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Cortical computations via metastable activity.

Giancarlo La Camera1, Alfredo Fontanini1, Luca Mazzucato2

  • 1Department of Neurobiology and Behavior, State University of New York at Stony Brook, Stony Brook, NY 11794, United States; Graduate Program in Neuroscience, State University of New York at Stony Brook, Stony Brook, NY 11794, United States.

Current Opinion in Neurobiology
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This summary is machine-generated.

Brain activity unfolds in discrete, metastable states, crucial for representing internal thoughts and external stimuli. This dynamic neural coding shifts focus from averaged activity to real-time ensemble representations.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Neural activity exhibits metastable dynamics, characterized by abrupt transitions between quasi-stationary states.
  • Metastable activity occurs during both stimulus-evoked and spontaneous brain function.
  • These states are increasingly recognized for subserving internal representations, independent of external triggers.

Purpose of the Study:

  • To review recent findings on metastable brain activity.
  • To explore the mechanistic origins of metastable representations in biologically realistic models.
  • To discuss the role of metastability in representing internal states and task-relevant variables.

Main Methods:

  • Review of recent experimental and theoretical findings on neural metastability.
  • Discussion of biologically plausible models generating metastable dynamics.
  • Analysis of decoding approaches utilizing metastable states for stimuli and decisions.

Main Results:

  • Accumulating evidence supports the view of cortical activity as a sequence of metastable states.
  • Metastable states can be decoded trial-by-trial, reflecting internal representations like deliberation, attention, and expectation.
  • Focusing on metastability offers a shift from trial-averaged neural coding to dynamic ensemble representations.

Conclusions:

  • Metastable brain dynamics provide a framework for understanding neural coding beyond traditional trial-averaging.
  • These dynamic ensemble representations are crucial for encoding both internal cognitive states and external information.
  • Future research should further elucidate the mechanisms and functional roles of neural metastability.