Biology subjects

Proklova, D.

Publications and source records attributed to Proklova, D..

4 recordsLinked to original sources

bioRxiv2023

Distinct neural components of visually guided grasping during planning and execution

Selecting suitable grasps on three-dimensional objects is a challenging visuomotor computation, which involves combining information about an object (e.g., its shape, size, and mass) with information about the actors body (e.g., the optimal grasp aperture and hand posture for comfortable manipulation). Here we used functional magnetic resonance imaging to investigate brain networks associated with these distinct aspects during grasp planning and execution. Human participants viewed and then executed preselected grasps on L-shaped objects made of wood and/or brass. By leveraging a computational approach that accurately predicts human grasp locations, we selected grasp points that disentangled the role of multiple grasp-relevant factors: grasp axis, grasp size, and object mass. Representational Similarity Analysis revealed that grasp axis was encoded along dorsal-stream regions during grasp planning. Grasp size was first encoded in ventral-stream areas during grasp planning, then in premotor regions during grasp execution. Object mass was encoded in ventral-stream and (pre)motor regions only during grasp execution. Premotor regions further encoded visual predictions of grasp comfort, whereas the ventral stream encoded grasp comfort during execution, suggesting its involvement in haptic evaluation. These shifts in neural representations thus capture the sensorimotor transformations that allow humans to grasp objects. Significance StatementGrasping requires integrating object properties with constraints on hand and arm postures. Using a computational approach that accurately predicts human grasp locations by combining such constraints, we selected grasps on objects that disentangled the relative contributions of object mass, grasp size, and grasp axis during grasp planning and execution in a neuroimaging study. Our findings reveal a greater role of dorsal-stream visuomotor areas during grasp planning, and surprisingly, increasing ventral stream engagement during execution. We propose that during planning, visuomotor representations initially encode grasp axis and size. Perceptual representations of object material properties become more relevant instead as the hand approaches the object and motor programs are refined with estimates of the grip forces required to successfully lift the object.

neuroscience↗

bioRxiv2021

Activity in perirhinal and entorhinal cortex predicts observer-specific perceived visual similarities between objects

Vision neuroscience has made great strides in understanding the hierarchical organization of object representations along the ventral visual stream (VVS). How VVS representations capture fine-grained visual similarities between objects that observers subjectively perceive has received limited examination so far. In the current study, we addressed this question by focusing on perceived visual similarities among subordinate exemplars of real world-categories. We hypothesized that these perceived similarities are reflected with highest fidelity in neural activity patterns downstream from inferotemporal regions, namely in perirhinal and anterolateral entorhinal cortex in the medial temporal-lobe. To address this issue with fMRI, we administered a modified 1-Back task that required discrimination between category exemplars as well as categorization. Further, we obtained observer-specific ratings of perceived visual similarities, which predicted behavioural performance during scanning. As anticipated, we found that activity patterns in perirhinal and anterolateral entorhinal cortex predicted the structure of perceived visual similarity relationships among category exemplars, including its observer-specific component, with higher precision than any other VVS region. Our findings provide new evidence that subjective aspects of object perception that rely on fine-grained visual differentiation are reflected with highest fidelity in the medial temporal lobe.

neuroscience↗

bioRxiv2020

The role of animal faces in the animate-inanimate distinction in the ventral temporal cortex

Animate and inanimate objects elicit distinct response patterns in the human ventral temporal cortex (VTC), but the exact features driving this distinction are still poorly understood. One prominent feature that distinguishes typical animals from inanimate objects and that could potentially explain the animate-inanimate distinction in the VTC is the presence of a face. In the current fMRI study, we investigated this possibility by creating a stimulus set that included animals with faces, faceless animals, and inanimate objects, carefully matched in order to minimize other visual differences. We used both searchlight-based and ROI-based representational similarity analysis (RSA) to test whether the presence of a face explains the animate-inanimate distinction in the VTC. The searchlight analysis revealed that when animals with faces were removed from the analysis, the animate-inanimate distinction almost disappeared. The ROI-based RSA revealed a similar pattern of results, but also showed that, even in the absence of faces, information about agency (a combination of animals ability to move and think) is present in parts of the VTC that are sensitive to animacy. Together, these analyses showed that animals with faces do elicit a stronger animate/inanimate response in the VTC, but that this effect is driven not by faces per se, or the visual features of faces, but by other factors that correlate with face presence, such as the capacity for self-movement and thought. In short, the VTC appears to treat the face as a proxy for agency, a ubiquitous feature of familiar animals. Significance StatementMany studies have shown that images of animals are processed differently from inanimate objects in the human brain, particularly in the ventral temporal cortex (VTC). However, what features drive this distinction remains unclear. One important feature that distinguishes many animals from inanimate objects is a face. Here, we used fMRI to test whether the animate/inanimate distinction is driven by the presence of faces. We found that the presence of faces did indeed boost activity related to animacy in the VTC. A more detailed analysis, however, revealed that it was the association between faces and other attributes such as the capacity for self-movement and thinking, not the faces per se, that was driving the activity we observed.

neuroscience↗

bioRxiv2017

MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects

Human high-level visual cortex shows a distinction between animate and inanimate objects, as revealed by fMRI. Recent studies have shown that object animacy can similarly be decoded from MEG sensor patterns. Which object properties drive this decoding? Here, we disentangled the influence of perceptual and categorical object properties by presenting perceptually matched objects (e.g., snake and rope) that were nonetheless easily recognizable as being animate or inanimate. In a series of behavioral experiments, three aspects of perceptual dissimilarity of these objects were quantified: overall dissimilarity, outline dissimilarity, and texture dissimilarity. Neural dissimilarity of MEG sensor patterns was modeled using regression analysis, in which perceptual dissimilarity (from the behavioral experiments) and categorical dissimilarity served as predictors of neural dissimilarity. We found that perceptual dissimilarity was strongly reflected in MEG sensor patterns from 80ms after stimulus onset, with separable contributions of outline and texture dissimilarity. Surprisingly, when controlling for perceptual dissimilarity, MEG patterns did not carry information about object category (animate vs inanimate) at any time point. Nearly identical results were found in a second MEG experiment that required basic-level object recognition. These results suggest that MEG sensor patterns do not capture object animacy independently of perceptual differences between animate and inanimate objects. This is in contrast to results observed in fMRI using the same stimuli, task, and analysis approach: fMRI showed a highly reliable categorical distinction in visual cortex even when controlling for perceptual dissimilarity. Results thus point to a discrepancy in the information contained in multivariate fMRI and MEG patterns.

neuroscience↗