CT-1.1

Fluctuating responses evoked by multiple objects: a general feature of visual representations

Meredith Schmehl, Duke University, United States; Valeria Caruso, University of Michigan, United States; Shawn Willett, University of Pittsburgh, United States; Yunran Chen, Na Young Jun, Jeff Mohl, Duke University, United States; Douglas Ruff, Marlene Cohen, University of Chicago, United States; Akinori Ebihara, Winrich Freiwald, The Rockefeller University, United States; Surya Tokdar, Jennifer Groh, Duke University, United States

Session:
Contributed Talks 1 Lecture

Track:
Cognitive science

Location:
South Schools / East Schools

Presentation Time:
Fri, 25 Aug, 15:00 - 15:15 United Kingdom Time

Abstract:
How neural representations preserve information about multiple stimuli is mysterious because tuning of individual neurons is coarse and the populations of neurons tasked with encoding each individual stimulus must in principle overlap. Here we show that when two perceptually distinguishable stimuli are presented, a subpopulation of neurons in MT and the IT face patch system exhibit fluctuating firing patterns, as if they responded to only one individual stimulus at a time. Furthermore, consistent with our previous results in the early visual area V1, the fluctuations in MT were only observed when the two stimuli formed distinguishable objects but not when they fused into one perceived object. In the face patches, fluctuations were observed for both face-face and face-object stimulus combinations. Taken together, these findings point toward an updated model of how the brain preserves sensory information about multiple stimuli for subsequent processing and behavioral action.

Manuscript:
License:
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI:
10.32470/CCN.2023.1511-0
Publication:
2023 Conference on Cognitive Computational Neuroscience
Presentation
Discussion
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Session CT-1
CT-1.1: Fluctuating responses evoked by multiple objects: a general feature of visual representations
Meredith Schmehl, Duke University, United States; Valeria Caruso, University of Michigan, United States; Shawn Willett, University of Pittsburgh, United States; Yunran Chen, Na Young Jun, Jeff Mohl, Duke University, United States; Douglas Ruff, Marlene Cohen, University of Chicago, United States; Akinori Ebihara, Winrich Freiwald, The Rockefeller University, United States; Surya Tokdar, Jennifer Groh, Duke University, United States
CT-1.2: NeuralPlayground: A Standardised Environment for Evaluating Models of Hippocampus and Entorhinal Cortex
Rodrigo Carrasco-Davis, Clementine Domine, Luke Hollingsworth, Caswell Barry, Andrew Saxe, UCL, United Kingdom
CT-1.3: Confidence is detection-like in high-dimensional spaces
Wiktoria Luczak, Stephen Fleming, University College London, United Kingdom
CT-1.4: Predictive Coding Networks for Temporal Prediction
Beren Millidge, Mufeng Tang, University of Oxford, United Kingdom; Mahyar Osanlouy, University of Auckland, New Zealand; Rafal Bogacz, University of Oxford, United Kingdom
CT-1.5: Age-Related Changes in Neural Noise in a Decision-Making Task
Fenying Zang, Leiden University, Netherlands; Anup Khanal, University of California Los Angeles, United States; International Brain Laboratory, www.internationalbrainlab.com, United States; Anne K Churchland, University of California Los Angeles, United States; Anne E Urai, Leiden University, Netherlands
CT-1.6: A shared neural circuit for maintenance and integration of information over time
Peter Murphy, Maynooth University, Ireland; Hannah McDermott, Freie University, Germany; Klaus Wimmer, Centre de Recerca Matemàtica, Spain; Jade Duffy, Trinity College Dublin, Ireland; Jose Esnaola-Acebes, Centre de Recerca Matemàtica, Spain; Albert Compte, Institut D’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain; Robert Whelan, Trinity College Dublin, Ireland