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Keywords = neurofeedback integrated system

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20 pages, 2062 KB  
Review
Neuroplasticity-Based Approaches to Sensory Processing Alterations in Autism Spectrum Disorder
by Maria Suprunowicz, Julia Bogucka, Natalia Szczerbińska, Stefan Modzelewski, Aleksandra Julia Oracz, Beata Konarzewska and Napoleon Waszkiewicz
Int. J. Mol. Sci. 2025, 26(15), 7102; https://doi.org/10.3390/ijms26157102 - 23 Jul 2025
Cited by 1 | Viewed by 2672
Abstract
Sensory dysregulation represents a core challenge in autism spectrum disorder (ASD), affecting perception, behavior, and adaptive functioning. The brain’s ability to reorganize, known as neuroplasticity, serves as the basic principle for therapeutic interventions targeting these deficits. Neuroanatomical mechanisms include altered connectivity in the [...] Read more.
Sensory dysregulation represents a core challenge in autism spectrum disorder (ASD), affecting perception, behavior, and adaptive functioning. The brain’s ability to reorganize, known as neuroplasticity, serves as the basic principle for therapeutic interventions targeting these deficits. Neuroanatomical mechanisms include altered connectivity in the sensory and visual cortices, as well as in the limbic system and amygdala, while imbalances of neurotransmitters, in particular glutamate and gamma-aminobutyric acid (GABA), contribute to atypical sensory processing. Traditional therapies used in sensory integration are based on the principles of neuroplasticity. Increasingly, new treatments use this knowledge, and modern therapies such as neurofeedback, transcranial stimulation, and immersive virtual environments are promising in modulating neuronal circuits. However, further research is needed to optimize interventions and confirm long-term effectiveness. This review discusses the role of neuroplasticity in the etiopathogenesis of sensory integration deficits in autism spectrum disorder. The neuroanatomical and neurotransmitter basis of impaired perception of sensory stimuli is considered, and traditional and recent therapies for sensory integration are discussed. Full article
(This article belongs to the Special Issue Molecular Investigations in Neurodevelopmental Disorders)
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13 pages, 814 KB  
Review
Biofeedback for Motor and Cognitive Rehabilitation in Parkinson’s Disease: A Comprehensive Review of Non-Invasive Interventions
by Pierluigi Diotaiuti, Giulio Marotta, Salvatore Vitiello, Francesco Di Siena, Marco Palombo, Elisa Langiano, Maria Ferrara and Stefania Mancone
Brain Sci. 2025, 15(7), 720; https://doi.org/10.3390/brainsci15070720 - 4 Jul 2025
Viewed by 1747
Abstract
(1) Background: Biofeedback and neurofeedback are gaining attention as non-invasive rehabilitation strategies in Parkinson’s disease (PD) treatment, aiming to modulate motor and non-motor symptoms through the self-regulation of physiological signals. (2) Objective: This review explores the application of biofeedback techniques, electromyographic (EMG) biofeedback, [...] Read more.
(1) Background: Biofeedback and neurofeedback are gaining attention as non-invasive rehabilitation strategies in Parkinson’s disease (PD) treatment, aiming to modulate motor and non-motor symptoms through the self-regulation of physiological signals. (2) Objective: This review explores the application of biofeedback techniques, electromyographic (EMG) biofeedback, heart rate variability (HRV) biofeedback, and electroencephalographic (EEG) neurofeedback in PD rehabilitation, analyzing their impacts on motor control, autonomic function, and cognitive performance. (3) Methods: This review critically examined 15 studies investigating the efficacy of electromyographic (EMG), heart rate variability (HRV), and electroencephalographic (EEG) feedback interventions in PD. Studies were selected through a systematic search of peer-reviewed literature and analyzed in terms of design, sample characteristics, feedback modality, outcomes, and clinical feasibility. (4) Results: EMG biofeedback demonstrated improvements in muscle activation, gait, postural stability, and dysphagia management. HRV biofeedback showed positive effects on autonomic regulation, emotional control, and cardiovascular stability. EEG neurofeedback targeted abnormal cortical oscillations, such as beta-band overactivity and reduced frontal theta, and was associated with improvements in motor initiation, executive functioning, and cognitive flexibility. However, the reviewed studies were heterogeneous in design and outcome measures, limiting generalizability. Subgroup trends suggested modality-specific benefits across motor, autonomic, and cognitive domains. (5) Conclusions: While EMG and HRV systems are more accessible for clinical or home-based use, EEG neurofeedback remains technically demanding. Standardization of protocols and further randomized controlled trials are needed. Future directions include AI-driven personalization, wearable technologies, and multimodal integration to enhance accessibility and long-term adherence. Biofeedback presents a promising adjunct to conventional PD therapies, supporting personalized, patient-centered rehabilitation models. Full article
(This article belongs to the Section Neurodegenerative Diseases)
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18 pages, 2663 KB  
Article
Brain-Computer Interface Based Engagement Feedback in Virtual Reality Rehabilitation: Promoting Motor Cortex Activation
by Hyunmi Lim, Bilal Ahmed and Jeonghun Ku
Electronics 2025, 14(5), 827; https://doi.org/10.3390/electronics14050827 - 20 Feb 2025
Cited by 1 | Viewed by 1780
Abstract
Maintaining optimal levels of engagement during rehabilitation training is crucial for inducing neuroplasticity in the motor cortex, which directly influences positive rehabilitation outcomes. In this research article, we propose a virtual reality (VR) rehabilitation system that incorporates a steady-state visual evoked potential (SSVEP) [...] Read more.
Maintaining optimal levels of engagement during rehabilitation training is crucial for inducing neuroplasticity in the motor cortex, which directly influences positive rehabilitation outcomes. In this research article, we propose a virtual reality (VR) rehabilitation system that incorporates a steady-state visual evoked potential (SSVEP) paradigm to provide engagement feedback. The system utilizes a flickering target and cursor to detect the user’s engagement levels during a target-tracking task. Eighteen healthy participants were recruited to experience three experimental conditions: no feedback (NoF), performance feedback (PF), and neurofeedback (NF). Our results reveal significantly greater Mu suppression in the NF condition compared to the other conditions. However, no significant differences were observed in performance metrics, such as tracking error, among the three conditions. The amount of feedback between the PF and NF conditions also showed no substantial difference. These findings suggest the efficacy of our SSVEP-based engagement feedback paradigm in stimulating motor cortex activity during rehabilitation. Consequently, we conclude that neurofeedback, based on the user’s attentional state, proves to be more effective in promoting motor cortex activation and facilitating neuroplastic changes. This research highlights the potential of integrating VR rehabilitation with an engagement feedback system for successful rehabilitation training. Full article
(This article belongs to the Special Issue EEG Analysis and Brain–Computer Interface (BCI) Technology)
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17 pages, 6739 KB  
Article
Real-Time Electroencephalogram Data Visualization Using Generative AI Art
by Andrei Virgil Puiac, Lucian-Ionel Cioca, Gheorghe Daniel Lakatos and Adrian Groza
Designs 2025, 9(1), 16; https://doi.org/10.3390/designs9010016 - 30 Jan 2025
Cited by 1 | Viewed by 5661
Abstract
This study is the result of the need to research the visualization of brainwaves. The aim is based on the idea of using generative AI art systems as a method. Data visualization is an important part of understanding the evolution of the world [...] Read more.
This study is the result of the need to research the visualization of brainwaves. The aim is based on the idea of using generative AI art systems as a method. Data visualization is an important part of understanding the evolution of the world around us. It offers the ability to see a representation that goes beyond numbers. Generative AI systems have gained the possibility of helping the process of visualizing data in new ways. This specific process includes real-time-generated artistic renderings of these data. This real-time rendering falls into the field of brainwave visualization, with the help of the EEG (electroencephalogram), which can serve here as input data for Generative AI systems. The brainwave measurement technology as a form of input to real-time generative AI systems represents a novel intersection of neuroscience and art in the field of neurofeedback art. The main question this paper hopes to address is as follows: How can brainwaves be effectively fed into generative AI art systems, and where can the outcome lead, in terms of progress? EEG data were successfully integrated with generative AI to create interactive art. The installation provided an immersive experience by moving the image with the change in the user’s mental focus, demonstrating the impact of EEG-based art. Full article
(This article belongs to the Section Smart Manufacturing System Design)
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16 pages, 278 KB  
Perspective
Nociplastic Pain: A Critical Paradigm for Multidisciplinary Recognition and Management
by Jacob N. Ablin
J. Clin. Med. 2024, 13(19), 5741; https://doi.org/10.3390/jcm13195741 - 26 Sep 2024
Cited by 8 | Viewed by 5585
Abstract
Our understanding of chronic pain has evolved significantly, shifting from a focus on peripheral damage to recognizing the central mechanisms underlying pain perception. This perspective article explores the concept of nociplastic pain, a term introduced by the International Association for the Study of [...] Read more.
Our understanding of chronic pain has evolved significantly, shifting from a focus on peripheral damage to recognizing the central mechanisms underlying pain perception. This perspective article explores the concept of nociplastic pain, a term introduced by the International Association for the Study of Pain (IASP) in 2017, which describes pain arising from altered pain modulation within the central nervous system, without clear evidence of tissue damage or inflammation. The historical progression from fibrositis to fibromyalgia, and now to nociplastic pain, underscores the complexity of chronic pain syndromes and the need for a multidisciplinary approach to management. Nociplastic pain is characterized by central sensitization, leading to heightened pain sensitivity and often accompanied by comorbidities such as fatigue, sleep disturbances, and cognitive difficulties. Advances in neuroimaging have revealed altered connectivity within key brain networks, such as the default mode and salience networks, in patients with nociplastic pain, providing insights into the neural underpinnings of this condition. The article also addresses controversies surrounding the role of small fiber neuropathy and autonomic dysfunction in nociplastic pain, highlighting the ongoing debates in the field. The practical importance of recognizing nociplastic pain across various medical disciplines—including primary care, orthopedics, neurology, psychiatry, and rheumatology—is emphasized, with recommendations for integrating this knowledge into clinical practice. Emerging therapies, such as neurofeedback, hyperbaric oxygen therapy, and neuromodulation, offer new avenues for treatment, particularly for patients who do not respond to conventional approaches. The article calls for continued research into the mechanisms of nociplastic pain, the development of reliable diagnostic tools, and the exploration of novel therapeutic strategies to improve patient outcomes. The recognition and management of nociplastic pain are crucial for advancing the care of patients with chronic pain, necessitating interdisciplinary collaboration and a patient-centered approach. Full article
(This article belongs to the Section Immunology & Rheumatology)
18 pages, 2295 KB  
Article
Effects of an Integrated Neurofeedback System with Dry Electrodes: EEG Acquisition and Cognition Assessment
by Guangying Pei, Jinglong Wu, Duanduan Chen, Guoxin Guo, Shuozhen Liu, Mingxuan Hong and Tianyi Yan
Sensors 2018, 18(10), 3396; https://doi.org/10.3390/s18103396 - 11 Oct 2018
Cited by 42 | Viewed by 9293
Abstract
Electroencephalogram (EEG) neurofeedback improves cognitive capacity and behaviors by regulating brain activity, which can lead to cognitive enhancement in healthy people and better rehabilitation in patients. The increased use of EEG neurofeedback highlights the urgent need to reduce the discomfort and preparation time [...] Read more.
Electroencephalogram (EEG) neurofeedback improves cognitive capacity and behaviors by regulating brain activity, which can lead to cognitive enhancement in healthy people and better rehabilitation in patients. The increased use of EEG neurofeedback highlights the urgent need to reduce the discomfort and preparation time and increase the stability and simplicity of the system’s operation. Based on brain-computer interface technology and a multithreading design, we describe a neurofeedback system with an integrated design that incorporates wearable, multichannel, dry electrode EEG acquisition equipment and cognitive function assessment. Then, we evaluated the effectiveness of the system in a single-blind control experiment in healthy people, who increased the alpha frequency band power in a neurofeedback protocol. We found that upregulation of the alpha power density improved working memory following short-term training (only five training sessions in a week), while the attention network regulation may be related to other frequency band activities, such as theta and beta. Our integrated system will be an effective neurofeedback training and cognitive function assessment system for personal and clinical use. Full article
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13 pages, 2739 KB  
Article
0.6 V, 116 nW Neural Spike Acquisition IC with Self-Biased Instrumentation Amplifier and Analog Spike Extraction
by Jong Pal Kim, Hankyu Lee and Hyoungho Ko
Sensors 2018, 18(8), 2460; https://doi.org/10.3390/s18082460 - 30 Jul 2018
Cited by 14 | Viewed by 4103
Abstract
This paper presents an ultralow power 0.6 V 116 nW neural spike acquisition integrated circuit with analog spike extraction. To reduce power consumption, an ultralow power self-biased current-balanced instrumentation amplifier (IA) is proposed. The passive RC lowpass filter in the amplifier acts as [...] Read more.
This paper presents an ultralow power 0.6 V 116 nW neural spike acquisition integrated circuit with analog spike extraction. To reduce power consumption, an ultralow power self-biased current-balanced instrumentation amplifier (IA) is proposed. The passive RC lowpass filter in the amplifier acts as both DC servo loop and self-bias circuit. The spike detector, based on an analog nonlinear energy operator consisting of a low-voltage open-loop differentiator and an open-loop gate-bulk input multiplier, is designed to emphasize the high frequency spike components nonlinearly. To reduce the spike detection error, the adjacent spike merger is also proposed. The proposed circuit achieves a low IA current consumption of 46.4 nA at 0.6 V, noise efficiency factor (NEF) of 1.81, the bandwidth from 102 Hz to 1.94 kHz, the input referred noise of 9.37 μVrms, and overall power consumption of 116 nW at 0.6 V. The proposed circuit can be used in the ultralow power spike pulses acquisition applications, including the neurofeedback systems on peripheral nerves with low neuron density. Full article
(This article belongs to the Section Biosensors)
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22 pages, 334 KB  
Review
Assessing the Effectiveness of Neurofeedback Training in the Context of Clinical and Social Neuroscience
by Franklin Orndorff-Plunkett, Fiza Singh, Oriana R. Aragón and Jaime A. Pineda
Brain Sci. 2017, 7(8), 95; https://doi.org/10.3390/brainsci7080095 - 7 Aug 2017
Cited by 37 | Viewed by 16215
Abstract
Social neuroscience benefits from the experimental manipulation of neuronal activity. One possible manipulation, neurofeedback, is an operant conditioning-based technique in which individuals sense, interact with, and manage their own physiological and mental states. Neurofeedback has been applied to a wide variety of psychiatric [...] Read more.
Social neuroscience benefits from the experimental manipulation of neuronal activity. One possible manipulation, neurofeedback, is an operant conditioning-based technique in which individuals sense, interact with, and manage their own physiological and mental states. Neurofeedback has been applied to a wide variety of psychiatric illnesses, as well as to treat sub-clinical symptoms, and even to enhance performance in healthy populations. Despite growing interest, there persists a level of distrust and/or bias in the medical and research communities in the USA toward neurofeedback and other functional interventions. As a result, neurofeedback has been largely ignored, or disregarded within social neuroscience. We propose a systematic, empirically-based approach for assessing the effectiveness, and utility of neurofeedback. To that end, we use the term perturbative physiologic plasticity to suggest that biological systems function as an integrated whole that can be perturbed and guided, either directly or indirectly, into different physiological states. When the intention is to normalize the system, e.g., via neurofeedback, we describe it as self-directed neuroplasticity, whose outcome is persistent functional, structural, and behavioral changes. We argue that changes in physiological, neuropsychological, behavioral, interpersonal, and societal functioning following neurofeedback can serve as objective indices and as the metrics necessary for assessing levels of efficacy. In this chapter, we examine the effects of neurofeedback on functional connectivity in a few clinical disorders as case studies for this approach. We believe this broader perspective will open new avenues of investigation, especially within social neuroscience, to further elucidate the mechanisms and effectiveness of these types of interventions, and their relevance to basic research. Full article
(This article belongs to the Special Issue Best Practices in Social Neuroscience)
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