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Updated: Mar 22, 2026

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
Published on: August 1, 2018
The anterior temporal cortex is a primary semantic source of top-down influences on object recognition
Rocco Chiou1, Matthew A Lambon Ralph1
1The Neuroscience and Aphasia Research Unit (NARU), School of Psychological Sciences, University of Manchester, England, UK.
None:
Perception emerges from a dynamic interplay between feed-forward sensory input and feedback modulation along the cascade of neural processing. Prior knowledge, a major form of top-down modulatory signal, benefits perception by enabling efficacious inference and resolving ambiguity, particularly under circumstances of degraded visual input. Despite semantic information being a potentially critical source of this top-down influence, to date, the core neural substrate of semantic knowledge (the anterolateral temporal lobe - ATL) has not been considered as a key component of the feedback system. Here we provide direct evidence of its significance for visual cognition - the ATL underpins the semantic aspect of object recognition, amalgamating sensory-based (amount of accumulated sensory input) and semantic-based (representational proximity between exemplars and typicality of appearance) influences. Using transcranial theta-burst stimulation combined with a novel visual identification paradigm, we demonstrate that the left ATL contributes to discrimination between visual objects. Crucially, its contribution is especially vital under situations where semantic knowledge is most needed for supplementing deficiency of input (brief visual exposure), discerning analogously-coded exemplars (close representational distance), and resolving discordance (target appearance violating the statistical typicality of its category). Our findings characterise functional properties of the ATL in object recognition: this neural structure is summoned to augment the visual system when the latter is overtaxed by challenging conditions (insufficient input, overlapped neural coding, and conflict between incoming signal and expected configuration). This suggests a need to revisit current theories of object recognition, incorporating the ATL that interfaces high-level vision with semantic knowledge.
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