Biology subjects

Kanwisher, N. G.

Publications and source records attributed to Kanwisher, N. G..

12 recordsLinked to original sources

bioRxiv2026

Causal reasoning is domain-specific in the human brain

Causal reasoning enables humans to explain the past, predict the future, and intervene on the present. Despite extensive interest in causal inference by philosophers, cognitive scientists, and developmental psychologists, few studies have investigated causal reasoning in the human brain. Here we use fMRI to ask whether a unified brain system exists that implements causal inference across content domains, or whether instead distinct brain systems are engaged in causal reasoning about social agents and physical objects. Across three pre-registered experiments, we find that causal reasoning about social and physical phenomena engage distinct cortical regions. The fronto-parietal Physics Network (PN), previously implicated in physical reasoning, and the temporo-parietal junction (TPJ), previously implicated in social reasoning, both showed stronger responses to causal than non-causal conditions, but only within their respective domains. Selective responses emerged in both a reading comprehension task (Experiment 1) and a sentence matching task (Experiment 2), and for preventative as well as generative causal reasoning (Experiment 3). No region selectively engaged causal reasoning or showed common patterns of response across voxels for causality in both physical and social domains in whole-brain analyses. Thus, despite its central role in human cognition, causal reasoning is implemented in separate domain-specific regions rather than a single unified brain region.

neuroscience↗

bioRxiv2026

Apparent food selectivity reflects multiple non-food image properties

Three recent publications have reported selective fMRI responses to images of food in the human ventral visual pathway. However, all three studies were based primarily on the Natural Scenes Dataset (NSD), in which high-level categories like food are correlated with other image properties such as the color and size of objects, and the distance of the scene. To test whether the reported food selectivity might reflect these or other correlates of food images rather than (or in addition to) food, we constructed novel stimuli that manipulated these properties on both food and non-food images, and collected data from new subjects in a data-rich design across two experiments pre-registered in OSF. We used a localizer paradigm based on a subset of NSD images to infer the "food component" in new subjects and then measured responses of this component to our new stimuli. In Experiment 1, we found that the food component response magnitude i) had a higher response to color than to greyscale images but showed no interaction between food and color, ii) showed a reduced preference for food over non-food when both were within reaching distance, and most importantly iii) was no higher for food than non-food when both were visually matched and presented as Cutouts on a white background. In Experiment 2, we found that the response of the food component could not be explained by object distance, real-world size, or mid-level visual image statistics. However, the response to non-food images with "gooey" material properties was as high as the response to food. Across both experiments, we consistently found a very low response (at or below fixation baseline) to NSD non-food images, which were predominantly outdoor scenes. Together, our results prompt a revision of prior claims including our own, indicating that the previously reported food component is better characterized as food-biased rather than strictly food-selective, and is driven in part by contextual or material features that are also present in non-food images. Our findings further highlight the importance of supplementing studies based on naturalistic images with experiments that unconfound image properties with carefully designed stimuli.

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bioRxiv2026

The Physics Network is Distinct from the Multiple Demand System in the Human Brain

Recent studies implicate regions of the human bilateral fronto-parietal cortices in intuitive physical reasoning--our ability to perceive, predict, and plan in the physical world. However, it remains unclear whether this "Physics Network" (PN) constitutes a distinct and domain-specific system, or whether instead it overlaps with the nearby domain-general multiple demand (MD) network. To answer this question, we scanned participants (N = 20) with fMRI in a pre-registered study and measured spatial overlap, response profile differences, and resting-state correlation between the PN and MD networks. We find that: (1) The PN and MD networks overlap only minimally within individual participants, (2) Each network exhibits distinct functional profiles across a broad array of tasks, and (3) Time courses of functional response are more correlated between subregions within the same network than subregions between networks. These findings indicate that the Physics Network is dissociable from the Multiple Demand system both spatially and functionally, supporting its distinct role in intuitive physical reasoning.

neuroscience↗

bioRxiv2026

Monosynaptic connections link functionally similar regions in human cortex

The functional organization of human cortex has been mapped in considerable detail1-5, yet the axonal connections linking these areas remain largely unknown. This gap precludes inferring either the computational pathways through cortical networks or the principles governing why each area connects to its particular target regions. Here, in patients undergoing intracranial monitoring for epilepsy, we used concurrent electrical stimulation and functional magnetic resonance imaging (es-fMRI), validated previously against tracer studies in nonhuman primates6, to map anatomical connectivity of cortical sites across the whole brain, and combined these maps with task and resting-state fMRI in the same individuals. Es-fMRI revealed four main findings. First, connectivity followed an asymmetric functional-similarity principle: connected sites tended to share similar functional profiles, but, because connectivity is sparse, most pairs of functionally similar sites were not connected. Second, although connectivity also declines with distance7, the functional profile explained three times as much variance in connectivity as distance did, and long-range connections were the most functionally specific. Third, es-fMRI revealed direct monosynaptic links between established functional regions, including between the fusiform face area (FFA)2 and the temporoparietal junction (TPJ)3 for social cognition. Fourth, resting-state functional connectivity (rsFC) of a stimulation site was only weakly correlated with that sites es-fMRI connectivity. Together, these results provide a first principled link between anatomical connectivity and functional organization in the human cortex, and establish es-fMRI as a scalable approach to building a tracer-grade connectome of the human brain.

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bioRxiv2025

Semantic reasoning takes place largely outside the language network

The brains language network is often implicated in the representation and manipulation of abstract semantic knowledge. However, this view is inconsistent with a large body of evidence suggesting that language processing is neurally distinct from the rest of cognition. Here, we use precision brain imaging to uncover a set of brain regions, separate from the language network, that are engaged in semantic processing of both linguistic and pictorial stimuli. In three fMRI experiments, participants (total n=41 tested across 49 sessions) viewed sentences and pictures depicting simple events. In separate blocks, they performed either a semantic task or a difficulty-matched perceptual task. Across all three experiments, several areas in left lateral prefrontal cortex, left temporo-parietal cortex, and right cerebellum responded to semantic tasks for both sentences and pictures. These semantic processing areas are spatially and functionally distinct from the nearby language-selective areas, as well as from the multiple demand and default mode networks, exhibiting a unique response profile. Our results provide evidence for a new kind of selectivity in the human brain and pave the way for future explorations of the neural mechanisms that underlie semantic reasoning.

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bioRxiv2024

Privileged representational axes in biological and artificial neural networks

How do neurons code information? Recent work emphasizes properties of population codes, such as their geometry and decodable information, using measures that are blind to the native tunings (or axes) of neural responses. But might these representational axes matter, with some privileged systematically over others? To find out, we developed methods to test for alignment of neural tuning across brains and deep convolutional neural networks (DCNNs). Across both vision and audition, both brains and DCNNs consistently favored certain axes for representing the natural world. Moreover, the representational axes of DCNNs trained on natural inputs were aligned to those in perceptual cortices, such that axis-sensitive model-brain similarity metrics better differentiated competing models of biological sensory systems. We further show that coding schemes that privilege certain axes can reduce downstream wiring costs and improve generalization. These results motivate a new framework for understanding neural tuning in biological and artificial networks and its computational benefits.

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bioRxiv2024

Fine-grained neural coding of bodies and body parts in human visual cortex

The visual image of a human body provides a valuable source of socially relevant information. However, our understanding of the neuronal mechanisms underlying body perception in humans remains limited given the spatiotemporal constraints of functional imaging. Here we recorded multi-unit spiking activity in two neurosurgical patients in or near the extrastriate body area (EBA), a critical region for body perception. Our recordings revealed a strong preference for human bodies over a large range of control stimuli. Notably, this preference was driven by a distinct selectivity for body parts. Moreover, the observed body selectivity generalized to non-photographic depictions of bodies such as silhouettes and stick figures. Overall, our study provides an unprecedented access into the representation of bodies in the human visual cortex to bridge the gap between human neuroimaging and macaque electrophysiology studies, and form a solid basis for computational models of human body processing.

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bioRxiv2022

A Highly Selective Response to Food in Human Visual Cortex Revealed by Hypothesis-Free Voxel Decomposition

Prior work has identified cortical regions selectively responsive to specific categories of visual stimuli. However, this hypothesis-driven work cannot reveal how prominent these category selectivities are in the overall functional organization of visual cortex, or what others might exist that scientists have not thought to look for. Further, standard voxel-wise tests cannot detect distinct neural selectivities that coexist within voxels. To overcome these limitations, we used data-driven voxel decomposition methods to identify the main components underlying fMRI responses to thousands of complex photographic images (Allen et al 2021). Our hypothesis-neutral analysis rediscovered components selective for faces, places, bodies, and words, validating our method and showing that these selectivities are dominant features of the ventral visual pathway. The analysis also revealed an unexpected component with a distinct anatomical distribution that responded highly selectively to images of food. Alternative accounts based on low to mid-level visual features like color, shape or texture failed to account for the food selectivity of this component. High-throughput testing and control experiments with matched stimuli on a highly accurate computational model of this component confirm its selectivity for food. We registered our methods and hypotheses before replicating them on held-out participants and in a novel dataset. These findings demonstrate the power of data-driven methods, and show that the dominant neural responses of the ventral visual pathway include not only selectivities for faces, scenes, bodies, and words, but also the visually heterogeneous category of food, thus constraining accounts of when and why functional specialization arises in the cortex.

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bioRxiv2021

Music-selective cortex is sensitive to structure in both pitch and time

Music is distinguished from other natural sounds by the presence of relatively discrete notes, which are then organized across pitch and time to convey melody, harmony, and rhythm. Growing evidence suggests that small clusters of neural populations within anterior and posterior human non-primary auditory cortex respond selectively to musical structure. However, it is unclear whether this selectivity reflects short-term musical structure at the level of individual notes, and/or the patterning of notes in pitch and time. We used fMRI voxel decomposition to measure the response of music-selective and non-selective auditory neural populations to synthetic music and drum stimuli whose notes were scrambled in pitch and/or time, disrupting musical pattern structure while largely preserving note-level structure. We observed reliably stronger responses to music with intact pitch and temporal pattern structure in both anterior and posterior music-selective regions bilaterally, but little difference between intact and scrambled music in non-selective populations. Further, only music-selective populations showed reliably stronger responses to note-scrambled music compared with non-music sounds. These results suggest that musical structure involving both individual notes and their patterning over time is specifically represented in localized music-selective neural populations of human non-primary auditory cortex.

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bioRxiv2021

Face-Selective Responses Present in Multiple Regions of the Human Infant Brain

In human adults, multiple cortical regions respond robustly to faces, including the occipital face area (OFA) and fusiform face area (FFA), implicated in face perception, and the superior temporal sulcus (STS) and medial prefrontal cortex (MPFC), implicated in higher level social functions. When in development does face selectivity arise in each of these regions? Here, we combined two awake infant functional magnetic resonance neuroimaging (fMRI) datasets to create a sample size twice the size of previous reports (n=65 infants, 2.6-9.6 months). Infants watched movies of faces, bodies, objects, and scenes while fMRI data were collected. Despite variable amounts of data from each infant, individual subject whole-brain activations maps revealed a significant response to faces compared to non-face visual categories in the approximate location of OFA, FFA, STS, and MPFC. To determine the strength and nature of face selectivity in these regions, we used cross-validated functional region of interest (fROI) analyses. Across this larger sample size, face responses in OFA, FFA, STS, and MPFC were significantly greater than responses to bodies, objects, and scenes. Even the youngest infants (2-5 months) showed significantly face-selective responses in FFA, STS, and MPFC, but not OFA. These results demonstrate that face selectivity is present in multiple cortical regions within months of birth, providing powerful constraints on theories of cortical development. Significance StatementSocial cognition often begins with face perception. In adults, several cortical regions respond robustly to faces, yet little is known about when and how these regions first arise in development. To test whether face selectivity changes in the first year of life, we combined two datasets, doubling the sample size relative to previous reports. In the approximate location of the fusiform face area (FFA), superior temporal sulcus (STS), and medial prefrontal cortex (MPFC) but not occipital face area (OFA), face selectivity was present in the youngest group. These findings demonstrate that face-selective responses are present across multiple lobes of the brain very early in life.

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bioRxiv2021

Invariant Representation of Physical Stability in the Human Brain

Successful engagement with the world requires the ability to predict what will happen next. Here we investigate how the brain makes the most basic prediction about the physical world: whether the situation in front of us is stable, and hence likely to stay the same, or unstable, and hence likely to change in the immediate future. Specifically, we ask if judgements of stability can be supported by the kinds of representations that have proven to be highly effective at visual object recognition in both machines and brains, or instead if the ability to determine the physical stability of natural scenes may require generative algorithms that simulate the physics of the world. To find out, we measured responses in both convolutional neural networks (CNNs) and the brain (using fMRI) to natural images of physically stable versus unstable scenarios. We find no evidence for generalizable representations of physical stability in either standard CNNs trained on visual object and scene classification (ImageNet), or in the human ventral visual pathway, which has long been implicated in the same process. However, in fronto-parietal regions previously implicated in intuitive physical reasoning we find both scenario-invariant representations of physical stability, and higher univariate responses to unstable than stable scenes. These results demonstrate abstract representations of physical stability in the dorsal but not ventral pathway, consistent with the hypothesis that the computations underlying stability entail not just pattern classification but forward physical simulation.

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bioRxiv2020

Visual Experience is not Necessary for the Development of Face Selectivity in the Lateral Fusiform Gyrus

Here we show robust face-selectivity in the lateral fusiform gyrus of congenitally blind participants during haptic exploration of 3D-printed stimuli, indicating that neither visual experience, nor fovea-biased input, nor visual expertise is necessary for face-selectivity to arise in its characteristic location. Similar resting fMRI correlation fingerprints in individual blind and sighted participants suggest a role for long-range connectivity in the specification of the cortical locus of face-selectivity.

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