A unifying framework for functional organization in early and higher ventral visual cortex.

A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly understood. Here, we develop the topographic deep artificial neural network (TDANN), the first model to predict several aspects of the functional organization of multiple cortical areas in the primate visual system. We analyze the factors driving the TDANN's success and find that it balances two objectives: learning a task-general sensory representation and maximizing the spatial smoothness of responses according to a metric that scales with cortical surface area. In turn, the representations learned by the TDANN are more brain-like than in spatially unconstrained models. Finally, we provide evidence that the TDANN's functional organization balances performance with between-area connection length. Our results offer a unified principle for understanding the functional organization of the primate ventral visual system.

Longitudinal development of category representations in ventral temporal cortex predicts word and face recognition.

Regions in ventral temporal cortex that are involved in visual recognition of categories like words and faces undergo differential development during childhood. However, categories are also represented in distributed responses across high-level visual cortex. How distributed category representations develop and if this development relates to behavioral changes in recognition remains largely unknown. Here, we used functional magnetic resonance imaging to longitudinally measure the development of distributed responses across ventral temporal cortex to 10 categories in school-age children over several years. Our results reveal both strengthening and weakening of category representations with age, which was mainly driven by changes across category-selective voxels. Representations became particularly more distinct for words in the left hemisphere and for faces bilaterally. Critically, distinctiveness for words and faces across category-selective voxels in left and right lateral ventral temporal cortex, respectively, predicted individual children's word and face recognition performance. These results suggest that the development of distributed representations in ventral temporal cortex has behavioral ramifications and advance our understanding of prolonged cortical development during childhood.

A Unifying Principle for the Functional Organization of Visual Cortex.

A key feature of many cortical systems is functional organization: the arrangement of neurons with specific functional properties in characteristic spatial patterns across the cortical surface. However, the principles underlying the emergence and utility of functional organization are poorly understood. Here we develop the Topographic Deep Artificial Neural Network (TDANN), the first unified model to accurately predict the functional organization of multiple cortical areas in the primate visual system. We analyze the key factors responsible for the TDANN's success and find that it strikes a balance between two specific objectives: achieving a task-general sensory representation that is self-supervised, and maximizing the smoothness of responses across the cortical sheet according to a metric that scales relative to cortical surface area. In turn, the representations learned by the TDANN are lower dimensional and more brain-like than those in models that lack a spatial smoothness constraint. Finally, we provide evidence that the TDANN's functional organization balances performance with inter-area connection length, and use the resulting models for a proof-of-principle optimization of cortical prosthetic design. Our results thus offer a unified principle for understanding functional organization and a novel view of the functional role of the visual system in particular.

White matter connections of high-level visual areas predict cytoarchitecture better than category-selectivity in childhood, but not adulthood.

Ventral temporal cortex (VTC) consists of high-level visual regions that are arranged in consistent anatomical locations across individuals. This consistency has led to several hypotheses about the factors that constrain the functional organization of VTC. A prevailing theory is that white matter connections influence the organization of VTC, however, the nature of this constraint is unclear. Here, we test 2 hypotheses: (1) white matter tracts are specific for each category or (2) white matter tracts are specific to cytoarchitectonic areas of VTC. To test these hypotheses, we used diffusion magnetic resonance imaging to identify white matter tracts and functional magnetic resonance imaging to identify category-selective regions in VTC in children and adults. We find that in childhood, white matter connections are linked to cytoarchitecture rather than category-selectivity. In adulthood, however, white matter connections are linked to both cytoarchitecture and category-selectivity. These results suggest a rethinking of the view that category-selective regions in VTC have category-specific white matter connections early in development. Instead, these findings suggest that the neural hardware underlying the processing of categorical stimuli may be more domain-general than previously thought, particularly in childhood.

Holistic face recognition is an emergent phenomenon of spatial processing in face-selective regions.

Spatial processing by receptive fields is a core property of the visual system. However, it is unknown how spatial processing in high-level regions contributes to recognition behavior. As face inversion is thought to disrupt typical holistic processing of information in faces, we mapped population receptive fields (pRFs) with upright and inverted faces in the human visual system. Here we show that in face-selective regions, but not primary visual cortex, pRFs and overall visual field coverage are smaller and shifted downward in response to face inversion. From these measurements, we successfully predict the relative behavioral detriment of face inversion at different positions in the visual field. This correspondence between neural measurements and behavior demonstrates how spatial processing in face-selective regions may enable holistic perception. These results not only show that spatial processing in high-level visual regions is dynamically used towards recognition, but also suggest a powerful approach for bridging neural computations by receptive fields to behavior.

Cortical recycling in high-level visual cortex during childhood development.

Human ventral temporal cortex contains category-selective regions that respond preferentially to ecologically relevant categories such as faces, bodies, places and words and that are causally involved in the perception of these categories. How do these regions develop during childhood? We used functional magnetic resonance imaging to measure longitudinal development of category selectivity in school-age children over 1 to 5 years. We discovered that, from young childhood to the teens, face- and word-selective regions in ventral temporal cortex expand and become more category selective, but limb-selective regions shrink and lose their preference for limbs. Critically, as a child develops, increases in face and word selectivity are directly linked to decreases in limb selectivity, revealing that during childhood, limb selectivity in ventral temporal cortex is repurposed into word and face selectivity. These data provide evidence for cortical recycling during childhood development. This has important implications for understanding typical as well as atypical brain development and necessitates a rethinking of how cortical function develops during childhood.

Differential spatial computations in ventral and lateral face-selective regions are scaffolded by structural connections.

Face-processing occurs across ventral and lateral visual streams, which are involved in static and dynamic face perception, respectively. However, the nature of spatial computations across streams is unknown. Using functional MRI and population receptive field (pRF) mapping, we measured pRFs in face-selective regions. Results reveal that spatial computations by pRFs in ventral face-selective regions are concentrated around the center of gaze (fovea), but spatial computations in lateral face-selective regions extend peripherally. Diffusion MRI reveals that these differences are mirrored by a preponderance of white matter connections between ventral face-selective regions and foveal early visual cortex (EVC), while connections with lateral regions are distributed more uniformly across EVC eccentricities. These findings suggest a rethinking of spatial computations in face-selective regions, showing that they vary across ventral and lateral streams, and further propose that spatial computations in high-level regions are scaffolded by the fine-grain pattern of white matter connections from EVC.