Systems and methods to analyze decision-making. A processor accesses at least one storage medium storing a high-fidelity recording, the high-fidelity recording includes a stimulus event and one or more rules associated with the stimulus event. The processor presents the high-fidelity recording through a presentation device. The processor receives neural metrics from a neural sensor while the high-fidelity recording is being presented. The processor applies rules to generate reference metrics associated with the stimulus event. The processor modifies elements of the high-fidelity recording based on the reference metrics to distinguish the stimulus event within the high fidelity recording. The processor presents the modified recording by the presentation device.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: accessing, by at least one processor, at least one storage medium storing a high-fidelity recording, wherein the high-fidelity recording includes a stimulus event and one or more rules associated with the stimulus event; presenting, with the at least one processor, the high-fidelity recording through a presentation device; receiving, at the at least one processor, one or more neural metrics from at least one neural sensor while the high-fidelity recording is being presented; applying, with the at least one processor the one or more rules to generate one or more reference metrics associated with the stimulus event; modifying, with the at least one processor, one or more elements of the high-fidelity recording based on the one or more reference metrics to distinguish the stimulus event within the high fidelity recording; and presenting, with the at least one processor, the modified recording by the presentation device. 2. The method as defined in claim 1 further comprising: receiving, at the at least one processor, one or more behavioral metrics from at least one other sensor while the high-fidelity recording is being presented; and presenting, with the at least one processor, a review recording comprising the reference recording, the one or more neural metrics, and the one or more behavioral metrics by the presentation device or another presentation device. 3. The method as defined in claim 1 further comprising generating at least one time marker for each of the one or more reference metrics based on a timer, the one or more neural metrics and the one or more behavioral metrics in response to the application of the one or more rules to the high-fidelity recording. 4. The method as defined in claim 3 further comprising processing the review recording to modify the one or more recording elements to correspond with a time marker associated with the one or more reference metrics. 5. The method as defined in claim 3 further comprising processing the review recording to modify the one or more recording elements to correspond with at least one time marker associated with the one or more neural metrics and the one or more behavioral metrics. 6. The method as defined in claim 1, wherein the one or more recording elements corresponds to an output in a form perceptible to a subject. 7. The method as defined in claim 6, wherein the one or more recording elements include at least one of a visual, an audio, or a tactile response. 8. The method as defined in claim 1 further comprising: generate one or more identifiers based on the one or more review metrics, the one or more neural metrics, and the one or more behavioral metrics, wherein the identifier is one of a text, a visual or an auditory identifier; overlay the one or more identifies onto the review recording; and present the review recording and the one or more identifiers to a subject. 9. The method as defined in claim 1, wherein a user input is collected by the sensor and transmitted to the controller by one of a wired or a wireless communication. 10. The method as defined in claim 9, wherein the sensor comprises at least one of an electroencephalogram, a mechanical switch, and a camera. 11. The method as defined in claim 1, wherein the high-fidelity recording comprises an audio-visual presentation. 12. The method as defined in claim 1, wherein the high-fidelity recording comprises an immersive training environment, wherein the recording elements comprise at least two of a temperature, a pressure, an olfactory stimulus, vibration, and movement. 13. At least one non-transitory, machine-readable storage device comprising machine readable instructions which, when executed, cause at least one processor to: process a high-fidelity recording comprising a stimulus event; present the high-fidelity recording by a presentation device; receive one or more neural metrics from at least one sensor in response to the presentation; identify one or more rules to define one or more metrics associated with the stimulus event; apply the one or more rules to the high-fidelity recording to generate one or more reference metrics associated with the stimulus event; modify one or more recording elements of the high-fidelity recording based on the one or more reference metrics to distinguish the stimulus event within the high fidelity recording; and present the modified recording by the presentation device. 14. The at least one non-transitory, machine-readable storage device comprising machine readable instructions as defined in claim 13, wherein the instructions, when executed, cause the processor to: present the high-fidelity recording by one or more of a visual display, an audible transmission, and a tactile response device; receive one or more behavioral metrics from at least one user input in response to the presentation; and create a review recording comprising the reference recording, the one or more neural metrics and the one or more behavioral metrics. 15. The at least one non-transitory, machine-readable storage device comprising machine readable instructions as defined in claim 13, wherein the instructions, when executed, cause the processor to present the review recording to a subject. 16. The at least one non-transitory, machine-readable storage device comprising machine readable instructions as defined in claim 13, wherein the instructions, when executed, cause the processor to: compare a timing component of the one or more reference metrics to a timing component of the one or more neural metrics and/or the one or more behavioral metrics; and generating a score corresponding to a level of expertise based on the comparison. 17. The at least one non-transitory, machine-readable storage device comprising machine readable instructions as defined in claim 13, wherein the instructions, when executed, cause the processor to: analyze the one or more neural metrics; and classify each of the one or more neural metrics as corresponding to at least one of a decision value and a preparedness value. 18. The at least one non-transitory, machine-readable storage device comprising machine readable instructions as defined in claim 17, wherein the instructions, when executed, cause the processor to: compare the decision value to an optimized decision value based on the reference metrics; and generate a decision value score based on the comparison. 19. The at least one non-transitory, machine-readable storage device comprising machine readable instructions as defined in claim 18, wherein the instructions, when executed, cause the processor to: compare the preparedness value to an optimized preparedness value based on the reference metrics; and generate a preparedness value score based on the comparison. 20. A method comprising: accessing, by at least one processor, at least one storage medium storing a high-fidelity recording, wherein the high-fidelity recording includes a stimulus event and one or more rues associated with the stimulus event; presenting, with the at least one processor, the high-fidelity recording through a presentation device; receiving, at the at least one processor, one or more neural metrics from at least one neural sensor while the high-fidelity recording is being presented; applying, with the at least one processor, the one or more rules to generate one or more reference metrics associated with the stimulus event; modifying, with the at least one processor, one or more recording elements of the high-fidelity recording based on the one or more reference metrics to distinguish the stimulus event within the high fidelity recording; creating, with the at least one processor, a reference recording comprising the high-fidelity recording; presenting, with the at least one processor, the high-fidelity recording by one or more of a visual display, an audio speaker, and a tactile response device; creating, with the at least one processor, a review recording comprising the reference recording, the one or more neural metrics and the one or more behavioral metrics. presenting, by the presentation device, the review recording; comparing, with the at least one processor, a timing component of the one or more reference metrics to a timing component of the one or more neural metrics and/or the one or more behavioral metrics; and generating, with the at least one processor, a score corresponding to a level of expertise based on the comparison.