Neural activity in prefrontal cortex during copying geometrical shapes. II. Decoding shape segments from neural ensembles

Bruno B. Averbeck, David A. Crowe, Matthew V. Chafee, Apostolos P. Georgopoulos

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74 Scopus citations

Abstract

We trained two monkeys to draw copies of geometrical shapes (e.g. squares, triangles) using a joystick, and found that several variables describing the arm trajectories were encoded in the activity of individual prefrontal neurons (Averbeck et al. 2003). Copy trajectories were drawn as sequences of segments, identified by the serial order in which they were drawn and the shape that they together produced. Here we use linear discriminant analysis to test how well the segments of copied shapes could be decoded from the neural activity patterns of small ensembles (3-22 neurons) of simultaneously recorded cells in prefrontal cortex. Using this analysis, the proper segment (drawn by the monkey) was correctly decoded from the ensemble activity pattern during the drawing of that segment in 60-80% of the cases when the largest ensembles were considered. The information transmitted by these ensembles, as well as by single neurons, was also calculated. We found that the information transmitted by the ensembles increased on average with the number of neurons they contained. Each neuron conveyed information about multiple segments within the drawing trajectory, suggesting that neurons were 'broadly tuned' across segments and that the neural code of segment was distributed.

Original languageEnglish (US)
Pages (from-to)142-153
Number of pages12
JournalExperimental Brain Research
Volume150
Issue number2
DOIs
StatePublished - May 2003

Keywords

  • Discriminant analysis
  • Information theory
  • Neural decoding
  • Neural ensemble
  • Prefrontal cortex

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