Abstract
Cortical activity exhibits distinct characteristics in different functional states. In awake behaving animals it shows less synchrony, while in rest or sleeping state cortical activity is most synchronous. Previous studies showed that switching between functional states can change the efficiency of flowing sensory information. Switching between functional states can be triggered by releasing neuromodulators which affect neurotransmitter release probability and depolarization of cortical neurons. In this work we focus on studying primary visual area V1, by using firing rate ring model with short-term synaptic depression (STD). We show that reconstruction of visual features from V1 activity depends on the functional state, with best precision achieved at the state with intermediate release probability. We suggest that this regime corresponds to the state of maximal visual attention.
Highlights
Numerous experimental observations show that during different functional states cortex generates different activity dynamics, characterized in particular by different degree of syncrhonization
We presented a model of a hypercolumn in the primary visual area V1, that is based on the well studied ring model (Ben-Yishai et al, 1995; Hansel and Sompolinsky, 1998)
We focused in particular on the precision of orientation representation for different functional states of the cortical networks. To this end we considered the effects of synaptic depression in the intracortical connections on the precision of orientation representation, and assumed that cortical states are regulated via the effects of neuromodulators on synaptic release probability and depolarization of cortical neurons
Summary
Numerous experimental observations show that during different functional states cortex generates different activity dynamics, characterized in particular by different degree of syncrhonization. Cortical functional state depends on whether the animal is awake and engaged in solving a task or it is quiet or sleeping (Poulet and Petersen, 2008; Okun et al, 2010; Harris and Thiele, 2011). Transition from one cortical state to another can be regulated by releasing neuromodulators such as acetylcholine (ACh), noradrenaline (NA) or others. These neuromodulators were shown to reduce neurotransmitter release probability by influencing presynaptic calcium channels while simultaneously reducing postsynaptic potassium conductance, enhancing depolarization (McCormick et al, 1993; Giocomo and Hasselmo, 2007). It was shown that in the case when animal is behaviorally engaged, cortical activity is asynchronous and vice versa in quiet state. Computational modeling demonstrated that in clustered networks, resembling cortical connectivity, information flow is most efficient in the regime of intermediate synchronization (Mark and Tsodyks, 2012)
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