Dynamic Control of Network Level Information Processing through Cholinergic Modulation

Network-level learning;Acetylcholine;Memory recall;Spatiotemporal pattern formation;Spike-frequency adaptation;Sleep;Neurosciences;Physiology;Health Sciences;Science;Neuroscience

Roach, JamesSander, Leonard M ;

University of Michigan

关键词: Network-level learning;    Acetylcholine;    Memory recall;    Spatiotemporal pattern formation;    Spike-frequency adaptation;    Sleep;    Neurosciences;    Physiology;    Health Sciences;    Science;    Neuroscience;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/147503/roachjp_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Acetylcholine (ACh) release is a prominent neurochemical marker of arousal statewithin the brain. Changes in ACh are associated with changes in neural activity andinformation processing, though its exact role and the mechanisms through which itacts are unknown. Here I show that the dynamic changes in ACh levels that areassociated with arousal state control informational processing functions of networksthrough its effects on the degree of Spike-Frequency Adaptation (SFA), an activitydependent decrease in excitability, synchronizability, and neuronal resonance displayedby single cells. Using numerical modeling I develop mechanistic explanationsfor how control of these properties shift network activity from a stable high frequencyspiking pattern to a traveling wave of activity. This transition mimics the changein brain dynamics seen between high ACh states, such as waking and Rapid EyeMovement (REM) sleep, and low ACh states such as Non-REM (NREM) sleep. Acorresponding, and related, transition in network level memory recall is also occursas ACh modulates neuronal SFA. When ACh is at its highest levels (waking) allmemories are stably recalled, as ACh is decreased (REM) in the model weakly encodedmemories destabilize while strong memories remain stable. In levels of AChthat match Slow Wave Sleep (SWS), no encoded memories are stably recalled. Thisresults from a competition between SFA and excitatory input strength and providesa mechanism for neural networks to control the representation of underlying synapticinformation. Finally I show that during the low ACh conditions, oscillatory conditionsallow for external inputs to be properly stored in and recalled from synaptic weights. Taken together this work demonstrates that dynamic neuromodulation iscritical for the regulation of information processing tasks in neural networks. Theseresults suggest that ACh is capable of switching networks between two distinct informationprocessing modes. Rate coding of information is facilitated during highACh conditions and phase coding of information is facilitated during low ACh conditions.Finally I propose that ACh levels control whether a network is in one ofthree functional states: (High ACh; Active waking) optimized for encoding of newinformation or the stable representation of relevant memories, (Mid ACh; restingstate or REM) optimized for encoding connections between currently stored memoriesor searching the catalog of stored memories, and (Low ACh; NREM) optimizedfor renormalization of synaptic strength and memory consolidation. This work providesa mechanistic insight into the role of dynamic changes in ACh levels for theencoding, consolidation, and maintenance of memories within the brain.