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\rhead[W. Rollason]{William Rollason}
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{E-I imbalance and ASD}
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\begin{document}



\title{Investigating the effect of E-I imbalance, and its effects }
\author{William Rollason}
\maketitle

\part{Case for support}
\section{Neuroscience background}
\noindent
Computational neuroscience is a branch of neuroscience which studies information processing in the brain using mathematical models. These models are usually too complex to be studied analytically so must be solved numerically using a computer. Research institutes such as the Allen Institute for Brain Science have conducted morphology and electropyhsiology experiments on both human and mouse neurons. Their data is made freely available and can be used to fit parameters for biologically accurate mathematical models of neurons. These models can then be used to directly test hypotheses about the biological systems that they represent. 
\\\\
The mammalian brain is made up of several billion neurons. Neurons consist of a cell body (soma), many dendrites and a singular axon. Incoming signals arrive at the dendrites, if there is enough stimulation an action potential is created that propagates down the neuron to the axon terminals. The space between the axon terminals and the dendrites of the next neuron is called a synapse. At a synapse the electrical signal from an action potential is converted into a chemical signal in the form of different types of neurotransmitter. This neurotransmitter travels across the synaptic cleft to the post-synaptic neuron's dendrite where it binds to a receptor.

\begin{figure}[ht]
  \includegraphics[width=0.7\linewidth]{img/Synapse_khan.png}
  \caption{Two neurons connected by a synapse. Image taken from Khan Academy, CC BY-NC-SA 4.0 }
  \label{fig:synapse}
\end{figure}

\noindent
In some cases this neurotransmitter will cause the post synaptic neuron to depolarise and therefore more likely to create an action potential, this is called an excitatory post synaptic potential. Otherwise the neurotransmitter will cause the membrane potential to decrease and the neuron will be less likely to create an action potential, this is called an inhibitory post synaptic potential.\\

\begin{figure}[ht]
  \includegraphics[width=0.7\linewidth]{img/Action_potential.png}
  \caption{A typical action potential produced from several excitatory post synaptic potentials. Image taken from Khan Academy, CC BY-NC-SA 4.0 }
  \label{fig:synapse}
\end{figure}

\section{Autism spectrum disorders}
\noindent
Autism spectrum disorders are a group of lifelong neurodevelopmental disorders. Autistic individuals often have problems with social interactions and communication, restricted interests and repetitive behaviours. The most recent prevalence studies show that 1.1\% of the UK population may be on the autism spectrum \cite{brugha2012estimating}. This is about 700,000 people and including affected families, autism spectrum disorders affect about 2.8 million people. The prevalence of autism spectrum disorders also has a marked influence on the UK economy. An individual with ASD and an intellectual disability is estimated to cost $ \pounds 1.5m $ over the course of their lifetime \cite{buescher2014costs}. These costs are mostly due to the provision of special education, lost employment (from the individual and the parents of the individual), and specialised residential care. 
\\\\
Care must be taken in steering away from the idea that autism can be cured, some see it as a normal variation in the human genome and a cure would be taking away from what makes an individual who they are. However, it cannot be ignored that ASD has a huge impact on the individuals diagnosed with the disorder, their families and society as a whole. Therefore, with more research, treatments can be developed that reduces these impacts whilst retaining the essence of the individual.
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Currently only behavioural and pharmacological treatments are available that help with the symptoms of ASD (such as anxiety and ADHD), and these are only effective for a fraction of patients. There is no known medication that can alleviate the central symptoms of autism, that is the social and communication deficits \cite{buitelaar2003have}.
\\
\section{E-I imbalance}
\noindent
Despite recent research linking several genes to autism, the underlying neurological causes are still a mystery. However, the leading theory for the aetiology of autism spectrum disorders is that there is some imbalance in the ratio of excitation to inhibition in the brain. Excitatory signals cause target neurons to fire whilst inhibitory signals suppress target neurons. The ratio of these two signals is called E-I balance. E-I balance is vital in maintaining normal brain function as it regulates the transfer of information throughout the brain. Too much excitation and neurons will constantly spike whereas if there is too much inhibition the neurons will not spike at all. In either of these states no information can be transferred (this is a similar concept to how in binary a series of just 1s or just 0s transfers no information, it is the combination of both in certain patterns that encodes data).
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An early study by Rubenstein and Merzenich \cite{rubenstein2003model} linked some forms of autism with high levels of excitation or low levels of inhibition in brain areas associated with sensory, mnemonic, social and emotional systems. They also postulated that E-I imbalance was caused by both genetic and environmental variables affecting a given neural system. Since then there has been plenty of research into the subject and any links to autism spectrum disorders \cite{gogolla2009common, nelson2015excitatory, cellot2014gabaergic}.
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Excitation-inhibition imbalance has been clearly observed in mouse models of autism spectrum disorders. Pharmacological or cell type-specific gene rescue carried out on these models rescues any autistic like symptoms. These studies into animal models have shown that there is a clear link between E-I imbalance and ASD, however, they are all using invasive techniques such as optogenetics or using genetically modified mice. Obviously these techniques cannot be used in humans, and therefore, we do not know if the mechanisms studied in mice bare any relevance to ASDs in humans. Quantifying the relationship between mouse and human neurons under the influence of different E-I conditions will be the basis of this project. 
\\
\section{Integrate and fire models}
\noindent
The simplest model of a neuron is the leaky integrate and fire neuron. This was proposed in 1907 by Louis Lapicque who modelled a neuron as a resistor and capacitor in series.
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As there is such a diverse range of neurons in the mammalian cortex the standard leaky integrate and fire does not emulate them all. Therefore for the simulator the leaky integrate and fire neuron will be enhanced with a number of generalisations. These generalisations will be based upon the ones described in \citeauthor{teeter2018generalized}\cite{teeter2018generalized} and will include after-spike current, threshold adaptation and biologically defined reset rules.
\\
\section{Project Objectives}
\noindent
The overarching aim of the research will be to investigate the links between E-I imbalance and autism spectrum disorders, and whether there is any substantial difference between the effects of E-I imbalance in human and animal models. This will be done through the use of computational models of neurons which have inputs from both excitatory and inhibitory synapses. Both mouse and human neurons will be simulated with varying inputs. The results from the models will then be compared to see if there is any difference in how sensitive the neurons are to changes in excitatory and inhibitory inputs.
\\
\subsection{Work package 1:}
\noindent
To accomplish this a generalised leaky integrate and fire simulator will be written in Python based on the equations proposed in the Allen Institute's GLIF technical paper \cite{allen2017GLIF}. The simulator will allow for inputs from both excitatory and inhibitory synapses and output a voltage trace and mean firing rate. The synapses will be simulated using Poisson spike trains with refractory periods. Creating the functions for this simulator will make up work package 1.
\\
\subsection{Work package 2:}
\noindent
Once the simulator is completed several experiments will be conducted using it. The first experiment will examine the effect of changes in synaptic weight on the output of a neuron. Excitatory and Inhibitory weights will be varied and changes in output firing rate observed. 
\\\\
The second experiment will involve varying the firing rates of the excitatory and inhibitory synapses and observing the outputs. Again 
\\\\
Using a doubly stochastic Poisson process, spike trains will be created according to a correlation matrix. This allows testing of the effects of correlation between the excitatory and inhibitory inputs. It will also the excitatory synapse inputs to be correlated with each other and similarly with the inhibitory inputs. 
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All the experiments will be run on the 1218 neurons with GLIF models available from the Allen institute. Each experiment will be run several times and results averaged as they will be slightly different given the random nature of the Poisson inputs. Several runs of each simulation combined with the number of neurons means this will be a very compute-intensive project.
\\\\
Finally, a metric will be created for each neuron that encapsulates how sensitive it is to imbalances in synaptic weight and synaptic firing rate. These can then be compared between human and mouse neurons to see if there is any difference.
\\
\subsection{Work package 3:}
\noindent
The third work package will contain similar experiments to work package 2. However, instead of running experiments on a single neuron, a network of neurons will be created. This requires many of the individual neuron simulators from work package 1 to be hooked up together. The network will be tested with varying excitatory and inhibitory synaptic weight and output analysed. It will then be tested with varying firing rate for the first layer of neurons. As there are many neurons in the network computation time multiplies, and so, there may not be enough time to simulate all of the neurons available. However, simulating the network with a reasonable subset of the neurons available should still provide some meaningful results that can be analysed.
\\
\subsection{Work package 4:}
\noindent	
All of the simulators created will be wrapped up in a GUI driven software package that will be distributed open source to the neuroscience community. This will allow experimental neuroscientists, who may not be familiar with programming, to input their neuronal data and conduct similar experiments to those that were done in work package 2 \& 3 without the need to code their own simulations.
\\
\subsection{Work package 5:}
\noindent
Work package 5 will mainly consist of distributing results and software. Firstly, a paper publicising the findings of work package 2 \& 3 will be written and submitted to eLife journal. The software created in work package 4 will be documented and then distributed freely and open source. Hopefully this will allow others to contribute more features and will aid in uptake of the software. A two day workshop will also be run during work package 5 to instruct a group of 30 experimental neuroscientists in how to use the software. Finally all of the findings and software will be presented at the Bernstein computational neuroscience conference in Berlin. 
\\
\section{Management plan}
\noindent
I will take responsibility for overall coordination and management of the project. The two PDRAs will lead on work package 2 \& 3 respectively and will have responsibility for one PhD student each to assist them. As work package 2 \& 3 contain similar experiments, the two PDRAs will meet regularly with each other and myself to discuss findings and to keep everyone up to date on progress.
\\\\
Work package 5 will require a technician to be hired to assist in the creation of the software package. The technician will collaborate with the two PDRAs and PhD students as they will have direct experience with the simulator and will know what features to concentrate efforts upon.

\part{Budget}
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\begin{tabular}{ p{2.5cm} p{7cm} P{3cm} }
 \hline
 %\multicolumn{3}{c}{Budget} \\
 Description & Purpose & Cost\\
 \hline
 Post-doctoral researcher   & For the 3 years. Will lead on work package 2. &  $\pounds 300,000$\\[5pt]
 Post-doctoral researcher   & For the 3 years. Will lead on work package 3.  &  $\pounds 300,000$\\[5pt]
 PhD student   & To do some research. Assist on work package 2.  &  $\pounds 100,000$\\[5pt]
 PhD student   & To do some research. Assist on work package 3.  &  $\pounds 100,000$\\[5pt]
 Computers   & 6 MacBook Pros for all of the researchers and technician at $\pounds 2,000$ each \& 1 Mac Pro work station at $\pounds 5,000$ &  $\pounds 17,000$\\[5pt]
 Conferences  & 4 Researchers and myself to go to one international conference each year for the three years of the project. Including travel expenses, accommodation, food and conference fees at $\pounds 1,500$ per person per conference.  &  $\pounds 22,500$\\[5pt]
 Technician   & To help with creating the software package. Most likely a computer science graduate with programming experience, preferably in UI design.   &  $\pounds 30,000$\\[5pt]
 Publishing costs   & Cost of publishing a paper to eLife journal at $ \$ 2500 $ & $\pounds 1,950$\\[5pt]
 Salary   & I will devote 20\% of my time to overseeing the project   &  $\pounds 20,000$\\[5pt]
 Workshop   & 2 day workshop for 30 participants, including catering and room hire. &  $\pounds 2,200$\\[5pt]
\cline{3-3}\\
 & & $ \pounds 893,650 $ \\
\end{tabular}
\end{center}

\part{Justification for resources}
\noindent
A technician is required to help build the software package and GUI. This is because the researchers will be computational neuroscientists and will not have much if any experience in building this type of application. The technician will also be able on hand to help during the workshop to clear up any technical problems.
\\\\
The computational neuroscience conferences attended by the project participants will help to keep the researchers up to date with the current state of the field as well as allowing them to discuss finding with other academics. 
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All participants will require computers to complete work on, these will be MacBook Pros to allow efficient work and also act as a good testing benchmark for software created in work package 4. A powerful workstation is also required as the programming tasks during work package 2, 3 \& 5 will be very iterative and compute intensive. This will take the form of a single 8-core Mac Pro server.
\\\\
The workshop run during work package 5 will also incur costs. Firstly to book a room at the University of Bristol ($\pounds 400$ per day for two days, totalling $\pounds 800$) and secondly to provide catering for the 30 participants and 5 presenters ($\pounds 20$ per person, per day, totalling $\pounds 1,400$).
\\
\part{Impact plan}
\noindent
Myself and the PhD students and Post Docs will attend one international computational neuroscience conference each year of the project (Most likely the Bernstein conference in Berlin or the CNS meeting in Barcelona). In the final third year of the project we will present our findings and software to one of these conferences. 
\\\\
A paper publishing the findings will be submitted to eLife journal, a well respected scientific journal with a 2017 impact factor of 7.6. eLife has a neuroscience section that will help publicise findings and software to both computational and experimental neuroscientists. Upon submission the paper will also be uploaded to biorxiv.org (a free pre-print service) to make our findings immediately available to the scientific community.
\\\\
The project will reach out to the National Autistic Society to help with evaluations and best practice within the project. Collaborating with the national autistic society will hopefully allow us to set-up talks for the general public who have been affected by autism. This will mainly be for parents of autistic children who are usually interested in any new research. The National Autistic society will also be able to publicise our findings through their social media to further increase visibility (e.g. through their twitter account which currently has 161,000 followers).
\\\\
The projects findings will also be distributed to therapeutics companies who are currently developing pharmacological treatments for autism. Depending on the results of the project, it will either reinforce the usefulness of drugs developed based on mouse models or cause a change in course. 
 \\\\
Considering the high prevalence of autism spectrum disorders and incurred cost to the economy, research into possible are inherently valuable to the general public. Therefore research such as this that will hopefully advance the creation of pharmacological therapeutics for autism will have an impact 
engage with public. parents of autistic children usually interested in work
\part{Work plan}
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\noindent The training section will consist of making sure all involved are proficient in the use of Python and ensuring that they are up to date with the literature surrounding E-I imbalance theories. Researchers will also be taught statistical methods for multivariate analysis which will be particularly useful in analysing results during work package 2 \& 3. This section will also allow time for hiring a technician to assist with work package 4.
\\\\
Elemnents of work package 5 can be completed without the completion of work package 4, hence the overlap. However distribution of any software will need to wait for work package 4 to be completed. 
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