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Massachusetts Institute of Technology

A prefrontal source of visual target enhancement in the macaque area V4

Abstract

dc:description.abstract

The ventral pre-arcuate area (VPA) in the primate prefrontal cortex has recently been found to play an important role in feature-based selection of visual targets in the context of a naturalistic free-gaze visual search task. While VPA neuronal activation was found to be necessary for behavioral performance as well as target selection in the FEF, its role in the broader context of the visual system remains to be addressed. To this end, we have interrogated the role of the VPA in mediating the effects of feature attention in the macaque visual area V4 by recording in V4 with and without muscimol inactivation in the VPA. We report here that neuronal activation in the VPA is necessary for firing rate increases related to target selection in V4. KEYWORDS: feature attention, visual search, muscimol, neurophysiology

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ghadooshahy, Azriel (Azriel Sion)
Advisor dc:contributor.advisor
  • Robert Desimone.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/114077
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/114077

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Ghadooshahy, Azriel (Azriel Sion). A prefrontal source of visual target enhancement in the macaque area V4. Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/114077