Biology subjects

Konkle, T.

Publications and source records attributed to Konkle, T..

25 records · Page 2Linked to original sources

bioRxiv2021

Emergent organization of multiple visuotopic maps without a feature hierarchy

The primate visual system is comprised of multiple visual areas. Despite their foundational relevance, there are no normative accounts for why there are multiple areas nor why they have their signature "mirrored map" topography. Here I show that the stereotyped cortical organization of multiple mirrored areas naturally emerges in simulated cortex, in which self-organizing processes are used to map a multi-scale representation of visual space smoothly onto a two-dimensional cortical sheet. Predominant accounts of multiple areas emphasize hierarchical processing, where each area extends and elaborates on the previous areas representation. Here, no explicit hierarchical relationships were required to manifest this multi-areal organization, suggesting that feature hierarchies may be the derived rather than the driving force of this organization. This modeling work thus provides a simple computational explanation for the hallmark features of early visual topography, and the presence of multiple areas, as emergent from a single functional goal -- to smoothly represent the visual field at multiple spatial scales. One Sentence SummaryThis work presents a formal model of simulated cortex with multiple visual areas, where purely spatial relationships underlie the large-scale motifs of visual cortex.

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bioRxiv2020

The contribution of object size, manipulability, and stability on neural responses to inanimate objects

In human occipitotemporal cortex, brain responses to depicted inanimate objects have a large-scale organization by real-world object size. Critically, the size of objects in the world is systematically related to behaviorally-relevant properties: small objects are often grasped and manipulated (e.g., forks), while large objects tend to be less motor-relevant (e.g., tables), though this relationship does not always have to be true (e.g., picture frames and wheelbarrows). To determine how these two dimensions interact, we measured brain activity with functional magnetic resonance imaging while participants viewed a stimulus set of small and large objects with either low or high motor-relevance. The results revealed that the size organization was evident for objects with both low and high motor-relevance; further, a motor-relevance map was also evident across both large and small objects. Targeted contrasts revealed that typical combinations (small motor-relevant vs. large non-motor-relevant) yielded more robust topographies than the atypical covariance contrast (small non-motor-relevant vs. large motor-relevant). In subsequent exploratory analyses, a factor analysis revealed that the construct of motor-relevance was better explained by two underlying factors: one more related to manipulability, and the other to whether an object moves or is stable. The factor related to manipulability better explained responses in lateral small-object preferring regions, while the factor related to object stability (lack of movement) better explained responses in ventromedial large-object preferring regions. Taken together, these results reveal that the structure of neural responses to objects of different sizes further reflect behavior-relevant properties of manipulability and stability, and contribute to a deeper understanding of some of the factors that help the large-scale organization of object representation in high-level visual cortex. Highlights- Examined the relationship between real-world size and motor-relevant properties in the structure of responses to inanimate objects. - Large scale topography was more robust for contrast that followed natural covariance of small motor-relevant vs. large non-motor-relevant, over contrast that went against natural covariance. - Factor analysis revealed that manipulability and stability were, respectively, better explanatory predictors of responses in small- and large-object regions.

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bioRxiv2020

Instance-level contrastive learning yields human brain-like representation without category-supervision

Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general learning of natural image structure? Here we present a fully self-supervised model which learns to represent individual images, rather than categories, such that views of the same image are embedded nearby in a low-dimensional feature space, distinctly from other recently encountered views. We find (i) category information implicitly emerges in the local similarity structure of this feature space, and (ii) these models learn hierarchical features which capture the structure of brain responses across the human ventral visual stream, on par with category-supervised models. These results provide computational support for a domain-general framework guiding the formation of visual representation, where the proximate goal is not explicitly about category information, but is instead to learn unique, compressed descriptions of the visual world.

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bioRxiv2020

Large-scale dissociations between views of objects, scenes, and reachable-scale environments in visual cortex

Space-related processing recruits a network of brain regions separate from those recruited in object-related processing. This dissociation has largely been explored by contrasting views of navigable-scale spaces compared to close-up views of isolated objects. However, in naturalistic visual experience, we encounter spaces intermediate to these extremes, like the tops of desks and kitchen counters, which are not navigable but typically contain multiple objects. How are such reachable-scale views represented in the brain? In two functional neuroimaging experiments with human observers, we find evidence for a large-scale dissociation of reachable-scale views from both navigable scene views and close-up object views. Three brain regions were identified which showed a systematic response preference to reachable views, located in the posterior collateral sulcus, the inferior parietal sulcus, and superior parietal lobule. Subsequent analyses suggest that these three regions may be especially sensitive to the presence of multiple objects. Further, in all classic scene and object regions, reachable-scale views dissociated from both objects and scenes with an intermediate response magnitude. Taken together, these results establish that reachable-scale environments have a distinct representational signature from both scene and object views.

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bioRxiv2019

Reliability-Based Voxel Selection

While functional magnetic resonance imaging (fMRI) studies typically measure responses across the whole brain, not all regions are likely to be informative for a given study. Which voxels should be considered? Here we propose a method for voxel selection based on the reliability of the data. This method isolates voxels that respond consistently across imaging runs while maximizing the reliability of multi-voxel patterns across the selected voxels. We estimate that it is suitable for designs with at least 15 conditions. In two example datasets, we found that this proposed method defines a smaller set of voxels than another common method, activity-based voxel selection. Broadly, this method eliminates the need to define regions or statistical thresholds a priori and puts the focus on data reliability as the first step in analyzing fMRI data.

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bioRxiv2019

Sociality and Interaction Envelope Organize Visual Action Representations

Humans observe a wide range of actions in their surroundings. How is the visual cortex organized to process this diverse input? Using functional neuroimaging, we measured brain responses while participants viewed short videos of everyday actions, then probed the structure in these responses using voxel-wise encoding modeling. Responses were well fit by feature spaces that capture the body parts involved in an action and the actions targets (i.e. whether the action was directed at an object, another person, the actor, and space). Clustering analyses revealed five large-scale networks that summarized the voxel tuning: one related to social aspects of an action, and four related to the scale of the interaction envelope, ranging from fine-scale manipulations directed at objects, to large-scale whole-body movements directed at distant locations. We propose that these networks reveal the major representational joints in how actions are processed by visual regions of the brain. Significance StatementHow does the brain perceive other peoples actions? Prior work has established that much of the visual cortex is active when observing others actions. However, this activity reflects a wide range of processes, from identifying a movements direction to recognizing its social content. We investigated how these diverse processes are organized within the visual cortex. We found that five networks respond during action observation: one that is involved in processing actions social content, and four that are involved in processing agent-object interactions and the scale of the effect that these actions have on the world (its "interaction envelope"). Based on these findings, we propose that sociality and interaction envelope size are two of the major features that organize action perception in the visual cortex.

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bioRxiv2017

A mid-level organization of the ventral stream

Human object-selective cortex shows a large-scale organization characterized by the high-level properties of both animacy and object-size. To what extent are these neural responses explained by primitive perceptual features that distinguish animals from objects and big objects from small objects? To address this question, we used a texture synthesis algorithm to create a novel class of stimuli--texforms--which preserve some mid-level texture and form information from objects while rendering them unrecognizable. We found that unrecognizable texforms were sufficient to elicit the large-scale organizations of object-selective cortex along the entire ventral pathway. Further, the structure in the neural patterns elicited by texforms was well predicted by curvature features and by intermediate layers of a deep convolutional neural network, supporting the mid-level nature of the representations. These results provide clear evidence that a substantial portion of ventral stream organization can be accounted for by coarse texture and form information, without requiring explicit recognition of intact objects.\n\nSIGNIFICANCE STATEMENTWhile neural responses to object categories are remarkably systematic across human visual cortex, the nature of these responses been hotly debated for the past 20 years. In this paper, a new class of stimuli (\"texforms\") is used to examine how mid-level features contribute to the large-scale organization of the ventral visual stream. Despite their relatively primitive visual appearance, these unrecognizable texforms elicited the entire large-scale organizations of the ventral stream by animacy and object size. This work demonstrates that much of ventral stream organization can be explained by relatively primitive mid-level features, without requiring explicit recognition of the objects themselves.

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