Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.03.09.642235

Local and distributed information coding in the ventral stream

Abstract

Neuroscience is replete with evidence that cognitive representations are distributed across many cortical regions. Yet, the scale and content of such distributed processing is unclear. Do findings of widespread information coding suggest a large-scale "forest" of regions interacting to represent information or instead imply a multitude of small-scale trees, processing information as localized modules. To investigate this distinction, we used visual and semantic representational analysis of fMRI data from 60 participants viewing everyday objects in multiple task contexts, and we examined the relationships between regions in terms of information coding. We demonstrate that coding of visual content in the occipital lobe is overwhelmingly modular, such that different occipital structures show limited coordination and tend to encode information redundantly. By contrast, the coding of semantic content in the inferior temporal lobe involves a high degree of coordination between regions, which optimize their coding to collectively represent a large semantic space with minimal redundancy between regions. No other brain area - neither the parietal nor prefrontal cortices - shows the preference for large-scale coding seen in the inferior temporal lobe. Taken together, these results outline a framework of how the ventral stream transitions from small-scale to large-scale coding as information progresses from visual to semantic representations. Significance statementHow does the brain convert incoming signals into usable information? Many studies have investigated this question by attempting to clarify which brain regions encode what information (e.g., V4 encodes color information). We instead aimed to shed light on the degree of coordination among information coding regions. We find that the visual-to-semantic transition as information flows anteriorly in the occipitotemporal cortex is accompanied by a shift from modular to distributed coding. That is, occipital regions encode perceptual information relatively independently with redundancy, while inferior temporal lobe regions cooperate to most efficiently represent a large space of semantic information. By leveraging ideas from information theory, our work introduces coding scale as a new dimension for understanding the architecture of information coding.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bogdan, P. C., Howard, C., Gillette, K., Cabeza, R., Davis, S. W.. 2025-03-11. Local and distributed information coding in the ventral stream. https://doi.org/10.1101/2025.03.09.642235

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗