bioRxiv

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A generative deep learning method for global species distribution prediction

bioRxiv Jan 1, 2025
Anthropogenic pressures on biodiversity necessitate efficient and scalable methods to predict global species distributions. Current species distribution models (SDMs) face limitations with large-scale datasets, complex interspecies interactions, and ...
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Adaptive recruitment of cortex-wide recurrence for visual object recognition

bioRxiv Jan 1, 2025
Theories of the neural mechanism underpinning rapid recognition debate whether it relies solely on a feedforward sweep through the ventral stream or instead requires recurrent processing, possibly engaging additional brain regions. Here we directly t...
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Auditory Working Memory in Adolescents with Specific Learning Disorders

bioRxiv Jan 1, 2025
Specific Learning Disorders (SLD), including dyslexia, dyscalculia, and dysgraphia, are associated with deficits in executive functions such as auditory working memory (AWM). This study investigated AWM performance and metacognitive monitoring in ado...
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Accurate protein structure determination from cryo-EM maps using deep learning and structure prediction

bioRxiv Jan 1, 2025
Cryo-electron microscopy (cryo-EM) has become the main-stream technique for macromolecular structure determination. However, due to intrinsic resolution heterogeneity, accurate modeling of all-atom structure from cryo-EM maps remains challenging even...
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Hierarchical Coarse-to-Fine cGAN for Subtype-Specific Freezing of Gait Signal Generation

bioRxiv Jan 1, 2025
Freezing of gait (FOG), a debilitating symptom of Parkinson’s disease, manifests in subtypes as shuffling, trembling, or akinesias, with occurrence and frequency varying across patients. While deep learning (DL) models show promise in FOG detection, ...
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Disentangling covariate effects on single cell-resolved epigenomes with DeepDive

bioRxiv Jan 1, 2025
Understanding the effects of individual biological factors from single cell-resolved epigenomic data is hindered by multicollinearity, particularly in human cohorts. We introduce DeepDive, a novel deep learning framework designed to systematically di...
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Ventral striatal astrocytes contribute to reinforcement learning

bioRxiv Jan 1, 2025
Astrocytes influence synaptic plasticity and neuronal function through astrocytic calcium dynamics (ACD). However, astrocytes’ contribution to cognitive operations like reinforcement learning (RL) remains unclear. To examine this, we trained mice on ...
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Stimulation with ECoG electrodes modulates cortical activity and sensory processing in the awake mouse brain

bioRxiv Jan 1, 2025
Electrical stimulation has been widely used to probe neural network properties and treat dysfunction. Electrocorticography (ECoG) electrodes, long used for activity monitoring, can also stimulate the brain in a minimally invasive and chronic manner. ...
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Deep Learning–Based Control of Electrically Evoked Activity in Human Visual Cortex

bioRxiv Jan 1, 2025
Visual cortical prostheses offer a promising path to sight restoration, but current systems elicit crude, variable percepts and rely on manual electrode-by-electrode calibration that does not scale. This work introduces an automated data-driven neura...
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Towards functional annotation with latent protein language model features

bioRxiv Jan 1, 2025
Protein Language Models (PLMs) create high-dimensional embeddings that can be transformed into interpretable sparse features using Sparse Autoencoders (SAEs), where each feature activates on specific protein elements or patterns. However, scalably id...
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