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ref: -0 tags: recurrent cortical model adaptation gain V1 LTD date: 02-11-2018 19:06 gmt revision:0 [head]

PMID-18336081 Adaptive integration in the visual cortex by depressing recurrent cortical circuits.

  • Mainly focused on the experimental observation that decreasing contrast increases latency to both behavioral and neural response (latter in the later visual areas..)
  • Idea is that synaptic depression in recurrent cortical connections mediates this 'adaptive integration' time-constant to maintain reliability.
  • Model also explains persistent activity after a flashed stimulus.
  • No plasticity or learning, though.
  • Rather elegant and well explained.

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ref: Sanchez-2005.06 tags: BMI Sanchez Nicolelis Wessberg recurrent neural network date: 01-01-2012 18:28 gmt revision:2 [1] [0] [head]

IEEE-1439548 (pdf) Interpreting spatial and temporal neural activity through a recurrent neural network brain-machine interface

  • Putting it here for the record.
  • Note they did a sensitivity analysis (via chain rule) of the recurrent neural network used for BMI predictions.
  • Used data (X,Y,Z) from 2 monkeys feeding.
  • Figure 6 is strange, data could be represented better.
  • Also see: IEEE-1300786 (pdf) Ascertaining the importance of neurons to develop better brain-machine interfaces Also by Justin Sanchez.

____References____

Sanchez, J.C. and Erdogmus, D. and Nicolelis, M.A.L. and Wessberg, J. and Principe, J.C. Interpreting spatial and temporal neural activity through a recurrent neural network brain-machine interface Neural Systems and Rehabilitation Engineering, IEEE Transactions on 13 2 213 -219 (2005)