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Emotion regulation plays a key role in human behavior and overall well-being. Neurofeedback is a non-invasive self-brain training technique used for emotion regulation to enhance brain function and treatment of mental disorders through…

Neurons and Cognition · Quantitative Biology 2023-11-06 Amin Dehghani , Hamid Soltanian-Zadeh , Gholam-Ali Hossein-Zadeh

Mindfulness-based interventions have proven its efficacy in treating post-traumatic stress disorder (PTSD), but the underlying neurobiological mechanism is unknown. To determine the neurobiological mechanism of action of mindfulness-based…

Neurons and Cognition · Quantitative Biology 2020-10-14 Seung Suk Kang , Ph. D. , Scott R. Sponheim , Ph. D. , Kelvin O. Lim , M. D

Topological data analysis (TDA) approaches are becoming increasingly popular for studying the dependence patterns in multivariate time series data. In particular, various dependence patterns in brain networks may be linked to specific tasks…

Methodology · Statistics 2023-12-04 Anass B. El-Yaagoubi , Hernando Ombao

Global brain activity self-organizes into discrete patterns characterized by distinct behavioral observables and modes of information processing. The human thalamocortical system is a densely connected network where local neural activation…

Recently, the application of deep learning models to diagnose neuropsychiatric diseases from brain imaging data has received more and more attention. However, in practice, exploring interactions in brain functional connectivity based on…

Machine Learning · Computer Science 2022-06-29 Sartaj Ahmed Salman , Zhichao Lian , Milad Taleby Ahvanooey , Hiroki Takahashi , Yuduo Zhang

Deep brain stimulation (DBS) can alleviate the movement disorders like Parkinson's disease (PD). Indeed, it is known that aberrant beta (13-30Hz)oscillations and the loss of dopaminergic neurons in the basal ganglia-thalamus (BGTH) and…

Neurons and Cognition · Quantitative Biology 2021-12-07 Hina Shaheen , Roderick Melnik

Dynamic functional connectivity is an effective measure for the brain's responses to continuous stimuli. We propose an inferential method to detect the dynamic changes of brain networks based on time-varying graphical models. Whereas most…

Applications · Statistics 2020-06-23 Dingjue Ji , Junwei Lu , Yiliang Zhang , Hongyu Zhao , Siyuan Gao

Depression is a major cause of global mental illness and significantly influences suicide rates. Timely and accurate diagnosis is essential for effective intervention. Electroencephalography (EEG) provides a non-invasive and accessible…

Signal Processing · Electrical Eng. & Systems 2025-11-11 Soujanya Hazra , Sanjay Ghosh

Background and Objective: Transcranial temporal interference stimulation (tTIS) is a promising non-invasive brain stimulation technique in which interference between electrical current fields extends the possibilities of electrical brain…

Numerical Analysis · Mathematics 2026-02-05 Santtu Söderholm , Maryam Samavaki , Sampsa Pursiainen

This study investigates brain connectivity and information flow during mental workload (MWL) by integrating electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals. Utilizing the N-back task to induce varying…

Signal Processing · Electrical Eng. & Systems 2025-11-05 Mohaddese Qaremohammadlou , Mohammad Bagher Shamsollahi

True-time delayers (TTDs) are popular analog devices for facilitating near-field wideband beamforming subject to the spatial-wideband effect. In this paper, an adaptive TTD configuration is proposed for short-range TTDs. Compared to the…

Information Theory · Computer Science 2024-03-28 Hsienchih Ting , Zhaolin Wang , Yuanwei Liu

Dynamic networks have been increasingly used to characterize brain connectivity that varies during resting and task states. In such characterizations, a connectivity network is typically measured at each time point for a subject over a…

Methodology · Statistics 2023-03-23 Maoyu Zhang , Biao Cai , Wenlin Dai , Dehan Kong , Hongyu Zhao , Jingfei Zhang

As the world's first primary morbidity factor, depression has a considerable impact on both an individual as well as a societal level. despite their discovery several decades ago, classical antidepressants have been shown to provide limited…

Quantitative Methods · Quantitative Biology 2020-07-17 Camile Bahi

Clinical depression or Major Depressive Disorder (MDD) is a common and serious medical illness. In this paper, a deep recurrent neural network-based framework is presented to detect depression and to predict its severity level from speech.…

Human-Computer Interaction · Computer Science 2020-03-13 Emna Rejaibi , Ali Komaty , Fabrice Meriaudeau , Said Agrebi , Alice Othmani

Exploring the human brain networks during rest is a topic of great interest. Several structural and functional studies have previously been conducted to study the intrinsic brain networks. In this paper, we focus on investigating the human…

Neurons and Cognition · Quantitative Biology 2016-07-05 Aya Kabbara , Wassim El Falou , Mohamad Khalil , Fabrice Wendling , Mahmoud Hassan

Recently, we reported an emotion self-regulation study (Zotev et al., 2020), in which patients with major depressive disorder (MDD) used simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) to upregulate two fMRI and two EEG…

Neurons and Cognition · Quantitative Biology 2020-10-23 Vadim Zotev , Jerzy Bodurka

High-definition transcranial direct current stimulation (HD-tDCS) dosing in children remains largely empirical, relying on one-size-fits-all protocols despite rapid developmental changes in head anatomy and tissue properties that strongly…

Quantitative Methods · Quantitative Biology 2025-12-02 Zeming Liu , Mo Wang , Xuanye Pan , Yuan Yang , Wilson Truccolo , Quanying Liu

Major depressive disorder (MDD) is one of the most common mental disorders, with significant impacts on many daily activities and quality of life. It stands as one of the most common mental disorders globally and ranks as the second leading…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Nojod M. Alotaibi , Areej M. Alhothali , Manar S. Ali

Background: The evolution of symptoms over time is at the heart of understanding and treating mental disorders. However, a principled, quantitative framework explaining symptom dynamics remains elusive. Here, we propose a Network Control…

Precision medicine has received attention both in and outside the clinic. We focus on the latter, by exploiting the relationship between individuals' social interactions and their mental health to develop a predictive model of one's…

Social and Information Networks · Computer Science 2019-08-08 Shikang Liu , David Hachen , Omar Lizardo , Christian Poellabauer , Aaron Striegel , Tijana Milenkovic
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