collaborators

7 papers

q-bio.NC2026

Flexibility and Invariance of Object Representations in the Human Brain

Julien Dirani, Shankar Chawla, Leila Wehbe +1

The human brain represents objects in a way that is both invariant across instances and flexible enough to support different contexts and tasks. Yet how the brain reconciles these…

physics.flu-dyn2026

Stresses and fluid flow in lamina cribrosa through anisotropic poroelasticty

Riccardo Cavuoto, Sofia Damian, Luca Deseri +5

To investigate the mechanical correlations between intraocular pressure (IOP) variations and glaucoma, this study presents a linear transversely isotropic poroelastic model of the…

cs.LG2025

Meta-Learning an In-Context Transformer Model of Human Higher Visual Cortex

Muquan Yu, Mu Nan, Hossein Adeli +6

Understanding functional representations within higher visual cortex is a fundamental question in computational neuroscience. While artificial neural networks pretrained on large-s…

q-bio.NC2025

Estimating Brain Activity with High Spatial and Temporal Resolution using a Naturalistic MEG-fMRI Encoding Model

Beige Jerry Jin, Leila Wehbe

Current non-invasive neuroimaging techniques trade off between spatial resolution and temporal resolution. While magnetoencephalography (MEG) can capture rapid neural dynamics and…

cs.CL2025

Modeling the language cortex with form-independent and enriched representations of sentence meaning reveals remarkable semantic abstractness

Shreya Saha, Shurui Li, Greta Tuckute +5

The human language system represents both linguistic forms and meanings, but the abstractness of the meaning representations remains debated. Here, we searched for abstract represe…

cs.CV2025

Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers

Andrew F. Luo, Jacob Yeung, Rushikesh Zawar +4

We introduce BrainSAIL, a method for linking neural selectivity with spatially distributed semantic visual concepts in natural scenes. BrainSAIL leverages recent advances in large-…