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Central and Divided Visual Field Presentation of Emotional Images to Measure Hemispheric Differences in Motivated Attention
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LFP polarity changes across cortical and eccentricity in primary visual cortex.

Fereshteh Khodaei1,2, S H Sadati1, Mahyar Doost2

  • 1Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.

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|March 16, 2023
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Summary
This summary is machine-generated.

Analyzing current source density (CSD) in the visual cortex reveals how stimulus size impacts neural activity. Larger stimuli showed suppression, while increased eccentricity boosted CSD strength across layers, offering insights for brain-computer interfaces.

Keywords:
LFP mappingLFP polarityV1 neuronscurrent source densityeccentricitylaminar organizationreceptive fieldsink-source

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Visual Neuroscience

Background:

  • Local field potentials (LFPs) assess cortical neural population activity.
  • Current source density (CSD) analysis reduces volume conduction effects compared to LFPs.
  • Understanding CSD morphology across cortical layers and eccentricities is crucial but limited.

Purpose of the Study:

  • To quantitatively map LFP-CSD in the primary visual cortex (V1).
  • To investigate how stimulus properties (size, type) influence CSD morphology.
  • To measure layer-dependent input/output information at different eccentricities.

Main Methods:

  • Recording LFP-CSD in the V1 of Macaque monkeys.
  • Presenting visual stimuli of varying sizes and types.
  • Analyzing sink and source morphology in relation to stimulus properties and eccentricity.

Main Results:

  • Stimuli smaller than the receptive field (RF) size exhibited lower strength.
  • Larger-than-optimized RF stimulus sizes demonstrated a suppression phenomenon.
  • CSD strength increased across cortical layers with greater eccentricity.

Conclusions:

  • Stimulus properties critically determine neural current flow in V1.
  • CSD morphology provides a quantitative measure of visual information processing.
  • Findings have implications for brain-computer interface (BCI) development and understanding neural coding.