scholarly journals Neural Correlates of Feedback Processing in Toddlers

2014 ◽  
Vol 26 (7) ◽  
pp. 1519-1527 ◽  
Author(s):  
Marlene Meyer ◽  
Harold Bekkering ◽  
Denise J. C. Janssen ◽  
Ellen R. A. de Bruijn ◽  
Sabine Hunnius
Keyword(s):  
Early Childhood ◽  
Brain Development ◽  
Brain Activity ◽  
Feedback System ◽  
Brain Regions ◽  
Adaptive Performance ◽  
Feedback Processing ◽  
Essential Information ◽  
Electrophysiological Studies ◽  
Neural Feedback

External feedback provides essential information for successful learning. Feedback is especially important for learning in early childhood, as toddlers strongly rely on external signals to determine the consequences of their actions. In adults, many electrophysiological studies have elucidated feedback processes using a neural marker called the feedback-related negativity (FRN). The neural generator of the FRN is assumed to be the ACC, located in medial frontal cortex. As frontal brain regions are the latest to mature during brain development, it is unclear when in early childhood a functional feedback system develops. Is feedback differentiated on a neural level in toddlers and in how far is neural feedback processing related to children's behavioral adjustment? In an EEG experiment, we addressed these questions by measuring the brain activity and behavioral performance of 2.5-year-old toddlers while they played a feedback-guided game on a touchscreen. Electrophysiological results show differential brain activity for feedback with a more negative deflection for incorrect than correct outcomes, resembling the adult FRN. This provides the first neural evidence for feedback processing in toddlers. Notably, FRN amplitudes were predictive of adaptive behavior: the stronger the differential brain activity for feedback, the better the toddlers' adaptive performance during the game. Thus, already in early childhood toddlers' feedback-guided performance directly relates to the functionality of their neural feedback processing. Implications for early feedback-based learning as well as structural and functional brain development are discussed.

scholarly journals Adolescent brain development in normality and psychopathology

2013 ◽  
Vol 25 (4pt2) ◽  
pp. 1325-1345 ◽  
Author(s):  
Monica Luciana
Keyword(s):  
Brain Development ◽  
Sensation Seeking ◽  
Brain Activity ◽  
Activity Patterns ◽  
Theoretical Models ◽  
Brain Regions ◽  
Incentive Motivation ◽  
Prefrontal Function ◽  
Adolescent Risk ◽  
Adolescent Brain Development

AbstractSince this journal's inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical–cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology–context interactions, represent the field's most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

Comparative analysis of changes of bioelectrical activity of the brain during the neutral touch and during the performance of the myofascial release technique

2018 ◽  
pp. 46-55
Author(s):  
A. F. Belyaev ◽  
G. E. Piskunova
Keyword(s):  
Soft Tissue ◽  
Brain Activity ◽  
Direct Action ◽  
Brain Regions ◽  
Therapeutic Touch ◽  
Bioelectrical Activity ◽  
Therapeutic Action ◽  
Osteopathic Treatment ◽  
The Difference ◽  
Multiparameter Analysis

Introduction. One of the main tools of an osteopath are soft tissue techniques, which have a number of particular qualities such as minimization of force and duration of indirect techniques with an emphasis on muscle and ligamentous structures; combination of gestures, tendency to maximal relaxation and exclusion of direct action on pathological symptoms such as tension, overtone and pain. Minimization of the force applied during the performance of soft tissue techniques often invites a question whether there are differences between the usual touch and the therapeutic touch of an osteopath.Goal of research - to reveal the changes in the bioelectrical activity of the cerebral cortex arising in the process of osteopathic treatment in order to prove its specifi city in comparison with nonspecifi c tactile stimulation (neutral touch).Materials and methods. 75 people were examined with the use of multiparameter analysis of multichannel EEG in different times. 25 patients were clinically healthy adults, whereas 50 patients had signs of somatic dysfunctions.Results. Computer encephalography permits to perceive the difference between the neutral touch and the therapeutic action. An identifi cation reaction is a response to the neutral touch (changes in brain bioelectrical activity with an increase in statistically signifi cant connections in the temporal lobes), whereas the therapeutic action provokes the state of purposeful brain activity during still point (intensifi cation of frontooccipital interactions).Conclusions. Osteopathic action causes additional tension in the processing of incoming information, which requires participation of different brain regions, including interhemispheric mechanisms associated with analysis, maintenance of attention and regulation of targeted activities.

scholarly journals Visual predictions, neural oscillations and naïve physics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blake W. Saurels ◽  
Wiremu Hohaia ◽  
Kielan Yarrow ◽  
Alan Johnston ◽  
Derek H. Arnold
Keyword(s):  
Brain Activity ◽  
Dynamic Environment ◽  
Predictive Performance ◽  
Brain Regions ◽  
Internal Models ◽  
Oscillatory Activity ◽  
Alpha Band ◽  
Core Property ◽  
Ball Tracking ◽  
Band Activity

AbstractPrediction is a core function of the human visual system. Contemporary research suggests the brain builds predictive internal models of the world to facilitate interactions with our dynamic environment. Here, we wanted to examine the behavioural and neurological consequences of disrupting a core property of peoples’ internal models, using naturalistic stimuli. We had people view videos of basketball and asked them to track the moving ball and predict jump shot outcomes, all while we recorded eye movements and brain activity. To disrupt people’s predictive internal models, we inverted footage on half the trials, so dynamics were inconsistent with how movements should be shaped by gravity. When viewing upright videos people were better at predicting shot outcomes, at tracking the ball position, and they had enhanced alpha-band oscillatory activity in occipital brain regions. The advantage for predicting upright shot outcomes scaled with improvements in ball tracking and occipital alpha-band activity. Occipital alpha-band activity has been linked to selective attention and spatially-mapped inhibitions of visual brain activity. We propose that when people have a more accurate predictive model of the environment, they can more easily parse what is relevant, allowing them to better target irrelevant positions for suppression—resulting in both better predictive performance and in neural markers of inhibited information processing.

scholarly journals Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

2021 ◽  
Author(s):  
Adeline Jabès ◽  
Giuliana Klencklen ◽  
Paolo Ruggeri ◽  
Christoph M. Michel ◽  
Pamela Banta Lavenex ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Resting State ◽  
Cognitive Aging ◽  
Temporal Dynamics ◽  
Spatial Working Memory ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Age Related

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

scholarly journals EEG-based diagnostics of the auditory system using cochlear implant electrodes as sensors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ben Somers ◽  
Christopher J. Long ◽  
Tom Francart
Keyword(s):  
Cochlear Implant ◽  
Auditory Evoked Potentials ◽  
Human Subjects ◽  
Electrode Array ◽  
Brain Regions ◽  
Hearing Impaired ◽  
Brain Responses ◽  
Listening Environments ◽  
Set Up ◽  
Neural Feedback

AbstractThe cochlear implant is one of the most successful medical prostheses, allowing deaf and severely hearing-impaired persons to hear again by electrically stimulating the auditory nerve. A trained audiologist adjusts the stimulation settings for good speech understanding, known as “fitting” the implant. This process is based on subjective feedback from the user, making it time-consuming and challenging, especially in paediatric or communication-impaired populations. Furthermore, fittings only happen during infrequent sessions at a clinic, and therefore cannot take into account variable factors that affect the user’s hearing, such as physiological changes and different listening environments. Objective audiometry, in which brain responses evoked by auditory stimulation are collected and analysed, removes the need for active patient participation. However, recording of brain responses still requires expensive equipment that is cumbersome to use. An elegant solution is to record the neural signals using the implant itself. We demonstrate for the first time the recording of continuous electroencephalographic (EEG) signals from the implanted intracochlear electrode array in human subjects, using auditory evoked potentials originating from different brain regions. This was done using a temporary recording set-up with a percutaneous connector used for research purposes. Furthermore, we show that the response morphologies and amplitudes depend crucially on the recording electrode configuration. The integration of an EEG system into cochlear implants paves the way towards chronic neuro-monitoring of hearing-impaired patients in their everyday environment, and neuro-steered hearing prostheses, which can autonomously adjust their output based on neural feedback.

scholarly journals Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics

2021 ◽  
Vol 11 (7) ◽  
pp. 885
Author(s):  
Maher Abujelala ◽  
Rohith Karthikeyan ◽  
Oshin Tyagi ◽  
Jing Du ◽  
Ranjana K. Mehta
Keyword(s):  
Machine Learning ◽  
Environmental Conditions ◽  
Brain Activity ◽  
Memory Task ◽  
Classification Problem ◽  
Brain Regions ◽  
Training Data ◽  
Information Encoding ◽  
Machine Learning Approach ◽  
Encoding And Retrieval

The nature of firefighters` duties requires them to work for long periods under unfavorable conditions. To perform their jobs effectively, they are required to endure long hours of extensive, stressful training. Creating such training environments is very expensive and it is difficult to guarantee trainees’ safety. In this study, firefighters are trained in a virtual environment that includes virtual perturbations such as fires, alarms, and smoke. The objective of this paper is to use machine learning methods to discern encoding and retrieval states in firefighters during a visuospatial episodic memory task and explore which regions of the brain provide suitable signals to solve this classification problem. Our results show that the Random Forest algorithm could be used to distinguish between information encoding and retrieval using features extracted from fNIRS data. Our algorithm achieved an F-1 score of 0.844 and an accuracy of 79.10% if the training and testing data are obtained at similar environmental conditions. However, the algorithm’s performance dropped to an F-1 score of 0.723 and accuracy of 60.61% when evaluated on data collected under different environmental conditions than the training data. We also found that if the training and evaluation data were recorded under the same environmental conditions, the RPM, LDLPFC, RDLPFC were the most relevant brain regions under non-stressful, stressful, and a mix of stressful and non-stressful conditions, respectively.

scholarly journals Peripheral arterial stiffness during electrocutaneous stimulation is positively correlated with pain-related brain activity and subjective pain intensity: an fMRI study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Toshio Tsuji ◽  
Fumiya Arikuni ◽  
Takafumi Sasaoka ◽  
Shin Suyama ◽  
Takashi Akiyoshi ◽  
...  
Keyword(s):  
Arterial Stiffness ◽  
Pain Intensity ◽  
Brain Activity ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Electrocutaneous Stimulation ◽  
Pain Matrix ◽  
Fmri Study ◽  
Subjective Pain ◽  
Peripheral Arterial

AbstractBrain activity associated with pain perception has been revealed by numerous PET and fMRI studies over the past few decades. These findings helped to establish the concept of the pain matrix, which is the distributed brain networks that demonstrate pain-specific cortical activities. We previously found that peripheral arterial stiffness $${\beta }_{\text{art}}$$ β art responds to pain intensity, which is estimated from electrocardiography, continuous sphygmomanometer, and photo-plethysmography. However, it remains unclear whether and to what extent $${\beta }_{\text{art}}$$ β art aligns with pain matrix brain activity. In this fMRI study, 22 participants received different intensities of pain stimuli. We identified brain regions in which the blood oxygen level-dependent signal covaried with $${\beta }_{\text{art}}$$ β art using parametric modulation analysis. Among the identified brain regions, the lateral and medial prefrontal cortex and ventral and dorsal anterior cingulate cortex were consistent with the pain matrix. We found moderate correlations between the average activities in these regions and $${\beta }_{\text{art}}$$ β art (r = 0.47, p < 0.001). $${\beta }_{\text{art}}$$ β art was also significantly correlated with self-reported pain intensity (r = 0.44, p < 0.001) and applied pain intensity (r = 0.43, p < 0.001). Our results indicate that $${\beta }_{\text{art}}$$ β art is positively correlated with pain-related brain activity and subjective pain intensity. This study may thus represent a basis for adopting peripheral arterial stiffness as an objective pain evaluation metric.

Distinguishing hypochondriasis and schizophrenia using regional homogeneity: a resting-state fMRI study and support vector machine analysis

2021 ◽  
pp. 1-29
Author(s):  
Kangyu Jin ◽  
Zhe Shen ◽  
Guoxun Feng ◽  
Zhiyong Zhao ◽  
Jing Lu ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Resting State ◽  
Parietal Lobe ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Middle Temporal Gyrus ◽  
Support Vector ◽  
Fmri Study

Abstract Objective: A few former studies suggested there are partial overlaps in abnormal brain structure and cognitive function between Hypochondriasis (HS) and schizophrenia (SZ). But their differences in brain activity and cognitive function were unclear. Methods: 21 HS patients, 23 SZ patients, and 24 healthy controls (HC) underwent Resting-state functional magnetic resonance imaging (rs-fMRI) with the regional homogeneity analysis (ReHo), subsequently exploring the relationship between ReHo value and cognitive functions. The support vector machines (SVM) were used on effectiveness evaluation of ReHo for differentiating HS from SZ. Results: Compared with HC, HS showed significantly increased ReHo values in right middle temporal gyrus (MTG), left inferior parietal lobe (IPL) and right fusiform gyrus (FG), while SZ showed increased ReHo in left insula, decreased ReHo values in right paracentral lobule. Additionally, HS showed significantly higher ReHo values in FG, MTG and left paracentral lobule but lower in insula than SZ. The higher ReHo values in insula were associated with worse performance in MCCB in HS group. SVM analysis showed a combination of the ReHo values in insula and FG was able to satisfactorily distinguish the HS and SZ patients. Conclusion: our results suggested the altered default mode network (DMN), of which abnormal spontaneous neural activity occurs in multiple brain regions, might play a key role in the pathogenesis of HS, and the resting-state alterations of insula closely related to cognitive dysfunction in HS. Furthermore, the combination of the ReHo in FG and insula was a relatively ideal indicator to distinguish HS from SZ.

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