Biology subjects

Pramod, R.

Publications and source records attributed to Pramod, R..

6 recordsLinked to original sources

bioRxiv2026

A Unified World Model in Human Posterior Parietal Cortex

How does the brain understand the physical world, predict future events, and plan actions? Are these problems solved by a unified world model, as hypothesized by cognitive scientists and artificial intelligence researchers? Posterior parietal cortex has been implicated in all these functions, but whether the same neurons support each of them is unknown. We recorded from the superior parietal lobule (SPL) of two tetraplegic participants implanted with microelectrode arrays. SPL units preferentially engaged by intuitive physics, judging block-tower stability and viewing naturalistic physical events, also predicted whether moving objects would collide hundreds of milliseconds before contact, generalizing between different physical scenarios. These populations also encoded which hand action the participant intended to perform. These findings identify SPL as a substrate for physical world modeling.

neuroscience↗

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

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↗

bioRxiv2024

Intuitive physical reasoning is not mediated by linguistic nor exclusively domain-general abstract representations

The ability to reason about the physical world is a critical tool in the human cognitive toolbox, but the nature of the representations that mediate physical reasoning remains debated. Here, we use fMRI to illuminate this question by investigating the relationship between the physical-reasoning system and two well-characterized systems: a) the domain-general Multiple Demand (MD) system, which supports abstract reasoning, including mathematical and logical reasoning, and b) the language system, which supports linguistic computations and has been hypothesized to mediate some forms of thought. We replicate prior findings of a network of frontal and parietal areas that are robustly engaged by physical reasoning and identify an additional physical-reasoning area in the left frontal cortex, which also houses components of the MD and language systems. Critically, direct comparisons with tasks that target the MD and the language systems reveal that the physical-reasoning system overlaps with the MD system, but is dissociable from it in fine-grained activation patterns, which replicates prior work. Moreover, the physical-reasoning system does not overlap with the language system. These results suggest that physical reasoning does not rely on linguistic representations, nor exclusively on the domain-general abstract reasoning that the MD system supports.

neuroscience↗

bioRxiv2022

Visual homogeneity computations in the brain enable solving generic visual tasks

Most visual tasks involve looking for specific object features. But we also often perform property-based tasks where we look for specific property in an image, such as finding an odd item, deciding if two items are same, or if an object has symmetry. How do we solve such tasks? These tasks do not fit into standard models of decision making because their underlying feature space and decision process is unclear. Using well-known principles governing multiple object representations, we show that displays with repeating elements can be distinguished from heterogeneous displays using a property we define as visual homogeneity. In behavior, visual homogeneity predicted response times on visual search, same-different and symmetry tasks. Brain imaging during visual search and symmetry tasks revealed that visual homogeneity was localized to a region in the object-selective cortex. Thus, property-based visual tasks are solved in a localized region in the brain by computing visual homogeneity. SIGNIFICANCE STATEMENTMost visual tasks involve looking for specific features, like finding a face in a crowd. But we also often look for a particular image property - such as finding an odd item, deciding if two items are same, or judging if an object is symmetric. How does our brain solve these disparate tasks? Here, we show that these tasks can all be solved using a simple computation over object representations in higher visual cortex, which we define as visual homogeneity.

neuroscience↗

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.

neuroscience↗