The Spatiotemporal Resolution of Cognitive Signals Revealed Through High-Density uECoG Mapping

Abstract

The spatiotemporal resolution of the neural code that underlies attention (and other cognitive signals) is not well understood, despite a large literature that tests how these signals are modulated at the level of the single neuron. These issues have not been resolved because, until recently, it was not possible to record from large numbers of brain sites simultaneously. The goal of this grant is to fill our knowledge by testing two hypotheses. First, attentional signals can be decoded from muECoG signals in the ventrolateral prefrontal cortex(vPFC), which is cortical region that is functionally involved in auditory attention. Second, the ability of a Bayesian linear estimator to decode attentional signals depends on the spatiotemporal resolution of the ECoG-array signals.

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Document Details

Document Type
Technical Report
Publication Date
Jan 24, 2019
Accession Number
AD1071963

Entities

People

  • Yale E. Cohen

Organizations

  • University of Pennsylvania

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Bioengineering
  • Biomedical Engineering
  • Decoding
  • Electrodes
  • Engineering
  • Frequency Bands
  • High Density
  • High Resolution
  • Military Research
  • Neural Engineering
  • Prosthetics
  • Signal Processing
  • Supervised Machine Learning
  • Technology Transfer
  • Universities

Readers

  • Neuroscience
  • Radar Systems Engineering.

Technology Areas

  • AI & ML