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Recent advances in biosensors technology and mobile electroencephalographic (EEG) interfaces have opened new application fields for cognitive monitoring. A computable biomarker for the assessment of spontaneous aesthetic brain responses…

Neurons and Cognition · Quantitative Biology 2016-09-26 Dimitrios A. Adamos , Stavros I. Dimitriadis , Nikolaos A. Laskaris

Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the regularity of their fluctuations: low values representing more random (decorrelated) while high values more persistent (correlated) dynamics. LRTCs…

Neurons and Cognition · Quantitative Biology 2018-02-05 Tomas Ros , Paul Frewen , Jean Theberge , Rosemarie Kluetsch , Andreas Mueller , Gian Candrian , Rakesh Jetly , Patrik Vuilleumier , Ruth Lanius

It is well known that Electroencephalography(EEG) and the respective evoked potentials have deep implications corresponding to specific cognitive tasks and in the diagnosis of several diseases such as epilepsy and schizophrenia. Some recent…

Neurons and Cognition · Quantitative Biology 2007-05-23 I. Mitra

The neuromagnetic activity (magnetoencephalogram, MEG) from healthy human brain and from an epileptic patient against chromatic flickering stimuli has been earlier analyzed on the basis of a memory functions formalism (MFF). Information…

Medical Physics · Physics 2010-06-29 O. Yu. Panischev , S. A. Demin , J. Bhattacharya

Impact of EEG biofeedback on event-related potentials (ERPs) in attention-deficit hyperactivity (ADHD) children. Introduction: ADHD is one of the most widely spread condition of school aged children affecting 5% of children of this age.The…

Neurons and Cognition · Quantitative Biology 2011-01-31 Sophio Bakhtadze , Marine Janelidze , Nana Khachapuridze

Electroencephalogram (EEG) signals play a crucial role in understanding brain activity and diagnosing neurological diseases. Because supervised EEG encoders are unable to learn robust EEG patterns and rely too heavily on expensive signal…

Machine Learning · Computer Science 2025-09-23 Junhong Lai , Jiyu Wei , Lin Yao , Yueming Wang

Premise. Patterns of electrical brain activity recorded via electroencephalography (EEG) offer immense value for scientific and clinical investigations. The inability of supervised EEG encoders to learn robust EEG patterns and their…

Signal Processing · Electrical Eng. & Systems 2025-12-25 Gayal Kuruppu , Neeraj Wagh , Vaclav Kremen , Sandipan Pati , Gregory Worrell , Yogatheesan Varatharajah

Feedback Alignment (FA) methods are biologically inspired local learning rules for training neural networks with reduced communication between layers. While FA has potential applications in distributed and privacy-aware ML, limitations in…

Machine Learning · Computer Science 2024-06-05 Zachary Robertson , Oluwasanmi Koyejo

Self-initiated attention shifts play a critical role in voluntary behavior but are difficult to study due to the absence of explicit temporal markers. While previous studies have examined their neural correlates, it remains unclear how…

Signal Processing · Electrical Eng. & Systems 2026-05-19 Yuwen Zeng , Dengzhe Hou , Zhang Zhang , Sai Sun , Yongsong Huang , Chia-huei Tseng , Satoshi Shioiri

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

This thesis delves into the world of non-invasive electrophysiological brain signals like electroencephalography (EEG) and magnetoencephalography (MEG), focusing on modelling and decoding such data. The research aims to investigate what…

Signal Processing · Electrical Eng. & Systems 2025-10-30 Richard Csaky

Many research works indicate that EEG bands, specifically the alpha and theta bands, have been potentially helpful cognitive load indicators. However, minimal research exists to validate this claim. This study aims to assess and analyze the…

Signal Processing · Electrical Eng. & Systems 2022-03-03 Bujar Raufi , Luca Longo

Targeted electrical stimulation of the brain perturbs neural networks and modulates their rhythmic activity both at the site of stimulation and at remote brain regions. Understanding, or even predicting, this neuromodulatory effect is…

Neurons and Cognition · Quantitative Biology 2021-06-29 Christoforos Papasavvas , Peter Neal Taylor , Yujiang Wang

Until recently, human behavioral data from reading has mainly been of interest to researchers to understand human cognition. However, these human language processing signals can also be beneficial in machine learning-based natural language…

Computation and Language · Computer Science 2021-08-11 Nora Hollenstein , Cedric Renggli , Benjamin Glaus , Maria Barrett , Marius Troendle , Nicolas Langer , Ce Zhang

The aim of this paper is to design and construct an electroencephalograph (EEG) based brain-controlled wheelchair to provide a communication bridge from the nervous system to the external technical device for people of determination or…

Human-Computer Interaction · Computer Science 2020-01-20 Mariam AlAbboudi , Maitha Majed , Fatima Hassan , Ali Bou Nassif

Electroencephalography (EEG) data present unique modeling challenges because recordings vary in length, exhibit very low signal to noise ratios, differ significantly across participants, drift over time within sessions, and are rarely…

Signal Processing · Electrical Eng. & Systems 2026-01-05 Shahar Ain Kedem , Itamar Zimerman , Eliya Nachmani

We present a novel methodology to enable control of a neuromorphic circuit in close analogy with the physiological neuromodulation of a single neuron. The methodology is general in that it only relies on a parallel interconnection of…

Neurons and Cognition · Quantitative Biology 2020-11-19 Luka Ribar , Rodolphe Sepulchre

In a growing world of technology, psychological disorders became a challenge to be solved. The methods used for cognitive stimulation are very conventional and based on one-way communication, which only relies on the material or method used…

Signal Processing · Electrical Eng. & Systems 2023-04-28 Kislay Raj , Aditya Singh , Abhishek Mandal , Teerath Kumar , Arunabha M. Roy

Neural oscillations are considered to be brain-specific signatures of information processing and communication in the brain. They also reflect pathological brain activity in neurological disorders, thus offering a basis for diagnoses and…

Neurons and Cognition · Quantitative Biology 2023-10-23 Tena Dubcek , Debora Ledergerber , Jana Thomann , Giovanna Aiello , Marc Serra-Garcia , Lukas Imbach , Rafael Polania

The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation,…

Neurons and Cognition · Quantitative Biology 2016-01-07 Sarah Feldt Muldoon , Fabio Pasqualetti , Shi Gu , Matthew Cieslak , Scott T. Grafton , Jean M. Vettel , Danielle S. Bassett