Content-based image retrieval (CBIR) in neuroimaging enables the identification of structurally similar brain scans, supporting diagnosis, prognosis, and treatment planning; however, existing methods are often limited to small datasets, single brain regions, or coarse class labels, thereby restricting their clinical ut...
Félix Nieto-del-Amor, Jing-Ru Fu, J.-Sebastian Muehlboeck et al.· 0 citations
Large-scale EEG foundation models have demonstrated promising transferability across neurological disorders, but often require millions of parameters and substantial computational resources. In this paper, we present the Universal Semantic EEG Foundation Model (USE-FM), a lightweight EEG foundation model that learns tr...
Decoding visual content from fMRI signals recorded while a person views images, and specifically answering questions about the seen images, is a long-standing challenge. While significant progress has been made in recent years in visual question answering (VQA) from fMRI, performance remains limited. Moreover, although...
Roman Beliy, Matias Cosarinsky, Oliver Heinimann et al.· 0 citations
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Researchers often support the claim that a model shares structure with the brain, or across languages, by reporting a similarity score. We ask what such a score reads when the shared structure is absent, or when the tool that measures it does not work. We check two settings, and in both the score is not what it appears...
Understanding how humans reason -- and how reasoning responses vary across tasks and individuals -- remains a core challenge for modeling and explanation in cognitive science. We investigate the stability of response patterns within reasoners and whether variation in these patterns can be used to predict learning effec...
Clemens Bombach, Rajmadan Lakshmanan, Marco Ragni· 0 citations
What can representational similarity matrices (RSMs) tell us about a neural code? As the popularity of these summary statistics grows, so too does the need for a more complete characterization of their properties. Here, we show that symmetries in network inputs can confound RSM-based analyses. Stimulus symmetries rende...
Farhad Pashakhanloo, Jacob A. Zavatone-Veth· 0 citations
Biological neural networks (BNNs) have been established as a powerful and adaptive substrate that offer the potential for incredibly energy and data efficient information processing with distinct learning mechanisms. Yet a core challenge to utilizing BNN for neurocomputation is determining the optimal encoding and deco...
Johnson Zhou, Daniel Tanneberg, Forough Habibollahi et al.· 0 citations
Contrastive representation learning is increasingly used to recover low-dimensional structure from neural recordings, but its output is typically validated by decoding accuracy rather than by the geometry of the manifold it produces. We apply CEBRA to EEG recorded from dyads in conversation, and analyze the resulting e...
Hubert Huang, Michelle McCleod, Brendan Ames et al.· 0 citations
Neural network loss landscapes have many symmetries, which are preserved by gradient flow but broken by finite-stepsize stochastic gradient descent (SGD). A canonical example of such a symmetry is scale in homogeneous networks: one can scale up the parameters in one layer and down in the next without changing the netwo...
Farhad Pashakhanloo, Jacob A. Zavatone-Veth· 0 citations
Understanding how neural activity represents higher-order cognition and how these representations evolve over time has long been a central pursuit in neuroscience. However, current analytical tools cannot easily distinguish representational plasticity from recording instability in chronic neural recordings. Here, we in...
Hanrui Lyu, Baiyuan Chen, Tianshu Tan et al.· 0 citations
Physical Activity (PA) is consistently associated with lower risk of dementia, yet the mechanism linking PA to dementia prevention remain incomopletely understood. Here, we integrate large language model (LLM)-guided causal discovery with mediation analysis in 42,293 older adults aged 60 years or older from the UK Biob...
Wasif Khan, Panayiotis V. Benos, Joshua K. Wong et al.· 0 citations
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