Abstract:Non-human primates, especially rhesus macaques, have played a significant role in our current understanding of the neural computations underlying human vision. Apart from the established homologies in the visual brain areas between these two species, and our extended abilities to probe detailed neural mechanisms in monkeys at multiple scales, one major factor that makes NHPs an extremely appealing animal model of human-vision is their ability to perform human-like visual behavior. Traditionally such behavioral… Show more
“…If the monkeys did not hold their gaze within a small window (±2°) before the choice screen appeared, the trial was aborted. To facilitate training and behavioral data collection, the monkeys also performed the same task in their home cages 71 , with the only difference being that they indicated their choice by touching a touchscreen instead of maintaining their gaze on the selected target for 700 ms.…”
Effective interaction with moving objects and the ability to infer and predict their motion (a core component of "intuitive physics") is essential for survival in the dynamic world. How does the primate visual system process such stimuli, enabling predictive capabilities for dynamic stimuli statistics like motion velocity and expected trajectories? In this study, we probed brain areas in the ventral visual pathway of rhesus macaques implicated in object recognition (areas V4 and inferior temporal, IT, cortex) to evaluate how they represent object motion speed and direction. We assessed the relationship between the distributed population activity in the ventral stream and two distinct object motion-based behaviors -- one reliant on information directly available in videos (speed discrimination) and the other predicated on predictive motion estimates from videos (future event predictions). Further, employing microstimulation strategies, we confirm the causal, functional role of the IT cortex in these behaviors. Our results underscore the need to re-examine the traditional functional segregation of the primate visual cortices into "what" and "where" pathways and provide empirical constraints to model their interaction for a better circuit-level understanding of visual motion and intuitive physics.
“…If the monkeys did not hold their gaze within a small window (±2°) before the choice screen appeared, the trial was aborted. To facilitate training and behavioral data collection, the monkeys also performed the same task in their home cages 71 , with the only difference being that they indicated their choice by touching a touchscreen instead of maintaining their gaze on the selected target for 700 ms.…”
Effective interaction with moving objects and the ability to infer and predict their motion (a core component of "intuitive physics") is essential for survival in the dynamic world. How does the primate visual system process such stimuli, enabling predictive capabilities for dynamic stimuli statistics like motion velocity and expected trajectories? In this study, we probed brain areas in the ventral visual pathway of rhesus macaques implicated in object recognition (areas V4 and inferior temporal, IT, cortex) to evaluate how they represent object motion speed and direction. We assessed the relationship between the distributed population activity in the ventral stream and two distinct object motion-based behaviors -- one reliant on information directly available in videos (speed discrimination) and the other predicated on predictive motion estimates from videos (future event predictions). Further, employing microstimulation strategies, we confirm the causal, functional role of the IT cortex in these behaviors. Our results underscore the need to re-examine the traditional functional segregation of the primate visual cortices into "what" and "where" pathways and provide empirical constraints to model their interaction for a better circuit-level understanding of visual motion and intuitive physics.
A spatially distributed population of neurons in the macaque inferior temporal (IT) cortex supports object recognition behavior, but the cell-type specificity of the population in forming “behaviorally sufficient” object decodes remain unclear. To address this, we recorded neural signals from the macaque IT cortex and compared the object identity information and the alignment of decoding strategies derived from putative inhibitory (Inh) and excitatory (Exc) neurons to the monkeys’ behavior. We observed that while Inh neurons represented significant category information, decoding strategies based on Exc neural population activity outperformed those from Inh neurons in overall accuracy and their image-level match to the monkeys’ behavioral reports. Interestingly, both Exc and Inh responses explained a fraction of unique variance of the monkeys’ behavior, demonstrating a distinct role of the two cell types in generating object identity solutions for a downstream readout. We observed that current artificial neural network (ANN) models of primate ventral stream, designed with AI goals of performance optimization on image categorization, better predict Exc neurons (and its contribution to object recognition behavior) than Inh neurons. Beyond, the refinement of linking propositions between IT and object recognition behavior, our results guide the development of more biologically constrained brain models by offering novel cell-type specific neural benchmarks.
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