows" the detection of relevant stimuli by the ventral attention system (Geng and Mangun, 2011; Vossel et al., 2012). Accordingly to this view the dorsal system generates top-down signals that modulate processing in visual cortex, which require re-setting when a relevant/infrequent "bottom-up" stimulus is presented outside the current focus of attention (Corbetta and Shulman, 2002; Shulman et al., 2009). A different prospective entails a more "direct" activation of the dorsal system due to forward input from the visual cortex. In this context, differences between the involvement of the posterior IPS and the anterior FEF nodes of the dorsal fronto-parietal system have been proposed. For example, using concurrent Transcranial Magnetic Stimulation-fMRI over either IPS or FEF, Ruff et al. (2008) showed that the inter-regional influence of FEF over visual cortex does not depend on the visual input, while the influence of IPS can change according to the current visual context. IPS-TMS affected activity in retinotopic visual areas (V1-V4) only in the absence of visual input, while activity in area V5/MT+ was modulated only in the presence of visual stimuli. The authors suggested that the difference between the effect of TMS over IPS and FEF reflects the primarily top-down nature of the FEF-tooccipital connectivity vs. the presence of strong bottom-up driving projections from visual-to-IPS areas (see also Buschman and Miller, 2007; who suggested fast bottom-up attentional signals in IPS vs. slow top-down effects in prefrontal areas). Our data with complex stimuli also showed a greater influence of the bottom-up signals in IPS with that of FEF: while both regions were modulated according to the efficacy of the salient visual input in attracting subject's attention, the activity in IPS also co-varied with the overall stimulus salience irrespective of efficacy (cf. above and see Geng and Mangun, 2009; who reported that the saliency of non-target visual stimuli is represented in IPS but not in FEF). Moreover, our study did not show any effect of sensory salience in vFP areas that instead activated when the display included attention-grabbing events (i.e., virtual human-like characters that entered the scene at unpredictable times, Nardo et al., 2011). Overall, these results are consistent with a "direct"—rather than via ventral areas—influence of bottom-up signals in the IPS, and fit with the hypothesis that the dorsal fronto-parietal cortex codes for the current attention priorities (Gottlieb, 2007).

These findings demonstrate that in complex and naturalistic experimental situations that involve high levels of sensory competition, the dorsal fronto-parietal system responds to bottom-up salient signals. However, these responses do not only reflect the impact of the external input but also they appear to index the efficacy of these signals for driving spatial selection. Eye-movement data provide us with one index of such selection processes, but do not gives us any hint about the possible consequences of the spatial selection bias. Using a working memory (WM) task, we sought to establish whether stimulus-driven attention to salient elements of a complex image has any consequence on subsequent memories of that image (Santangelo and Macaluso, 2013). Specifically, we asked whether salient objects associated with activation of the dorsal attention network are more likely to be remembered than non-salient objects or salient objects that do not activate the dorsal system (i.e., non-efficacious salient stimuli, cf. also Nardo et al., 2011). For this, we presented pictures of complex natural scenes and—following a short delay—we probed memory for one object. Critically, the probe was extracted either from an highly salient location of the image or a location of minimal saliency (see also Fine and Minnery, 2009). Behaviorally, we found better WM performance for high than low saliency probes. Analysis of the imaging data during encoding revealed increased activation in the posterior parietal cortex when the trial included a salient probe that—later, at retrieval—would be successfully remembered. This demonstrates that the selection of salient elements in a complex environment do not only trigger on-line spatial orienting (cf. eye-movements), but also leads to in-depth processing including stimulus' storage in WM.

The finding of an interplay between attention and WM is not surprising, given the wealth of data showing analogous patterns of activation during attention and WM tasks (LaBar et al., 1999; Corbetta et al., 2002; Anderson et al., 2010). Several accounts have been put forward to explain the role of attention in WM. One of the main proposal is that attention contributes to the maintenance of items/objects in WM and that activation of the dorsal attention system—and IPS in particular—reflects the process of shifting endogenous attention between these items (see Awh and Jonides, 2001; Majerus et al., 2007; Magen et al., 2009; and Nee et al., 2013; albeit note that the latter meta-analysis pointed to inferior rather than superior parietal areas for attention shifting in WM). Related more directly to the issue of the contribution of bottom-up signals, Bundesen et al. (2011) proposed a computational framework that integrates mechanisms of selective attention and the access to WM storage by a subset of items in multi-items displays. The model emphasizes the dynamic remapping/changes of neurons' receptive fields and the modulation of inter-regional communication (i.e., what information is sent from lower to higher levels of the visual hierarchy), via attentional weights generated by "priority" maps (cf., Gottlieb, 2007; Ptak, 2012).

These accounts are primarily concerned with the interplay between attention and WM considering situations were multiple, unrelated items compete for the access to a limited capacity WM buffer (typically holding 3–4 items, see Todd and Marois, 2004; Xu and Chun, 2006). However, in our experiment with naturalistic stimuli (Santangelo and Macaluso, 2013) the various items/objects in the scenes were not unrelated, rather they existed in relation to each other (e.g., glasses are typically found on a table, while shoes are on the floor). This, together with the finding of an increased functional coupling between the parietal cortex and the hippocampus when subjects encoded objects that later would be correctly retrieved, lead us to interpret our results in a slightly different framework. Specifically, we suggested that prior knowledge about the global scene configuration plays a role during the encoding of the position of objects within natural scenes. This would fit with theories proposing that WM entails the activation of long-term memory (LTM) representations, and that selective attention provides a possible mechanism to activate relevant portions of the LTM system (Cowan, 1993; Oberauer, 2002). In this context, attention does not only provide "pointers" to objects that are relevant, but may also help integrating bottomup signals with information stored in LTM.

In sum, by making use of naturalistic stimuli that entail high levels of competition for processing resources, we showed activation in posterior parietal regions when salient visual signals trigger orienting of spatial attention (Nardo et al., 2011) and when salient visual objects are successfully encoded in WM (Santangelo and Macaluso, 2013). These results indicate that bottom-up salience contributes to making a given location/object relevant (stimulus-driven selection), which in turns increases the likelihood of on-line spatial orienting towards that location and the storage in memory of information concerning that location.

Based on these findings, it would be also important to assess whether any effect of bottom-up salience is maintained or disrupted in patients with unilateral attentional deficits, as left spatial neglect (see also Section Hemispheric Lateralization and the Spatial Neglect Syndrome, below). The dorsal attention system is usually structurally intact in these patients: nonetheless, the activity of dorsal areas can be functionally reduced due to structural lesions of adjacent areas in the ventral attention system. Consistent with this, the study of visual ERPs suggested that in neglect patients bottom-up visual processing can be impaired at around 130 ms post-stimulus, at the level of structurally intact dorsal attention areas (i.e., the IPS plus dorsal occipital cortex, cf. N1 component; DiRusso et al., 2008). However, the population of neglect patients is characterized by a high between-patients variability, linked to the location and extent of brain damage, so that a corresponding variability in the processing of bottom-up salience can be expected.

## **SPATIAL REORIENTING AND EXPECTANCY COMPONENTS IN THE VENTRAL ATTENTION SYSTEM**

As noted in the introduction, the classical comparison highlighting the activation of the vFP system involves contrasting "invalid" versus "valid" trials within spatial cueing paradigms including central predictive cues. A main assumption of this approach is that the predictive cues generate a "validity context" associated to the ratio of valid over invalid cues. The statistical contingency between cues and targets cumulates during task performance and it is thought to modify behavioral performance and brain activity related to the different operations implicated in attentional orienting. Under this assumption, one may expect that symbolic cues indicating the position of the upcoming targets at chancelevel will be ineffective in biasing attention and will not produce any validity effect. Here we review evidence demonstrating that, unexpectedly and contrary to the initial assumption, effects of cue validity can be also observed within a neutral "validity context", i.e., when valid trials are as frequent as invalid ones and cues are statistically non-predictive. These experimental conditions are of particular relevance because they dissociate the effects of spatial re-orienting on invalid trials from any violation of expectations that characterize invalid trials presented within a predictive "validity context".

The first study that emphasized the importance of isolating the neural correlates of the violation of expectancy carried by targets presented at unexpected spatial or temporal locations is a PET investigation by Nobre et al. (1999). Through the reanalysis of data from a previous study (Coull and Nobre, 1998), these authors compared brain activations recorded during phases of a Posner-like task in which the percentage of valid trials was 100% to those recorded in phases with 60% of valid and 40% of invalid trials. Invalid trials selectively engaged inferior parietal areas bilaterally, though with a larger activation in the right hemisphere, the right lateral premotor cortex and the inferior-orbitofrontal cortex bilaterally. The authors concluded that the response of the inferior-orbitofrontal cortex to invalid trials is recruited by violation in the expected cue-target congruency and that the parietal and premotor areas might instead be prevalently involved in more exquisitely spatial-attentional processes, as the shift of the attentional focus. Although the experimental design did not include any comparison of brain activations related to blocks with frequent vs infrequent invalid trials, i.e., trials implying identical spatial-attentional operations though carrying different degrees of unexpected violation of cue-target congruency, the points made by these authors were the first that set the terms of the spatial/expectancy components in reorienting.

A few years later, Giessing et al. (2004) reasoned that although event-related fMRI designs are more suitable to study transient neural processes related to infrequent events like invalid trials in a conventional endogenous Posner task, they can be insensitive to more sustained neural processes related to reorienting of attention. To isolate both transient and sustained neural components of reorienting, these authors used a hybrid event-related/block design arranging invalid trials within blocks having different ratios of valid vs. invalid trials: 100% valid–0% invalid, 75% valid–25% invalid and 50% valid–50% invalid. This allowed comparing both transient event-related (invalid vs valid contrast independently of block type) and sustained (100% Valid–0% Invalid blocks vs. 50% valid–50% invalid blocks) brain activity related to reorienting. The study revealed common event- and block-related activations in the right intraparietal sulcus. Moreover, in the blocked design the activation of this area was positively correlated with the number of invalid trials in a block. The blocked design also revealed the activation of the right occipital-parietal junction whereas the event-related analysis isolated additional activations in the right superior parietal lobule and in the left intraparietal sulcus. Unfortunately, this study did not provide us with detailed results of the contrast between the 75% and 50% block validity conditions that would have allowed for a first glance to the spatial and expectancy components of reorienting. At a behavioral level, this study reported the maintenance of the validity effect in blocks with non-predictive cues (50% valid–50% invalid): however, one should consider that this finding can still be accounted by the general positive "validity context" of the task, since across the different types of validity blocks the majority of trials were valid (73.4%).

Capitalizing on behavioral evidence showing that the ratio of valid vs. invalid cues modulates the validity effect (Jonides, 1980, 1983; Eriksen and Yeh, 1985; Madden, 1992), Vossel et al. (2006) were the first to directly assess the influence of the validity context on neural activity related to attentional reorienting. These authors used an event-related design where, in each trial, differently colored central arrow-cues predicted with different validity the position of ensuing targets, e.g., green arrow 90% of validity vs. blue arrow 60% of validity. The comparison between trialrelated brain activities (i.e., with no separation of cue- and targetrelated brain response) in the two validity conditions showed that infrequent invalid trials (i.e., 90% validity) determined greater activation in the right IFG and middle frontal gyrus (MFG) and in the right inferior parietal cortex (angular and supramarginal gyrus, plus the intraparietal sulcus). As in previous studies, the reaction times (RT) advantage for validly cued targets was larger in the high-validity condition (90%). The authors' advanced alternative hypotheses for the heightened response in parietal and frontal areas observed for invalid trials presented in the highvalidity context (90%). For the frontal areas, they proposed that infrequent invalid trials might be more unexpected and novel or might induce stronger prefrontal inhibition of motor responses until accomplishment of spatial reorienting. The parietal response to the validity context received two possible interpretations: (1) more demanding reorienting effort to infrequent invalid targets; (2) less frequent and thus more surprising violation of expectancy with infrequent invalid targets.

More recently, Shulman et al. (2009) investigated spatial vs. expectancy components of reorienting using a modified version of the shift/stay paradigm devised by Yantis et al.(2002). Participants had to detect a target-object that was presented within one of two visual streams of object-groups, one presented to the left and one to the right side of central fixation. At the beginning of each stream-trial, the stream to be attended was cued by a peripheral red box shortly appearing to the left or the right of fixation. Crucially, streams were presented within three different block-conditions: (1) in a first condition the probability that on ensuing stream-trials the red-cue shifted from one side of fixation to the other was high (86% shift cues) whereas the probability of remaining on the same side-stream was low (14% stay cues); (2) in a second condition the probability of occurrence of shift and stay cues was equal (50%); (3) in a third condition the probability of shifting attention from the left to right of fixation or viceversa was low (14% shift cues) while the probability of remaining on the same side-stream was high (86%). In this way reorienting of spatial attention to the peripheral red box was made orthogonal to the likelihood of operating reorienting. In other words, spatial reorienting and unexpectedness of reorienting were operationally dissociated among blocks with different shift/stay probabilities. Analysis of Blood oxygen-level dependent (BOLD) signal revealed that the right TPJ was significantly activated by shift cues independently of the likelihood of reorienting (note that this is at variance with previous data by Vossel et al. (2006), showing sensitivity of the right TPJ to the expectancy component of reorienting; see also below for a further discussion of this). In contrast, the response of the right IFG was strongly influenced by unexpected shifts of attention (High Stay/Low Shift cuing condition). The basal ganglia and the frontal insular region were also activated by unexpected shifts of attention: however, analysis of resting state connectivity demonstrated that this network was functionally separated from the classical TPJ-IFG ventral system. The authors proposed that the response of the basal gangliainsular network might be linked to the change in the attentional set, or to higher inhibition of competing attentional processes elicited by unexpected peripheral cues triggering reorienting of attention. Finally, dorsal attentional areas in the IPS and FEF showed intermediate sensitivity to expectancy: according to the authors the increased response of these areas to unexpected shifts of attention was driven by expectedness-related responses in the right IFG and in the basal ganglia-insular network.

The studies summarized above investigated the influence of the "validity context" by examining brain responses related to the entire cue-target period or to peripheral stimuli that acted both as attentional relevant stimuli and cues (Shulman et al., 2009). However, one important finding in the study of attention is that cumulated knowledge about the occurrence of previous stimuli (trials' history) can influence the focusing of attention ahead of the occurrence of new relevant stimuli. Shulman et al. (2007) showed that the more target occurrence in a rapid visual stream becomes probable along the timeline, the more TPJ is deactivated. Put in other words, the response of the attention controlling networks is modulated according to the likelihood/predictability of a given target type to occur. With respect to studies using the Posner task with central cues, the observation by Shulman et al. (2007) highlights the importance of disentangling the influence of the validity context on cue- and target-related brain activity.

With this aim we recently reinvestigated the influence of cuepredictiveness on cue- and target-related brain activity (Doricchi et al., 2010). Two groups of participants were considered: one performed an endogenous Posner task with highly predictive cues (80% valid–20% invalid trials) whereas the other performed the task using non-predictive cues (50% valid–50% invalid trials). Keeping a fixed cue-target probabilistic relationship during the entire task allowed avoiding the possible influence of strategic factors related to trial-by-trial or block-by-block changes in the probabilistic cue-target congruency. In the same study, we also introduced spatially-neutral cued trials to assess the influence of the validity context on attentional benefits (RT advantage to validly cued vs neutrally cued targets) and costs (RT advantage to neutral vs invalidly cued targets). We found that during endogenous orienting, predictive cues lead to a greater deactivation of the right TPJ as compared to non-predictive ones. Since deactivation of the TPJ has been previously related to the filtering out of unattended events (Shulman et al., 2007), this finding suggests that when cues are not predictive and invalid targets frequent, the TPJ reduces the filtering out of uncued locations to facilitate reorienting. The study of target-related activation showed that, compared to valid targets, frequent and infrequent invalid targets equally activated the right TPJ, whereas infrequent invalid targets produced a stronger response in the right IFG and MFG: this shows that the TPJ is sensitive to the simple mismatch between cued and actual target location and that IFG-MFG are sensitive to the unexpectedness of such a mismatch. Both the left and right TPJ displayed no preference for targets presented in the ipsilateral or contralateral space (unpublished data). No effect of validity context was found in cue- and targetrelated responses of dorsal attentional areas (IPS and FEF). This seems at variance with findings by Shulman et al. (2009): this

different result, however, could be accounted on the fact that in our study the validity context was stable, whereas in the study by Shulman et al. (2009) the predictiveness of peripheral shift/stay cues was randomly alternated between 14%, 50%, and 86% across the 20 blocks of trials. Finally, unlike the right IFG/MFG that was modulated according to expectancy (cf. infrequent invalid targets), the left TPJ and left IFG responded to frequent valid targets matching cue-related expectations. In agreement with these results, DiQuattro and Geng (2011) reported activation of the left TPJ and IFG in response to salient contextual stimuli predicting, i.e., matching, the concomitant task-related stimuli.

The comparison of brain and behavioral responses to valid and invalid targets with those to neutrally cued ones provided a number of additional functional and behavioral observations. Independently of cue predictiveness, valid targets activated the left TPJ, whereas invalid targets activated both the left and right TPJs. These findings suggest that the selective activation of right TPJ that is usually found in the direct comparison between invalid and valid trials (but see below for a number of studies reporting bilateral TPJ response to invalid targets) may result from a common response to both valid and invalid target in the left TPJ. At the behavioral level, in the non-predictive condition the validity effect was reduced, though, not abolished. This is important because it shows that even when the general validity context of an endogenous Posner task is constant and neutral, non-predictive cuing can still bias participants' attention. Even more importantly, the analyses of the benefits and costs, showed—quite surprisingly that the reduction of the validity effect in the non-predictive condition was entirely explained by a drop in the costs; whereas benefits were equivalent in the predictive and non-predictive conditions (it is worth noting that only participants showing a reliable validity effect, i.e., RT advantage to valid vs. invalid targets, during a training pre-test session with 80% valid cuing were included in the study). All together these findings show that: (a) the left TPJ hosts both neuronal populations coding the mismatch between cued and actual target location on invalid trials and cuetarget matches on valid trials; (b) the right TPJ hosts neuronal populations coding the mismatch between cued and actual target location; (c) the validity context modulates TPJ activity during the cue period but shows no comparable influence on target-related brain response: this suggests that in fMRI studies investigating the influence of the validity effect it is suitable to disentangle cue- and target-related effects. Cue- vs. target-related effects also provides us with a possible explanation for the different findings between the study of Vossel et al. (2006), which reported sensitivity of the TPJ to the validity context, and those by Shulman et al. (2009) who did not report any such effect. In the study by Vossel et al. (2006) there was no separation between central/cue- and peripheral/target-related brain responses, whereas in the study by Shulman et al. (2009) only peripheral/target-related responses were studied. In our study (Doricchi et al., 2010), cue- and targetrelated brain responses were investigated separately. This showed that the right TPJ is sensitive to expectancy during the cueperiod, when it showed a greater deactivation for informative compared to non-informative cues, though not during the target period, when it showed equivalent levels of activity both in the low- and high-expectancy conditions. These results suggest that in Vossel et al. (2006) the expectancy effects in the right TPJ may have been partially due to cue-related activity, whereas the effects in the right IFG-MFG can be attributed to the sensitivity of these areas to target-related expectancy, i.e., greater responses to unexpected/infrequent invalid targets.

In two other studies we investigated the response pattern of the vFP system seeking to further dissociate pure stimulusdriven effects from expectation and task-relevance (Natale et al., 2009, 2010). In one study (Natale et al., 2010), we made use of an attention capture paradigm with non-predictive cues (Folk et al., 1992) to investigate whether task-irrelevant visual features associated with the target modulate activity in TPJ-IFG. The paradigm consisted in classical exogenous cueing task, with a box briefly flashed in one or the other hemifield, shortly followed by a task-relevant visual target at the same (50% valid trials) or the opposite side (50% invalid trials). By virtue of this 1:1 ratio between valid and invalid cues, the experiment entailed a fully neutral "validity context". The target was a triangle presented within the box and the task of the subjects was to report whether the triangle was pointing upward or downward. Critically, here we manipulated the color of the targets (red or blue) and the color of the cues (red or green). Despite the red/blue color of the target was fully task-irrelevant, at the behavioral level we found larger effects of cue-validity (invalid vs. valid trials) when the cue was red (set-relevant cues: same color as the target set) than when the cue was green (set-irrelevant cues: color not included in the target set). The imaging data revealed that invalid set-relevant red-cues activated the right TPJ, irrespective of target color; while invalid trials with set-irrelevant green-cues did not activate the TPJ. These results confirm that in the absence of any relationship between cues and targets (green cue + red/blue target), exogenous invalid cues do not trigger any spatial selection processes in the ventral attention system. However, it is sufficient that the cue shares some propriety with the current task-set (here, "redness") to activate the ventral network, even in the absence of any breach of expectation. Since this effect was specific for the invalid trials (vs. valid trials), we assumed that it arose at the onset of the target. However, because of the specific timing of the stimuli, we were unable to separately assess the effect of set-relevance on cue-related vs. target-related activity (i.e., targets were presented immediately after the cues) nor whether any differential pattern of de-activation compared to resting state activity played any role here (i.e., the range of inter-trial intervals was only 1.9–3.0 s; cf. Shulman et al., 2007). Nonetheless, these results highlighted that external signals—specifically, the spatial relationship between the cue and the target—and internal information about the current task-set jointly contribute to the re-orienting effects in ventral attention system (see also Serences et al., 2005).

Another approach that enabled us to investigate the interplay between non-predictive signals and endogenous task-settings involved using a double-cue paradigm (Berger et al., 2005). The aim of a double cue paradigm is to engage endogenous and exogenous attention control concurrently within the same trial, thus providing a direct measure of whether/how these two mechanisms interact with each other. Specifically, the presentation of a peripheral non-predictive cue after a predictive endogenous cue enables studying the effect of a fully task-irrelevant and non-predictive stimulus (i.e., the exogenous cue) presented under conditions of top-down focused attention. This may be important when considering that the typical situation yielding to activation of TPJ-IFG involves shifting attention from a relevant location (e.g., that signaled by a predictive cue) to another relevant location (i.e., the position of an invalidly cued target). On each trial we presented first an endogenous predictive cue, then an exogenous peripheral cue and, finally, the visual target (Natale et al., 2009). The results highlighted activation of the vFP network when the endogenous cue was invalid, irrespective of the validity/invalidity of the exogenous cues. This demonstrated that this network does not process task-irrelevant and non-predictive stimuli, even when attention has been endogenously focused and the task-irrelevant stimuli provide spatial information that mismatches the current spatial expectations (i.e., trials including "invalid" exogenous cues). These results support the view that activation of the ventral attention system is involved in stimulus-driven updating of spatial expectations, only when the stimulus (e.g., a task-relevant target or a set-relevant cue) signals a "new" location that is potentially relevant.

To summarize, there is now ample evidence that activity in the vFP system reflects some interplay between stimulus-driven factors (e.g., the onset of an unexpected stimulus) and other endogenous/internal constraints. Mere bottom-up stimulus onset is insufficient to activate this network (e.g., Kincade et al., 2005; Indovina and Macaluso, 2007), while the specific relationship between the characteristics of the external signal and the internal goals/expectations plays a pivotal role for the activation of this system (e.g., see Corbetta et al., 2008, for review; Natale et al., 2010). This relationship may be relatively direct, e.g., the stimulus requires some overt judgment/response despite breaching current expectations (e.g., a task-relevant invalid target, following a predictive cue); or can be more subtle, e.g., the stimulus is taskirrelevant but still taps into task constraints that are currently relevant (e.g., contingent capture paradigms).

## **INTEGRATION OF ENDOGENOUS AND EXOGENOUS SIGNALS: OPEN ISSUES AND FUTURE WORK HEMISPHERIC LATERALIZATION AND THE SPATIAL NEGLECT SYNDROME**

Despite the common assumption that mechanisms of attentional reorienting are predominantly—if not exclusively—homed in the right hemisphere (Shulman et al., 2010), a number of studies have reported bilateral rather than right unilateral activation of the TPJ in response to unexpected and invalid targets (Serences et al., 2005; Asplund et al., 2010). Through comparisons with neutral trials, we have recently shown that the left TPJ activation to invalid targets is often missed because this area responds both to invalid and valid targets (Doricchi et al., 2010). Here, we wish to emphasize that these effects in the left hemisphere can help understanding the reorienting deficits in neglect patients. The observation that the same regions that in the right ventral attention network (TPJ and IFG-MFG) are activated by reorienting towards both sides of space are also the most frequently damaged in patients with left spatial neglect (Doricchi and Tomaiuolo, 2003; Mort et al., 2003; Bartolomeo et al., 2007; He et al., 2007; Doricchi et al., 2008; Verdon et al., 2010) was taken as evidence to explain the higher incidence of neglect after right brain damage (Corbetta et al., 2008). However, assuming an exclusive competence of the right ventral network in reorienting towards both side of space would imply that damage to this network should cause a bilateral reorienting deficit. At variance with this prediction, neglect patients show severely impaired reorienting towards invalid targets in the contralesional left side of space, but no comparable ipsilesional deficits (Posner et al., 1984; Morrow and Ratcliff, 1988; Friedrich et al., 1998; Losier and Klein, 2001; Vossel et al., 2010; Rengachary et al., 2011). A possible explanation of this is that the residual ipsilesional reorienting abilities in neglect patients are based on the reorienting response of the intact left hemisphere. The competence of the left ventral network in detecting both cue-target matches on valid trials and cue-target mismatches in invalid trials may also explain the preserved ability of neglect patients in representing and exploiting the statistical contingency governing the spatial distribution of attentional relevant stimuli (Bartolomeo et al., 2001; Geng and Behrmann, 2002). We advise reconsidering hemispheric lateralization during spatial re-orientating, as this will potentially refine our understanding of pathologies associated with deficits of spatial attention.

#### **EARLY OR LATE ATTENTIONAL FUNCTION FOR THE TPJ?**

Electrophysiological investigations suggest that the TPJ plays a crucial role in the late phases of attentional processing, when it is believed to generate the P300b component signaling the match or mismatch between actual and predicted sensory input (Knight and Scabini, 1998). Capitalizing on this evidence we have proposed (Doricchi et al., 2010) that the response of the right and left TPJ to invalid targets may reflect the activity of a late-processing "MisMatch" system and the response of the left TPJ to valid targets that of a complementary "Match" system. Both systems would provide signals that help the brain in updating the internal models of statistical cue-target congruency which, in turn, would help keeping or switching the attentional task-set and the building-up of predictions about the position of upcoming targets. DiQuattro and Geng (2011) recently have provided evidence showing that one important function of the left hemispheric "Match" system concerns the processing of salient visual contextual cues that regularly predict, i.e., match, the position of concurrent but less salient targets. Interestingly, while the reorienting of attention after invalid central cues does activate the right (and left) TPJ, reorienting after invalid exogenous peripheral cues does not (e.g., Kincade et al., 2005). Based on our interpretation of the role of TPJ, this finding suggests that a key difference between exogenous and endogenous orienting is that only in the latter case a template of the expected target can be prepared during the cue period and then compared, through a Match/MisMatch process, with the actual target.

However, in a recent fMRI study Vossel et al. (2012) provided evidence challenging the idea that spatial reorienting is first initiated in dorsal parietal areas and that the TPJ comes into play only in a late phase of target processing. These authors used dynamic causal to characterize the effective connectivity within and between the ventral and dorsal attentional system during orienting to valid targets and reorienting to invalid targets. One key finding of this study was that invalid cuing enhanced connectivity from the ventral right TPJ to the dorsal right IPS rather than viceversa. The authors concluded that the violation of the expected cue-target congruency signaled by the TPJ may precede and help the reorienting-related shift of spatial attention governed by dorsal areas.

The notion that the allocation of processing resources involves some comparisons between expectations stored in "internal models" and the incoming sensory input (cf., Match/MisMatch systems, above) bears some relationship with recent proposals concerning the role of "predictive coding" in visual processing (Rao and Ballard, 1999). These postulate a hierarchical organization of processing where higher-order nodes represent the expected signal and inform lower-level nodes about this prediction (topdown influences). Upon stimulation, the input is compared with the predictions and any resulting error is fed-forward in order to update the internal model. Such architectures have been used to explain several visual phenomena (e.g., extra-classical receptive fields, Rao and Ballard, 1999) and, more recently, expectationrelated effects in visual attention (Spratling, 2008; see also Summerfield and Egner, 2009, for review; Feldman and Friston, 2010). In this context, low probability invalid trials may generate a prediction error, possibly with an additional update of an internal model that would keep track of the probabilistic relationship between the positions signaled by the cues and where the targets are actually presented. Nonetheless, we should notice that a central tenet of predictive coding concerns the hierarchical organization of processing, which appears suitable to describe attention-related effects within occipital areas (e.g., Spratling, 2012, who implemented predictive coding to model saliencyrelated effects in primary visual cortex) or between high-order parietal (frontal) regions and visual areas (see also den Ouden et al., 2010, for a possible role of sub-cortical structures); but may be less appropriate to explain interactions between the dorsal and the vFP networks or between the left and the right TPJ.

In summary the interplay between dorsal areas adjacent to the IPS and the ventral TPJ appears to be an important challenge for future studies. These will have to be cautiously taken into account that a given area can show both fast and slow responses to invalid targets (Chambers et al., 2004) and that the interaction between different visual-attentional areas can be characterized by complex reciprocal exchange of feedback/forward signals. In addition it would of interest to investigate the role played by the ventral and dorsal attentional network when the statistical predictiveness of cue stimuli is updated and exploited to anticipate upcoming target events. Available evidence allows us to hypothesize that the ventral attentional system may perform a dynamic, trial-by-trial evaluation of the cue-target contingency and that the results of this is fed to dorsal areas. In turn, dorsal regions would make use of this information to update higher-order salience/priority maps that—via top-down control—modulate the processing of incoming signals in occipital sensory areas. This may be tested using TMS perturbations of the TPJ and dorsal parietal regions at different intervals, following the presentation of cues with variable validity/predictiveness.

## **ONE OR MULTIPLE FILTERS FOR THE ALLOCATION OF ATTENTIONAL RESOURCES?**

We reviewed several studies showing that the validity context modulates the validity effect: the higher the statistical predictiveness of the cues, the higher the RT advantage for valid as compared to invalid targets. This relationship has been modeled as the result of a single-filtering operation, where the ratio between the accumulation of attentional resources at the attended position and the withdrawal of resources from unattended locations is positively correlated to the predictiveness of the cues. However, we have recently found that the reduction of the validity effect with non predictive endogenous cues (i.e., neutral "validity context") can be selectively driven by the abatement of attentional costs, whereas benefits can be maintained with both predictive and non predictive cuing (i.e., with both positive and neutral "validity contexts"). In an ensuing ERPs study (Lasaponara et al., 2011) we have recently found that the abatement in attentional costs is matched with the disappearance of differences in the amplitude of the P1 wave evoked by invalidly vs. neutrally cued targets (see Luck et al., 1994). By contrast the maintenance of benefits in predictive and non-predictive cuing conditions is paralleled by larger N1 amplitude in response to validly vs. neutrally cued targets. This difference between the effect of predictiveness on costs and benefits cannot be easily accounted for by a single filtering mechanism. A linear relationship between the level of cue predictiveness and the ratio between the activation of the cued vs. the uncued location would predict a symmetrical reduction of benefits and costs with non-predictive cuing. A more articulated interpretation is needed (Lasaponara et al., 2011).

At a neurophysiological level, visual-spatial orienting is regulated by the combined action of different—though functionally related—pools of visual, visuomotor and saccadic neurons within the dorsal fronto-parietal network (e.g., in the intraparital cortex: Ipata et al., 2006; Thomas and Parè, 2007; Superior Colliculus: McPeek and Keller, 2002; and in the FEF: Bruce and Goldberg, 1985; Schall and Hanes, 1993; Hanes and Schall, 1996; Thompson et al., 1996, 1997; Sommer and Wurtz, 1998; Bisley and Goldberg, 2003; Juan et al., 2004; Schall, 2004; Thompson et al., 2005). This allows hypothesizing synergic filtering mechanisms, via anatomically separated but functionally related pools of neurons. Some degree of independence between these pools can provide us with an explanation for the differential effect of the "validity context" on benefits and costs. For example, in the case of non-predictive cuing, the activation of visuomotor responses directed toward the cued location could guarantee the

## preservation of attentional benefits, whereas concomitant visual selection of both cued and uncued locations might help reducing attentional costs. In humans, some segregation between mechanisms of visual and visuomotor selection was demonstrated in cortical areas traditionally involved in saccadic programming. Muggleton et al. (2003) showed that the inactivation of the FEF by TMS stimulation slows down the selection of poorly salient or non-predictable visual targets in visual search tasks (see Thompson et al., 1997, for equivalent neurophysiological findings in the macaque). These observations highlight the need of exploring further the complex and multi-stages mechanisms that regulate the strategic allocation of attentional resources in space.

## **CONCLUSION**

Traditional views of attention control posit a distinction between endogenous control in dorsal fronto-parietal regions and stimulus-driven control in vFP areas. However, in recent years, such a strict dichotomy has been challenged. Here we reviewed evidence that the dorsal system makes use of bottom-up salient signals to select relevant elements in complex environments; and that the processing of external stimuli in the ventral system takes into account endogenous factors associated with the experimental context (e.g., task-set, expectations, predictiveness). We emphasize that attention control must pick up statistical ir-/regularities of the environment and integrate these with on-line information about the current sensory input. This interaction determines the selection of the most relevant stimuli and governs the allocation of the attentional resources. At the physiological level, this is likely to require some interplay between the dorsal and the ventral attention systems. We propose that the ventral system performs moment-to-moment match/mismatch operations, comparing current expectations/predictions with the actual sensory input. The result of these operations leads to a continuous update of the expectations and predictions, which the dorsal system utilizes to control the allocation of spatial attention.

## **ACKNOWLEDGMENTS**

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013) / ERC grant agreement 242809 to Emiliano Macaluso; and from the Italian Ministry of Health to Fabrizio Doricchi (grant RF10.091). The Fondazione Santa Lucia, is supported by The Italian Ministry of Health.

## **REFERENCES**

*Curr. Opin. Neurobiol.* 3, 171–176. doi: 10.1016/0959-4388(93)90206-e Arrington, C. M., Carr, T. H., Mayer, A. R., and Rao, S. M. (2000). Neural mechanisms of visual attention: object-based selection of a region in space. *J. Cogn. Neurosci.* 12(Suppl. 2), 106–117. doi: 10.

1162/089892900563975 Asplund, C. L., Todd, J. J., Snyder, A. P., and Marois, R. (2010). A central role for the lateral prefrontal cortex in goal-directed and stimulusdriven attention. *Nat. Neurosci.* 13, 507–514. doi: 10.1038/nn. 2509

task. *Cereb. Cortex* 20, 1574–1585. doi: 10.1093/cercor/bhp215

*Sci.* 13, 520–525. doi: 10.1111/1467- 9280.00491

430. doi: 10.1126/science.274.5286. 427

47, 1790–1798. doi: 10.1016/j. neuropsychologia.2009.02.015

meta-analysis of executive components of working memory. *Cereb. Cortex* 23, 264–282. doi: 10. 1093/cercor/bhs007

activation of frontal, parietal, and sensory regions underlying anticipatory visual spatial attention. *J. Neurosci.* 31, 13880–13889. doi: 10. 1523/jneurosci.1519-10.2011

identified in the activity of macaque frontal eye field neurons during visual search. *J. Neurophysiol.* 76, 4040–4055.

involvement in visual attention. *Neuron* 23, 747–764. doi: 10. 1016/s0896-6273(01)80033-7

**Conflict of Interest Statement**: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 30 May 2013; accepted: 29 September 2013; published online: 21 October 2013.*

*Citation: Macaluso E and Doricchi F (2013) Attention and predictions: control of spatial attention beyond the endogenous-exogenous dichotomy. Front. Hum. Neurosci. 7:685. doi: 10.3389/fnhum.2013.00685*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Macaluso and Doricchi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## The dorsal attentional system in oculomotor learning of predictive information

*Philip Tseng1,2, Chi-Fu Chang1,2, Hui-Yan Chiau1,2, Wei-Kuang Liang1,2, Chia-Lun Liu1,2, Tzu-Yu Hsu1,2, Daisy L. Hung1,2, Ovid J. L. Tzeng1,3 and Chi-Hung Juan1,2\**

*1 Institute of Cognitive Neuroscience, National Central University, Jhongli, Taiwan*

*2 Laboratories for Cognitive Neuroscience, National Yang-Ming University, Taipei, Taiwan*

*3 Institute of Linguistics, Academia Sinica, Taipei, Taiwan*

#### *Edited by:*

*Joy Geng, University of California Davis, USA*

#### *Reviewed by:*

*Britt Anderson, Brown University, USA Amanda Ellison, Durham University, UK*

#### *\*Correspondence:*

*Chi-Hung Juan, Institute of Cognitive Neuroscience, National Central University, No.300, Jhongda Rd. Jhongli City 320, Taiwan e-mail<EMAIL_ADDRESS>
The dorsal attentional network is known for its role in directing top-down visual attention toward task-relevant stimuli. This goal-directed nature of the dorsal network makes it a suitable candidate for processing and extracting predictive information from the visual environment. In this review we briefly summarize some of the findings that delineate the neural substrates that contribute to predictive learning at both levels within the dorsal attentional system: including the frontal eye field (FEF) and posterior parietal cortex (PPC). We also discuss the similarities and differences between these two regions when it comes to learning predictive information. The current findings from the literature suggest that the FEFs may be more involved in top-down spatial attention, whereas the parietal cortex is involved in processing task-relevant attentional influences driven by stimulus salience, both contribute to the processing of predictive cues at different time points.

**Keywords: probability, predictability, visual attention, eye movements, TMS, transcranial magnetic stimulation**

Regularities in the visual environment are predictive of future events. Learning of such regularities may therefore help the visual system generate anticipatory activities (i.e., expectations) and reduce computational burden. Take traffic lights, for example; there is a serial order for which signals light up (temporal), as well as the color (feature based) and location (spatial) of each light, thus reflecting regularities in several domains of one's daily life. This information can be fully predictive of future events if they are always 100% valid, such as the traffic light. But even with partial predictive power (not always 100% valid), which we refer to as probabilistic, it remains advantageous to pick up such information, as the knowledge of any regularities can help the visual system reduce its computational load because future events can be anticipated and better managed in advance. This learning of predictive information is especially useful given that our ability to represent multiple objects within a scene at any given moment is rather limited (e.g., Buschman et al., 2011; Tsubomi et al., 2013). Indeed, many studies have already demonstrated the visual system's capability to learn and exhibit knowledge of regularities in the environment with and without subjective awareness (e.g., Chun and Jiang, 1998; Fiser and Aslin, 2001; Kristjánsson et al., 2001; Nakayama et al., 2004; Geng and Behrmann, 2005). Eye movement studies have also shown that people can direct their eyes and attention to highly probable locations faster than to low-probability locations without employing an explicit strategy to do so (e.g., Farrell et al., 2009). In this paper, we attempt to review evidence demonstrating the existence of predictive learning as well as their possible neural mechanism, such as the dorsal attentional network.

The dorsal attentional network is comprised of the frontal eye fields (FEF) and the posterior parietal cortex (PPC), where PPC includes the superior parietal lobule (SPL) and intraparietal sulcus (IPS). The dorsal network has been shown to be involved in voluntary top-down orienting of visual attention. This network shows strong activity when a spatial cue is presented, explicitly indicating where participants should direct their attention (Corbetta et al., 2008). However, it is important to note that even in the absence of a cue, contextual information, if predictive, can sometimes work in similar ways as a spatial cue in directing one's attention. For example, visual search with a repetitive and predictive distractor layout can promote implicit learning and efficient attentional orienting to the target location in observers over time, a phenomenon known as contextual cuing (Chun and Jiang, 1998). In this case, the contextual information (i.e., distractor configuration) is predictive of the target location, thus functioning like a probabilistic spatial cue in directing visual attention, and thereby activating the dorsal network (Manginelli et al., 2013). Therefore, the dorsal network has been suggested to mediate the processes of top-down attentional set, such as the expectation of a cue (Corbetta et al., 2008). This pre- and post-stimulus activation of the dorsal network can facilitate efficient selection of, and orienting toward, the stimuli of interest.

## **POSTERIOR PARIETAL CORTEX**

The idea that one's visual attention is efficiently oriented toward the predictive and salient cue in the environment is plausible, because one of the functions of PPC is indeed attentional orienting and capture. Specifically, the right (hemisphere) PPC has been associated with a variety of functions in visual attention (Behrmann et al., 2004; Rushworth and Taylor, 2006), including attentional control (Nobre et al., 1997; Ellison and Cowey, 2006; Morris et al., 2007), updating spatial mapping (Andersen et al., 1985; Merriam et al., 2003; Morris et al., 2007), and shifting spatial attention (Ellison et al., 2003; Chambers et al., 2004; Constantinidis and Steinmetz, 2005; Mevorach et al., 2006; Schenkluhn et al., 2008). Damage to the right PPC may lead to hemifield neglect, where patients become unaware of the contralateral visual space although their visual acuity is not affected (Heilman and Van Den Abell, 1980; Mesulam, 1981). In the contextual cuing example above, it is important to note that the predictive context is facilitative by efficiently directing eye gazes toward the target location (Neider and Zelinsky, 2006; also see Kunar et al., 2007; for an effect in response selection). Indeed, Peterson and Kramer (2001) monitored participants' eye movements and found that fewer saccades were made when context was repeated, suggesting a more efficient allocation of attention to the old condition. Thus, predictive contextual information, even with uneven probability (Tseng et al., 2011), can have a direct impact on visual attention and eye movements, suggesting a critical involvement of the dorsal attentional network that is also heavily involved in oculomotor control. Indeed, Schankin and Schubo (2009) measured event-related potentials (ERP) using this paradigm and found greater negativity in the posterior parietal region around 200 ms after display onset. This component is known as the N2pc component (Luck and Hillyard, 1994), which reflects the allocation of visual attention in the parietal region that is contralateral to the visual field of the attended stimulus. This physiological evidence demonstrates an important correlation between attentional allocation and PPC. In contextual cuing, however, there exists a confound between distractor saliency and predictability, thus the exact role of PPC remains unclear. That is, it is unclear whether the activation of PPC was due to the bottom-up salience of the distractors, or because of their predictive nature that matched the top-down task set. To dissociate these two factors, one needs a situation where salient but nonpredictive distractors compete with the target and therefore need to be suppressed. To answer this question, one important study by Geng and Mangun (2008) used a visual search paradigm, where the search target appeared either with a low-contrast (low competition) or high-contrast (high competition) distractor. These authors found that target-induced aIPS (part of PPC) activation scaled linearly with increasing RT, especially when the distractor was salient. Thus, PPC activation seemed to be coupled with salient distractors at the perceptual level. Subsequent study by Mazaheri et al. (2011) recorded EEG activity using the same paradigm. Critically, in the 1-s pre-stimulus time window before each high-competition trial, these authors found higher alpha activity from PPC on trials where the target was correctly identified by the first saccade. Based on the wealth of literature that suggests alpha activity as an indication of cortical inhibition (e.g., see Klimesch, 2012 for a review), the results suggest that PPC alpha was indicative of suppression of salient distractors, consistent with the conclusion by Geng and Mangun (2008) that PPC is involved in processing salient perceptual information.

Using brain stimulation, another direct test of such idea was carried out by Chao et al. (2011), with the use of transcranial magnetic stimulation (TMS) coupled with a similar 1-target and 1-distractor visual orienting paradigm (see also Hodsoll et al., 2009) that is preceded by either a spatially-predictive or neutral cue. In this study, saccade curvatures, along with saccade latency and accuracy, were recorded as they have been shown to be indicative of the active excitation and suppression processes that the visual system must resolve between the target and the distractor (e.g., Walker et al., 2006; McSorley et al., 2009). Not surprisingly, people could saccade faster and with more precision and smaller curvature (less "pulling" effect from the distractors) when the target location was predictable. The pattern becomes interesting when TMS was applied over the right PPC. When target location was predictable, PPC TMS had no significant effect on saccade curvature. However, when target location was unpredictable, TMS over the right PPC decreased saccade curvature toward the distractor such that impaired PPC functioning actually strengthened distractor suppression (**Figure 1**). These results suggest that PPC plays an important role in attentional capture (thus why PPC TMS would decrease attentional capture toward the distractor), and subsequent study has shown that such effect took place at modulating the torque of each eye movements (Liang and Juan, 2012). Together, the alpha inhibition and TMS suppression of PPC from Mazaheri et al. (2011) and Chao et al. (2011) demonstrate that PPC is sensitive to salient distractors, and is indirectly sensitive to predictive information when predictability also becomes a salient feature.

**FIGURE 1 | Effect of TMS on PPC in predictable and unpredictable contexts, from Chao et al. (2011).** The Y axis denotes the range of saccade curvatures, where negative numbers indicate less curvature toward the distractor. Panel **(A)** shows that PPC TMS decreased saccade curvature toward the distractor when distractor location is unpredictable, whereas Panel **(B)** shows that PPC TMS had no effect when distractor location can be predicted in advance. This suggests a critical role for the right PPC in attentional capture, and how predictability can modulate PPC involvement.

Without a salient distractor, is PPC still involved in predictive processing? As mentioned, research has shown that as long as predictability is a relevant aspect of the task, PPC should also play an important role in processing targets and predictive information. For example, a TMS study by Ellison et al. (2003) found that TMS over PPC disrupted performance in visual search when participants had to decide whether a single item presented was a target or not. This impairment effect, however, was only present when target location was unpredictable. Further support comes from an fMRI study by Kristjánsson et al. (2007), who found decreased PPC activation when target form or location is known ahead of time via priming, suggesting that PPC is sensitive to predictability and unpredictability beyond salience competition between target and distractors.

Here it is important to emphasize again the goal-directed nature of the dorsal network when interpreting these results regarding PPC. Specifically, PPC does not respond to all perceptually-salient distrators, but only those that are relevant to the current task set. One important fMRI study by Downar et al. (2001) instructed participants to monitor a change either in visual or auditory modality. These authors observed increased activation in right PPC when a change occurred, but only when the change happened in the modality that is relevant to participants' current behavior. Indeed, monkey neurophysiology has already shown that lateral intraparietal cortex (LIP, equivalent to the vicinity of human PPC) encodes behaviorally salient objects (Gottlieb et al., 1998), desirable actions (Dorris and Glimcher, 2004), and the color of a cue if it is associated with an eye movement (Toth and Assad, 2002). In addition, target predictability, when leading to reward (i.e., behaviorally salient), can have a significant effect in modulating LIP activity as it can represent predictive information such as the weighted likelihood of certain shape combinations (Konen et al., 2004; Yang and Shadlen, 2007). Together, it is plausible to conclude from these studies that all manipulations of various psychological constructs such as salience (Geng and Mangun, 2008), predictability (Chao et al., 2011), reward (Yang and Shadlen, 2007), desirability (Dorris and Glimcher, 2004), and behavioral relevance (Toth and Assad, 2002; Muggleton et al., 2011), are all essentially similar in nature. That is, PPC activation is observed as long as a stimulus, be it a target or distractor, is closely matched with one's current task/goal. This idea may help generalize the nature of PPC activation across different contexts. And as such, PPC is not only crucial to spatial attention, but can also be involved in processing predictive information when such information is perceptually or behaviorally relevant, or salient.

## **FRONTAL EYE FIELDS**

On the other end of the dorsal attentional network is FEF. As its name implies, much of the work on FEF have been devoted to the oculomotor control of eye movements and visual attention, although studies have begun to document FEF involvement in other domains of cognition such as inhibitory control (e.g., Muggleton et al., 2010). Early studies such as Miller (1988) studied the effects of absolute and relative target position. A target letter was to be detected in a sequence of four letters in which one location had a higher probability of containing the target. The letter sequence was occasionally offset in horizontal position to probe whether the effects of high probability was dependent on absolute position or the position in the sequence (relative position). It was found that target location probability benefited from both types of spatial relationship. Subsequent study by Kingstone and Klein (1991) also demonstrated that people can be sensitive to the likelihood that a specific stimulus form would appear in a particular spatial location.

More recently, Geng and Behrmann (2005) investigated the role of targets' spatial probabilities in a visual conjunction search task, combined with endogenous and exogenous cues. These authors found that spatial probability indeed induced an implicit facilitation to attentional orienting. But most importantly, the facilitation from spatial probability is additive to the explicit endogenous cue (the effect was purely additive) and interacted with the salient exogenous cue. Thus, the effect of probability in visual selection seems to occur early at the stage where salient exogenous cues are processed. To further investigate this issue, Liu et al. (2010) used a similar setup while recording participants' eye movements. In this version of the task, participants responded with pro- and antisaccade eye movements, which refers to eye movements toward (pro) and away from (anti) the target (**Figure 2A**). Prosaccades have been consistently found to have shorter and longer RT due to the extra stages of suppression in antisaccades (termed the antisaccade cost; Everling and Fischer, 1998; Kristjansson, 2007; Kristjánsson et al., 2001; Kristjansson et al., 2004; Olk and Kingstone, 2003; Munoz and Everling, 2004), and therefore the magnitude of the antisaccade cost provides a suitable measure of the modulating effect that probability may have on oculomotor control. These authors found that under these conditions, prosaccades to the probabilistically-salient location became faster. The sizes of the antisaccade cost also changed to compliment the magnitude of prosaccade probability. Most important, the saccade RTs followed the magnitude of probability saliency such that the RTs decreased gradually as the probability of a certain location increased, and vice versa (**Figure 2B**). Together, these results suggest that the oculomotor system is sensitive to multiple levels of spatial probability. It is important to note that both studies by Geng and Behrmann (2005) and Liu et al. (2010) accounted for the effect of repetition priming by taking trial-totrial RT facilitation into account. While the effect of repetition priming is undoubtedly present, the effect of spatial probability is independent of such effect.

The neural mechanism behind such spatial probability learning in oculomotor behaviors likely involves FEF, as it tends to produce pretarget-related neural activity during saccade selection and saccade preparation, respectively (Schall et al., 1995; Thompson et al., 1996, 1997; Schall, 1997; Bichot and Schall, 2002; Sato and Schall, 2003; Juan et al., 2004, 2008). Note that, however, the bilateral FEF both have distinctive functions in mediating oculomotor control. Studies have shown that the left FEF behaves much like the right PPC, where it is mostly involved when target location is unpredictable. One notable study by Lane et al. (2012) manipulated spatial predictability via spatial priming in a visual search task while applying TMS over either left FEF, right FEF, or right PPC. These authors found that when target location was predictable, TMS only increased reaction time when

2011). Participants were shown a central disc that cued either a prosaccade or antisaccade. This paradigm is able to manipulate levels of probability in prosaccade locations but not antisaccade locations. Behavioral results suggested that these two types of saccades can indeed be dissociated since the effect of probability in prosaccade is not transferred to the same location in an antisaccade. **(B)** Effect of spatial probability on antisaccade cost and SRT from Liu et al. (2010, 2011). This figure shows how the magnitude of antisaccade cost correlates linearly with the level of prosaccade probability. This is because the prosaccades are facilitated by spatial probability while antisaccade SRT remained relatively similar, thereby creating bigger discrepancies between the two SRTs (antisaccade cost).

it was applied over the right FEF, and not the left FEF or the right PPC. Their findings suggest that left FEF and right PPC are only involved when target location is unpredictable (also see Campana et al., 2007), whereas the right FEF is more involved in top-down visual attention that treats predictability in a task-driven manner. In addition, using the same orienting paradigm and manipulation of probability as their previous study (Liu et al., 2010), Liu and colleagues (2011) applied theta burst TMS over participants' right FEF or supplementary eye fields (SEF) for 20 s (**Figure 3A**) and found that FEF TMS, but not SEF, successfully disrupted the effect of probability such that high-probability prosaccades became slower when TMS was applied. These results suggest that right FEF, but not SEF, is critical to the learning of spatial probabilities 1 in this orienting paradigm (**Figure 3B**). Furthermore, when a target becomes less predictable, the top-down effort in search of the new target also requires heavy FEF involvement, presumably because the neuronal buildup has to start over toward a new target that is either located at a new location or defined by one or more new features. As such, TMS over rFEF when target suddenly becomes unpredictable (Muggleton et al., 2003) or is no longer defined by an old set of features (Muggleton et al., 2011) will also impair saccade latency. Together, these studies suggest that rFEF is critical to the processes of target selection either via pretarget neuronal buildup (when target is predictable) or top-down attentional orienting (when target is unpredictable). Indeed, TMS over rFEF at early and late time points during an antisaccade task revealed that FEF involvement occurs at early (target selection) and late (endpoint selection) stages (**Figure 4**), both of which are necessary component for mediating the effect of probability (Juan et al., 2008). In addition, preparatory-related activities can be found in FEF with trained monkeys in an antisaccade task, where the endpoints of the probable saccade type enjoys a lower threshold or early neural activity buildup (Dorris and Munoz, 1998; Dorris et al., 2000; Everling and Munoz, 2000; Connolly et al., 2005) and speeds up the process of saccade preparation and thus decrease saccade latency. fMRI data also showed that rFEF activity can be used to predict saccadic reaction time (SRT) in humans (Connolly et al., 2005). Thus, these findings suggest that the effect of location probability on SRT could be reflective of the neural firing rate within a subpopulation of neurons in the rFEF. This may account for the role of rFEF in mediating the effects of location probability because both target and endpoint selections are necessary for the benefit of location probability to surface.

## **COMPARING FEF AND PPC**

If FEF and PPC both process predictive and probabilistic cues in the environment, how do they differ from each other in terms of timing and function? Several neuroimaging and stimulation studies that compares FEF and PPC involvement using the same paradigm may provide some clues to this question. First, in a nonpredictive visual search array, Kalla et al. (2008) applied TMS over either FEF or PPC at various timings and found that FEF involvement took place early (0–40 ms) while PPC is late (120–160 ms). But as previously mentioned, FEF involvement in oculomotor control can occur both early and late (under the right conditions), covering both stages of target selection and endpoint selection. Indeed, in the aforementioned study by Lane et al. (2012), they found that TMS over right FEF impaired visual search in both primed (predictable) and non-primed (unpredictable) condition, suggesting a general search mechanism that is mediated by right FEF. Stimulation over PPC had no effect when the target was at a predictable location, which is in line with the results from

1It is worth mentioning that due to the nature of brain stimulation, one alternative account to this pattern of result is that perhaps TMS is affecting the connections between brain regions, instead of the neural locus itself. Therefore, it remains possible that some of the stimulation results reviewed here is due to a connectivity issue of FEF or PPC's communication with other areas.

on saccade latency, results from Liu et al. (2011). Mean saccadic RTs as a function of TMS, saccade type, and probability. The top two panels indicated FEF and SEF TMS conditions, respectively. In FEF TMS condition, the pattern of the location probability effect was affected by TMS and also the general

the mean. Panel **(B)** show how right FEF TMS decreased SRT in prosaccades to the high probability location, suggesting a critical role for the right FEF in mediating the effect of spatial probability. This effect was not observed in the SEF TMS condition.

the Chao et al. (2011) study, who also found that PPC TMS is effective in saccade curvature only when target location is unpredictable. An fMRI study using a cuing paradigm also found that PPC activation was modulated by the perceptual salience of the stimuli (target and distractor alike), whereas FEF activation was associated with the location of spatial attention (Geng and Mangun, 2008). This suggests that FEF may be more involved in top-down spatial attention, whereas PPC is involved in processing task-relevant attentional influences driven by stimulus salience, both of which can be utilized in processing predictive cues in the environment.

## **CONCLUSION**

In this paper we have briefly reviewed how predictive information in the environment can powerfully modulate human visual attention and oculomotor control. Importantly, neurophysiological studies suggest that such learning requires a dynamic interplay between regions within the dorsal attentional network, which includes PPC and FEF. Specifically, FEF is responsive to predictive information via its top-down early preparatory neural activity buildup that biases the processes of target selection and saccade preparation; whereas PPC responds to salient bottom-up stimuli that carry predictive information, even if they are not targets, if such information matches one's current behavioral goal. Much of the work until now has emphasized the individual contributions of these regions to mediate probability learning. Future studies that disentangle the timing, roles, functional connectivities, and interactions between these regions will provide exciting new insights into how the visual system strategically adapts to the environment.

## **ACKNOWLEDGMENTS**

We are grateful to Neil G. Muggleton and Chang-Mao Chao for their constructive suggestions to earlier versions of the manuscript. This work was sponsored by the

#### **REFERENCES**

National Science Council, Taiwan (101-2628-H-008-001- MY4, 102-2420-H-008-001-MY3, 99-2410-H-008-022-MY3, 97-2511-S-008-008-MY5). Philip Tseng is supported by NSC (101-2811-H-008-014).

context guides spatial attention. *Cogn. Psychol.*, 36, 28–71. doi: 10.1006/cogp.1998.0681

and frontal eye fields in spatially primed visual search. *Brain Stimul*. 5, 11–17.

in visual search tasks. *J. Exp. Psychol. Hum. Percept. Perform.* 14, 453–471. doi: 10.1037/0096-1523. 14.3.453

representations for attention and action. *Neuropsychologia* 44, 2700–2716.

668–679. doi: 10.1111/j.1469-8986. 2009.00807.x

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 24 May 2013; accepted: 09 July 2013; published online: 02 August 2013. Citation: Tseng P, Chang C-F, Chiau H-Y, Liang W-K, Liu C-L, Hsu T-Y, Hung DL Tzeng OJL and Juan C-H (2013) The dorsal attentional system in oculomotor learning of predictive information. Front. Hum. Neurosci. 7:404. doi: 10.3389/fnhum.2013.00404 Copyright © 2013 Tseng, Chang, Chiau, Liang, Liu, Hsu, Hung, Tzeng and Juan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## Dissociations between spatial-attentional processes within parietal cortex: insights from hybrid spatial cueing and change detection paradigms

## *Rik Vandenberghe1,2\* and Céline R. Gillebert 1,3*

*1 Laboratory for Cognitive Neurology, Department of Neurosciences, Katholieke Universiteit Leuven, Leuven, Belgium*

*2 Neurology Department, University Hospitals Leuven, Leuven, Belgium*

*3 Department of Experimental Psychology, University of Oxford, Oxford, UK*

#### *Edited by:*

*Simone Vossel, University College London, UK*

#### *Reviewed by:*

*Emiliano Macaluso, Fondazione Santa Lucia, Italy Radek Ptak, University Hospital Geneva, Switzerland*

#### *\*Correspondence:*

*Rik Vandenberghe, Neurology Department, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium e-mail: rik.vandenberghe@ uz.kuleuven.ac.be*

Spatial cueing has been used by many different groups under multiple forms to study spatial attention processes. We will present evidence obtained in brain-damaged patients and healthy volunteers using a variant of this paradigm, the hybrid spatial cueing paradigm, which, besides single-target trials with valid and invalid cues, also contains trials where a target is accompanied by a contralateral competing stimulus (competition trials). This allows one to study invalidity-related processes and selection between competing stimuli within the same paradigm. In brain-damaged patients, lesions confined to the intraparietal sulcus result in contralesional attentional deficits, both during competition and invalid trials, according to a pattern that does not differ from that observed following inferior parietal lesions. In healthy volunteers, however, selection between competing stimuli and invalidity-related processes are partially dissociable, the former relying mainly on cytoarchitectonic areas hIP1-3 in the intraparietal sulcus, the latter on cytoarchitectonic area PF in the right inferior parietal lobule. The activity profile in more posterior inferior parietal areas PFm and PGa, does not distinguish between both types of trials. The functional account for right PF and adjacent areas is further constrained by the activity profile observed during other experimental paradigms. In a change detection task with variable target and distracter set size, for example, these inferior parietal areas show highest activity when the stimulus array consists of only one single target, while the intraparietal sulcus show increased activity as the array contains more targets and distracters. Together, these findings lead us to the hypothesis that right PF functions as a target singleton detector, which is activated when a target stands out from the background, referring both to the temporal background (expectancy) and the momentaneous background (stimulus-driven saliency).

**Keywords: area PF, temporoparietal junction, intraparietal sulcus, superior parietal lobule, invalidity, attentional priority map**

## **1. INTRODUCTION**

Spatial attention encompasses a wide set of divergent processes that govern the distribution of attentional weights over locations that are, or may be, occupied by objects. A powerful concept in spatial attention research, stemming from neurophysiology and computational neurobiology, is the "attentional priority map". The attentional priority map refers to a topographic representation of attentional weights (Bushnell et al., 1981; Koch and Ullman, 1985; Colby et al., 1996; Gottlieb et al., 1998; Itti and Koch, 2001; Bisley and Goldberg, 2003; Vandenberghe and Gillebert, 2009; Ptak, 2012; Jerde and Curtis, 2013). The attentional weights depend, among other variables, on sensory evidence (Bundesen and Habekost, 2008) obtained through multiple input channels (visual, auditory, ···). The current review will be restricted to effects obtained within the visual modality. Although attentional priorities may be sustained over a prolonged period of time (Vandenberghe et al., 2001a,b; Husain and Rorden, 2003), most evidence with regards to parietal cortex relates to its role in transitions between attentional priority maps (Vandenberghe et al., 2001a; Molenberghs et al., 2007). Here we will describe novel evidence obtained using two paradigms, the hybrid spatial cueing paradigm (Gillebert et al., 2011, 2012a, 2013) and the change detection paradigm with varying target and distracter set size (Gillebert et al., 2012b), in patients (Gillebert et al., 2011) and in the intact brain (Gillebert et al., 2012a,b, 2013), both from a localizationist and a connectionist perspective.

## **2. THE HYBRID SPATIAL CUEING TASK**

## **2.1. CONVERGING EVIDENCE FROM FUNCTIONAL IMAGING AND PATIENT LESION DATA**

Numerous experiments in humans have provided converging evidence for the distinct role of different parietal regions in spatial attention (for reviews, see Vandenberghe and Gillebert, 2009; Vandenberghe et al., 2012). Here we will focus on the hybrid spatial cueing paradigm (**Figures 1A**,**B**) which allows one to simultaneously study two key operations of spatially selective attention: selection between competing stimuli (Desimone and Duncan, 1995) and the processing of invalidly cued targets (Corbetta et al., 2000). The hybrid spatial cueing paradigm enables one to contrast the neuroanatomy of both processes within the same subjects, both in healthy volunteers and in patients with parietal brain damage, and to relate the findings to the cytoarchitectonic organization of the parietal cortex, provided that proper sensory control conditions are used (Vandenberghe et al., 2005; Molenberghs et al., 2008; Gillebert et al., 2013). Compared to baseline, the validly cued singlegrating trials require interpretation of the central arrow cue (Woldorff et al., 2004; Bonato et al., 2009), assignment of a

high attentional weight to the cued peripheral location, shortterm maintenance of that weight, detection of the grating at the cued location and discrimination of its orientation, response selection based on a conditional-associative rule and response execution. Compared to the validly cued single-grating trials, the presence of an irrelevant contralateral distracter induces a need to select a target among nearly identical distracting stimuli on the basis of the instructional spatial cue, and to suppress undue interference by the distracter's orientation on response selection. Behaviorally, competition trials are usually associated with a cost compared to valid single-grating trials (Vandenberghe et al., 2005; Molenberghs et al., 2008). By titrating the orientation difference to be discriminated, performance measures during functional magnetic resonance imaging (fMRI)

**FIGURE 1 | Experimental paradigms at the focus of the current review. (A,B)** Hybrid spatial cueing paradigm. **(A)** Timing. **(B)** Spatial cueing with single validly cued target, invalidly cued trials (20%) and competition trials (20%). For the competition trials proper sensory control experiments were conducted to tease out attentional and sensory effects of adding a distracter. **(C,D)** Change detection paradigm. **(C)** Timing and basic design. In reality the target set size was varied in discrete steps (1, 2, 4, or 6

targets) as well as the distracter set size (0, 2, 4, or 6 distracters) according to a factorial design. Letters were targets, numbers distracters. **(D)** Factorial design with varying targets (T) and distracters (D) within the array. The height of the bars corresponds to the number of targets (#T in VSTM) and the number of distracters (#D in VSTM) loaded into visual short-term memory (VSTM) in each of the cells of the factorial design, according to the Theory of Visual Attention.

can be strictly matched between the two trial types, removing the potential confound of aspecific differences in task difficulty (Vandenberghe et al., 2005; Molenberghs et al., 2008). The addition of a distracter also causes a sensory mismatch with the valid single-grating trials. Additional sensory control trials therefore are necessary to distinguish attentional effects from the sensory effect induced by adding a distracter (Vandenberghe et al., 2005; Molenberghs et al., 2008; Gillebert et al., 2013). The cognitive processes induced by invalidly cued trials have been intensively studied and described before [see Corbetta et al. (2008) for a review]. Briefly, with the delay durations and trial frequencies we used, when an invalidly cued grating appears, subjects have to detect the grating at the unexpected location and shift attention from the predicted location to the target location.

When subjects have to select between competing stimuli, the middle segment of the intraparietal sulcus (IPS) is consistently more active compared to single stimulus conditions (Vandenberghe et al., 2005; Molenberghs et al., 2008; Gillebert et al., 2012a, 2013) This difference in middle IPS activity between double stimulation and single grating stimulation is absent under sensory control conditions where attention is directed centrally (Vandenberghe et al., 2005; Molenberghs et al., 2008; Gillebert et al., 2013). When the functional activity map obtained in healthy volunteers by contrasting competition trials vs. singlegrating trials is overlaid with the voxel-based lesion-symptom map obtained in patients with unifocal cortical stroke from a closely similar contrast, the overlap is situated at the lower bank of middle IPS (Molenberghs et al., 2008). This provides evidence that the deficit in spatially selective attention following inferior parietal lesions can be accounted for by extension of the lesions into the lower bank of the middle IPS which is also activated in healthy controls (Molenberghs et al., 2008). Further evidence for the critical role of middle IPS in this selective attention paradigm comes from a detailed study of a case with a reversible lesion confined to middle IPS with extension into the superior parietal lobule caused by a venous sinus thrombosis, case NV (**Figure 2A**): the lesion provoked a deficit during spatial cueing when a distracter was present ipsilesionally compared to single-stimulus conditions and also during invalidly cued trials (Gillebert et al., 2011) (**Figure 2B**). The effect of adding a distracter was limited to the contralesional target conditions while the effect on invalidly cued trials was present for both ipsi- and contralesional targets (Gillebert et al., 2011; Vandenberghe et al., 2012). The shifting deficit for both left- and rightward attention may possibly be due to the extension into the superior parietal lobule (see below) (Vandenberghe et al., 2001a; Yantis et al., 2002; Molenberghs et al., 2007). When the lesion partially regressed due to the resolution of vasogenic edema, the behavioral deficit also recovered (**Figure 2B**) (Gillebert et al., 2011).

Studies of rare focal lesions in parietal cortex have been fruitful in elucidating the critical role of specific parietal areas during

**FIGURE 2 | (A,B)** Case NV. **(A)** In green the right middle IPS lesion in case NV, affecting the horizontal segment of IPS with extension into the superior parietal lobule. **(B)** NV's accuracy (expressed as A- ) obtained in the different conditions of the hybrid spatial cueing paradigm (red), compared to age-matched controls (black). NV was tested on two instances. On day 4

(full red line) the lesion was as visualized in **(A)**, on day 107 the lesion had substantially regressed (dotted red line). For more details see Gillebert et al. (2011). **(C,D)** Case HH. **(C)** In blue the left posterior IPS lesion in case HH. **(D)** HH's performance obtained in the different conditions of the hybrid spatial cueing paradigm (red), compared to age-matched controls (black).

spatially selective attention and reorienting. Such lesions can have a size of only one or a few cm3, sparing white matter tracts and sometimes with only limited effects on connected regions at a distance (Gillebert et al., 2011). Such lesions provide a spatial resolution far beyond what can be obtained from ischemic lesions of major branches of the middle cerebral artery. In order to properly evaluate the functional effects at a distance, restingstate (Carter et al., 2010; Gillebert et al., 2011; Gratton et al., 2012) or task-related fMRI (He et al., 2007; Gillebert et al., 2011) in the same patients is often essential. The value of such a multimodal imaging approach is also clear from a second case (case HH) with a focal lesion of the descending segment of left IPS, (**Figure 2C**), giving rise to a strictly lateralized contralesional spatial-attentional deficit (**Figure 2D**) (Gillebert et al., 2011). The lesion was significantly smaller than NV's lesion and confined to posterior IPS only (**Figure 3**). The lesion hit an area largely corresponding to IPS0/1. IPS0/1 is a visually responsive retinotopically organized region (Silver and Kastner, 2009; Bressler and Silver, 2010) that shows increased activity when attention is directed to the contralateral hemispace (Yantis et al., 2002; Vandenberghe et al., 2005; Vandenberghe and Gillebert, 2009). Apart from effects of the direction of attention, IPS0/1 is also influenced by spatiotopic mnemonic factors (Sheremata et al., 2010; Jerde and Curtis, 2013). Gillebert et al. (2011) reported the first evidence of the consequences of a lesion of IPS0/1. A lesion of left IPS0/1 preserves the visual fields leaving performance during single-target valid trials intact (**Figure 2D**). When the attentional demands are increased by adding an ipsilateral distracter, performance drops for contralesional targets. This is also true following an invalid spatial cue (**Figure 2D**). The deficit is not due to functional effects at a distance: in the IPS0/1 lesion case, both task-related and resting-state fMRI reveal that the inferior parietal lobule and the ventral attention network (Corbetta and Shulman, 2002; Corbetta et al., 2008) are functioning within a normal range (Gillebert et al., 2011). Although no right-sided isolated IPS0/1 lesions have been reported as yet, a recent study showed that repetitive transcranial magnetic stimulation (TMS) over the right IPS0/1 of healthy volunteers impairs target discrimination in the contralateral side of space (Capotosto et al., 2013). Together with results from fMRI activity in the intact brain (Yantis et al., 2002; Vandenberghe et al., 2005; Xu and Chun, 2006; Molenberghs et al., 2008; Xu and Chun, 2009), these findings can be integrated in a functional-anatomical model where IPS is subdivided in different areas (**Figure 4**). Posterior and middle IPS may intervene at different stages of attentional selection. The effects of IPS0/1 lesions can be accounted for by a strictly lateralized loss of attentional enhancement of a visual response to contralateral stimulation under attentionally demanding conditions (**Figure 4**). The middle IPS segment, on the other hand, may be involved in calibration of attentional weights for individual visuoperceptual units. According to this hypothesis, the role of IPS0/1 in attentional enhancement is defined in purely spatial coordinates while the contribution of middle IPS occurs at a stage where individual objects that occupy specific locations have already been identified (Xu and Chun, 2006, 2009; Gillebert et al., 2012b). This hypothesis is principally founded on fMRI studies in the intact brain (Vandenberghe et al., 2005; Xu and Chun, 2006, 2009) (for review, see Vandenberghe and Gillebert, 2009) and still requires further validation. It is compatible with the performance deficits seen in the two single cases with IPS lesions. By themselves, the differences in behavioral deficits between NV and HH should not be overinterpreted: the attentional deficits in these two cases do not constitute a double dissociation, the lesions do not only differ in hemispheric side but also in extent and degree of involvement of the superior parietal lobule, and the posterior portion of NV's lesion overlaps substantially with HH lesion (**Figure 3**). The different degree of laterality of the spatial-attentional deficit between the two cases does not necessarily mean that the right IPS has a more bilateral representation of space than the left (Weintraub and Mesulam, 1987). It can also be explained by the extension of NV's lesion into the medial wall of the superior parietal lobule which has involved in spatial shifting regardless of hemispace or direction (Vandenberghe et al., 2001a; Molenberghs et al., 2007). Based on a recent single-pulse TMS experiment (Szczepanski and Kastner, 2013), we would predict that a right-sided IPS0/1 lesion would give a similarly lateralized left-sided deficit as that provoked by the left-sided lesion in HH to the right, but this remains to be proven.

Noteworthy, the behavioral deficit on invalid or competition trials following focal IPS lesions does not differ statistically from the deficits following typical inferior parietal lesions that clinically lead to hemispatial neglect or visual extinction (**Figure 5**) (Gillebert et al., 2011). At first this may seem to contradict

canonical findings reported by Friedrich et al. (1998) but detailed analysis of the data reported by Friedrich et al. (1998) shows that in fact the two studies are compatible. The Friedrich et al. (1998) study is often interpreted as if it localizes the pathological increase of the invalidity effect to the inferior parietal cortex as opposed to superior parietal cortex. In the Friedrich et al. (1998) study, however, the main analysis did not contrast superior with inferior parietal lesions but parietal lesions extending into the superior temporal gyrus (STG) (the "TPJ" group) with parietal lesions that do not extend into STG (the "PAR" group). The "PAR" cases also had inferior parietal damage and some of the "TPJ" lesions extended into superior parietal cortex. Furthermore, the sensitivity for detecting a shifting deficit in the "PAR" group was probably relatively low given the complex factorial design (4 factors) (for a detailed discussion, see Vandenberghe et al., 2012). A voxel-based lesion-symptom mapping study in 20 left-sided neglect patients also confirmed that IPS is one of the critical regions associated with a contralateral orienting deficit and a pathological increase of the invalidity effect for contralateral targets, along with the temporoparietal junction (TPJ) and middle frontal gyrus (Ptak and Schnider, 2011).

It is important to note that the hybrid spatial cueing paradigm isolates specific components of the spatial-attentional deficits that can be seen clinically following parietal lesion. While a deficit in the competition trials compared to the single-grating trials can occur even when the clinical extinction test is within the normal range, as of yet we have not encountered clinical extinction without a deficit in the competition trials (Molenberghs et al., 2008; Gillebert et al., 2011). Likewise, patients with a deficit on target cancelation whom we tested always had a deficit on the invalid trials compared to the single-grating trials (Molenberghs et al., 2008). It is worth noting that our data are principally based on patients with unifocal cortical lesions who can do computerized testing in the acute stage with a proper sitting balance and therefore has not included patients with moderate or severe neglect.

A further parietal structure, the superior parietal lobule (SPL), has been implicated by numerous functional imaging studies (Vandenberghe et al., 2001a; Yantis et al., 2002; Shomstein and Yantis, 2004; Molenberghs et al., 2007; Serences and Yantis, 2007; Kelley et al., 2008) in the spatial displacement of the focus of attention. This is surprising as previous lesion evidence in humans provided relatively few hints for a role of superior parietal lobule in spatial shifting. According to recent evidence, however, based on the hybrid spatial cueing paradigm (Vandenberghe et al., 2012), a bilateral lesion of SPL leads to an impairment in shifting attention from the invalidly cued location to the target, regardless of its location and with preserved performance during competition trials. Medial parietal and superior parietal lesions also lead to an increased movement time during visual search (Müller-Plath et al., 2010). Recent electrophysiological recording (Brignani et al., 2009) and electrophysiological stimulation studies (Capotosto et al., 2013) have provided further evidence for the critical role of SPL in spatial shifting. A spatial shift against a sustained attention baseline provokes an event-related potential starting around 330 ms with posterior parietal distribution which does not depend on the direction of the shift, leftward or rightward (Brignani et al., 2009). Furthermore, 150 ms of repetitive TMS at 20 Hz targeting right superior parietal medial cortex 500 ms prior to onset of the shifting cue impairs target discrimination regardless of target location, in left or right visual fields (Capotosto et al., 2013).

At the moment, what is missing is statistical evidence for a double dissociation between spatial attentional processes when patients with focal lesions of parietal cortex in different locations are directly compared to each other, hence the importance

of defining functional dissociations in the intact brain. The latter studies can then serve as a basis for designing paradigms in patients that may be successful in detecting double functional dissociation following lesions.

## **2.2. HYBRID SPATIAL CUEING WITHIN A CYTOARCHITECTONIC REFERENCE FRAME**

TPJ is consistently activated when reorienting attention or during breaches of expectancy (Corbetta et al., 2000). Coordinates of TPJ foci, however, vary widely between studies (Decety and Lamm, 2007; Mars et al., 2012). The inferior parietal lobule, which encompasses TPJ, is by no means homogeneous cytoarchitectonically (Caspers et al., 2006, 2011). According to cytoarchitectonic studies of postmortem brains, the angular gyrus can be subdivided into areas PGa and PGp, and the supramarginal gyrus into areas PFop, PFt, PF, PFm, and PFcm (Caspers et al., 2006, 2011) (**Figure 6A**). Are these human cytoarchitectonic areas differentially involved in competition vs. invalid trials (Gillebert et al., 2013) when controlling for expectancy (trial frequency kept at 20% of all trials for each of the two types of trials)? To answer this question, we applied a dual approach: starting from the cytoarchitectonical divisions, we defined volumes of interest and compared the aggregate response amplitude between the single target trials, the competition trials and the invalid trials in the hybrid spatial cueing paradigm. In a second approach, starting from the functional activity map, we overlaid the activations on the cytoarchitectonic map in order to evaluate to which degree functional boundaries coincide with cytoarchitectonic boundaries (Gillebert et al., 2013). The main challenge is the inter-individual variability in the extent and boundaries of the cytoarchitectonic areas and the probabilistic nature of assignment of voxels to a specific cytoarchitectonic area. This variability has been estimated from a relatively small set of postmortem brains (*n* = 10). This information is incorporated in the probabilistic maps (Eickhoff et al., 2005, 2006). The variability between subjects in size and borders can be relatively high in specific areas, such as hIP1-3 (Scheperjans et al., 2008).

Right PF is the only area exclusively activated for invalid vs. valid trials and not during competition trials (Gillebert et al., 2013) (**Figure 6B**). In right PF the difference in response amplitude between invalid and valid cueing is significantly larger than the difference between competition trials and single-target trials (Gillebert et al., 2013). In contrast, cytoarchitectonic areas hIP1 and hIP3 in IPS exhibit significantly higher activity levels during competition trials compared to invalid trials (**Figure 6B**). Other inferior parietal areas, such as PFm, PGa, and PGp, were bilaterally involved both in competition and invalid trials, without any significant differences between the two trial types (**Figure 6B**). The differential activity pattern between hIP1- 3 and PF provides evidence for a functional dissociation between two types of attentional processes, those related to invalidity vs. processes of selection between competing stimuli. Note that Friedrich et al. (1998) suggested the term "extinction-like" for the invalidly cued trials but according to the above evidence, selection between competing stimuli and spatial reorienting following invalid cues are anatomically dissociable processes. A probabilistic tractography study (Caspers et al., 2011) suggested that PFm and PGa corresponded to the TPJ node of the ventral attention network (Corbetta and Shulman, 2002). Instead, our fMRI findings within a cytoarchitectonic reference frame suggest that right PF is most tightly linked to the invalidity effect in the classical spatial cueing paradigm while PFm and PGa are more generally involved in invalid as well as competition trials, at least when both trial types have a low expectancy rate.

In a second step, we superimposed the activity clusters obtained by contrasting the invalid with the valid single-target trials and by contrasting the double- with the single-target trials onto the cytoarchitectonic map (Gillebert et al., 2013). Boundaries of activation did not follow boundaries between cytoarchitectonic areas. This may suggest that, for the cognitive operations fulfilled by inferior parietal cortex, there is no functional segregation within strict cytoarchitectonic boundaries. This is also apparent from the connectivity pattern of the cytoarchitectonic areas which shows gradients between areas rather than strict segregation (**Figures 6C**,**D**) (Caspers et al., 2011; Gillebert

areas as derived from Caspers et al. (2006). **(B)** Time-activity curves in a selection of cytoarchitectonic areas that showed differential effects between the competition trials, the invalid and the valid single-target trials. **(C)** Hierarchical clustering analysis based on the time courses during resting-state fMRI in the different cytoarchitectonic areas that

cueing paradigm. **(D)** Functional connectivity matrix. The cross-correlation matrix is sorted on the basis of the hierarchical clustering results, so that adjacent VOIs have the most similar connectivity profiles. Significant correlations (*P <* 0*.*05, Bonferroni-corrected for the number of pairwise comparisons) are indicated by a black dot.

et al., 2013). There was, however, one exception: the contrast of invalid vs. valid trials yielded a right inferior parietal activity cluster that coincided relatively closely with area PF (Gillebert et al., 2013).

## **2.3. INVALIDITY, COMPETITION, AND CONNECTIVITY**

Next, we evaluated to which degree the different cytoarchitectonic areas belong to different resting-state networks (Gillebert et al., 2013). First, we derived the time courses of each of the cytoarchitectonic areas and performed a hierarchical clustering analysis (**Figure 6C**). Right PF was the only parietal area where the time course did not cluster with any of the other parietal regions. The time courses of hIP1-3 clustered with the time courses of PFm (Gillebert et al., 2013). When we used the cytoarchitectonic areas as seeds for a resting-state connectivity analysis across the entire brain, the patterns we obtained were in line with prior evidence (**Figure 6D**): Right PF belonged to a network with inferior frontal gyrus and anterior insula, hIP1-3 and PFm were connected to prefrontal cortex, and PGa was part of the default mode network (Gillebert et al., 2013). The connectivity pattern of PFm and PGa/PGp may provide hints about their functional contribution. PFm has been implicated in the multiple demand network (Duncan, 2010) or "executive control network" (Seeley et al., 2007) while PGa/PGp probably corresponds to the inferior parietal nodes of the default mode network.