About

Professor Marina Bedny is a faculty member whose research focuses on understanding how different life experiences affect sentence processing and the neural basis of language. Her current investigations explore how congenitally blind individuals and sighted people process complex sentences during reading and listening. This work aims to elucidate the neural mechanisms underlying language comprehension across diverse sensory experiences. Through her research, Professor Bedny contributes to the broader understanding of how sensory deprivation and life experiences shape language processing in the brain.

Research topics

• Computer Science
• Artificial Intelligence
• Natural Language Processing
• Psychology
• Cognitive science
• Cognitive psychology
• Machine Learning
• Neuroscience
• Programming language
• Communication
• Linguistics
• Theoretical computer science
• Mathematics

Selected publications

• Rapid “recycling” of logical algorithm representations in fronto-parietal reasoning systems following computer programming instructions

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-01-10

  preprintOpen accessSenior author

  Abstract Programming is a cornerstone of modern society, yet its cognitive and neural basis remains poorly understood. In this study, we test the hypothesis that programming “recycles” pre-existing neural mechanisms and representations in fronto-parietal reasoning networks. Using fMRI, we scanned programming-naïve undergraduates (n=22) before (PRE) and after (POST) an introductory Python course. During the PRE scan, participants viewed pseudocode (plain English descriptions of algorithms), and during the POST scan, they read Python code. We found that a left-lateralized fronto-parietal network, previously implicated in programming experts, distinguished between “for” loops and “if” conditionals across both pseudocode and Python code. Representational similarity analysis revealed consistent representations of algorithms across formats (code/pseudocode) and learning stages. Furthermore, such representations encode abstract meanings rather than superficial features. Our findings demonstrate that programming not only recycles pre-existing neural resources evolved for logical reasoning, but the recycling takes place rapidly with only a single semester of training.

  PublisherDOI

• Animacy semantic network supports implicit causal inferences about illness

  eLife · 2025-05-02

  preprintOpen accessSenior author

  Abstract Inferring the causes of illness is a culturally universal example of causal thinking. We tested the hypothesis that implicit causal inferences about biological processes (e.g., illness) depend on the animacy semantic network. Participants (n=20) undergoing fMRI read two-sentence vignettes that elicited causal inferences across sentences, either about the emergence of illness or about the mechanical breakdown of inanimate objects, in addition to noncausal control vignettes. All vignettes were about people and were linguistically matched. The same participants performed localizer tasks: language, logical reasoning, and mentalizing. Inferring illness causes, relative to all control conditions, selectively engaged a portion of the precuneus (PC) previously implicated in the semantic representation of animates (e.g., people, animals). Neural responses to causal inferences about illness were adjacent to but distinct from responses to mental state inferences, suggesting a neural mind/body distinction. We failed to find evidence for domain-general responses to causal inference. Implicit causal inferences are supported by content-specific semantic networks that encode causal knowledge.

  PublisherDOI

• Author response: Animacy semantic network supports causal inferences about illness

  2025-11-12

  peer-reviewOpen accessSenior author

  Making causal inferences about illness, compared to making causal inferences about mechanical breakdown and reading causally unconnected sentences, activates a semantic brain network implicated in the conceptual representation of animate entities (e.g. people, animals).

  PublisherDOI

• Author response: Animacy semantic network supports implicit causal inferences about illness

  2025-05-02

  peer-reviewOpen accessSenior author

  Inferring the causes of illness is a culturally universal example of causal thinking. We tested the hypothesis that implicit causal inferences about biological processes (e.g., illness) depend on the animacy semantic network. Participants (n=20) undergoing fMRI read two-sentence vignettes that elicited causal inferences across sentences, either about the emergence of illness or about the mechanical breakdown of inanimate objects, in addition to noncausal control vignettes. All vignettes were about people and were linguistically matched. The same participants performed localizer tasks: language, logical reasoning, and mentalizing. Inferring illness causes, relative to all control conditions, selectively engaged a portion of the precuneus (PC) previously implicated in the semantic representation of animates (e.g., people, animals). Neural responses to causal inferences about illness were adjacent to but distinct from responses to mental state inferences, suggesting a neural mind/body distinction. We failed to find evidence for domain-general responses to causal inference. Implicit causal inferences are supported by content-specific semantic networks that encode causal knowledge.

  PublisherDOI

• Visual experience contributes to separation of face and language responses in the ventral stream

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-01-02

  preprintOpen accessSenior authorCorresponding

  Summary Human ventral occipitotemporal cortex (vOTC) contains specialized regions that support visual recognition of behaviorally-relevant categories, including faces, written language and places (e.g., 1–4 ). An open question is how experience interacts with innate constraints to enable functional specialization. We investigate this question by comparing vOTC function across sighted and congenitally blind adults. In sighted adults, a region in lateral vOTC called the fusiform face area (FFA) responds preferentially to faces, whereas distinct left-lateralized portions of vOTC respond to written language 1,2,5–12 . In blind people, lateral vOTC responds to face touching, braille and speech, but their functional co-localization has not been tested 13–16 . The same group of congenitally blind adults (n=20) touched faces and spatial layouts (Experiment 1) and performed a reading (braille) and spoken language task (Experiment 2). Sighted adults performed analogous tasks in the visual modality (n=28). Using within subject analyses, we replicate the separation of faces and written language in sighted adults: written language responses are found only in left vOTC and within that hemisphere they are separate from faces. By contrast, left and right vOTC responds to language in people born blind and in the left hemisphere face and language responses overlap. These findings suggest that visual experience contributes to segregating responses to face and language in vOTC. Co-localization of face and language responses suggests an innate predisposition for communication-relevant processing in lateral vOTC.

  PublisherOA PDFDOI

• Constructing Meaning from Language: Visual Knowledge in People Born Blind and in Large Language Models

  Annual Review of Linguistics · 2025-11-04 · 1 citations

  articleSenior author

  A key function of language is to enable concept construction, but empirically disentangling the contribution of language from the contribution of other (e.g., sensory) experiences is challenging. Comparing visual knowledge across sighted people, people born blind, and artificial intelligence (AI) trained exclusively on text provides rare insight. Blind people acquire rich visual knowledge, including normative meanings of light emission and visual perception verbs; similarity of colors; and size, shape, and texture of distal objects. Evidence from text-trained AI models suggests that such visual knowledge can be derived from language. Going beyond meanings of single words, blind people also construct causal intuitive theories of color, light, and visual perception, enabling generative inferences about visual phenomena (e.g., inferring the likelihood that a sighted character will see an object at a distance and the likely number of colors for a given artifact). Language enables concept construction from the ground up, without sensory evidence, and is intimately linked to intuitive theories.

  PublisherDOI

• Visual experience shapes functional connectivity between occipital and non-visual networks

  eLife · 2025-10-03

  articleOpen accessSenior author

  Abstract Comparisons of visual cortex function across blind and sighted adults reveals effects of experience on human brain function. Since almost all research has been done with adults, little is known about the developmental origins of plasticity. We compared resting state functional connectivity of visual cortices of blind adults (n = 30), blindfolded sighted adults (n = 50) to a large cohort of sighted infants (Developing Human Connectome Project, n = 475). Visual cortices of sighted adults show stronger coupling with non-visual sensory-motor networks (auditory, somatosensory/motor), than with higher-cognitive prefrontal cortices (PFC). In contrast, visual cortices of blind adults show stronger coupling with higher-cognitive PFC than with nonvisual sensory-motor networks. Are infant visual cortices functionally like those of sighted adults? Alternatively, do infants start like blind adults, with vision required to set up the sighted adult pattern? Remarkably, we find that, in infants, secondary visual cortices are more like those of blind adults: stronger coupling with PFC than with nonvisual sensory-motor networks, suggesting that visual experience establishes elements of the sighted-adult long-range connectivity. Infant primary visual cortices are in-between blind and sighted adults i.e., equal PFC and sensory-motor connectivity. The lateralization of occipital-to-frontal connectivity in infants resembles the sighted adults, consistent with reorganization by blindness. These results reveal instructive effects of vision and reorganizing effects of blindness on functional connectivity.

  PublisherDOI

• The interaction of innate constraints and experience at the language/vision interface

  Journal of Vision · 2025-07-15

  articleOpen access1st authorCorresponding

  Although most humans learn their first language via speech, visual communication is part of our evolutionary heritage and one of our earliest ways of connecting to other people in infancy (e.g., looking at faces). Studies with people who have distinctive sensory experiences (i.e., people born deaf or blind) reveal how intrinsic connections between the visual and language systems enable a broad range of adaptive behaviors. The lateral ventral occipito-temporal cortex (vOTC) sits at the junctions of the visual and language systems and in sighted people develops specialization for visual print (i.e., visual word form area.) We find that in people born blind, the lateral vOTC shows enhanced responses to spoken and written (tactile braille) language. Language responses peak in the location of the so called ‘fusiform face area’ and extend throughout the lateral vOTC and into early visual circuits. Deaf speakers of visuo-manual sign languages robustly recruit the lateral vOTC during language comprehension. The lateral vOTC becomes synchronized across Deaf individuals when viewing Polish Sign Language stories and shows higher synchrony for stories and sentences than lists of unconnected words. During story comprehension, the vOTC shows functional connectivity with the fronto-temporal language network. Together these data reveal the intrinsic connectivity between the lateral vOTC and language systems as well as the capacity of this connectivity to adapt to varying behavioral needs of the individual.

  PublisherDOI

• Visual experience shapes functional connectome gradients

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-03-02

  preprintOpen access

  Abstract The human cortex is organized along continuous functional gradients that capture systematic transitions in functional connectivity across the brain. These gradients describe large-scale organizational principles, including hierarchical transitions from unimodal to transmodal regions. Here, we provide the first characterization of cortical gradients in a large sample of congenitally blind (n = 41) and sighted (n = 44) adults to assess the relative contributions of intrinsic (genetic) and experiential factors to cortical gradient organization. Using resting-state fMRI, we compared functional connectome gradients and their association with cortical structure. Both groups exhibited similar principal gradients: unimodal to transmodal, somatosensory to visual, and frontoparietal segregation, demonstrating that the fundamental scaffold of cortical organization emerges largely independently of visual experience. However, blindness altered specific features of the functional connectome: the visual network was more segregated from the sensorimotor network and more integrated with transmodal and frontoparietal networks. Moreover, blind individuals showed reduced canonical hierarchical ordering within early visual areas, weaker structure–function coupling in visual and temporal regions, and altered functional areal boundaries in V1. These findings suggest that the development of large-scale cortical gradients reflects a genetically guided scaffold that is subsequently refined by sensory experience.

  PublisherOA PDFDOI

• Learning to Program “Recycles” Preexisting Frontoparietal Population Codes of Logical Algorithms

  Journal of Neuroscience · 2025-10-27 · 1 citations

  articleOpen accessSenior author

  Computer programming is a cornerstone of modern society, yet little is known about how the human brain enables this recently invented cultural skill. According to the neural recycling hypothesis, cultural skills (e.g., reading, math) repurpose preexisting neural “information maps.” Alternatively, such maps could emerge de novo during learning, as they do in artificial neural networks. Representing and manipulating logical algorithms, such as “for” loops and “if” conditionals, is key to programming. Are representations of these algorithms acquired when people learn to program? Alternatively, do they predate instruction and get “recycled”? College students ( n = 22, 11 females and 11 males) participated in a functional magnetic resonance imaging study before and after their first programming course (Python) and completed a battery of behavioral tasks. After a one-semester Python course, reading Python functions (relative to working memory control) activated an independently localized left-lateralized frontoparietal reasoning network. This same network was already engaged by pseudocode, plain English descriptions of Python, even before the course. Critically, multivariate population codes in this frontoparietal network distinguished “for” loops and “if” conditional algorithms, both before and after. Representational similarity analysis revealed shared information in the frontoparietal network before and after instruction. Programming recycles preexisting representations of logical algorithms in frontoparietal cortices, supporting the recycling framework of cultural skill acquisition.

  PublisherOA PDFDOI

Recent grants

• Effects of experience on shared information across brains: Insights from blindness

  NSF · $165k · 2019–2022

• Visual cortex plasticity in blindness: a window into flexibility of human cortex

  NIH · $2.4M · 2017–2022

Frequent coauthors

• Rhodri Cusack

  National Institute on Drug Abuse

  81 shared

• Mengyu Tian

  Beijing Normal University

  59 shared

• Xiang Xiao

  Beijing Normal University

  52 shared

• Huiqing Hu

  Qilu Hospital of Shandong University

  51 shared

• Rebecca Saxe

  Institute of Cognitive and Brain Sciences

  47 shared

• Álvaro Pascual‐Leone

  Hebrew SeniorLife

  45 shared

• Maria Zimmermann

  Johns Hopkins University

  28 shared

• Marcin Szwed

  27 shared

Labs

• BednyLabPI

  Research on how different life experiences can affect sentence processing and the neural basis of language.