Functional networks for cognitive control in a stop signal task: independent component analysis.
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ABSTRACT:
SUBMITTER: Zhang S
PROVIDER: S-EPMC3674850 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cognitive control is a critical executive function. Many studies have combined general linear modeling and the stop signal task (SST) to delineate the component processes of cognitive control. For instance, by contrasting stop success (SS) and stop error (SE) trials in the SST, investigators examined regional responses to stop signal inhibition. In contrast to this parameterized approach, independent component analysis (ICA) elucidates brain networks subserving cognitive control. In our earlier work of 59 adults performing the SST during fMRI, we characterized six independent components (ICs). However, none of these ICs correlated with stop signal performance, raising questions about their behavioral validity. Here, in a larger sample (n = 100), we identified and explored 23 ICs for correlation with the stop signal reaction time (SSRT), a measure of the efficiency of response inhibition. At a corrected threshold (P < 0.0005), a paracentral lobule-midcingulate network and a left inferior parietal-supplementary motor-somatomotor network showed a positive correlation between SE beta weight and SSRT. In contrast, a midline cerebellum-thalamus-pallidum network showed a negative correlation between SE beta weight and SSRT. These findings suggest that motor preparation and execution prolongs the SSRT, likely via an interaction between the go and stop processes as suggested by the race model. Behaviorally, consistent with this hypothesis, the difference in G and SE reaction times is positively correlated with SSRT across subjects. These new results highlight the importance of cognitive motor regions in response inhibition and support the utility of ICA in uncovering functional networks for cognitive control in the SST.
| S-EPMC4545723 | biostudies-literature
Project description:Men and women show important differences in clinical conditions in which deficits in cognitive control are implicated. We used functional magnetic resonance imaging to examine gender differences in the neural processes of cognitive control during a stop-signal task. We observed greater activation in men, compared to women, in a wide array of cortical and sub-cortical areas, during stop success (SS) as compared to stop error (SE). Conversely, women showed greater regional brain activation during SE > SS, compared to men. Furthermore, compared to women, men engaged the right inferior parietal lobule to a greater extent during post-SE go compared to post-go go trials. Women engaged greater posterior cingulate cortical activation than men during post-SS slowing in go trial reaction time (RT) but did not differ during post-SE slowing in go trial RT. These findings extended our previous results of gender differences in regional brain activation during response inhibition. The results may have clinical implications by, for instance, helping initiate studies to understand why women are more vulnerable to depression while men are more vulnerable to impulse control disorders.
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Project description:BACKGROUND:The P3 component of the event-related potential (ERP) has been particularly useful in alcohol research for identifying endophenotypes of alcohol-use disorder (AUD) risk in sober subjects. However, practice and/or fatigue reduce P3 amplitude, limiting the ability to ascertain acute and adaptive effects of alcohol exposure. Here, we report acute alcohol effects on P3 amplitude and latency using an adaptive stop signal task (aSST). METHODS:One hundred forty-eight non-dependent moderate to heavy social drinkers, ages 21 to 27, participated in two single-blind, alcohol or placebo, counterbalanced sessions approximately 1 week apart. During each session, subjects performed an adaptive stop signal task (aSST) at 1) baseline, 2) upon reaching the target 60 mg/dL breath alcohol concentration or at the equivalent time during the placebo session, and 3) approximately 135 min later while the breath alcohol concentration was clamped. Here, we report on differences between baseline and first subsequent measurements across the experimental sessions. During each aSST run, the stop signal delay (SSD, the time between stop and go signals) adjusted trial-by-trial, based on the subject's performance. RESULTS:The aSST reliably generated a STOP P3 component that did not change significantly with repeated task performance. The pre-infusion SSD distribution was bimodal, with mean values several hundred msec apart (FAST: 153 msec and SLOW: 390 msec). This suggested different response strategies: FAST SSD favoring "going" over "stopping", and SLOW SSD favoring "stopping" over "going". Exposure to alcohol at 60 mg/dL differentially affected the amplitude and latency of the STOP P3 according to SSD group. Alcohol significantly reduced P3 amplitude in the SLOW SSD compared to the FAST SSD group, but significantly increased P3 latency in the FAST SSD compared to the SLOW SSD group. CONCLUSIONS:The aSST is a robust and sensitive task for detecting alcohol-induced changes in inhibition behavior as measured by the P3 component in a within-subject design. Alcohol was associated with P3 component changes, which varied by SSD group, suggesting a differential effect as a function of task strategy. Overall, the data support the potential utility of the aSST in the detection of alcohol response-related AUD risk.
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Project description:Each bacterial species has specific regulatory systems to control physiology, adaptation, and host interactions. One challenge posed by this diversity is to define the evolving gene regulatory networks. This study aims to characterise two-component systems (TCS) in Streptococcus gagalactiae, the main cause of neonatal meningitis. Here we demonstrate signal-independent activation of signalling pathways by systematically targeting the conserved mechanism of phosphatase activity of the histidine kinases of the two main TCS families. Transcriptomic analysis resolves most pathways with high resolution, encompassing specialized, connected, and global regulatory systems. The activated network notably reveals the connection between CovRS and SaeRS signaling through the adhesin PbsP, linking the main regulators of host interactions to balance pathogenicity. Additionally, constitutive activation of the BceRS system reveals its role in cell envelope homeostasis beyond antimicrobial resistance. Overall, this study demonstrates the generalizability and versatility of TCS genetic activation to uncover regulatory logics and biological processes.
2024-03-25 | GSE261394 | GEO
Project description:Restrictive and repetitive behavior in autism may be related to deficits in cognitive control. Here, we aimed to assess functional connectivity during a cognitive control task and compare brain network activity and connectivity in children with autism spectrum disorders (ASD) and typically developing children using a multivariate data-driven approach. 19 high-functioning boys with ASD and 19 age-matched typically developing boys were included in this study. Functional magnetic resonance imaging was performed at 3T during the performance of a cognitive control task (go/no-go paradigm). Functional networks were identified using independent component analysis. Network activity and connectivity was compared between groups and correlated with clinical measures of rigid behavior using multivariate analysis of covariance. We found no differences between the groups in task performance or in network activity. Power analysis indicated that, if this were a real difference, it would require nearly 800 subjects to show group differences in network activity using this paradigm. Neither were there correlations between network activity and rigid behavior. Our data do not provide support for the presence of deficits in cognitive control in children with ASD, or the functional networks supporting this ability.
| S-EPMC4141973 | biostudies-literature
Project description:Spontaneous fluctuations in MRI signals from gray matter (GM) in the brain are interpreted as originating from variations in neural activity, and their inter-regional correlations may be analyzed to reveal functional connectivity. However, most studies of intrinsic neuronal activity have ignored the spontaneous fluctuations that also arise in white matter (WM). In this work, we explore spontaneous fluctuations in resting state MRI signals in WM based on spatial independent component analyses (ICA), a data-driven approach that separates signals into independent sources without making specific modeling assumptions. ICA has become widely accepted as a valuable approach for identifying functional connectivity within cortex but has been rarely applied to derive equivalent structures within WM. Here, BOLD signal changes in WM of a group of subjects performing motor tasks were first detected using ICA, and a spatial component whose time course was consistent with the task was found, demonstrating the analysis is sensitive to evoked BOLD signals in WM. Secondly, multiple spatial components were derived by applying ICA to identify those voxels in WM whose MRI signals showed similar temporal behaviors in a resting state. These functionally-related structures are grossly symmetric and coincide with corresponding tracts identified from diffusion MRI. Finally, functional connectivity was quantified by calculating correlations between pairs of structures to explore the synchronicity of resting state BOLD signals across WM regions, and the experimental results revealed that there exist two distinct groupings of functional correlations in WM tracts at rest. Our study provides further insights into the nature of activation patterns, functional responses and connectivity in WM, and support previous suggestions that BOLD signals in WM show similarities with cortical activations and are characterized by distinct underlying structures in tasks and at rest.
| S-EPMC7736513 | biostudies-literature
Project description:Signal-independent activation reveals two-component regulatory networks.
| PRJNA1086844 | ENA
Project description:Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).
| S-EPMC5375118 | biostudies-literature
Project description:BackgroundGamification in mental health could increase training adherence, motivation, and transfer effects, but the external validity of gamified tasks is unclear. This study documents that gamified task variants can show preserved associations between markers of behavioral deficits and health-related variables. We draw on the inhibitory control deficit in overweight populations to investigate effects of gamification on performance measures in a web-based experimental task.ObjectiveThis study tested whether associations between inhibitory control and overweight were preserved in a gamified stop-signal task (SST).MethodsTwo versions of an adaptive SST were developed and tested in an online experiment. Participants (n=111) were randomized to 1 of the 2 task variants and completed a series of questionnaires along with either the gamified SST or a conventional SST. To maximize its possible effects on participants' inhibitory control, the gamified SST included multiple game elements in addition to the task itself and the stimuli. Both variants drew on the identical core mechanics, but the gamified variant included an additional narrative, graphical theme, scoring system with visual and emotional feedback, and the presence of a companion character. In both tasks, food and neutral low-poly stimuli were classified based on their color tone (go trials), but responses were withheld in 25% of the trials (stop trials). Mean go reaction times and stop-signal reaction times (SSRT) were analyzed as measures of performance and inhibitory control.ResultsParticipants in the gamified SST had longer reaction times (803 [SD 179] ms vs 607 [SD 90] ms) and worse inhibitory control (SSRT 383 [SD 109] ms vs 297 [SD 45] ms). The association of BMI with inhibitory control was relatively small (r=.155, 95% CI .013-.290). Overweight participants had longer reaction times (752 [SD 217] ms vs 672 [SD 137] ms) and SSRTs (363 [SD 116] ms vs 326 [SD 77] ms). Gamification did not interact with the effect of overweight on mean performance or inhibitory control. There were no effects of gamification on mood and user experience, despite a negative effect on perceived efficiency.ConclusionsThe detrimental effects of heightened BMI on inhibitory control were preserved in a gamified version of the SST. Overall, the effects of overweight were smaller than in previously published web-based and laboratory studies. Gamification elements can impact behavioral performance, but gamified tasks can still assess inhibitory control deficits. Although our results are promising, according validations may differ for other types of behavior, gamification, and health variables.
| S-EPMC8092187 | biostudies-literature
Project description:Response inhibition is an essential control function necessary to adapt one's behavior. This key cognitive capacity is assumed to be dependent on the prefrontal cortex and basal ganglia. It is unresolved whether varying inhibitory demands engage different control mechanisms or whether a single motor inhibitory mechanism is involved in any situation. We addressed this question by comparing electrophysiological activity in conditions that require stopping a response to conditions that require switching to an alternate response. Analyses of electrophysiological data obtained from stop-signal tasks are complicated by overlapping stimulus-related activity that is distributed over frontal and parietal cortical recording sites. Here, we applied Laplacian transformation and independent component analysis (ICA) to overcome these difficulties. Participants were faster in switching compared to stopping a response, but we did not observe differences in neural activity between these conditions. Both stop- and change-trials Laplacian transformed ERPs revealed a comparable bilateral parieto-occipital negativity around 180 ms and a frontocentral negativity around 220 ms. ICA results suggested an inhibition-related frontocentral component which was characterized by a negativity around 200 ms with a likely source in anterior cingulate cortex. The data provide support for the importance of posterior mediofrontal areas in inhibitory response control and are consistent with a common neural pathway underlying stopping and changing of a motor response. The methodological approach proved useful to distinguish frontal and parietal sources despite similar timing and the ICA approach allowed assessment of single-trial data with respect to behavioral data.
| S-EPMC4529397 | biostudies-literature