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dc.contributor.author | Maia, Pedro | |
dc.contributor.author | Kutz, J. Nathan | |
dc.date.accessioned | 2021-06-09T17:01:45Z | |
dc.date.available | 2021-06-09T17:01:45Z | |
dc.date.issued | 2017-04 | |
dc.identifier.uri | http://hdl.handle.net/10106/29917 | |
dc.description.abstract | **Please note that the full text is embargoed** ABSTRACT: The presence of diffuse Focal Axonal Swellings (FAS) is a hallmark cellular feature in many neurological diseases and traumatic brain injury. Among other things, the FAS have a significant impact on spike-train encodings that propagate through the affected neurons, leading to compromised signal processing on a neuronal network level. This work merges, for the first time, three fields of study: (i) signal processing in excitatory-inhibitory (EI) networks of neurons via population codes, (ii) decision-making theory driven by the production of evidence from stimulus, and (iii) compromised spike-train propagation through FAS. As such, we demonstrate a mathematical architecture capable of characterizing compromised decision-making driven by cellular mechanisms. The computational model also leads to several novel predictions and diagnostics for understanding injury level and cognitive deficits, including a key finding that decision-making reaction times, rather than accuracy, are indicative of network level damage. The results have a number of translational implications, including that the level of network damage can be characterized by the reaction times in simple cognitive and motor tests. [This is a post-peer-review, pre-copyedit version of an article published in Journal of Computational Neuroscience. The final authenticated version is available online at:https://link.springer.com/article/10.1007/s10827-017-0643-y] | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature | en_US |
dc.relation.ispartofseries | Journal of Computational Neuroscience; | |
dc.subject | Alzheimer | en_US |
dc.subject | Focal Axonal Swellings | en_US |
dc.subject | Cognitive Deficits | en_US |
dc.subject | Decision Making | en_US |
dc.subject | Neural Networks | en_US |
dc.subject | Neurological Diseases | en_US |
dc.subject | Multiple Sclerosis | en_US |
dc.subject | Parkinson | en_US |
dc.subject | Traumatic Brain Injury | en_US |
dc.title | Reaction time impairments in decision-making networks as a diagnostic marker for traumatic brain injuries and neurological diseases | en_US |
dc.type | Article | en_US |
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