Revealing the brain's adaptability and the transcranial direct current stimulation facilitating effect in inhibitory control by multiscale entropy

Liang, Wei Kuang; Lo, Men Tzung; Yang, Albert C.; Peng, Chung-Kang; Cheng, Shih Kuen; Tseng, Philip; Juan, Chi Hung

doi:10.1016/j.neuroimage.2013.12.048

Cited by 75 publications

(77 citation statements)

References 57 publications

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“…We did not however, observe a stimulation-induced effect on SSRTs, inhibition accuracy and signal-respond RTs. While two recent studies found polarity-specific effects on SSRTs after anodal stimulation over pre-SMA (Liang et al, 2014;Yu et al, 2015), the lack of SSRTs and signal-respond RTs are in line with the findings from recent studies by Hsu and colleagues (2011) and . The authors applied anodal and cathodal tDCS over the SMFC to investigate its functional role in response inhibition operations.…”

Section: Discussionsupporting

confidence: 90%

“…tDCS is a non-invasive brain stimulation method that can be employed to modulate cortical activity and establish a causal role of specific regions or functionally/anatomically connected networks in behaviour (Liang et al, 2014;Yu, Tseng, Hung, Wu, & Juan, 2015). In addition, it can shed light on the systems-level neural mechanisms of specific cognitive operations by influencing performance in a polarityspecific manner (Filmer, Dux, & Mattingley, 2014).…”

Section: Discussionmentioning

confidence: 99%

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Selecting and inhibiting responses: Common cognitive and neural substrates?

Bender¹

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Despite the brain receiving a constant influx of sensory information in ever-changing environments, humans are nonetheless able to flexibly guide their behaviour in accordance with higher goals and plans. The cognitive system achieves this by implementing executive control processes that monitor, regulate and alter the settings of lower level cognitive processes that are involved in analyzing incoming sensory information and executing motor plans. At the core of goal-directed behaviour are the abilities to select appropriate responses and inhibit planned actions in response to changes in the environment or internal states. While there have been considerable advancements made in understanding the behavioural and neural substrates of response selection and response inhibition, we currently know relatively little about the relationship and possible interplay between these two key cognitive operations. The experiments in this thesis investigate the behavioural and neural overlap in response selection and response inhibition processes by identifying the latent structure that underpins performance in a wide range of action control tasks, exploring the causal role of a brain region that has been implicated in both processes, and by inspecting the degree to which response selection training transfers to other response selection and inhibitory control tasks.Study 1 describes a behavioural study that employed an individual differences approach to investigate the underlying relationships across a battery of common response selection tasks (as measured by the psychological refractory period paradigm (PRP), single response selection task, and attentional blink (AB) task), and response inhibition tasks (as measured by the stop-signal task (SST), Go-Nogo tasks, Stroop, and Flanker task). In order to avoid task impurity and construct validity problems that can seriously undermine the utility of correlational and exploratory factor analytic studies, I used confirmatory factor analysis to statistically extract only what is common about the tasks.Using this approach, I found that response inhibition and response selection were separable, with SST and Go-Nogo task performance related to response inhibition, and the PRP, Stroop, Single Response Selection, and AB tasks related to response selection.These findings suggest that response selection and response inhibition reflect two distinct cognitive operations.As neurocognitive work has implicated the superior medial frontal cortex (SMFC) in both response selection and the proactive modulation of response tendencies when stopping is occasionally required (inhibitory response selection control), it suggests that the neural substrates for these two cognitive operations overlap in this brain region. In Response selection performance is typically compromised due to the processing limitations associated with cognitive control and decision-making when completing two tasks together relative to when completing the component tasks in isolation. While these multitasking performance decr...

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Selecting and inhibiting responses: Common cognitive and neural substrates?

Bender¹

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“…To better investigate the adaptability and complexity of the neural systems during the stop-signal task, a 2014 study by Liang et al [10] calculated the multiscale entropy (MSE; [11][12][13][14]) of EEG signals acquired along with the stop-signal experiment. The prior study was based on three hypotheses: (1) the complexity of a biological system reflects its ability to adapt and function in a fast-changing environment; (2) biological systems need to operate across multiple spatial and temporal scales, and hence their complexity is also multi-scaled; (3) the "ability to adapt" by the brain for a cognitive function is associated with the neuroplasticity of this function [10,14,15].…”

Section: Introductionmentioning

confidence: 99%

“…The prior study was based on three hypotheses: (1) the complexity of a biological system reflects its ability to adapt and function in a fast-changing environment; (2) biological systems need to operate across multiple spatial and temporal scales, and hence their complexity is also multi-scaled; (3) the "ability to adapt" by the brain for a cognitive function is associated with the neuroplasticity of this function [10,14,15]. However, the prior study only applied MSE to EEG signals approximately from the go signal onset to the end of the stop-signal reaction time (SSRT).…”

Section: Introductionmentioning

confidence: 99%

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

Huang

Tseng²,

Liang

2015

Entropy

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Abstract:The ability to inhibit impulses and withdraw certain responses are essential for human's survival in a fast-changing environment. These processes happen fast, in a complex manner, and require our brain to make a fast adaptation to inhibit the impulsive response. The present study employs multiscale entropy (MSE) to analyzing electroencephalography (EEG) signals acquired alongside a behavioral stop-signal task to theoretically quantify the complexity (indicating adaptability and efficiency) of neural systems to investigate the dynamical change of complexity in the brain during the processes of inhibitory control. We found that the complexity of EEG signals was higher for successful than unsuccessful inhibition in the stage of peri-stimulus, but not in the pre-stimulus time window. In addition, we found that the dynamical change in the brain from pre-stimulus to peri-stimulus stage for inhibitory control is a process of decreasing complexity. We demonstrated both by sensor-level and source-level MSE that the processes of losing complexity is temporally slower and spatially restricted for successful inhibition, and is temporally quicker and spatially extensive for unsuccessful inhibition.

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“…This computational tool groups data points according to multiple different timescales to reveal repeated patterns, enabling the theoretical quantification of the complexity of the data using a variety of measures of entropy. MSE can be applied both to physical and physiological data sets; for example, this can be used to measure the complexity of physiological signals during the process of inhibitory control [17]. Higher MSE values signify that the signal is less predictable and information-rich, whereas lower MSE values imply that the time series is more regular and less complex [6,16,18].…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Entropy Analysis of Body Sway for Investigating Balance Ability During Exergame Play Under Different Parameter Settings

Lee

Sun

2015

Entropy

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Abstract:The goal of this study was to investigate the parameters affecting exergame performance using multi-scale entropy analysis, with the aim of informing the design of exergames for personalized balance training. Test subjects' center of pressure (COP) displacement data were recorded during exergame play to examine their balance ability at varying difficulty levels of a balance-based exergame; the results of a multi-scale entropy-based analysis were then compared to traditional COP indicators. For games involving static posture frames, variation in posture frame travel time was found to significantly affect the complexity of both the anterior-posterior (MSE-AP) and medio-lateral (MSE-ML) components of balancing movements. However, in games involving dynamic posture frames, only MSE-AP was found to be sensitive to the variation of parameters, namely foot-lifting speed. Findings were comparable to the COP data published by Sun et al., indicating that the use of complexity data is a feasible means of distinguishing between different parameter sets and of understanding how human design considerations must be taken into account in exergame development. Not only can this method be used as another assessment index in the future, it can also be used in the optimization of parameters within the virtual environments of exergames.

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Revealing the brain's adaptability and the transcranial direct current stimulation facilitating effect in inhibitory control by multiscale entropy

Cited by 75 publications

References 57 publications

Selecting and inhibiting responses: Common cognitive and neural substrates?

Selecting and inhibiting responses: Common cognitive and neural substrates?

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

Multi-Scale Entropy Analysis of Body Sway for Investigating Balance Ability During Exergame Play Under Different Parameter Settings

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