scholarly journals Dynamical Change of Signal Complexity in the Brain During Inhibitory Control Processes

Entropy ◽  
2015 ◽  
Vol 17 (12) ◽  
pp. 6834-6853 ◽  
Author(s):  
Shih-Lin Huang ◽  
Philip Tseng ◽  
Wei-Kuang Liang
Keyword(s):  
Inhibitory Control ◽  
Control Processes ◽  
Signal Complexity ◽  
The Brain ◽  
Dynamical Change

scholarly journals Reactive and Proactive Adaptation of Cognitive and Motor Neural Signals during Performance of a Stop-Change Task

2021 ◽  
Vol 11 (5) ◽  
pp. 617
Author(s):  
Adam T. Brockett ◽  
Matthew R. Roesch
Keyword(s):  
Inhibitory Control ◽  
Common Ground ◽  
Large Body ◽  
Stop Signal Task ◽  
Behavioral Strategies ◽  
Neural Signals ◽  
Brain Areas ◽  
Control Processes ◽  
Change Task ◽  
The Brain

The ability to inhibit or suppress unwanted or inappropriate actions, is an essential component of executive function and cognitive health. The immense selective pressure placed on maintaining inhibitory control processes is exemplified by the relatively small number of instances in which these systems completely fail in the average person’s daily life. Although mistakes and errors do inevitably occur, inhibitory control systems not only ensure that this number is low, but have also adapted behavioral strategies to minimize future failures. The ability of our brains to adapt our behavior and appropriately engage proper motor responses is traditionally depicted as the primary domain of frontal brain areas, despite evidence to the fact that numerous other brain areas contribute. Using the stop-signal task as a common ground for comparison, we review a large body of literature investigating inhibitory control processes across frontal, temporal, and midbrain structures, focusing on our recent work in rodents, in an effort to understand how the brain biases action selection and adapts to the experience of conflict.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

scholarly journals On the interrelation of 1/f neural noise and norepinephrine system activity during motor response inhibition

2019 ◽  
Vol 121 (5) ◽  
pp. 1633-1643 ◽  
Author(s):  
Maik Pertermann ◽  
Moritz Mückschel ◽  
Nico Adelhöfer ◽  
Tjalf Ziemssen ◽  
Christian Beste
Keyword(s):  
Information Processing ◽  
Cognitive Control ◽  
Inhibitory Control ◽  
Response Inhibition ◽  
Pupil Diameter ◽  
Human Information Processing ◽  
System Activity ◽  
Neural Noise ◽  
Control Processes ◽  
Norepinephrine System

Several lines of evidence suggest that there is a close interrelation between the degree of noise in neural circuits and the activity of the norepinephrine (NE) system, yet the precise nexus between these aspects is far from being understood during human information processing and cognitive control in particular. We examine this nexus during response inhibition in n = 47 healthy participants. Using high-density EEG recordings, we estimate neural noise by calculating “1/ f noise” of those data and integrate these EEG parameters with pupil diameter data as an established indirect index of NE system activity. We show that neural noise is reduced when cognitive control processes to inhibit a prepotent/automated response are exerted. These neural noise variations were confined to the theta frequency band, which has also been shown to play a central role during response inhibition and cognitive control. There were strong positive correlations between the 1 /f neural noise parameter and the pupil diameter data within the first 250 ms after the Nogo stimulus presentation at centro-parietal electrode sites. No such correlations were evident during automated responding on Go trials. Source localization analyses using standardized low-resolution brain electromagnetic tomography show that inferior parietal areas are activated in this time period in Nogo trials. The data suggest an interrelation of NE system activity and neural noise within early stages of information processing associated with inferior parietal areas when cognitive control processes are required. The data provide the first direct evidence for the nexus between NE system activity and the modulation of neural noise during inhibitory control in humans. NEW & NOTEWORTHY This is the first study showing that there is a nexus between norepinephrine system activity and the modulation of neural noise or scale-free neural activity during inhibitory control in humans. It does so by integrating pupil diameter data with analysis of EEG neural noise.

scholarly journals Human Memory Retrieval and Inhibitory Control in the Brain: Beyond Correlational Evidence

2014 ◽  
Vol 34 (19) ◽  
pp. 6606-6610 ◽  
Author(s):  
B. Penolazzi ◽  
D. F. Stramaccia ◽  
M. Braga ◽  
S. Mondini ◽  
G. Galfano
Keyword(s):  
Inhibitory Control ◽  
Memory Retrieval ◽  
Human Memory ◽  
The Brain

scholarly journals Measures of frontal functioning and the emergence of inhibitory control processes at 10 months of age

2012 ◽  
Vol 2 (2) ◽  
pp. 235-243 ◽  
Author(s):  
Kimberly Cuevas ◽  
Margaret M. Swingler ◽  
Martha Ann Bell ◽  
Stuart Marcovitch ◽  
Susan D. Calkins
Keyword(s):  
Inhibitory Control ◽  
Control Processes ◽  
Frontal Functioning

Electrophysiological activity underlying inhibitory control processes in normal adults

2006 ◽  
Vol 44 (3) ◽  
pp. 384-395 ◽  
Author(s):  
Mariana Schmajuk ◽  
Mario Liotti ◽  
Laura Busse ◽  
Marty G. Woldorff
Keyword(s):  
Inhibitory Control ◽  
Electrophysiological Activity ◽  
Control Processes ◽  
Normal Adults

scholarly journals Multimethod Investigation of the Neurobiological Basis of ADHD Symptomatology in Children Aged 9-10: Baseline Data from the ABCD Study

2020 ◽  
Author(s):  
Max Michael Owens ◽  
Nicholas Allgaier ◽  
Sage Hahn ◽  
Dekang Yuan ◽  
Matthew Albaugh ◽  
...  
Keyword(s):  
Working Memory ◽  
Inhibitory Control ◽  
Internalizing Symptoms ◽  
Memory Task ◽  
Reward Processing ◽  
Continuous Measure ◽  
Neurocognitive Deficits ◽  
Brain Morphometry ◽  
The Brain ◽  
Adhd Symptomatology

Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.

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