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Related Experiment Video

Updated: May 11, 2026

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Published on: August 1, 2018

Expectation-dependent stimulus selectivity in the ventral visual cortical pathway.

Tiago S Altavini¹, Minggui Chen¹, Guadalupe Astorga¹

¹Laboratory of Neurobiology, The Rockefeller University, New York, NY 10065.

Proceedings of the National Academy of Sciences of the United States of America

|March 27, 2025

Summary

This summary is machine-generated.

Neurons dynamically adjust their feature selectivity based on expectations and tasks, challenging the fixed feedforward model of object recognition. This research reveals flexible neural coding in the ventral visual pathway.

Keywords:

adaptive processing feedback object recognition top–down visual cortex

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Related Experiment Videos

Last Updated: May 11, 2026

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

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Published on: August 1, 2018

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

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Published on: May 12, 2019

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex

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Published on: February 8, 2020

Area of Science:

Neuroscience
Cognitive Science
Computational Neuroscience

Background:

The ventral object recognition pathway traditionally follows a hierarchical, feedforward model.
This model posits a fixed set of object primitives leading to whole-object representations in the inferotemporal cortex.

Purpose of the Study:

To challenge the fixed feedforward model of object recognition.
To investigate the dynamic, moment-to-moment changes in neuronal stimulus selectivity.
To explore the influence of top-down factors like object expectation and perceptual task on neural representations.

Main Methods:

Utilized an ethologically curated stimulus set to derive stimulus feature selectivity.
Employed a delayed match-to-sample task to identify informative components for object recognition.
Identified responsive cortical areas using functional magnetic resonance imaging (fMRI).
Guided the placement of chronically implanted electrode arrays based on fMRI data.

Main Results:

Neuronal stimulus selectivities are not fixed but change dynamically based on top-down influences.
Top-down effects were observed for both informative and uninformative stimulus components.
Identified specific cortical areas involved in this dynamic object recognition process.

Conclusions:

Neuronal coding in the ventral visual pathway is more flexible than previously assumed.
Object expectation and task demands significantly modulate neural representations.
This dynamic coding mechanism is crucial for adaptive object recognition in complex environments.