[Paper] Discovering Functionally Selective Brain Regions with a Deep Topographic Multimodal Model
Source: arXiv - 2606.09770v1
Overview
Nearby neurons in cortex share similar response profiles, producing systematic spatial organization across sensory and cognitive systems. Recent topographic models reproduce aspects of this structure but remain unimodal and spatially constrain each layer separately, yielding fragmented maps that capture neither the contiguity of cortical processing streams nor their integration across modalities. We introduce Topo-Omni, a topographic multimodal model in which visual, auditory, and language/cognitive processing share a single contiguous in-silico sheet. Built by fine-tuning a pretrained foundation model with a spatial smoothness objective, this architecture develops clusters across modalities that are consistent with human neuroimaging, from sensory to cognitive systems. Driving or suppressing a cluster selectively biases or impairs perception, paralleling human intervention studies. Finally, we use our model to screen for novel clusters in-silico and discover new natural landscape and animal networks which we validate in human data. A single spatial principle thus organizes representations across modalities and processing stages, yielding testable hypotheses about cortical organization.
Key Contributions
This paper presents research in the following areas:
- q-bio.NC
- cs.LG
Methodology
Please refer to the full paper for detailed methodology.
Practical Implications
This research contributes to the advancement of q-bio.NC.
Authors
- Badr AlKhamissi
- Johannes Mehrer
- Lara Marinov
- Ahmed Abdelaal
- Abdulkadir Gokce
- Martin Schrimpf
Paper Information
- arXiv ID: 2606.09770v1
- Categories: q-bio.NC, cs.LG
- Published: June 8, 2026
- PDF: Download PDF