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Data-driven benchmarks have led to significant progress in key scientific modeling domains including weather and structural biology. Here, we introduce the Zebrafish Activity Prediction Benchmark (ZAPBench) to measure progress on the…

Brain activity is characterized by brain-wide spatiotemporal patterns which emerge from synapse-mediated interactions between individual neurons. Calcium imaging provides access to in vivo recordings of whole-brain activity at single-neuron…

Neurons and Cognition · Quantitative Biology 2023-09-13 Richard E. Rosch , Dominic R. W. Burrows , Christopher W. Lynn , Arian Ashourvan

Contemporary computational neuroscience features two prominent modeling traditions. Bottom-up whole-brain modeling (WBM) builds biophysically detailed simulations of brain structure and dynamics, whereas top-down neuroconnectionism…

Neurons and Cognition · Quantitative Biology 2026-05-19 Mario Senden , Leonardo Dalla Porta , Jan Fousek , Jorge F. Mejias , Gorka Zamora-López

Epileptic seizures are characterised by abnormal brain dynamics at multiple scales, engaging single neurons, neuronal ensembles and coarse brain regions. Key to understanding the cause of such emergent population dynamics, is capturing the…

Neurons and Cognition · Quantitative Biology 2022-12-13 Dominic RW Burrows

Larval zebrafish exhibit a variety of complex undulatory swimming patterns. This repertoire is controlled by the 300 neurons projecting from brain into spinal cord. Understanding how descending control signals shape the output of spinal…

Neurons and Cognition · Quantitative Biology 2007-05-23 Scott A. Hill , Xiao-Ping Liu , Melissa A. Borla , Jorge V. Jose , Donald M. O'Malley

We introduce a foundational model for brain dynamics that utilizes stochastic optimal control (SOC) and amortized inference. Our method features a continuous-discrete state space model (SSM) that can robustly handle the intricate and noisy…

Machine Learning · Computer Science 2025-02-10 Joonhyeong Park , Byoungwoo Park , Chang-Bae Bang , Jungwon Choi , Hyungjin Chung , Byung-Hoon Kim , Juho Lee

Humanoid robots are drawing significant attention as versatile platforms for complex motor control, human-robot interaction, and general-purpose physical intelligence. However, achieving efficient whole-body control (WBC) in humanoids…

Robotics · Computer Science 2026-02-10 Mingqi Yuan , Tao Yu , Wenqi Ge , Xiuyong Yao , Huijiang Wang , Jiayu Chen , Bo Li , Wei Zhang , Wenjun Zeng , Hua Chen , Xin Jin

To overcome the quadratic cost of self-attention, recent works have proposed various sparse attention modules, most of which fall under one of two groups: 1) sparse attention under a hand-crafted patterns and 2) full attention followed by a…

Machine Learning · Computer Science 2022-10-28 Sungjun Cho , Seonwoo Min , Jinwoo Kim , Moontae Lee , Honglak Lee , Seunghoon Hong

Constructing mechanistic models of neural circuits is a fundamental goal of neuroscience, yet verifying such models is limited by the lack of ground truth. To rigorously test model discovery, we establish an in silico testbed using…

Neurons and Cognition · Quantitative Biology 2026-02-05 Jan-Matthis Lueckmann , Viren Jain , Michał Januszewski

Neuroscience research has made immense progress over the last decade, but our understanding of the brain remains fragmented and piecemeal: the dream of probing an arbitrary brain region and automatically reading out the information encoded…

Larval zebrafish hunting provides a tractable setting to study how ecological and energetic constraints shape adaptive behavior in both biological brains and artificial agents. Here we develop a minimal agent-based model, training recurrent…

Neurons and Cognition · Quantitative Biology 2025-10-07 Raaghav Malik , Satpreet H. Singh , Sonja Johnson-Yu , Nathan Wu , Roy Harpaz , Florian Engert , Kanaka Rajan

We present a unified statistical framework for characterizing community structure of brain functional networks that captures variation across individuals and evolution over time. Existing methods for community detection focus only on…

Machine Learning · Computer Science 2022-01-10 Chee-Ming Ting , S. Balqis Samdin , Meini Tang , Hernando Ombao

Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured…

Machine Learning · Computer Science 2025-02-25 Bishal Thapaliya , Esra Akbas , Jiayu Chen , Raam Sapkota , Bhaskar Ray , Pranav Suresh , Vince Calhoun , Jingyu Liu

In this report, we introduce a novel self-supervised learning method for extracting latent embeddings from behaviors of larval zebrafish. Drawing inspiration from Masked Modeling techniquesutilized in image processing with Masked…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Lanxin Xu , Shuo Wang

Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impel…

Biological Physics · Physics 2016-01-28 Bertrand Collignon , Axel Séguret , José Halloy

Large-scale neuronal activity recordings with fluorescent calcium indicators are increasingly common, yielding high-resolution 2D or 3D videos. Traditional analysis pipelines reduce this data to 1D traces by segmenting regions of interest,…

The stochastic block model (SBM) is widely studied as a benchmark for graph clustering aka community detection. In practice, graph data often come with node attributes that bear additional information about the communities. Previous works…

Disordered Systems and Neural Networks · Physics 2023-09-12 O. Duranthon , L. Zdeborová

The cerebellum plays a distinctive role within our motor control system to achieve fine and coordinated motions. While cerebellar lesions do not lead to a complete loss of motor functions, both action and perception are severally impacted.…

Robotics · Computer Science 2020-11-04 Omar Zahra , David Navarro-Alarcon , Silvia Tolu

Foundation models show strong potential for large-scale, high-dimensional biomedical applications, yet their ability to capture relevant neurobiological characteristics remains underexplored. We systematically evaluate embeddings from two…

Signal Processing · Electrical Eng. & Systems 2026-04-17 Ye Tao , Bradley T. Baker , Yu Wu , Anand D. Sarwate , Sandeep Panta , Sergey Plis , Vince D. Calhoun

Collective movements are pervasive behaviours among social organisms and have led to the development of many models. However, modelling animal trajectories and social interactions in simple bounded environments remains a challenge.…

Neurons and Cognition · Quantitative Biology 2018-11-28 Leo Cazenille , Nicolas Bredeche , José Halloy
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