scholarly journals Stimulus Intervals Modulate the Balance of Brain Activity in the Human Primary Somatosensory Cortex: An ERP Study

2021 ◽  
Vol 14 ◽  
Author(s):  
Yang Liu ◽  
Bo Dong ◽  
Jiajia Yang ◽  
Yoshimichi Ejima ◽  
Jinglong Wu ◽  
...  
Keyword(s):  
Animal Studies ◽  
Standard Stimulus ◽  
Brain Activity ◽  
Somatosensory System ◽  
Body Part ◽  
Single Stimulus ◽  
Suppression Effect ◽  
Neuronal Excitation ◽  
The Brain ◽  
Somatosensory Areas

Neuronal excitation and inhibition occur in the brain at the same time, and brain activation reflects changes in the sum of excitation and inhibition. This principle has been well-established in lower-level sensory systems, including vision and touch, based on animal studies. However, it is unclear how the somatosensory system processes the balance between excitation and inhibition. In the present ERP study, we modified the traditional spatial attention paradigm by adding double stimuli presentations at short intervals (i.e., 10, 30, and 100 ms). Seventeen subjects participated in the experiment. Five types of stimulation were used in the experiment: a single stimulus (one raised pin for 40 ms), standard stimulus (eight pins for 40 ms), and double stimuli presented at intervals of 10, 30, and 100 ms. The subjects were asked to attend to a particular finger and detect whether the standard stimulus was presented to that finger. The results showed a clear attention-related ERP component in the single stimulus condition, but the suppression components associated with the three interval conditions seemed to be dominant in somatosensory areas. In particular, we found the strongest suppression effect in the ISI-30 condition (interval of 30 ms) and that the suppression and enhancement effects seemed to be counterbalanced in both the ISI-10 and ISI-100 conditions (intervals of 10 and 100 ms, respectively). This type of processing may allow humans to easily discriminate between multiple stimuli on the same body part.

scholarly journals Wrist and finger motor representations embedded in the cerebral and cerebellar resting-state activation

2021 ◽  
Author(s):  
Toshiki Kusano ◽  
Hiroki Kurashige ◽  
Isao Nambu ◽  
Yoshiya Moriguchi ◽  
Takashi Hanakawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Body Part ◽  
Resting State Fmri ◽  
Body Parts ◽  
Finger Movements ◽  
Multiple Components ◽  
Brain Activity Pattern ◽  
Motor Representations ◽  
The Brain

AbstractSeveral functional magnetic resonance imaging (fMRI) studies have demonstrated that resting-state brain activity consists of multiple components, each corresponding to the spatial pattern of brain activity induced by performing a task. Especially in a movement task, such components have been shown to correspond to the brain activity pattern of the relevant anatomical region, meaning that the voxels of pattern that are cooperatively activated while using a body part (e.g., foot, hand, and tongue) also behave cooperatively in the resting state. However, it is unclear whether the components involved in resting-state brain activity correspond to those induced by the movement of discrete body parts. To address this issue, in the present study, we focused on wrist and finger movements in the hand, and a cross-decoding technique trained to discriminate between the multi-voxel patterns induced by wrist and finger movement was applied to the resting-state fMRI. We found that the multi-voxel pattern in resting-state brain activity corresponds to either wrist or finger movements in the motor-related areas of each hemisphere of the cerebrum and cerebellum. These results suggest that resting-state brain activity in the motor-related areas consists of the components corresponding to the elementary movements of individual body parts. Therefore, the resting-state brain activity possibly has a finer structure than considered previously.

scholarly journals EEG-based brain–computer interfaces exploiting steady-state somatosensory-evoked potentials: a literature review

2021 ◽  
Vol 18 (5) ◽  
pp. 051003
Author(s):  
Jimmy Petit ◽  
José Rouillard ◽  
François Cabestaing
Keyword(s):  
Steady State ◽  
Brain Activity ◽  
Somatosensory System ◽  
Classification Performance ◽  
Brain Response ◽  
Somatosensory Stimulation ◽  
External Stimulation ◽  
Sustained Change ◽  
External Stimuli ◽  
The Brain

Abstract A brain–computer interface (BCI) aims to derive commands from the user’s brain activity in order to relay them to an external device. To do so, it can either detect a spontaneous change in the mental state, in the so-called ‘active’ BCIs, or a transient or sustained change in the brain response to an external stimulation, in ‘reactive’ BCIs. In the latter, external stimuli are perceived by the user through a sensory channel, usually sight or hearing. When the stimulation is sustained and periodical, the brain response reaches an oscillatory steady-state that can be detected rather easily. We focus our attention on electroencephalography-based BCIs (EEG-based BCI) in which a periodical signal, either mechanical or electrical, stimulates the user skin. This type of stimulus elicits a steady-state response of the somatosensory system that can be detected in the recorded EEG. The oscillatory and phase-locked voltage component characterising this response is called a steady-state somatosensory-evoked potential (SSSEP). It has been shown that the amplitude of the SSSEP is modulated by specific mental tasks, for instance when the user focuses their attention or not to the somatosensory stimulation, allowing the translation of this variation into a command. Actually, SSSEP-based BCIs may benefit from straightforward analysis techniques of EEG signals, like reactive BCIs, while allowing self-paced interaction, like active BCIs. In this paper, we present a survey of scientific literature related to EEG-based BCI exploiting SSSEP. Firstly, we endeavour to describe the main characteristics of SSSEPs and the calibration techniques that allow the tuning of stimulation in order to maximise their amplitude. Secondly, we present the signal processing and data classification algorithms implemented by authors in order to elaborate commands in their SSSEP-based BCIs, as well as the classification performance that they evaluated on user experiments.

scholarly journals Placebo analgesia does not reduce empathy for naturalistic depictions of others’ pain in a somatosensory specific way

2020 ◽  
Author(s):  
Helena Hartmann ◽  
Federica Riva ◽  
Markus Rütgen ◽  
Claus Lamm
Keyword(s):  
Brain Activity ◽  
Somatosensory System ◽  
Body Part ◽  
General Effect ◽  
Placebo Analgesia ◽  
Brain Functions ◽  
Hand Pain ◽  
Fmri Study ◽  
Empathy For Pain ◽  
The Right

AbstractEmpathy for pain involves the affective-motivational and sensory-discriminative pain network. The shared representations account postulates that sharing another’s pain recruits underlying brain functions also engaged during first-hand pain. Critically, causal evidence for this has only been shown for affective pain processing, while the specific contribution of one’s own somatosensory system to empathy remains controversial. Experimental paradigms used in previous studies did not a) direct attention towards a specific body part or b) employed naturalistic depictions of others’ pain, which could explain the absence of somatosensory effects. In this preregistered fMRI study, we thus aimed to test whether a causal manipulation of first-hand pain affects processing of empathy in a somatotopically- matched manner. Forty-five participants underwent a placebo analgesia induction in the right hand and observed pictures of right vs. left hands in pain. We found neither behavioral nor neural evidence for laterality-specific modulation of empathy for pain. However, exploratory analyses revealed a general effect of the placebo on empathy, and higher brain activity in bilateral anterior insula when viewing others’ hands in pain corresponding to one’s own placebo hand. These results refine our knowledge regarding the mechanisms underlying empathy for pain by specifying the influence of first-hand pain on empathic responding.

rTMS and nondeclarative learning

2021 ◽  
Author(s):  
Michael V. Freedberg ◽  
Eric M. Wassermann
Keyword(s):  
Magnetic Stimulation ◽  
Animal Studies ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Brain Activity ◽  
Brain Networks ◽  
Procedural Learning ◽  
Imaging Studies ◽  
Brain Areas ◽  
Cortical Regions ◽  
The Brain

Nondeclarative learning and memory involve acquiring and retaining skills or habits and include subtypes, such as procedural learning, priming, and classical conditioning. Animal studies, lesion, and functional imaging studies in humans have implicated a range of brain areas, including frontal and parietal cortical regions, basal ganglia, cerebellum in these functions. Repetitive transcranial magnetic stimulation (rTMS) can modulate functional connectivity in brain networks and provide causal evidence for their involvement in behavior. In this chapter, we review the use of rTMS to investigate the brain networks underlying nondeclarative learning by stimulating their cortical nodes and examining the effects of these interventions on behavior and imaging measures of brain activity and connectivity, with emphasis on how the timing of stimulation (before, during, or after learning) affects these measures.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

Relation Between Level of Prefrontal Activity and Subject's Performance

1999 ◽  
Vol 13 (2) ◽  
pp. 117-125 ◽  
Author(s):  
Laurence Casini ◽  
Françoise Macar ◽  
Marie-Hélène Giard
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Practice Phase ◽  
Trained Subjects ◽  
Anagram Task ◽  
Economic Information ◽  
Long Duration ◽  
Level Of Activity ◽  
The Brain ◽  
Processing Mechanism

Abstract The experiment reported here was aimed at determining whether the level of brain activity can be related to performance in trained subjects. Two tasks were compared: a temporal and a linguistic task. An array of four letters appeared on a screen. In the temporal task, subjects had to decide whether the letters remained on the screen for a short or a long duration as learned in a practice phase. In the linguistic task, they had to determine whether the four letters could form a word or not (anagram task). These tasks allowed us to compare the level of brain activity obtained in correct and incorrect responses. The current density measures recorded over prefrontal areas showed a relationship between the performance and the level of activity in the temporal task only. The level of activity obtained with correct responses was lower than that obtained with incorrect responses. This suggests that a good temporal performance could be the result of an efficacious, but economic, information-processing mechanism in the brain. In addition, the absence of this relation in the anagram task results in the question of whether this relation is specific to the processing of sensory information only.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

scholarly journals (Ascorb)ing Pb Neurotoxicity in the Developing Brain

Antioxidants ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1311
Author(s):  
Faraz Ahmad ◽  
Ping Liu
Keyword(s):  
Ascorbic Acid ◽  
Animal Studies ◽  
Redox Homeostasis ◽  
Special Role ◽  
Developmental Exposure ◽  
Brain Functions ◽  
Brain States ◽  
Pb Exposure ◽  
The Brain ◽  
Potent Therapeutic Agent

Lead (Pb) neurotoxicity is a major concern, particularly in children. Developmental exposure to Pb can alter neurodevelopmental trajectory and has permanent neuropathological consequences, including an increased vulnerability to further stressors. Ascorbic acid is among most researched antioxidant nutrients and has a special role in maintaining redox homeostasis in physiological and physio-pathological brain states. Furthermore, because of its capacity to chelate metal ions, ascorbic acid may particularly serve as a potent therapeutic agent in Pb poisoning. The present review first discusses the major consequences of Pb exposure in children and then proceeds to present evidence from human and animal studies for ascorbic acid as an efficient ameliorative supplemental nutrient in Pb poisoning, with a particular focus on developmental Pb neurotoxicity. In doing so, it is hoped that there is a revitalization for further research on understanding the brain functions of this essential, safe, and readily available vitamin in physiological states, as well to justify and establish it as an effective neuroprotective and modulatory factor in the pathologies of the nervous system, including developmental neuropathologies.

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