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A brain-computer interface (BCI) is a system that aims for establishing a non-muscular communication path for subjects who had suffer from a neurodegenerative disease. Many BCI systems make use of the phenomena of event-related…

Computer Vision and Pattern Recognition · Computer Science 2016-12-28 Jaime Fernando Delgado Saa , Mujdat Cetin

Brain-computer interfaces (BCIs), particularly the P300 BCI, facilitate direct communication between the brain and computers. The fundamental statistical problem in P300 BCIs lies in classifying target and non-target stimuli based on…

Applications · Statistics 2024-02-16 Bangyao Zhao , Jane E. Huggins , Jian Kang

Running title: Frontoparietal anodal tDCS reduces ketamine-induced oscillopathies.Abstract: During the prodromal phase of schizophrenia with its complex and insidious clinical picture, electroencephalographic recordings detect widespread…

Neurons and Cognition · Quantitative Biology 2020-10-14 Caroline Lahogue , Didier Pinault

The reconstruction of brain neural network connections occurs not only during the infancy and early childhood stages of brain development, but also in patients with cognitive impairment in middle and old age under the therapy with…

Neurons and Cognition · Quantitative Biology 2024-03-12 Xuan Zhang , Duoyu Feng , Djibrina Barry , Jiajia Li

A new type of non-invasive deep-brain stimulation is conceived and demonstrated by computer simulations. The process is based on spatio-temporal Fourier synthesis using multiple electrode pairs with sinusoidal current drive to limit skin…

General Physics · Physics 2024-08-02 Laszlo B. Kish , Andrea Antal

Online field experiments are the gold-standard way of evaluating changes to real-world interactive machine learning systems. Yet our ability to explore complex, multi-dimensional policy spaces - such as those found in recommendation and…

Machine Learning · Statistics 2019-04-30 Benjamin Letham , Eytan Bakshy

Bayesian optimization has become a fundamental global optimization algorithm in many problems where sample efficiency is of paramount importance. Recently, there has been proposed a large number of new applications in fields such as…

Artificial Intelligence · Computer Science 2019-02-06 Ruben Martinez-Cantin

Most brain disorders are very heterogeneous in terms of their underlying biology and developing analysis methods to model such heterogeneity is a major challenge. A promising approach is to use probabilistic regression methods to estimate…

Machine Learning · Statistics 2018-12-03 Seyed Mostafa Kia , Christian F. Beckmann , Andre F. Marquand

Our findings indicated that brain stimulation exerted no effect on the patients cognitive functions. The study outcome suggest that tDCS over primary motor cortex may be considered as a potential nonpharmochological treatment add-on in MG.…

Objective: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique used to generate conduction currents in the head and disrupt brain functions. To rapidly evaluate the tDCS-induced current density in…

Quantitative Methods · Quantitative Biology 2022-10-07 Xiaofan Jia , Sadeed Bin Sayed , Nahian Ibn Hasan , Luis J. Gomez , Guang-Bin Huang , Abdulkadir C. Yucel

Low-intensity Transcranial Ultrasonic Stimulation (TUS) is a non-invasive brain stimulation technique enabling cortical and deep brain targeting with unprecedented spatial accuracy. Given the high rate of adoption by new users with varying…

Concurrency of transcranial magnetic stimulation with electroencephalography (TMS-EEG) technique is a powerful and challenging methodology for basic research and clinical applications. Aspects considered in experiments for effective TMS-EEG…

Neurons and Cognition · Quantitative Biology 2024-03-18 Hua Cheng

Non-invasive methods to measure brain activity are important to understand cognitive processes in the human brain. A prominent example is functional magnetic resonance imaging (fMRI), which is a noisy measurement of a delayed signal that…

Neurons and Cognition · Quantitative Biology 2020-08-17 Hans-Christian Ruiz-Euler , Jose R. Ferreira Marques , Hilbert J. Kappen

Bayesian inference promises to ground and improve the performance of deep neural networks. It promises to be robust to overfitting, to simplify the training procedure and the space of hyperparameters, and to provide a calibrated measure of…

Machine Learning · Computer Science 2019-08-12 Jonathan Heek , Nal Kalchbrenner

This thesis is dedicated to the statistical analysis of multi-sub ject fMRI data, with the purpose of identifying bain structures involved in certain cognitive or sensori-motor tasks, in a reproducible way across sub jects. To overcome…

Applications · Statistics 2010-05-19 Merlin Keller , Alexis Roche , Marc Lavielle

Sequential experimental design to discover interventions that achieve a desired outcome is a key problem in various domains including science, engineering and public policy. When the space of possible interventions is large, making an…

Machine Learning · Computer Science 2023-08-17 Jiaqi Zhang , Louis Cammarata , Chandler Squires , Themistoklis P. Sapsis , Caroline Uhler

In this work we perform a meta-analysis of neuroimaging data, consisting of locations of peak activations identified in 162 separate studies on emotion. Neuroimaging meta-analyses are typically performed using kernel-based methods. However,…

Applications · Statistics 2012-06-29 Yu Ryan Yue , Martin A. Lindquist , Ji Meng Loh

Whether transcranial direct current stimulation (tDCS) benefits stroke rehabilitation remains unclear. To investigate how tDCS reorganizes brain circuitry, nineteen post-stroke patients underwent rehabilitation sessions with bi-hemispheric…

Spinal cord injury (SCI) is a debilitating condition that often results in significant motor and sensory deficits, impacting the quality of life. Current rehabilitation methods, including physical therapy and electrical stimulation, offer…

Neurons and Cognition · Quantitative Biology 2024-12-18 Ruidong Cheng , Yuling Shao , Xi Li , Li Zhang , Zehao Sheng , Chenyang Li , Xu Xie , Huilin Mou , Weidong Chen , Shaomin Zhang , Yuchen Xu , Minmin Wang

We propose to fuse two currently separate research lines on novel therapies for stroke rehabilitation: brain-computer interface (BCI) training and transcranial electrical stimulation (TES). Specifically, we show that BCI technology can be…