The impact of hypoxemia and/or hypotension on electrical brain activity as measured using the Maastricht cerebral monitor

AbstractDance as one of the earliest cultural assets of mankind is practised in different cultures, mostly for wellbeing or for treating psycho-physiological disorders like Parkinson, depression, autism. However, the underlying neurophysiological mechanisms are still unclear and only few studies address the effects of particular dance styles. For a first impression, we were interested in the effects of modern jazz dance (MJD) on the brain activation that would contribute to the understanding of these mechanisms. 11 female subjects rehearsed a MJD choreography for three weeks (1h per week) and passed electroencephalographic (EEG) measurements in a crossover-design thereafter. The objectives were to establish the differences between dancing physically and participating just mentally with or without music. Therefore, each subject realized the four following test conditions: dancing physically to and without music, dancing mentally to and without music. Each of the conditions were performed for 15 minutes. Before and after each condition, the EEG activities were recorded under resting conditions (2 min. eyes-open, 2 min. eyes-closed) followed by a subsequent wash-out phase of 10 minutes.The results of the study revealed no time effects for the mental dancing conditions, either to or without music. An increased electrical brain activation was followed by the physical dancing conditions with and without music for the theta, alpha-1, alpha-2, beta and gamma frequency band across the entire scalp. Especially the higher frequencies (alpha-2, beta, gamma) showed increased brain activation across all brain areas. Higher brain activities for the physical dancing conditions were identified in comparison to the mental dancing condition. No statistically significant differences could be found as to dancing to or without music. Our findings demonstrate evidence for the immediate influence of modern jazz dance and its sweeping effects on all brain areas for all measured frequency bands, when dancing physically. In comparison, dancing just mentally does not result in similar effects.

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The Impact of Musicianship on the Cortical Mechanisms Related to Separating Speech from Background Noise

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00758 ◽

2015 ◽

Vol 27 (5) ◽

pp. 1044-1059 ◽

Cited By ~ 22

Author(s):

Benjamin Rich Zendel ◽

Charles-David Tremblay ◽

Sylvie Belleville ◽

Isabelle Peretz

Keyword(s):

Task Performance ◽

Lexical Access ◽

Auditory Processing ◽

Background Noise ◽

Brain Activity ◽

Active Listening ◽

N400 Amplitude ◽

Speech In Noise ◽

Electrical Brain Activity ◽

The Impact

Musicians have enhanced auditory processing abilities. In some studies, these abilities are paralleled by an improved understanding of speech in noisy environments, partially due to more robust encoding of speech signals in noise at the level of the brainstem. Little is known about the impact of musicianship on attention-dependent cortical activity related to lexical access during a speech-in-noise task. To address this issue, we presented musicians and nonmusicians with single words mixed with three levels of background noise, across two conditions, while monitoring electrical brain activity. In the active condition, listeners repeated the words aloud, and in the passive condition, they ignored the words and watched a silent film. When background noise was most intense, musicians repeated more words correctly compared with nonmusicians. Auditory evoked responses were attenuated and delayed with the addition of background noise. In musicians, P1 amplitude was marginally enhanced during active listening and was related to task performance in the most difficult listening condition. By comparing ERPs from the active and passive conditions, we isolated an N400 related to lexical access. The amplitude of the N400 was not influenced by the level of background noise in musicians, whereas N400 amplitude increased with the level of background noise in nonmusicians. In nonmusicians, the increase in N400 amplitude was related to a reduction in task performance. In musicians only, there was a rightward shift of the sources contributing to the N400 as the level of background noise increased. This pattern of results supports the hypothesis that encoding of speech in noise is more robust in musicians and suggests that this facilitates lexical access. Moreover, the shift in sources suggests that musicians, to a greater extent than nonmusicians, may increasingly rely on acoustic cues to understand speech in noise.

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An in-vivo validation of ESI methods with focal sources

10.1101/2021.09.10.459782 ◽

2021 ◽

Author(s):

Annalisa Pascarella ◽

Ezequiel Mikulan ◽

Federica Sciacchitano ◽

Simone Sarasso ◽

Annalisa Rubino ◽

...

Keyword(s):

Brain Activity ◽

Input Parameter ◽

Synthetic Data ◽

Single Pulse ◽

Source Imaging ◽

Electrical Brain Activity ◽

Operative Outcomes ◽

Input Parameters ◽

The Impact

AbstractElectrical source imaging (ESI) aims at reconstructing the electrical brain activity from measurements of the electric field on the scalp. Even though the localization of single focal sources should be relatively straightforward, different methods provide diverse solutions due to the different underlying assumptions. Furthermore, their input parameter(s) further affects the solution provided by each method, making localization even more challenging. In addition, validations and comparisons are typically performed either on synthetic data or through post-operative outcomes, in both cases with considerable limitations.We use an in-vivo high-density EEG dataset recorded during intracranial single pulse electrical stimulation, in which the true sources are substantially dipolar and their locations are known. We compare ten different ESI methods under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of the parameters on the localization performance.Best reconstructions often fall within 1 cm from the true source, with more accurate methods outperforming less accurate ones by 1 cm, on average. Expectedly, dipolar methods tend to outperform distributed methods. Sensitivity to input parameters varies widely between methods. Depth weighting played no role for three out of six methods implementing it. In terms of regularization parameters, for several distributed methods SNR=1 unexpectedly turned out to be the best choice among the tested ones.Our data show similar levels of accuracy of ESI techniques when applied to “conventional” (32 channels) and dense (64, 128, 256 channels) EEG recordings.Overall findings reinforce the importance that ESI may have in the clinical context, especially when applied to identify the surgical target in potential candidates for epilepsy surgery.

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Skipping Breakfast Affects the Early Steps of Cognitive Processing

Journal of Psychophysiology ◽

10.1027/0269-8803/a000214 ◽

2019 ◽

Vol 33 (2) ◽

pp. 109-118

Author(s):

Andrés Antonio González-Garrido ◽

Jacobo José Brofman-Epelbaum ◽

Fabiola Reveca Gómez-Velázquez ◽

Sebastián Agustín Balart-Sánchez ◽

Julieta Ramos-Loyo

Keyword(s):

Working Memory ◽

Cognitive Processing ◽

Task Difficulty ◽

Brain Activity ◽

Reaction Times ◽

Brain Potentials ◽

Brain Functioning ◽

Attentional Processes ◽

Electrical Brain Activity ◽

Skipping Breakfast

Abstract. It has been generally accepted that skipping breakfast adversely affects cognition, mainly disturbing the attentional processes. However, the effects of short-term fasting upon brain functioning are still unclear. We aimed to evaluate the effect of skipping breakfast on cognitive processing by studying the electrical brain activity of young healthy individuals while performing several working memory tasks. Accordingly, the behavioral results and event-related brain potentials (ERPs) of 20 healthy university students (10 males) were obtained and compared through analysis of variances (ANOVAs), during the performance of three n-back working memory (WM) tasks in two morning sessions on both normal (after breakfast) and 12-hour fasting conditions. Significantly fewer correct responses were achieved during fasting, mainly affecting the higher WM load task. In addition, there were prolonged reaction times with increased task difficulty, regardless of breakfast intake. ERP showed a significant voltage decrement for N200 and P300 during fasting, while the amplitude of P200 notably increased. The results suggest skipping breakfast disturbs earlier cognitive processing steps, particularly attention allocation, early decoding in working memory, and stimulus evaluation, and this effect increases with task difficulty.

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Emotional Reactivity to Visual Content as Revealed by ERP Component Clustering

Journal of Psychophysiology ◽

10.1027/0269-8803/a000145 ◽

2015 ◽

Vol 29 (4) ◽

pp. 135-146 ◽

Cited By ~ 3

Author(s):

Miroslaw Wyczesany ◽

Szczepan J. Grzybowski ◽

Jan Kaiser

Keyword(s):

Emotional Reactivity ◽

Brain Activity ◽

Affective State ◽

Occipital Lobe ◽

Stimulus Onset ◽

Emotional States ◽

Neural Basis ◽

Temporoparietal Junction ◽

The Right ◽

The Impact

Abstract. In the study, the neural basis of emotional reactivity was investigated. Reactivity was operationalized as the impact of emotional pictures on the self-reported ongoing affective state. It was used to divide the subjects into high- and low-responders groups. Independent sources of brain activity were identified, localized with the DIPFIT method, and clustered across subjects to analyse the visual evoked potentials to affective pictures. Four of the identified clusters revealed effects of reactivity. The earliest two started about 120 ms from the stimulus onset and were located in the occipital lobe and the right temporoparietal junction. Another two with a latency of 200 ms were found in the orbitofrontal and the right dorsolateral cortices. Additionally, differences in pre-stimulus alpha level over the visual cortex were observed between the groups. The attentional modulation of perceptual processes is proposed as an early source of emotional reactivity, which forms an automatic mechanism of affective control. The role of top-down processes in affective appraisal and, finally, the experience of ongoing emotional states is also discussed.

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An Adaptive and Learning System for Feedback-Controlled Evoked Response Studies

Methods of Information in Medicine ◽

10.1055/s-0038-1635302 ◽

1981 ◽

Vol 20 (03) ◽

pp. 169-173

Author(s):

J. Wagner ◽

G. Pfurtscheixer

Keyword(s):

Brain Activity ◽

Evoked Response ◽

Learning System ◽

Time Interval ◽

Electrical Brain Activity ◽

Long Time ◽

The Subject ◽

Eeg Power ◽

Stimulation System ◽

Background Eeg

The shape, latency and amplitude of changes in electrical brain activity related to a stimulus (Evoked Potential) depend both on the stimulus parameters and on the background EEG at the time of stimulation. An adaptive, learnable stimulation system is introduced, whereby the subject is stimulated (e.g. with light), whenever the EEG power is subthreshold and minimal. Additionally, the system is conceived in such a way that a certain number of stimuli could be given within a particular time interval. Related to this time criterion, the threshold specific for each subject is calculated at the beginning of the experiment (preprocessing) and adapted to the EEG power during the processing mode because of long-time fluctuations and trends in the EEG. The process of adaptation is directed by a table which contains the necessary correction numbers for the threshold. Experiences of the stimulation system are reflected in an automatic correction of this table. Because the corrected and improved table is stored after each experiment and is used as the starting table for the next experiment, the system >learns<. The system introduced here can be used both for evoked response studies and for alpha-feedback experiments.

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

Information and Control Systems ◽

10.31799/1684-8853-2018-4-115-122 ◽

2018 ◽

pp. 115-122 ◽

Cited By ~ 1

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.

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Delta band activity contributes to the identification of command following in disorder of consciousness

Scientific Reports ◽

10.1038/s41598-021-95818-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Gonzalo Rivera-Lillo ◽

Emmanuel A. Stamatakis ◽

Tristan A. Bekinschtein ◽

David K. Menon ◽

Srivas Chennu

Keyword(s):

Functional Neuroimaging ◽

Brain Activity ◽

Disorder Of Consciousness ◽

Fine Grained ◽

Electrical Brain Activity ◽

Delta Band ◽

Delta Modulation ◽

Command Following ◽

Band Activity

AbstractThe overt or covert ability to follow commands in patients with disorders of consciousness is considered a sign of awareness and has recently been defined as cortically mediated behaviour. Despite its clinical relevance, the brain signatures of the perceptual processing supporting command following have been elusive. This multimodal study investigates the temporal spectral pattern of electrical brain activity to identify features that differentiated healthy controls from patients both able and unable to follow commands. We combined evidence from behavioural assessment, functional neuroimaging during mental imagery and high-density electroencephalography collected during auditory prediction, from 21 patients and 10 controls. We used a penalised regression model to identify command following using features from electroencephalography. We identified seven well-defined spatiotemporal signatures in the delta, theta and alpha bands that together contribute to identify DoC subjects with and without the ability to follow command, and further distinguished these groups of patients from controls. A fine-grained analysis of these seven signatures enabled us to determine that increased delta modulation at the frontal sensors was the main feature in command following patients. In contrast, higher frequency theta and alpha modulations differentiated controls from both groups of patients. Our findings highlight a key role of spatiotemporally specific delta modulation in supporting cortically mediated behaviour including the ability to follow command. However, patients able to follow commands nevertheless have marked differences in brain activity in comparison with healthy volunteers.

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