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Deep Brain Stimulation (DBS) is an effective treatment for Parkinson's disease, but conventional fixed-parameter stimulation can reduce battery life and cause side effects while failing to adapt to changing neural dynamics. Recent…

Functional magnetic resonance imaging (fMRI) has been widely utilized to study the motor deficits and rehabilitation following stroke. In particular, functional connectivity(FC) analyses with fMRI at rest can be employed to reveal the…

Neurons and Cognition · Quantitative Biology 2023-01-19 Kaichao Wu , Beth Jelfs , Katrina Neville , John Q. Fang

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is widely used to study the reactivity and connectivity of brain regions for clinical or research purposes. The electromagnetic pulse of the TMS device…

Quantitative Methods · Quantitative Biology 2019-10-30 Panteleimon Vafeidis , Vasilios K. Kimiskidis , Dimitris Kugiumtzis

The mechanisms by which blast pressure waves cause mild to moderate traumatic brain injury (mTBI) are an open question. Possibilities include acceleration of the head, direct passage of the blast wave via the cranium, and propagation of the…

Medical Physics · Physics 2008-12-31 Amy Courtney , Michael Courtney

Dynamic Causal Modeling (DCM) is a Bayesian framework for inferring on hidden (latent) neuronal states, based on measurements of brain activity. Since its introduction in 2003 for functional magnetic resonance imaging data, DCM has been…

Quantitative Methods · Quantitative Biology 2021-04-08 Inês Pereira , Stefan Frässle , Jakob Heinzle , Dario Schöbi , Cao Tri Do , Moritz Gruber , Klaas E. Stephan

Objective: A major challenge in designing closed-loop brain-computer interfaces is finding optimal stimulation patterns as a function of ongoing neural activity for different subjects and objectives. Approach: To achieve goal-directed…

Neurons and Cognition · Quantitative Biology 2023-03-22 Matthew J. Bryan , Linxing Preston Jiang , Rajesh P N Rao

In 1996, Berger and Slonczewski independently predicted that a large enough spin-polarized dc current density sent perpendicularly through a ferromagnetic layer could produce magnetic excitations (spin-waves) or reversal of magnetization…

Materials Science · Physics 2009-11-10 J. Bass , S. Urazhdin , Norman O. Birge , W. P. Pratt

Posttraumatic stress disorder (PTSD) is a chronic and disabling neuropsychiatric disorder characterized by insufficient top-down modulation of the amygdala activity by the prefrontal cortex. Real-time fMRI neurofeedback (rtfMRI-nf) is an…

Neurons and Cognition · Quantitative Biology 2018-04-13 Vadim Zotev , Raquel Phillips , Masaya Misaki , Chung Ki Wong , Brent E. Wurfel , Frank Krueger , Matthew Feldner , Jerzy Bodurka

Perceived outcomes from DBS for PD were sampled for 52 cases by surveying 46 DBS recipients and 45 carers. Post-DBS experience ranged from 10-129 months. There were significant variations in perceived outcomes over time. In some cases…

Neurons and Cognition · Quantitative Biology 2015-08-11 N. W. Page , C. Hall , S. D. Page

This paper investigates the controllability of a broad class of recurrent neural networks widely used in theoretical neuroscience, including models of large-scale human brain dynamics. Motivated by emerging applications in non-invasive…

Optimization and Control · Mathematics 2025-09-29 Cyprien Tamekue , Ruiqi Chen , ShiNung Ching

Automated vehicles will allow occupants to engage in non-driving tasks, but limited visual cues will make them vulnerable to unexpected movements. These unpredictable perturbations create a "surprise factor," forcing the central nervous…

Systems and Control · Electrical Eng. & Systems 2025-08-05 Chrysovalanto Messiou , Riender Happee , Georgios Papaioannou

This study demonstrates the capability of external signal recording into memory and the reproduction of memory trace of this pattern in EEG by direct AC electrical stimulation of rat cerebral cortex. Additionally, we examine shifts of the…

Neurons and Cognition · Quantitative Biology 2011-11-23 A. G. Shapkin , M. V. Taborov , Yu. G. Shapkin

A deep neural network (DNN) that can reliably model muscle responses from corresponding brain stimulation has the potential to increase knowledge of coordinated motor control for numerous basic science and applied use cases. Such cases…

Current theories of language recovery after stroke are limited by a reliance on small studies. Here, we aimed to test predictions of current theory and resolve inconsistencies regarding right hemispheric contributions to long-term recovery.…

Neurons and Cognition · Quantitative Biology 2017-01-13 Joseph C. Griffis , Rodolphe Nenert , Jane B. Allendorfer , Jennifer Vannest , Scott Holland , Aimee Dietz , Jerzy P. Szaflarski

Electroencephalographic neurofeedback (EEG-NF) has been proposed as a promising technique to modulate brain activity through real-time EEG-based feedback. Alpha neurofeedback in particular is believed to induce rapid self-regulation of…

Neurons and Cognition · Quantitative Biology 2025-09-15 Jacob Maaz , Laurent Waroquier , Alexandra Dia , Véronique Paban , Arnaud Rey

Electrical brain stimulation relies on externally applied currents to modulate neural activity, but safety constraints require each stimulation cycle to be charge-balanced, enforcing a zero net injected charge. However, how such…

Systems and Control · Electrical Eng. & Systems 2025-12-09 Yuzhen Qin , Zonglin Liu , Marcel van Gerven

Vagus nerve stimulation (VNS) has emerged as a promising therapeutic intervention across various neurological and psychiatric conditions, including epilepsy, depression, and stroke rehabilitation; however, its mechanisms of action on neural…

Neurons and Cognition · Quantitative Biology 2025-02-03 Shinichi Kumagai , Tomoyo Isoguchi Shiramatsu , Kensuke Kawai , Hirokazu Takahashi

Long-term efficacy of internal globus pallidus (GPi) deep-brain stimulation (DBS) in DYT1 dystonia and disease progression under DBS was studied. Twenty-six patients of this open-label study were divided into two groups: (A) with single…

Extracting causal connections can advance interpretable AI and machine learning. Granger causality (GC) is a robust statistical method for estimating directed influences (DC) between signals. While GC has been widely applied to analysing…

Neurons and Cognition · Quantitative Biology 2024-08-06 Abdoreza Asadpour , KongFatt Wong-Lin

Multiscale modelling presents a multifaceted perspective into understanding the mechanisms of the brain and how neurodegenerative disorders like Parkinson's disease (PD) manifest and evolve over time. In this study, we propose a novel…

Neurons and Cognition · Quantitative Biology 2025-09-18 Aaron Herrera , Hina Shaheen