Small Networks Encode Decision-Making in Primary Auditory Cortex

Nikolas A. Francis, Daniel E. Winkowski, Alireza Sheikhattar, Kevin Armengol, Behtash Babadi, Patrick O. Kanold

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Sensory detection tasks enhance representations of behaviorally meaningful stimuli in primary auditory cortex (A1). However, it remains unclear how A1 encodes decision-making. Neurons in A1 layer 2/3 (L2/3) show heterogeneous stimulus selectivity and complex anatomical connectivity, and receive input from prefrontal cortex. Thus, task-related modulation of activity in A1 L2/3 might differ across subpopulations. To study the neural coding of decision-making, we used two-photon imaging in A1 L2/3 of mice performing a tone-detection task. Neural responses to targets showed attentional gain and encoded behavioral choice. To characterize network representation of behavioral choice, we analyzed functional connectivity using Granger causality, pairwise noise correlations, and neural decoding. During task performance, small groups of four to five neurons became sparsely linked, locally clustered, and rostro-caudally oriented, while noise correlations both increased and decreased. Our results suggest that sensory-based decision-making involves small neural networks driven by the sum of sensory input, attentional gain, and behavioral choice. Francis et al. studied the neural coding of decision-making in auditory cortex using two-photon imaging. Neural activity showed attentional gain and encoded behavioral choice. Small neuronal networks predicted behavioral choice. Functional connectivity became sparse, rostro-caudally oriented, and locally clustered during target recognition.

Original languageEnglish (US)
Pages (from-to)885-897.e6
Issue number4
StatePublished - Feb 21 2018
Externally publishedYes


  • 2-photon
  • Granger
  • attention
  • auditory
  • behavior
  • cortex
  • decision-making
  • decoding
  • imaging
  • mouse

ASJC Scopus subject areas

  • General Neuroscience


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