scholarly journals Mirroring and brain connectivity of gesture observation

2021 ◽  
pp. 79-105
Author(s):  
Giulia Fronda
Keyword(s):  
Brain Connectivity ◽  
Brain Activity ◽  
Alpha Activity ◽  
Verbal Communication ◽  
Theta Activity

Non-verbal communication involves di rent channels, as gestures, to communicate different information. The present study aims investigating the electrophysiological (EEG) correlates underlying the use of affective, social, and informative gestures during gesture observation by an encoder (who observed to reproduce the gestures successively) and decoder (who simply observed the gestures). Mirroring mechanisms were considered for a gesture observation task. Results showed an increase of frontal alpha, delta, and theta brain responsiveness and intra-brain connectivity for affective and social gestures. and of posterior (temporo-parietal) alpha activity and alpha and delta intra-brain connectivity for informative ones. Concerning inter-agents' role, similar responses were found for all gestures. Regarding gesture valence, an increase of delta and theta activity was observed for positive gestures on the left cerebral side. This study, therefore, revealed the function of gestures' type and valence in influencing individuals' brain activity, showing the presence of mirroring mechanisms underlying gesture observation.

scholarly journals Gesture in hyperscanning during observation. Inter-brain connectivity

2020 ◽  
pp. 59-81
Author(s):  
Michela Balconi ◽  
Giulia Fronda
Keyword(s):  
Joint Action ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Action Observation ◽  
Verbal Communication ◽  
Theta Activity ◽  
Neural Responses ◽  
Brain Responses ◽  
Connectivity Patterns

Non-verbal communication is a joint action defined by the use of different gestures’ types. The present research aimed to investigate the electrophysiological (EEG) correlates during the observation of affective, social and informative gestures in non-verbal communication between encoder and decoder. Moreover, the hyperscanning paradigm allows investigating the individuals’ inter-brain connectivity. Regarding gestures’ type, the study’s results showed a decrease of alpha (increased brain activity), and an increase of delta and theta brain responsiveness and inter-brain connectivity for affective and social gestures in frontal and posterior areas for informative ones. Concerning gestures’ valence, an increase of left frontal theta activity and inter-brain connectivity was observed. Finally, about the inter-agents’ role, the same brain responses and inter-brain connectivity patterns emerged both in encoder and decoder. This study allows discovering neural responses underlying gestures’ type and valence during action observation, highlighting the validity of hyperscanning to investigate inter-brain connectivity mechanisms.

scholarly journals The Use of Hyperscanning to Investigate the Role of Social, Affective, and Informative Gestures in Non-Verbal Communication. Electrophysiological (EEG) and Inter-Brain Connectivity Evidence

2020 ◽  
Vol 10 (1) ◽  
pp. 29 ◽  
Author(s):  
Michela Balconi ◽  
Giulia Fronda
Keyword(s):  
Joint Action ◽  
Brain Connectivity ◽  
Alpha Activity ◽  
Verbal Communication ◽  
Verbal Interaction ◽  
Body Movements ◽  
The Right

Communication can be considered as a joint action that involves two or more individuals transmitting different information. In particular, non-verbal communication involves body movements used to communicate different information, characterized by the use of specific gestures. The present study aims to investigate the electrophysiological (EEG) correlates underlying the use of affective, social, and informative gestures during a non-verbal interaction between an encoder and decoder. From the results of the single brain and inter-brain analyses, an increase of frontal alpha, delta, and theta brain responsiveness and inter-brain connectivity emerged for affective and social gestures; while, for informative gestures, an increase of parietal alpha brain responsiveness and alpha, delta, and theta inter-brain connectivity was observed. Regarding the inter-agents’ role, an increase of frontal alpha activity was observed in the encoder compared to the decoder for social and affective gestures. Finally, regarding gesture valence, an increase of theta brain responsiveness and theta and beta inter-brain connectivity was observed for positive gestures on the left side compared to the right one. This study, therefore, revealed the function of the gesture type and valence in influencing individuals’ brain responsiveness and inter-brain connectivity, showing the presence of resonance mechanisms underlying gesture execution and observation.

Error-related Persistence of Motor Activity in Resting-state Networks

2018 ◽  
Vol 30 (12) ◽  
pp. 1883-1901 ◽  
Author(s):  
Nicolò F. Bernardi ◽  
Floris T. Van Vugt ◽  
Ricardo Ruy Valle-Mena ◽  
Shahabeddin Vahdat ◽  
David J. Ostry
Keyword(s):  
Motor Learning ◽  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Neural Activation ◽  
Resting State Functional Connectivity ◽  
Movement Training ◽  
Movement Error ◽  
Human Participants

The relationship between neural activation during movement training and the plastic changes that survive beyond movement execution is not well understood. Here we ask whether the changes in resting-state functional connectivity observed following motor learning overlap with the brain networks that track movement error during training. Human participants learned to trace an arched trajectory using a computer mouse in an MRI scanner. Motor performance was quantified on each trial as the maximum distance from the prescribed arc. During learning, two brain networks were observed, one showing increased activations for larger movement error, comprising the cerebellum, parietal, visual, somatosensory, and cortical motor areas, and the other being more activated for movements with lower error, comprising the ventral putamen and the OFC. After learning, changes in brain connectivity at rest were found predominantly in areas that had shown increased activation for larger error during task, specifically the cerebellum and its connections with motor, visual, and somatosensory cortex. The findings indicate that, although both errors and accurate movements are important during the active stage of motor learning, the changes in brain activity observed at rest primarily reflect networks that process errors. This suggests that error-related networks are represented in the initial stages of motor memory formation.

scholarly journals Rhythmically Enhanced Music as Analgesic for Chronic Pain: A Pilot, Non-Controlled Observational Study

2021 ◽  
Vol 7 (1) ◽  
pp. 2
Author(s):  
Richard Merrill ◽  
Mariam Taher Amin
Keyword(s):  
Chronic Pain ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Mobile App ◽  
Double Blind ◽  
Pain Scores ◽  
Medication Dosage ◽  
Slow Tempo ◽  
Brainwave Entrainment

Chronic pain changes brain connectivity, brainwaves, and volume, often resulting in disability, anxiety, and depression. Opioid pain relievers impair function, with risk of addiction. Music analgesia research suggests that music for long-term analgesia includes slow tempo, pleasantness, and self-choice. Hypothesis: individuals listening to self-chosen music with embedded beats ½ h twice a day, could show brainwave entrainment (BWE) at healthy frequencies of healthy descending pain modulatory system. BWE may change brain activity, restoring organization in DPMS altered by chronic pain. Volunteers with chronic pain >1 year participated in a study of 4 weeks of listening to one half hour of music twice a day, and four weeks of non-listening, reporting pain and analgesic use bi-weekly using visual analog scale (VAS) and 0–10 numerical pain scores (NPS), medication types, and dosage. Volunteers selected from 27 half-hour pieces of music in several genres in a mobile app. Isochronic beats were embedded in the music with tempo, key, and isochronic theta frequencies proportional, to enhance the brain’s perception of rhythmic patterns and harmonics. Mean NPS showed a 26% reduction (p = 0.018). Significantly, mean medication dosage declined by over 60% (p = 0.008). Double-blind studies, larger populations are needed in future.

scholarly journals Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

2021 ◽  
Author(s):  
Takashi Nakano ◽  
Masahiro Takamura ◽  
Haruki Nishimura ◽  
Maro Machizawa ◽  
Naho Ichikawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Fmri Data ◽  
Independent Test ◽  
The Individual ◽  
The Brain

AbstractNeurofeedback (NF) aptitude, which refers to an individual’s ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation system’s characteristics in task-free resting-state brain activity.

scholarly journals Physiological and head motion signatures in static and time-varying functional connectivity and their subject discriminability

2020 ◽  
Author(s):  
Alba Xifra-Porxas ◽  
Michalis Kassinopoulos ◽  
Georgios D. Mitsis
Keyword(s):  
Functional Connectivity ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Large Data ◽  
Head Motion ◽  
Time Varying ◽  
Resting State Networks ◽  
Human Connectome Project ◽  
Noninvasive Biomarker ◽  
Recurrent Patterns

AbstractHuman brain connectivity yields significant potential as a noninvasive biomarker. Several studies have used fMRI-based connectivity fingerprinting to characterize individual patterns of brain activity. However, it is not clear whether these patterns mainly reflect neural activity or the effect of physiological and motion processes. To answer this question, we capitalize on a large data sample from the Human Connectome Project and rigorously investigate the contribution of the aforementioned processes on functional connectivity (FC) and time-varying FC, as well as their contribution to subject identifiability. We find that head motion, as well as heart rate and breathing fluctuations, induce artifactual connectivity within distinct resting-state networks and that they correlate with recurrent patterns in time-varying FC. Even though the spatiotemporal signatures of these processes yield above-chance levels in subject identifiability, removing their effects at the preprocessing stage improves identifiability, suggesting a neural component underpinning the inter-individual differences in connectivity.

scholarly journals Neural Dynamics of Associative Learning during Human Sleep

2019 ◽  
Vol 30 (3) ◽  
pp. 1708-1715
Author(s):  
Andrés Canales-Johnson ◽  
Emiliano Merlo ◽  
Tristan A Bekinschtein ◽  
Anat Arzi
Keyword(s):  
Associative Learning ◽  
Learning Process ◽  
Brain Activity ◽  
Theta Activity ◽  
Neural Dynamics ◽  
New Associations ◽  
Human Sleep ◽  
New Information ◽  
Early Acquisition ◽  
Dynamic Interplay

Abstract Recent evidence indicates that humans can learn entirely new information during sleep. To elucidate the neural dynamics underlying sleep-learning, we investigated brain activity during auditory–olfactory discriminatory associative learning in human sleep. We found that learning-related delta and sigma neural changes are involved in early acquisition stages, when new associations are being formed. In contrast, learning-related theta activity emerged in later stages of the learning process, after tone–odor associations were already established. These findings suggest that learning new associations during sleep is signaled by a dynamic interplay between slow-waves, sigma, and theta activity.

scholarly journals Integrating TMS, EEG, and MRI as an Approach for Studying Brain Connectivity

2020 ◽  
Vol 26 (5-6) ◽  
pp. 471-486
Author(s):  
Romina Esposito ◽  
Marta Bortoletto ◽  
Carlo Miniussi
Keyword(s):  
Brain Function ◽  
Closed Loop ◽  
Current Knowledge ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Brain Regions ◽  
Integrative Approach ◽  
Resonance Imaging ◽  
Neural Communication ◽  
Neural Interactions

The human brain is a complex network in which hundreds of brain regions are interconnected via thousands of axonal pathways. The capability of such a complex system emerges from specific interactions among smaller entities, a set of events that can be described by the activation of interconnections between brain areas. Studies that focus on brain connectivity have the aim of understanding and modeling brain function, taking into account the spatiotemporal dynamics of neural communication between brain regions. Much of the current knowledge regarding brain connectivity has been obtained from stand-alone neuroimaging methods. Nevertheless, the use of a multimodal approach seems to be a powerful way to investigate effective brain connectivity, overcoming the limitations of unimodal approaches. In this review, we will present the advantages of an integrative approach in which transcranial magnetic stimulation–electroencephalography coregistration is combined with magnetic resonance imaging methods to explore effective neural interactions. Moreover, we will describe possible implementations of the integrative approach in open- and closed-loop frameworks where real-time brain activity becomes a contributor to the study of cognitive brain networks.

scholarly journals Neurophenomenology of near-death experience memory in hypnotic recall: a within-subject EEG study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Charlotte Martial ◽  
Armand Mensen ◽  
Vanessa Charland-Verville ◽  
Audrey Vanhaudenhuyse ◽  
Daniel Rentmeister ◽  
...  
Keyword(s):  
Subjective Experience ◽  
Brain Activity ◽  
Alpha Activity ◽  
High Density ◽  
Proof Of Concept ◽  
Time Period ◽  
Death Experience ◽  
Eeg Changes ◽  
The One ◽  
Near Death Experiences

Abstract The neurobiological basis of near-death experiences (NDEs) is unknown, but a few studies attempted to investigate it by reproducing in laboratory settings phenomenological experiences that seem to closely resemble NDEs. So far, no study has induced NDE-like features via hypnotic modulation while simultaneously measuring changes in brain activity using high-density EEG. Five volunteers who previously had experienced a pleasant NDE were invited to re-experience the NDE memory and another pleasant autobiographical memory (dating to the same time period), in normal consciousness and with hypnosis. We compared the hypnosis-induced subjective experience with the one of the genuine experience memory. Continuous high-density EEG was recorded throughout. At a phenomenological level, we succeeded in recreating NDE-like features without any adverse effects. Absorption and dissociation levels were reported as higher during all hypnosis conditions as compared to normal consciousness conditions, suggesting that our hypnosis-based protocol increased the felt subjective experience in the recall of both memories. The recall of a NDE phenomenology was related to an increase of alpha activity in frontal and posterior regions. This study provides a proof-of-concept methodology for studying the phenomenon, enabling to prospectively explore the NDE-like features and associated EEG changes in controlled settings.

scholarly journals Recent advances in functional neuroimaging analysis for cognitive neuroscience

2018 ◽  
Vol 2 ◽  
pp. 239821281775272 ◽  
Author(s):  
Nitin Williams ◽  
Richard N. Henson
Keyword(s):  
Functional Neuroimaging ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Recent Analysis ◽  
Temporal Data ◽  
New Methods ◽  
Neuroimaging Data ◽  
The Rich ◽  
Scientific Questions ◽  
The Brain

Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives.

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