Results 51 to 60 of about 2,017,547 (269)

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

COMPUTATIONAL NEUROSCIENCE FOR ADVANCING ARTIFICIAL INTELLIGENCE

Cuadernos de Neuropsicología, 2011
resumen del libro de Alonso, E. y Mondragón, E. (2011). Hershey, NY: Medical Information Science Reference. La neurociencia como disciplinapersigue el entendimiento del cerebro y su relación con el funcionamiento de la mente a través del análisis de la ...
Fernando P. Ponce
doaj   +2 more sources

Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm [v1; ref status: indexed, http://f1000r.es/2qo]

F1000Research, 2014
When studying animal behaviour within an open environment, movement-related data are often important for behavioural analyses. Therefore, simple and efficient techniques are needed to present and analyze the data of such movements.
Christopher R Madan, Marcia L Spetch
doaj   +1 more source

Gravity‐Dependent Modulation of Downbeat Nystagmus: Insights From Velocity‐Storage Dysfunction

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Downbeat nystagmus varies with head position, a phenomenon termed gravity‐dependent modulation. We aimed to clarify its mechanism using a velocity‐storage model. Methods In 10 patients with downbeat nystagmus due to cerebellar disorders, we recorded eye movements at different pitch‐ and roll‐axis head positions.
Ji‐Hyung Park, Eun‐Hyuk Choi, Jorge Otero‐Millan, David S. Zee, Jeong‐Yoon Choi, Ji‐Soo Kim   +5 more
wiley   +1 more source

Towards Explainable Deep Learning in Computational Neuroscience: Visual and Clinical Applications

Mathematics
Deep learning has emerged as a powerful tool in computational neuroscience, enabling the modeling of complex neural processes and supporting data-driven insights into brain function. However, the non-transparent nature of many deep learning models limits
Asif Mehmood, Faisal Mehmood, Jungsuk Kim   +2 more
doaj   +1 more source

Equilibrium and response properties of the integrate-and-fire neuron in discrete time

Frontiers in Computational Neuroscience, 2010
The integrate-and-fire neuron with exponential postsynaptic potentials is a frequently employed model to study neural networks. Simulations in discrete time still have highest performance at moderate numerical errors, which makes them first choice for ...
Moritz Helias, Moritz Helias, Moritz Deger, Moritz Deger, Markus Diesmann, Markus Diesmann, Markus Diesmann, Stefan Rotter, Stefan Rotter   +8 more
doaj   +1 more source

Neuroscience Needs Network Science [PDF]

, 2023
The brain is a complex system comprising a myriad of interacting neurons, posing significant challenges in understanding its structure, function, and dynamics.
Bullmore, E, Sporns, O, Kovács, IA, Hernán Makse, Christos Papadimitriou, Albert-László Barabási, György Buzsáki, Hongkui Zeng, Bianconi, G, Ed Bullmore, Zador, AM, Tina Eliassi-Rad, Thomas E. Nichols, Towlson, EK, Zeng, H, Anthony M. Zador, Buzsáki, G, Kim Stachenfeld, Burgess, M, Nichols, TE, Olaf Sporns, Amy Bernard, Barabási, DL, Dileep George, Emma K. Towlson, Bernard, A, Stachenfeld, K, Mark Burgess, SueYeon Chung, Zoltán Toroczkai, Chung, S, Dániel L. Barabási, George, D, Ginestra Bianconi, Eliassi-Rad, T, István A. Kovács, Makse, H, Barabási, A-L, Toroczkai, Z, Papadimitriou, C   +39 more
core   +1 more source

Temporal Interference Stimulation of Centromedian‐Parafascicular Complex in Disorders of Consciousness: A Pilot Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu, Changgeng Song, Dianwei Wu, Xiaoqian Niu, Jianmin Hao, Lijuan Liu, Xiaogang Kang, Wen Jiang   +7 more
wiley   +1 more source

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

Reproducing asymmetrical spine shape fluctuations in a model of actin dynamics predicts self-organized criticality

Scientific Reports, 2021
Dendritic spines change their size and shape spontaneously, but the function of this remains unclear. Here, we address this in a biophysical model of spine fluctuations, which reproduces experimentally measured spine fluctuations.
Mayte Bonilla-Quintana, Florentin Wörgötter, Elisa D’Este, Christian Tetzlaff, Michael Fauth   +4 more
doaj   +1 more source