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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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Early selection of task-relevant features through population gating.

Joao Barbosa1, Rémi Proville2, Chris C Rodgers3

  • 1Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure - PSL Research University, 75005, Paris, France. palerma@gmail.com.

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|October 26, 2023
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Summary
This summary is machine-generated.

Brain circuits filter distractions by enhancing relevant stimuli in the auditory cortex (A1). Top-down signals from the medial prefrontal cortex (mPFC) control this selection process, enabling flexible behavior.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Auditory Perception

Background:

  • The brain's ability to filter irrelevant stimuli is crucial for guiding behavior.
  • This filtering is thought to involve progressive selection across the cortical hierarchy, but underlying neural interactions remain unclear.

Purpose of the Study:

  • To investigate the role of population gating in primary auditory cortex (A1), modulated by medial prefrontal cortex (mPFC) inputs, for stimulus selection.
  • To elucidate the neural mechanisms supporting across-area communication for flexible behavior.

Main Methods:

  • Recorded single-unit activity in rats performing an auditory context-dependent task.
  • Utilized low-rank recurrent neural networks (RNNs) to model neural population dynamics.
  • Analyzed neural representations of relevant and irrelevant stimuli in A1 and mPFC.

Main Results:

  • A1 encoded stimuli along a common dimension, with enhanced relevant stimulus representation along an additional dimension.
  • mPFC selectively encoded context-relevant stimuli.
  • Identified context-modulated neural populations in A1 that gate stimuli, a mechanism controlled by mPFC top-down inputs.

Conclusions:

  • Population gating within A1, driven by mPFC top-down control, supports across-area stimulus selection.
  • This mechanism enables flexible communication between brain regions, crucial for adaptive behavior despite fixed connectivity.