Taliah Muhammad

omnimouse-dataset

Paul G. Fahey, Kayla Ponder, Taliah Muhammad, Rachel Froebe et autres

OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens

Konstantin F. Willeke, Polina Turishcheva, Alex Gilbert, Goirik Chakrabarty et autres

Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to modeling brain activity remains unclear. Here we leveraged a dataset of 3.1 million neurons from the visual cortex of 73 mice across …

OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens

Konstantin F. Willeke, Polina Turishcheva, Alex Gilbert, Goirik Chakrabarty et autres

Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to modeling brain activity remains unclear. Here we leveraged a dataset of 3.1 million neurons from the visual cortex of 73 mice across …

cz, us, ca, de (code pays fourni par la source)

Functional bipartite invariance in mouse primary visual cortex receptive fields

Zhiwei Ding, Dat T. Tran, Kayla Ponder, Zhuokun Ding et autres

This dataset contains large-scale recordings from layer 2/3 neurons in mouse primary visual cortex (V1) collected under awake, head-fixed conditions. It supports the study “Functional bipartite invariance in mouse primary visual cortex receptive fields” (Ding, Tran, et al., Nature Neuroscience, 2026). The …

us, cz, bg, gr, de, it (code pays fourni par la source)

An Intelligent CT Image Analysis System for Automated Detection of Kidney Stones Using Deep Learning

Daniel Lucky Dr. Enosegbe, Theophilus Aniemeka Enem, Suleiman Abu Usman, Taliah Muhammad

Kidney stone disease is a common ailment that needs to be diagnosed in due time and in an accurate manner to avoid extreme complications like obstruction of the kidney, infection and permanent damages to the kidney. Computed Tomography (CT) imaging is considered …

Nigéria, us (code pays fourni par la source)

Foundation model of neural activity predicts response to new stimulus types

Eric Y. Wang, Paul G. Fahey, Zhuokun Ding, Stelios Papadopoulos et autres

Abstract The complexity of neural circuits makes it challenging to decipher the brain’s algorithms of intelligence. Recent breakthroughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brain’s computational objectives and neural coding. However, it …

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Functional connectomics reveals general wiring rule in mouse visual cortex

Zhuokun Ding, Paul G. Fahey, Stelios Papadopoulos, Eric Y. Wang et autres

; however, broader connectivity rules remain unknown. Here we leverage the millimetre-scale MICrONS dataset to analyse synaptic connectivity and functional properties of neurons across cortical layers and areas. Our results reveal that neurons with similar response properties are preferentially connected within and …

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Functional connectomics spanning multiple areas of mouse visual cortex

J. Alexander Bae, Mahaly Baptiste, Maya R. Baptiste, Caitlyn A. Bishop et autres

Abstract Understanding the brain requires understanding neurons’ functional responses to the circuit architecture shaping them. Here we introduce the MICrONS functional connectomics dataset with dense calcium imaging of around 75,000 neurons in primary visual cortex (VISp) and higher visual areas (VISrl, VISal …

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Heterogeneous orientation tuning in the primary visual cortex of mice diverges from Gabor-like receptive fields in primates

Jiakun Fu, Paweł A. Pierzchlewicz, Konstantin F. Willeke, Mohammad Bashiri et autres

A key feature of neurons in the primary visual cortex (V1) of primates is their orientation selectivity. Recent studies using deep neural network models showed that the most exciting input (MEI) for mouse V1 neurons exhibit complex spatial structures that predict non-uniform …

us, de, gr (code pays fourni par la source)

Foundation model of neural activity predicts response to new stimulus types and anatomy

Eric Y. Wang, Paul G. Fahey, Zhuokun Ding, Stelios Papadopoulos et autres

The complexity of neural circuits makes it challenging to decipher the brain's algorithms of intelligence. Recent breakthroughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brain's computational objectives and neural coding. However, these models …

us, de (code pays fourni par la source)

Bipartite invariance in mouse primary visual cortex

Zhiwei Ding, Dat Thanh Tran, Kayla Ponder, Erick Cobos et autres

A defining characteristic of intelligent systems, whether natural or artificial, is the ability to generalize and infer behaviorally relevant latent causes from high-dimensional sensory input, despite significant variations in the environment. To understand how brains achieve generalization, it is crucial to identify …

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Pattern completion and disruption characterize contextual modulation in the visual cortex

Jiakun Fu, Suhas Shrinivasan, Luca Baroni, Zhuokun Ding et autres

Vision is fundamentally context-dependent, with neuronal responses influenced not just by local features but also by surrounding contextual information. In the visual cortex, studies using simple grating stimuli indicate that congruent stimuli - where the center and surround share the same orientation …

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