Abstract
Cognitive behaviors originate in the responses of neuronal populations. We have a reasonable understanding of how the activity of a single neuron can be related to a specific behavior. However, it is still unclear how more complex behaviors are inferred from the responses of neuronal populations. This is a particularly timely problem because multi-neuronal recording techniques have recently become increasingly available, simultaneously spurring advances in the analysis of neuronal population data. These developments are, however, constrained by the challenges of combining theoretical and experimental approaches because both approaches have their unique set of constraints. A solution to this problem is to design computational models that are either derived or inspired by cortical computations.
Highlights
Cognitive behaviors originate in the responses of neuronal populations
This topic is essential for understanding the neuronal correlates of behavior, because often it is driven by decisions based on sensory inputs
These findings are important for experimental data analysis utilizing the Poisson model, e.g., in the Bayesian inference framework, commonly used for reading out sensory inputs or behaviors based on neuronal population activity
Summary
Cognitive behaviors originate in the responses of neuronal populations. We have a reasonable understanding of how the activity of a single neuron can be related to a specific behavior. The contributors present key findings on subjects including the response properties of single neurons, cortical networks, sensory predictions, and behavioral predictions. Several contributions focused on the question of sensory predictions from neuronal population responses. This topic is essential for understanding the neuronal correlates of behavior, because often it is driven by decisions based on sensory inputs.
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