Prestimulus Neural Oscillations Inhibit Visual Perception via Modulation of Response Gain

2014 ◽  
Vol 26 (11) ◽  
pp. 2514-2529 ◽  
Author(s):  
Maximilien Chaumon ◽  
Niko A. Busch
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Inhibitory Effect ◽  
Qualitative Description ◽  
Alpha Power ◽  
Alpha Oscillations ◽  
External Stimuli ◽  
Functional Mechanisms ◽  
The Brain ◽  
Output Transformation

The ongoing state of the brain radically affects how it processes sensory information. How does this ongoing brain activity interact with the processing of external stimuli? Spontaneous oscillations in the alpha range are thought to inhibit sensory processing, but little is known about the psychophysical mechanisms of this inhibition. We recorded ongoing brain activity with EEG while human observers performed a visual detection task with stimuli of different contrast intensities. To move beyond qualitative description, we formally compared psychometric functions obtained under different levels of ongoing alpha power and evaluated the inhibitory effect of ongoing alpha oscillations in terms of contrast or response gain models. This procedure opens the way to understanding the actual functional mechanisms by which ongoing brain activity affects visual performance. We found that strong prestimulus occipital alpha oscillations—but not more anterior mu oscillations—reduce performance most strongly for stimuli of the highest intensities tested. This inhibitory effect is best explained by a divisive reduction of response gain. Ongoing occipital alpha oscillations thus reflect changes in the visual system's input/output transformation that are independent of the sensory input to the system. They selectively scale the system's response, rather than change its sensitivity to sensory information.

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.

scholarly journals Microcurrent Stimulation at Shenmen Acupoint Facilitates EEG Associated with Sleepiness and Positive Mood: A Randomized Controlled Electrophysiological Study

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Mei-chun Cheung ◽  
Agnes S. Chan ◽  
Joanne Yip
Keyword(s):  
Placebo Group ◽  
Brain Activity ◽  
Frontal Region ◽  
Electrocutaneous Stimulation ◽  
Alpha Power ◽  
Sham Stimulation ◽  
Alpha Asymmetry ◽  
Frontal Alpha Asymmetry ◽  
The Brain ◽  
Experimental Group

To examine the electrophysiological effects of microcurrent stimulation at the Shenmen acupoint, 40 healthy normal subjects were randomly assigned to a placebo group (sham stimulation) and an experimental group (bilateral electrocutaneous stimulation at the Shenmen). The following two electroencephalographic indicators were used to measure brain activity. (1) Arousal level was measured with reference to log-transformed absolute alpha power and power source and analyzed using low-resolution electromagnetic tomography and (2) frontal alpha asymmetry was used as an indicator of mood. After real stimulation for 10 minutes, absolute alpha power was globally reduced in the experimental group, particularly in the anterior and centrotemporal regions of the brain. This indicates a decline in the brain activity associated with arousal. Moreover, the reduction was more prominent in the left frontal region, as compared to the right frontal region, resulting in significant increase from negative to positive frontal alpha asymmetry scores and reflecting an increase in the brain activity associated with enhanced mood. However, the placebo group exhibited no significant changes in two indicators after sham stimulation. This study provides initial electrophysiological evidence of changes in brain activity associated with reduced arousal (and thus greater sleepiness) and enhanced mood after microcurrent stimulation at the Shenmen acupoint.

scholarly journals Remote Photonic Detection of Human Senses Using Secondary Speckle Patterns

2021 ◽  
Author(s):  
Zeev Kalyuzhner ◽  
Sergey Agdarov ◽  
Itai Orr ◽  
Yafim Beiderman ◽  
Aviya Bennett ◽  
...  
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Spatiotemporal Analysis ◽  
Physical Contact ◽  
Physiological Processes ◽  
Speckle Patterns ◽  
The Subject ◽  
And Behavior ◽  
Activity Sensing ◽  
The Brain

Abstract Neural activity research has recently gained significant attention due to its association with sensory information and behavior control. However, current methods of brain activity sensing require expensive equipment and physical contact with the subject. We propose a novel photonic-based method for remote detection of human senses. Physiological processes associated with hemodynamic activity due to activation of the cerebral cortex affected by different senses have been detected by remote monitoring of nano‐vibrations generated due to the transient blood flow to specific regions of the brain. We have found that combination of defocused, self‐interference random speckle patterns with a spatiotemporal analysis using Deep Neural Network (DNN) allows associating between the activated sense and the seemingly random speckle patterns.

The phase of prestimulus alpha oscillations affects tactile perception

2014 ◽  
Vol 111 (6) ◽  
pp. 1300-1307 ◽  
Author(s):  
Lei Ai ◽  
Tony Ro
Keyword(s):  
Brain Activity ◽  
Brain Regions ◽  
Stimulus Onset ◽  
Tactile Perception ◽  
Alpha Power ◽  
Perceptual Awareness ◽  
Alpha Oscillations ◽  
Left Hand ◽  
Tactile Stimuli ◽  
Significant Difference

Previous studies have shown that neural oscillations in the 8- to 12-Hz range influence sensory perception. In the current study, we examined whether both the power and phase of these mu/alpha oscillations predict successful conscious tactile perception. Near-threshold tactile stimuli were applied to the left hand while electroencephalographic (EEG) activity was recorded over the contralateral right somatosensory cortex. We found a significant inverted U-shaped relationship between prestimulus mu/alpha power and detection rate, suggesting that there is an intermediate level of alpha power that is optimal for tactile perception. We also found a significant difference in phase angle concentration at stimulus onset that predicted whether the upcoming tactile stimulus was perceived or missed. As has been shown in the visual system, these findings suggest that these mu/alpha oscillations measured over somatosensory areas exert a strong inhibitory control on tactile perception and that pulsed inhibition by these oscillations shapes the state of brain activity necessary for conscious perception. They further suggest that these common phasic processing mechanisms across different sensory modalities and brain regions may reflect a common underlying encoding principle in perceptual processing that leads to momentary windows of perceptual awareness.

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 Spotting the path that leads nowhere: Modulation of human theta and alpha oscillations induced by trajectory changes during navigation

2018 ◽  
Author(s):  
Amir-Homayoun Javadi ◽  
Eva Zita Patai ◽  
Aaron Margois ◽  
Heng-Ru M. Tan ◽  
Darshan Kumaran ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Brain Activity ◽  
Cognitive Map ◽  
Lava Flows ◽  
Neural Dynamics ◽  
Alpha Power ◽  
Neural Basis ◽  
Alpha Oscillations ◽  
Fine Grained ◽  
Desert Island

AbstractThe capacity to take efficient detours and exploit novel shortcuts during navigation is thought to be supported by a cognitive map of the environment. Despite advances in understanding the neural basis of the cognitive map, little is known about the neural dynamics associated with detours and shortcuts. Here, we recorded magnetoencephalography from humans as they navigated a virtual desert island riven by shifting lava flows. The task probed their ability to take efficient detours and shortcuts to remembered goals. We report modulation in event-related fields and theta power as participants identified real shortcuts and differentiated these from false shortcuts that led along suboptimal paths. Additionally, we found that a decrease in alpha power preceded ‘back-tracking’ where participants spontaneously turned back along a previous path. These findings help advance our understanding of the fine-grained temporal dynamics of human brain activity during navigation and support the development of models of brain networks that support navigation.

scholarly journals EEG analysis on human reflection towards relaxation of mind

2019 ◽  
Vol 15 (2) ◽  
pp. 185-189
Author(s):  
Nurasma Jalaudin ◽  
Muhammad Kamal Mohammed Amin
Keyword(s):  
Systems Engineering ◽  
Brain Activity ◽  
Human Life ◽  
Total Duration ◽  
Interdisciplinary Studies ◽  
Alpha Power ◽  
Topographic Map ◽  
State Of Mind ◽  
The Subject ◽  
The Brain

This paper presents an interdisciplinary studies of electronic systems: engineering, psychology and neuro-cognition. It evaluates the neurophysiological activities of human emotion using electroencephalography (EEG). This study is aimed to classify a comparison of Electroencephalogram (EEG) signal to observe human reflection towards relaxation state of mind during divine Quran recitation and listening to music. The objectives of this study is to measure the changes in alpha band and prove that the brain is less active when the subject is listening to Quran compared to music. Six healthy subjects were recruited to measure their behaviors of the mind for a total duration of three minutes. We have highlighted the observation in Topographic Map of the brain through ERP Analysis to observe whether the brain experience any changes. The results showed that the brain activity is less active and the Alpha Power is higher when the subject is listening to Quran Recitation. We conclude that listening to Quran Recitation is a useful tool for a healthy and happy mind which can help people recognize the need of Islamic practice in human life.

scholarly journals Alpha oscillations do not implement gain control in early visual cortex but rather gating in parieto-occipital regions

2020 ◽  
Author(s):  
Alexander Zhigalov ◽  
Ole Jensen
Keyword(s):  
Visual Cortex ◽  
Spatial Attention ◽  
Neuronal Excitability ◽  
Brain Activity ◽  
Gain Control ◽  
Alpha Power ◽  
Alpha Band ◽  
Alpha Oscillations ◽  
Early Visual Cortex ◽  
Broadband Frequency

AbstractSpatial attention provides a mechanism for respectively enhancing relevant and suppressing irrelevant information. While it is well-established that attention modulates oscillations in the alpha band, it remains unclear if alpha oscillations are involved in directly modulating the neuronal excitability associated with the allocation of spatial attention. In this study in humans, we utilized a novel broadband frequency (60 – 70 Hz) tagging paradigm to quantify neuronal excitability in relation to alpha oscillations in a spatial attention paradigm. We used magnetoencephalography to characterize ongoing brain activity as it allows for localizing the sources of both the alpha and frequency tagging responses. We found that attentional modulation of alpha power and the frequency tagging response are uncorrelated over trials. Importantly, the neuronal sources of the tagging response were localized in early visual cortex (V1) whereas the sources of the alpha activity were identified around parieto-occipital sulcus. Moreover, we found that attention did not modulate the latency of the frequency tagged responses. Our findings point to alpha band oscillations serving a downstream gating role rather than implementing gain control of excitability in early visual regions.Significance StatementBy combining magnetoencephalography and a novel broadband frequency tagging approach, we show that spatial attention differently modulates alpha oscillations and neuronal excitability. Importantly, the sources of the alpha oscillations and tagging responses were spatially distinct and the alpha power and tagging response were not related over trials. These results are inconsistent with previous ideas suggesting that alpha oscillations are involved in gain control of early sensory regions; rather alpha oscillations are involved in the allocation of neuronal resources in downstream regions.

Beyond the Passive/Active Dichotomy: A Spectrum Model of the Brain’s Neural Activities

2018 ◽  
pp. 3-26
Author(s):  
Georg Northoff
Keyword(s):  
Spontaneous Activity ◽  
Empirical Data ◽  
Resting State ◽  
Brain Activity ◽  
Empirical Support ◽  
Theoretical Issue ◽  
Active Model ◽  
External Stimuli ◽  
The Brain ◽  
Spectrum Model

Neuroscience has made considerable progress over the last decades in revealing neuronal mechanisms on different levels of brain activity including genetic, molecular, cellular, regional and network levels. However, despite all this progress, no particular model of the brain has commanded consensus. A model of the brain should attribute clear features to the brain, such as its degree of participation in its own processing of stimuli. While primarily a theoretical issue, models of the brain may create major reverberations within neuroscientific investigation and philosophical work on the mind-brain problem. Both philosophers and neuroscientists often presuppose a passive model of the brain wherein the brain passively receives and processes external stimuli. However, recent empirical data do not support a passive view of the brain. Accordingly, I will advocate for an active model of the brain. The empirical support for an active model of brain comes from findings concerning its resting state or spontaneous activity. Empirical data shows that the brain’s stimulus-induced activity results from the integration of spontaneous activity and external stimuli. However, the brain’s activity can vary with respect to the extent of integration of resting state activity and external stimuli. This leads me to suggest what I describe as a spectrum model of the brain. The spectrum model claims that stimulus-induced activity is based on a spectrum or continuum of different possible relationships or balances between spontaneous activity and external stimuli.

scholarly journals Dynamics of Alpha Control: Preparatory Suppression of Posterior Alpha Oscillations by Frontal Modulators Revealed with Combined EEG and Event-related Optical Signal

2014 ◽  
Vol 26 (10) ◽  
pp. 2400-2415 ◽  
Author(s):  
Kyle E. Mathewson ◽  
Diane M. Beck ◽  
Tony Ro ◽  
Edward L. Maclin ◽  
Kathy A. Low ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Brain Activity ◽  
Conscious Experience ◽  
Optical Signal ◽  
Alpha Power ◽  
Top Down ◽  
Spatiotemporal Resolution ◽  
Attention Networks ◽  
Alpha Oscillations ◽  
Eeg Alpha

We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously, we proposed that alpha (8–12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top–down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently recorded EEG, while participants performed a visual target detection task. The pretarget alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha's inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across participants. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks before posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top–down control from attention networks modulates both posterior alpha and awareness of visual stimuli.

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