Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs

Navi, Farhad Farkhondeh Tale; Heysieattalab, Soomaayeh; Ramanathan, Dhakshin; Raoufy, Mohammad Reza; Nazari, Mohammad Ali

doi:10.1016/j.neuroscience.2021.12.004

Cited by 10 publications

(5 citation statements)

References 217 publications

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“…It is important to note that the developed combination of resonance scanning with EEG-guided adaptive neurostimulation is in line with several promising trends in the development of non-invasive brain stimulation technologies. One of them is a quickly arising line of research related to development of the closed-loop brain state-dependent stimulation (CLBSDS) technique for modulating brain circuits and networks in clinic and to improve mental health and well-being in normal people [ 1 , 24 ]. Another trend is the rapidly evolving field of physiologically informed neuromodulation methodology and techniques, dealing with stimulation paradigms that are guided by patients’ neurophysiology to improve therapy efficacy and make patient management more efficient [ 25 ].…”

Section: Discussionmentioning

confidence: 99%

Resonance Scanning as an Efficiency Enhancer for EEG-Guided Adaptive Neurostimulation

Федотчев

Парин

Polevaya

2023

Life

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Electroencephalogram (EEG)-guided adaptive neurostimulation is an innovative kind of non-invasive closed-loop brain stimulation technique that uses audio–visual stimulation on-line modulated by rhythmical EEG components of the individual. However, the opportunity to enhance its effectiveness is a challenging task and needs further investigation. The present study aims to experimentally test whether it is possible to increase the efficiency of EEG-guided adaptive neurostimulation by pre- strengthening the modulating factor (subject’s EEG) through the procedure of resonance scanning, i.e., LED photostimulation with the frequency gradually increasing in the range of main EEG rhythms (4–20 Hz). Thirty-six university students in a state of exam stress were randomly assigned to two matched groups. One group was presented with the EEG-guided adaptive neurostimulation alone, whereas another matched group was presented with the combination of resonance scanning and EEG-guided adaptive neurostimulation. The changes in psychophysiological indicators after stimulation relative to the initial level were used. Although both types of stimulation led to an increase in the power of EEG rhythms, accompanied by a decrease in the number of errors in the word recognition test and a decrease in the degree of emotional maladjustment, these changes reached the level of significance only in experiments with preliminary resonance scanning. Resonance scanning increases the brain’s responsiveness to subsequent EEG-guided adaptive neurostimulation, acting as a tool to enhance its efficiency. The results obtained clearly indicate that the combination of resonance scanning and EEG-guided adaptive neurostimulation is an effective way to reach the signs of cognitive improvement in stressed individuals.

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Section: Discussionmentioning

confidence: 99%

Resonance Scanning as an Efficiency Enhancer for EEG-Guided Adaptive Neurostimulation

Федотчев

Парин

Polevaya

2023

Life

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“…This procedures allow an improved control of some neurological conditions such as epilepsy ( Ranjandish and Schmid, 2020 ; Farkhondeh Tale Navi et al, 2022 ), and can also be used for better control of obsessive-compulsive disorders and depression ( Figee et al, 2022 ; Visser-Vandewalle et al, 2022 ). Furthermore, it has been shown that the outcome of brain stimulation to treat Parkinson’s disease can be improved by recording brain activity and stimulating only when the local field potentials collected by electrodes inserted in the subthalamic nucleus exceed a certain threshold ( Little et al, 2013 ), or by associating the brain stimulation to specific phases of patients’ tremor activity ( Cagnan et al, 2017 ).…”

Section: Learning To Control Brain Electrical Stimulationmentioning

confidence: 99%

“…To achieve the ambitious objectives envisioned by cortical visual prostheses, we should be able to stimulate the occipital cortex in a way as similar as possible to the physiological response to visual stimuli, mimicking the human visual pathway ( Nirenberg and Pandarinath, 2012 ; Qiao et al, 2019 ; Brackbill et al, 2020 ; Li et al, 2022 ; Price and Gavornik, 2022 ). In this framework, we should consider that closed-loop circuits exist in just about every part of the nervous system ( Farkhondeh Tale Navi et al, 2022 ; Khodagholy et al, 2022 ). However, current cortical visual prosthesis approaches are primarily unidirectional and do not incorporate any adaptive system for the modulation of the electrical stimulation used to induce visual perception.…”

Section: Introductionmentioning

confidence: 99%

Toward a personalized closed-loop stimulation of the visual cortex: Advances and challenges

Grani

Soto-Sánchez

Fimia

et al. 2022

Front. Cell. Neurosci.

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Current cortical visual prosthesis approaches are primarily unidirectional and do not consider the feed-back circuits that exist in just about every part of the nervous system. Herein, we provide a brief overview of some recent developments for better controlling brain stimulation and present preliminary human data indicating that closed-loop strategies could considerably enhance the effectiveness, safety, and long-term stability of visual cortex stimulation. We propose that the development of improved closed-loop strategies may help to enhance our capacity to communicate with the brain.

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“…Since an 8 weeks short-term training of MBSR is effective on behavioral and brain function modulation even for novices ( Kirk et al, 2016 ; Kral et al, 2018 ; Kwak et al, 2019 ; Favre et al, 2021 ; Rahrig et al, 2021 ; Guendelman et al, 2022 ), MBSR training is helpful for emotion and attention regulation, as well as decision making and executive functions, therefore has many clinical applications. It is important to assess the training effectiveness of MBSR practitioners and provide feedback to improve their performance ( Farkhondeh Tale Navi et al, 2022 ; Yu et al, 2022 ). Therefore, mindfulness meditation state recognition is of great importance for online or offline feedback during MBSR training and practice ( Brandmeyer and Delorme, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

EEG-based investigation of effects of mindfulness meditation training on state and trait by deep learning and traditional machine learning

Shang,

Duan,

et al. 2023

Front. Hum. Neurosci.

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IntroductionThis study examines the state and trait effects of short-term mindfulness-based stress reduction (MBSR) training using convolutional neural networks (CNN) based deep learning methods and traditional machine learning methods, including shallow and deep ConvNets as well as support vector machine (SVM) with features extracted from common spatial pattern (CSP) and filter bank CSP (FBCSP).MethodsWe investigated the electroencephalogram (EEG) measurements of 11 novice MBSR practitioners (6 males, 5 females; mean age 35.7 years; 7 Asians and 4 Caucasians) during resting and meditation at early and late training stages. The classifiers are trained and evaluated using inter-subject, mix-subject, intra-subject, and subject-transfer classification strategies, each according to a specific application scenario.ResultsFor MBSR state effect recognition, trait effect recognition using meditation EEG, and trait effect recognition using resting EEG, from shallow ConvNet classifier we get mix-subject/intra-subject classification accuracies superior to related previous studies for both novice and expert meditators with a variety of meditation types including yoga, Tibetan, and mindfulness, whereas from FBSCP + SVM classifier we get inter-subject classification accuracies of 68.50, 85.00, and 78.96%, respectively.ConclusionDeep learning is superior for state effect recognition of novice meditators and slightly inferior but still comparable for both state and trait effects recognition of expert meditators when compared to the literatures. This study supports previous findings that short-term meditation training has EEG-recognizable state and trait effects.

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Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs

Cited by 10 publications

References 217 publications

Resonance Scanning as an Efficiency Enhancer for EEG-Guided Adaptive Neurostimulation

Resonance Scanning as an Efficiency Enhancer for EEG-Guided Adaptive Neurostimulation

Toward a personalized closed-loop stimulation of the visual cortex: Advances and challenges

EEG-based investigation of effects of mindfulness meditation training on state and trait by deep learning and traditional machine learning

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