Fundamental Study for Relationship between Cognitive Task and Brain Activity During Car Driving

Behavioral studies have shown that consistent practice of a cognitive task can increase the speed of performance and reduce variability of responses and error rate, reflecting a shift from controlled to automatic processing. This study examines how the shift from controlled to automatic processing changes brain activity. A verbal Sternberg task was used with continuously changing targets (novel task, NT) and with constant, practiced targets (practiced task, PT). NT and PT were presented in a blocked design and contrasted to a choice reaction time (RT) control task (CT) to isolate working memory (WM)-related activity. The three-dimensional (3-D) PRESTO functional magnetic resonance imaging (fMRI) sequence was used to measure hemodynamic responses. Behavioral data revealed that task processing became automated after practice, as responses were faster, less variable, and more accurate. This was accompanied specifically by a decrease in activation in regions related to WM (bilateral but predominantly left dorsolateral prefrontal cortex (DLPFC), right superior frontal cortex (SFC), and right frontopolar area) and the supplementary motor area. Results showed no evidence for a shift of foci of activity within or across regions of the brain. The findings have theoretical implications for understanding the functional anatomical substrates of automatic and controlled processing, indicating that these types of information processing have the same functional anatomical substrate, but differ in efficiency. In addition, there are practical implications for interpreting activity as a measure for task performance, such as in patient studies. Whereas reduced activity can reflect poor performance if a task is not sensitive to practice effects, it can reflect good performance if a task is sensitive to practice effects.

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Studying the effect of Heartfulness Meditation on Brain Activity

Inquiry@Queen's Undergraduate Research Conference Proceedings ◽

10.24908/iqurcp.10470 ◽

2018 ◽

Author(s):

Pallavi Gupta ◽

Jahnavi Mundluru ◽

Arth Patel ◽

Shankar Pathmakanthan

Keyword(s):

Problem Solving ◽

Creative Thinking ◽

Brain Activity ◽

Cognitive Task ◽

Thinking Skills ◽

Cognitive Tasks ◽

Logical Thinking ◽

Meditation Practice ◽

Guided Relaxation

Long-term meditation practice is increasingly recognized for its health benefits. Heartfulness meditation represents a quickly growing set of practices that is largely unstudied. Heartfulness is unique in that it is a meditation practice that focuses on the Heart. It helps individuals to connect to themselves and find inner peace. In order to deepen ones’ meditation, the element of Yogic Energy (‘pranahuti’) is used as an aid during meditation. The purpose of this study was to determine whether consistent EEG effects of Heartfulness meditation be observed in sixty experienced Heartfulness meditators, each of whom attended 6 testing sessions. In each session, participants performed three conditions: a set of cognitive tasks, Heartfulness guided relaxation, and Heartfulness Meditation. Participants during the cognitive portion were required to answer questions that tested their logical thinking (Cognitive Reflective Test) and creative thinking skills. (Random Associative Test) The order of condition was randomly counter balanced across six sessions. It was hypothesized that Heartfulness meditation would bring increased alpha (8-12Hz) brain activity during meditation and better cognitive task scores in sessions where the tasks followed meditation. Heartfulness meditation produces a significant decrease in brain activity (as indexed by higher levels of alpha during the early stages of meditation. As the meditation progressed deep meditative state (as indexed by higher levels of delta) were observed until the end of the condition. This lead to the conclusion that Heartfulness Meditation produces a state that is clearly distinguishable from effortful problem solving.

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Caffeine boosts preparatory attention for reward-related stimulus information

10.1101/697177 ◽

2019 ◽

Author(s):

Berry van den Berg ◽

Marlon de Jong ◽

Marty G. Woldorff ◽

Monicque M. Lorist

Keyword(s):

Brain Activity ◽

Cognitive Task ◽

Relevant Information ◽

Caffeine Intake ◽

Alpha Power ◽

Behavioral Measures ◽

Placebo Condition ◽

Electrical Brain Activity ◽

Preparatory Attention ◽

Stroop Stimulus

AbstractBoth the intake of caffeine-containing substances and the prospect of reward for performing a cognitive task have been associated with improved behavioral performance. To investigate the possible common and interactive influences of caffeine and reward-prospect on preparatory attention, we tested 24 participants during a 2-session experiment in which they performed a cued-reward color-word Stroop task. On each trial, participants were presented with a cue to inform them whether they had to prepare for presentation of a Stroop stimulus and whether they could receive a reward if they performed well on that trial. Prior to each session, participants received either coffee with caffeine (3 mg/kg bodyweight) or with placebo (3 mg/kg bodyweight lactose). In addition to behavioral measures, electroencephalography (EEG) measures of electrical brain activity were recorded. Results showed that both the intake of caffeine and the prospect of reward improved speed and accuracy, with the effects of caffeine and reward-prospect being additive on performance. Neurally, reward-prospect resulted in an enlarged contingent negative variation (CNV) and reduced posterior alpha power (indicating increased cortical activity), both hallmark neural markers for preparatory attention. Moreover, the CNV enhancement for reward-prospect trials was considerably more pronounced in the caffeine condition as compared to the placebo condition. These results thus suggest that caffeine intake boosts preparatory attention for task-relevant information, especially when performance on that task can lead to reward.

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Sleeping While Awake: The Intrusion of Neural Activity Associated with Sleep Onset in the Awake Human Brain

10.1101/2020.06.04.133603 ◽

2020 ◽

Cited By ~ 2

Author(s):

Stephanie Hawes ◽

Carrie R. H. Innes ◽

Nicholas Parsons ◽

Sean P.A. Drummond ◽

Karen Caeyensberghs ◽

...

Keyword(s):

Human Brain ◽

Basal Forebrain ◽

Brain Activity ◽

Cognitive Task ◽

Sleep Onset ◽

Theoretical Modelling ◽

Related Activity ◽

Independent Dataset ◽

Time Graph ◽

The Brain

AbstractSleep can intrude into the awake human brain when sleep deprived or fatigued, even while performing cognitive tasks. However, how the brain activity associated with sleep onset can co-exist with the activity associated with cognition in the awake humans remains unexplored. Here, we used simultaneous fMRI and EEG to generate fMRI activity maps associated with EEG theta (4-7 Hz) activity associated with sleep onset. We implemented a method to track these fMRI activity maps in individuals performing a cognitive task after well-rested and sleep-deprived nights. We found frequent intrusions of the fMRI maps associated with sleep-onset in the task-related fMRI data. These sleep events elicited a pattern of transient fMRI activity, which was spatially distinct from the task-related activity in the frontal and parietal areas of the brain. They were concomitant with reduced arousal as indicated by decreased pupil size and increased response time. Graph theoretical modelling showed that the activity associated with sleep onset emerges from the basal forebrain and spreads anterior-posteriorly via the brain’s structural connectome. We replicated the key findings in an independent dataset, which suggests that the approach can be reliably used in understanding the neuro-behavioural consequences of sleep and circadian disturbances in humans.

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Cognitive and Motor Loops of the Human Cerebro-cerebellar System

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2009.21382 ◽

2010 ◽

Vol 22 (11) ◽

pp. 2663-2676 ◽

Cited By ~ 150

Author(s):

Juha Salmi ◽

Karen Johanne Pallesen ◽

Tuomas Neuvonen ◽

Elvira Brattico ◽

Antti Korvenoja ◽

...

Keyword(s):

Cognitive Load ◽

Brain Activity ◽

Cognitive Task ◽

Memory Task ◽

Diffusion Weighted Mri ◽

Motor Functions ◽

Diffusion Weighted ◽

Sensory Motor ◽

Load Increase ◽

Crus I

We applied fMRI and diffusion-weighted MRI to study the segregation of cognitive and motor functions in the human cerebro-cerebellar system. Our fMRI results show that a load increase in a nonverbal auditory working memory task is associated with enhanced brain activity in the parietal, dorsal premotor, and lateral prefrontal cortices and in lobules VII–VIII of the posterior cerebellum, whereas a sensory-motor control task activated the motor/somatosensory, medial prefrontal, and posterior cingulate cortices and lobules V/VI of the anterior cerebellum. The load-dependent activity in the crus I/II had a specific relationship with cognitive performance: This activity correlated negatively with load-dependent increase in RTs. This correlation between brain activity and RTs was not observed in the sensory-motor task in the activated cerebellar regions. Furthermore, probabilistic tractography analysis of the diffusion-weighted MRI data suggests that the tracts between the cerebral and the cerebellar areas exhibiting cognitive load-dependent and sensory-motor activity are mainly projected via separated pontine (feed-forward tracts) and thalamic (feedback tracts) nuclei. The tractography results also indicate that the crus I/II in the posterior cerebellum is linked with the lateral prefrontal areas activated by cognitive load increase, whereas the anterior cerebellar lobe is not. The current results support the view that cognitive and motor functions are segregated in the cerebellum. On the basis of these results and theories of the function of the cerebellum, we suggest that the posterior cerebellar activity during a demanding cognitive task is involved with optimization of the response speed.

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Your Brain Knows if You're Iron Deficient: Distinct Brain Dynamics in Iron Deficient vs. Sufficient Females in a Visual Category Learning Task

Current Developments in Nutrition ◽

10.1093/cdn/nzab049_042 ◽

2021 ◽

Vol 5 (Supplement_2) ◽

pp. 929-929

Author(s):

Michael Wenger ◽

Stephanie Rhoten ◽

Lisa De Stefano ◽

Amy Barnett ◽

Laili Boozary

Keyword(s):

Time Window ◽

Brain Activity ◽

Iron Status ◽

Cognitive Task ◽

Area Under The Curve ◽

Learning Task ◽

Outcome Variable ◽

Global Field Power ◽

Iron Deficient ◽

Neural Efficiency

Abstract Objectives The present study sought to determine the possibility of identifying someone as either iron deficient or sufficient based solely on brain activity, and, if possible, how quickly (based on processing time on a cognitive task) this could be done. Methods Both iron sufficient(IS) and iron deficient non-anemic (IDNA) females (mean age 21.1 y) learned two visual categorization tasks while concurrent EEG was acquired. Both tasks involved classifying gray-scale gabor patches on the basis of spatial frequency and orientation; one task used an easily-verbalized rule (rule-based, RB), the other required complex integration of the information (II). Moving windows (20 ms width) of EEG data from 100 electrodes were used to predict the participant's iron status using logistic regression; model form was determined using stepwise variable selection. The outcome variable was the area under the curve (AUC) of the receiver operating characteristic for the classification. We set a criterion of AUC ≥ 0.80 for successful classification performance. Results For both tasks, successful classification was possible before 200 ms of processing on the basis of fewer than 12 electrodes. Classification in the RB task suggested some early right lateralization in the selection of electrodes, which became more central as processing proceeded. Classification in the II task did not suggest lateralization, although there was some change to more central electrodes as processing proceeded. At each 20 ms time window, for each of the selected set of electrodes, a measure of neural efficiency was calculated as the ratio of the hazard function of the reaction time distribution and the global field power of the selected set of electrodes. This ratio can be interpreted as the amount of work accomplished per unit of energy expended. In all cases, neural efficiency for the IS females exceeded that for the IDNA females, suggesting that the efficiency with which neural energy is expended in cognitive work differs as a function of iron status. Conclusions Iron deficiency without anemia results in distinct patterns of brain activity early in processing that reflect reduced levels of neural efficiency, relative to females who are iron sufficient. Funding Sources OU Office of the Vice President for Research.

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On causality of extreme events

10.7287/peerj.preprints.1827v1 ◽

2016 ◽

Author(s):

Massimiliano Zanin

Keyword(s):

Extreme Events ◽

Chaotic Systems ◽

Brain Activity ◽

Cognitive Task ◽

Synthetic Data ◽

Data Sets ◽

Confounding Factors ◽

Cross Sectional ◽

Static Data ◽

Multiple Metrics

Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect both linear and non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task.

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