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Habibollahi, F.

Publications and source records attributed to Habibollahi, F..

2 recordsLinked to original sources

Neural Networks Are Tuned Near Criticality During a Cognitive Task and Distanced from Criticality In a Psychopharmacological Model of Alzheimer's Disease

Dynamical systems exhibit transitions between ordered and disordered states and "criticality" occurs when the system lies at the borderline between these states at which the input is neither strongly damped nor excessively amplified. Impairments in brain function such as dementia or epilepsy could arise from failure of adaptive criticality, and deviation from criticality may be a potential biomarker for cognition-related neurological and psychiatric impairments. Miniscope wide-field calcium imaging of several hundred hippocampal CA1 neurons in freely-behaving mice was studied during rest, a cognitive task of novel object recognition (NOR), and novel object recognition following scopolamine administration that greatly impairs spatial memory encoding. We find that while hippocampal networks exhibit characteristics of a near-critical system at rest, the network activity shifts significantly closer to a critical state when the mice engaged in the NOR task. The dynamics shift away from criticality with impairment of novel object performance due to scopolamine-induced memory impairment. These results support the concept that hippocampal neural networks move closer to criticality when successfully processing increased cognitive load, taking advantage of maximal dynamical range, information content, and transmission that occur in critical regimes.

neuroscience↗

Critical dynamics arise during structured information presentation: analysis of embodied in vitro neuronal networks

AO_SCPLOWBSTRACTC_SCPLOWAmongst the characteristics about information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations have precluded a definite answer about when and why neural criticality arises. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of Pong. We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings have compelling implications for the role of neural criticality.

neuroscience↗