Modulation Of Cognitive Control Research Articles

Working memory capacity preferentially enhances implementation of proactive control.

Previous research has linked working memory capacity (WMC) with enhanced proactive control. However, it remains unclear the extent to which this relationship reflects the influence of WMC on the tendency to engage proactive control, or rather, the ability to implement it. The current study sought to clarify this ambiguity by leveraging the Dual Mechanisms of Cognitive Control (DMCC) version of the AX-CPT task, in which the mode of cognitive control is experimentally manipulated across distinct testing sessions. To adjudicate between competing hypotheses, Bayesian mixed modeling was used to conduct sequential analyses involving two separate data sets. Posterior parameter estimates obtained from the initial analysis were entered as informed priors during the replication analysis to evaluate the influence of new data on previous estimates. Results yielded strong evidence demonstrating that the influence of WMC on proactive control is most robust under experimentally controlled conditions, during which use of proactive control is standardized across participants via explicit training and instruction. Critically, the observed pattern of findings suggests that the relationship between WMC and proactive control may be better characterized as individual differences in the ability to implement proactive control, rather than a more generalized tendency to engage it. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Influences of social and non-social rewards on cognitive control in childhood

The modulation of cognitive control by rewards has long been discussed, but there is scarce evidence of how social and non-social rewards influence cognitive control in childhood, especially in the preschool years. Critically, sociality has often been confounded with other important reward dimensions (e.g., tangibility) in prior studies, hence potentially misestimating the effect of social rewards. Thus, the present study re-examined the effects of social and non-social rewards on cognitive control, particularly on proactive and reactive control engagement during childhood. Thirty 5- to 6-year-olds and thirty 9- to 10-year-olds completed an AX-Continuous Performance Task (AX-CPT) during an online session in three conditions: control, social reward, and non-social (i.e., monetary) reward conditions. Social rewards increased younger and older children’s response accuracy, suggesting greater cognitive control. However, no influence on how children engage cognitive control (i.e., proactively or reactively) was observed. The provision of non-social rewards did not influence cognitive performance in either group of children. When controlling for other reward dimension, we found evidence that social rewards, but not non-social rewards, can promote cognitive control performance in childhood.

Triple Interactions Between the Environment, Brain, and Behavior in Children: An ABCD Study

BackgroundEnvironmental exposures play a crucial role in shaping children's behavioral development. However, the mechanisms by which these exposures interact with brain functional connectivity and influence behavior remain unexplored. MethodsWe investigated the comprehensive environment-brain-behavior triple interactions through rigorous association, prediction, and mediation analyses, while adjusting for multiple confounders. Particularly, we examined the predictive power of brain functional network connectivity (FNC) and 41 environmental exposures for 23 behaviors related to cognitive ability and mental health in 7655 children selected from the Adolescent Brain Cognitive Development (ABCD) Study at both baseline and follow-up. ResultsFNC demonstrated more predictability for cognitive abilities than for mental health, with cross-validation from the UK Biobank study (N = 20,852), highlighting the importance of thalamus and hippocampus in longitudinal prediction, while FNC+environment demonstrated more predictive power than FNC in both cross-sectional and longitudinal prediction of all behaviors, especially for mental health (r = 0.32–0.63). We found that family and neighborhood exposures were common critical environmental influencers on cognitive ability and mental health, which can be mediated by FNC significantly. Healthy perinatal development was a unique protective factor for higher cognitive ability, whereas sleep problems, family conflicts, and adverse school environments specifically increased risk of poor mental health. ConclusionsThis work revealed comprehensive environment-brain-behavior triple interactions based on the ABCD Study, identified cognitive control and default mode networks as the most predictive functional networks for a wide repertoire of behaviors, and underscored the long-lasting impact of critical environmental exposures on childhood development, in which sleep problems were the most prominent factors affecting mental health.

Dynamic structure–function coupling across three major psychiatric disorders

Abstract Background Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure–function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). Methods We quantified the dynamic structure–function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure–function coupling with the topological features of functional networks to examine how the structure–function relationship facilitates brain information communication over time. Results The dynamic structure–function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure–function coupling and the topological features of functional networks are altered in a manner indicative of state specificity. Conclusions These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure–function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Structural brain network degeneration associated with agitation in dementia

AbstractBackgroundAgitation is a behavioral syndrome involving increased motor activity, restlessness, aggressiveness and emotional distress. Its has a 30% prevalence across multiple types of dementia and is associated with negative outcomes, including reduced quality of life, caregiver distress, and mortality. Pharmacological treatment risks serious side effects, including mortality. Understanding brain network topology could provide insights into novel treatment methods.MethodParticipants comprised 600 subjects from 3 existing databases: the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Frontotemporal Lobar Degeneration Neuroimaging Initiative (NIFD) and the Mesulam Center for Cognitive Neurology and Alzheimer’s Disease at Northwestern University. Participants were clinically diagnosed with either behavioral variant frontotemporal dementia (bvFTD), mild cognitive impairment (MCI), dementia of the Alzeheimer type (DAT) or cognitively normal (CN). The Neuropsychiatric Inventory Questionnaire (NPI‐Q) caregiver rating was used to determine whether individuals were agitated or not. Morphometric similarity networks (MSNs) were generated from Freesurfer statistics calculated from T1‐weighted MRIs. 7 surface‐based cortical metrics (e.g. gray matter volume, surface area) were calculated for each of 360 parcels. Pairwise inter‐parcel Pearson correlations of feature vectors were calculated to produce a morphometric similarity matrix for each individual. We calculated sub‐matrices for salience (SN) cognitive control (CCN) and default mode networks (DMN). Brain Connectivity Toolbox calculated transitivity and global efficiency of each network. Metrics were calculated at different thresholds to ensure the results were not threshold‐dependent. We calculated 2 (Agitation present/absent) x 4 (Diagnosis) repeated measures ANCOVAS for transitivity and global efficiency for each network. Covariates were age, sex, race, database, education, ICV, CDR‐SB and days MRI‐NPI‐Q.ResultFor the SN, people with Agitation had significantly lower global efficiency than people without Agitation (Figure 1). There were no significant effects of diagnosis or interaction. For the CCN, people with agitation had significantly lower transitivity than people without Agitation (Figure 2). There were no significant effect of diagnosis or interaction.ConclusionAcross different forms of dementia, Agitation is associated with reduced integration (global efficiency) of the salience network, and reduced segregation (transitivity) of the cognitive control network. Interventions that alter these topological network features may be effective in reducing agitation in dementia, regardless of clinical diagnosis.

Structural brain network degeneration associated with agitation in dementia

AbstractBackgroundAgitation is a behavioral syndrome involving increased motor activity, restlessness, aggressiveness and emotional distress. Its has a 30% prevalence across multiple types of dementia and is associated with negative outcomes, including reduced quality of life, caregiver distress, and mortality. Pharmacological treatment risks serious side effects, including mortality. Understanding brain network topology could provide insights into novel treatment methods.MethodParticipants comprised 600 subjects from 3 existing databases: the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Frontotemporal Lobar Degeneration Neuroimaging Initiative (NIFD) and the Mesulam Center for Cognitive Neurology and Alzheimer’s Disease at Northwestern University.Participants were clinically diagnosed with either behavioral variant frontotemporal dementia (bvFTD), mild cognitive impairment (MCI), dementia of the Alzeheimer type (DAT) or cognitively normal (CN). The Neuropsychiatric Inventory Questionnaire (NPI‐Q) caregiver rating was used to determine whether individuals were agitated or not.Morphometric similarity networks (MSNs) were generated from Freesurfer statistics calculated from T1‐weighted MRIs. 7 surface‐based cortical metrics (e.g. gray matter volume, surface area) were calculated for each of 360 parcels. Pairwise inter‐parcel Pearson correlations of feature vectors were calculated to produce a morphometric similarity matrix for each individual. We calculated sub‐matrices for salience (SN) cognitive control (CCN) and default mode networks (DMN). Brain Connectivity Toolbox calculated transitivity and global efficiency of each network. Metrics were calculated at different thresholds to ensure the results were not threshold‐dependent.We calculated 2 (Agitation present/absent) x 4 (Diagnosis) repeated measures ANCOVAS for transitivity and global efficiency for each network. Covariates were age, sex, race, database, education, ICV, CDR‐SB and days MRI‐NPI‐Q.ResultFor the SN, people with Agitation had significantly lower global efficiency than people without Agitation (Figure 1). There were no significant effects of diagnosis or interaction.For the CCN, people with agitation had significantly lower transitivity than people without Agitation (Figure 2). There were no significant effect of diagnosis or interaction.ConclusionAcross different forms of dementia, Agitation is associated with reduced integration (global efficiency) of the salience network, and reduced segregation (transitivity) of the cognitive control network. Interventions that alter these topological network features may be effective in reducing agitation in dementia, regardless of clinical diagnosis.

Increased regional Hurst exponent reflects response inhibition related neural complexity alterations in pediatric bipolar disorder patients during an emotional Go-Nogo task.

Fractal patterns have been shown to change in resting- and task-state blood oxygen level-dependent signals in bipolar disorder patients. However, fractal characteristics of brain blood oxygen level-dependent signals when responding to external emotional stimuli in pediatric bipolar disorder remain unclear. Blood oxygen level-dependent signals of 20 PBD-I patients and 17 age- and sex-matched healthy controls were extracted while performing an emotional Go-Nogo task. Neural responses relevant to the task and Hurst exponent of the blood oxygen level-dependent signals were assessed. Correlations between clinical indices and Hurst exponent were estimated. Significantly increased activations were found in regions covering the frontal lobe, parietal lobe, temporal lobe, insula, and subcortical nuclei in PBD-I patients compared to healthy controls in contrast of emotional versus neutral distractors. PBD-I patients exhibited higher Hurst exponent in regions that involved in action control, such as superior frontal gyrus, inferior frontal gyrus, inferior temporal gyrus, and insula, with Hurst exponent of frontal orbital gyrus correlated with onset age. The present study exhibited overactivation, increased self-similarity and decreased complexity in cortical regions during emotional Go-Nogo task in patients relative to healthy controls, which provides evidence of an altered emotional modulation of cognitive control in pediatric bipolar disorder patients. Hurst exponent may be a fractal biomarker of neural activity in pediatric bipolar disorder.

Brain Engagement During a Cognitive Flexibility Task Relates to Academic Performance in English Learners

ABSTRACTEnglish Learners (ELs), students from non‐English‐speaking backgrounds, are a fast‐growing, understudied, group of students in the U.S. with unique learning challenges. Cognitive flexibility—the ability to switch between task demands with ease—may be an important factor in learning for ELs as they have to manage learning in their non‐dominant language and access knowledge in multiple languages. We used functional MRI to measure cognitive flexibility brain activity in a group of Hispanic middle school ELs (N = 63) and related it to their academic skills. We found that brain engagement during the cognitive flexibility task was related to both out‐of‐scanner reading and math measures. These relationships were observed across the brain, including in cognitive control, attention, and default mode networks. This work suggests the real‐world importance of cognitive flexibility for adolescent ELs, where individual differences in brain engagement were associated with educational outcomes.

Aperiodic neural activity reflects metacontrol.

Higher-level cognitive functions are mediated via complex oscillatory activity patterns and its analysis is dominating cognitive neuroscience research. However, besides oscillatory (period) activity, also aperiodic activity constitutes neural dynamics, but its relevance for higher-level cognitive functions is only beginning to be understood. The present study examined whether the broadband EEG aperiodic activity reflects principles of metacontrol. Metacontrol conceptualizes whether it is more useful to engage in more flexible processing of incoming information or to shield cognitive processes from incoming information (persistence-heavy processing). We examined EEG and behavioral data from a sample of n = 191 healthy participants performing a Simon Go/NoGo task that can be assumed to induce different metacontrol states (persistence-biased vs. flexibility-biased). Aperiodic activity was estimated using the FOOOF toolbox in the EEG power spectrum. There was a higher aperiodic exponent and offset in NoGo trials compared with Go trials, in incongruent (Go) trials compared with congruent (Go) trials. Thus, aperiodic activity increases during persistence-heavy processing, but decreases during flexibility-heavy processing. These findings link aperiodic features of the EEG signal and concepts describing the dynamics of how cognitive control modes are applied. Therefore, the study substantially extends the importance of aperiodic activity in understanding cognitive functions.

Prefrontal transcranial direct current stimulation over the right prefrontal cortex reduces proactive and reactive control performance towards emotional material in healthy individuals

The prefrontal cortex plays a crucial role in cognitive processes, both during anticipatory and reactive modes of cognitive control. Transcranial Direct Current Stimulation (tDCS) can modulate these cognitive resources. However, there is a lack of research exploring the impact of tDCS on emotional material processing in the prefrontal cortex, particularly in regard to proactive and reactive modes of cognitive control. In this study, 35 healthy volunteers underwent both real and sham tDCS applied to the right prefrontal cortex in a counterbalanced order, and then completed the Cued Emotion Control Task (CECT). Pupil dilation, a measure of cognitive resource allocation, and behavioral outcomes, such as reaction time and accuracy, were collected. The results indicate that, as compared to sham stimulation, active right-sided tDCS reduced performance and resource allocation in both proactive and reactive modes of cognitive control. These findings highlight the importance of further research on the effects of tDCS applied to the right prefrontal cortex on cognitive engagement, particularly for clinical trials utilizing the present electrode montage in combination with cognitive interventions.

A deep residual model for characterization of 5D spatiotemporal network dynamics reveals widespread spatiodynamic changes in schizophrenia.

Schizophrenia is a severe brain disorder with serious symptoms including delusions, disorganized speech, and hallucinations that can have a long-term detrimental impact on different aspects of a patient's life. It is still unclear what the main cause of schizophrenia is, but a combination of altered brain connectivity and structure may play a role. Neuroimaging data has been useful in characterizing schizophrenia, but there has been very little work focused on voxel-wise changes in multiple brain networks over time, despite evidence that functional networks exhibit complex spatiotemporal changes over time within individual subjects. Recent studies have primarily focused on static (average) features of functional data or on temporal variations between fixed networks; however, such approaches are not able to capture multiple overlapping networks which change at the voxel level. In this work, we employ a deep residual convolutional neural network (CNN) model to extract 53 different spatiotemporal networks each of which captures dynamism within various domains including subcortical, cerebellar, visual, sensori-motor, auditory, cognitive control, and default mode. We apply this approach to study spatiotemporal brain dynamism at the voxel level within multiple functional networks extracted from a large functional magnetic resonance imaging (fMRI) dataset of individuals with schizophrenia (N = 708) and controls (N = 510). Our analysis reveals widespread group level differences across multiple networks and spatiotemporal features including voxel-wise variability, magnitude, and temporal functional network connectivity in widespread regions expected to be impacted by the disorder. We compare with typical average spatial amplitude and show highly structured and neuroanatomically relevant results are missed if one does not consider the voxel-wise spatial dynamics. Importantly, our approach can summarize static, temporal dynamic, spatial dynamic, and spatiotemporal dynamics features, thus proving a powerful approach to unify and compare these various perspectives. In sum, we show the proposed approach highlights the importance of accounting for both temporal and spatial dynamism in whole brain neuroimaging data generally, shows a high-level of sensitivity to schizophrenia highlighting global but spatially unique dynamics showing group differences, and may be especially important in studies focused on the development of brain-based biomarkers.

Event Segmentation Enhances Older Adults’ Reactive Cognitive Control Bias

ABSTRACT The present study examined the effect of event segmentation on cognitive control mode use in a sample of older adults (N = 30; Mage  = 73, SDage  = 4.75) using a modified AX-Continuous Performance Test (AX-CPT). This task included a perceptual event boundary between each cue and its forthcoming probe by means of a spatial shift across the left and right side of the display. Past research showed that young adults’ existing proactive control bias could be enhanced in an event segmented AX-CPT relative to their performance on a standard AX-CPT. For older adults who adopt reactive control by default, the event boundary was expected to impede cue-reactivation during probe presentation, and thus further enhance their existing reactive control bias. To examine this, older adults were tested with a standard and an event segmented AX-CPT in two blocks, with error rates revealing a shift toward greater reactive control use in the event segmented relative to the standard AX-CPT. Findings supported our hypothesis that placing a spatial event boundary between each cue and forthcoming probe would further enhance older adults’ reactive control bias. This study contributes to the sparse but growing literature on the effects of task-specific manipulations on cognitive control use. The results are discussed in light of the dual mechanisms of control framework and the event horizon model.

Increased cortical thickness in nodes of the cognitive control and default mode networks in psychosis of epilepsy

ObjectiveTo explore the cortical morphological associations of the psychoses of epilepsy. MethodsPsychosis of epilepsy (POE) has two main subtypes - postictal psychosis and interictal psychosis. We used automated surface-based analysis of magnetic resonance images to compare cortical thickness, area, and volume across the whole brain between: (i) all patients with POE (n = 23) relative to epilepsy-without psychosis controls (EC; n = 23), (ii) patients with interictal psychosis (n = 10) or postictal psychosis (n = 13) relative to EC, and (iii) patients with postictal psychosis (n = 13) relative to patients with interictal psychosis (n = 10). ResultsPOE is characterised by cortical thickening relative to EC, occurring primarily in nodes of the cognitive control network; (rostral anterior cingulate, caudal anterior cingulate, middle frontal gyrus), and the default mode network (posterior cingulate, medial paracentral gyrus, and precuneus). Patients with interictal psychosis displayed cortical thickening in the left hemisphere in occipital and temporal regions relative to EC (lateral occipital cortex, lingual, fusiform, and inferior temporal gyri), which was evident to a lesser extent in postictal psychosis patients. There were no significant differences in cortical thickness, area, or volume between the postictal psychosis and EC groups, or between the postictal psychosis and interictal psychosis groups. However, prior to correction for multiple comparisons, both the interictal psychosis and postictal psychosis groups displayed cortical thickening relative to EC in highly similar regions to those identified in the POE group overall. SignificanceThe results show cortical thickening in POE overall, primarily in nodes of the cognitive control and default mode networks, compared to patients with epilepsy without psychosis. Additional thickening in temporal and occipital neocortex implicated in the dorsal and ventral visual pathways may differentiate interictal psychosis from postictal psychosis. A novel mechanism for cortical thickening in POE is proposed whereby normal synaptic pruning processes are interrupted by seizure onset.

Timing characteristics of reactive and proactive emotion regulation

The dual mechanisms of control (DMC) framework is important for portraying two temporally distinct modes of cognitive control. In parallel with this model, understanding emotion regulation (ER) from a dual-mechanism perspective becomes plausible since cognitive control is a crucial element of ER. The present study characterized reactive and proactive ER based on a dual mechanisms framework to identify their distinct temporal dynamics using electroencephalography (EEG) recordings. The reappraisal cue, compared with the watch-cue and no-cue conditions, evoked a larger fronto-central P3a magnitude, suggesting that participants could adaptively distribute their attention resources to prepare for strategy use. To track the cognitive effort that supports the ER process, we measured the frontal late positive potential (LPP). The results indicated that the reactive group, compared with the proactive group, used more effort to complete the reappraisal task when participants were subjected to decreased negative-emotional experiences to the same degree. Furthermore, decoding analysis showed that proactive ER starts earlier than reactive ER. These findings highlight the advantages of proactive ER. Further understanding of the modes of ER will help elucidate the control mechanisms underlying ER, which can then be applied to a variety of conditions, such as alcoholism, gambling, and drug addiction, to avert self-regulation failures caused by negative emotions.

The Dual Mechanisms of Cognitive Control (DMCC) project: Validation of an online behavioural task battery.

Cognitive control serves a crucial role in human higher mental functions. The Dual Mechanisms of Control theoretical framework provides a unifying account that decomposes cognitive control into two qualitatively distinct mechanisms-proactive control and reactive control. Here, we describe the Dual Mechanisms of Cognitive Control (DMCC) task battery, which was developed to probe cognitive control modes in a theoretically targeted manner, along with detailed descriptions of the experimental manipulations used to encourage shifts to proactive or reactive mode in each of four prototypical domains of cognition: selective attention, context processing, multitasking, and working memory. We present results from this task battery, conducted from a large (N > 100), online sample that rigorously evaluates the group effects of these manipulations in primary indices of proactive and reactive control, establishing the validity of the battery in providing dissociable yet convergent measures of the two cognitive control modes. The DMCC battery may be a useful tool for the research community to examine cognitive control in a theoretically targeted manner across different individuals and groups.

Cingulate-Prefrontal Connectivity During Dynamic Cognitive Control Mediates Association Between p Factor and Adaptive Functioning in a Transdiagnostic Pediatric Sample

BackgroundCovariation among psychiatric symptoms is being actively pursued for transdiagnostic dimensions of psychopathology with predictive utility. A superordinate dimension, the p factor, reflects overall psychopathology burden and has support from genetic and neuroimaging correlates. However, the neurocognitive correlates that link an elevated p factor to maladaptive outcomes are unknown. We tested the mediating potential of dynamic adjustments in cognitive control rooted in functional connections anchored by the dorsal anterior cingulate cortex (dACC) in a transdiagnostic pediatric sample. MethodsA multiple mediation model tested the association between the p factor (derived by principal component analysis of Child Behavior Checklist syndrome scales) and outcome measured with the Vineland Adaptive Behavior Scale-II in 89 children ages 8 to 13 years (23 female) with a variety of primary neurodevelopmental diagnoses who underwent functional magnetic resonance imaging during a socioaffective Stroop-like task with eye gaze as distractor. Mediators included functional connectivity of frontoparietal- and salience network–affiliated dACC seeds during conflict adaptation. ResultsHigher p factor scores were related to worse adaptive functioning. This effect was partially mediated by conflict adaptation–dependent functional connectivity between the frontoparietal network–affiliated dACC seed and the right dorsolateral prefrontal cortex. Post hoc follow-up indicated that the p factor was related to all Vineland Adaptive Behaviors Scale-II domains; the association was strongest for socialization followed by daily living skills and then communication. Mediation results remained significant for socialization only. ConclusionsHigher psychopathology burden was associated with worse adaptive functioning in early adolescence. This association was mediated by weaker dACC–dorsolateral prefrontal cortex functional connectivity underlying modulation of cognitive control in response to contextual contingencies. Our results contribute to the identification of transdiagnostic and developmentally relevant neurocognitive endophenotypes of psychopathology.

Brain responses in aggression-prone individuals: A systematic review and meta-analysis of functional magnetic resonance imaging (fMRI) studies of anger- and aggression-eliciting tasks

Reactive aggression in response to perceived threat or provocation is part of humans' adaptive behavioral repertoire. However, high levels of aggression can lead to the violation of social and legal norms. Understanding brain function in individuals with high levels of aggression as they process anger- and aggression-eliciting stimuli is critical for refining explanatory models of aggression and thereby improving interventions. Three neurobiological models of reactive aggression – the limbic hyperactivity, prefrontal hypoactivity, and dysregulated limbic-prefrontal connectivity models – have been proposed. However, these models are based on neuroimaging studies involving mainly non-aggressive individuals, leaving it unclear which model best describes brain function in those with a history of aggression.We conducted a systematic literature search (PubMed and Psycinfo) and Multilevel Kernel Density meta-analysis (MKDA) of nine functional magnetic resonance imaging (fMRI) studies (eight included in the between-group analysis [i.e., aggression vs. control groups], five in the within-group analysis). Studies examined brain responses to tasks putatively eliciting anger and aggression in individuals with a history of aggression alone and relative to controls.Individuals with a history of aggression exhibited greater activity in the superior temporal gyrus and in regions comprising the cognitive control and default mode networks (right posterior cingulate cortex, precentral gyrus, precuneus, right inferior frontal gyrus) during reactive aggression relative to baseline conditions. Compared to controls, individuals with a history of aggression exhibited increased activity in limbic regions (left hippocampus, left amygdala, left parahippocampal gyrus) and temporal regions (superior, middle, inferior temporal gyrus), and reduced activity in occipital regions (left occipital cortex, left calcarine cortex).These findings lend support to the limbic hyperactivity model in individuals with a history of aggression, and further indicate altered temporal and occipital activity in anger- and aggression-eliciting conditions involving face and speech processing.

P341. Acute Ketamine Modulates Cognitive Control Network Activity During Cognitive Inhibition: Evidence From a Mechanistic Trial

The neural mechanisms underlying the effect of subanesthetic ketamine, a rapidly acting antidepressant, on modulation of cognitive control remain controversial. We addressed this issue in a mechanistic study assessing real-time ketamine effects with acute post-infusion imaging.

P 33 Changes in functional connectivity relate to modulation of cognitive control by subthalamic stimulation

Introduction Using cognitive control, humans can flexibly influence behavior based on set goals, which includes overriding impulses by inhibiting automatic responses in a conflicting environment. The basal ganglia have been hypothesized as an integral part in a cortico-subcortical network that modulates inhibitory control in both motor and non-motor domains. Subthalamic (STN) deep brain stimulation (DBS) in Parkinson‘s disease (PD) patients not only improves kinematic parameters of movement but also modulates cognitive control in the motor and non-motor domain, especially in situations of high conflict. Materials & Methods During DBS ON and OFF conditions, we conducted a visuomotor task in 14 PD patients who previously underwent resting-state functional MRI (rs-fMRI) acquisitions DBS ON and OFF. In the task, participants had to move a cursor with a pen on a digital tablet either towards (automatic condition) or in the opposite direction (controlled condition) of a target. Behaviorally, the first main outcome parameter was reaction time, and specifically, the difference in reaction time between automatic and controlled condition that reflects the additional time associated with engagement of cognitive control. Furthermore, average movement velocity ON vs. OFF DBS in automatic and controlled trials was assessed. Analysis of the imaging data focused on STN DBS induced modulation of rs-fMRI connectivity as a function of changes in behavior ON vs. OFF DBS and was estimated using link-wise network-based statistics within an a-priori defined network parcellation with 7 bihemispheric regions of interest (STN, internal/external pallidum (GPi and GPe), striatum, motor thalamus (VAn, VAp, VLd/VLv nuclei combined), motor and premotor cortices, supplementary motor area (SMA) and pre-SMA). Results Behavioral results showed diminished reaction time adaptation under DBS, i.e., PD patients ON DBS slowed down significantly less in the controlled condition compared to the automatic condition than they did OFF DBS. Additionally, pen-to-target movement velocity was increased under DBS in both automatic and controlled condition. Resting-state imaging data analysis revealed that DBS-induced reaction time reduction was associated with attenuated functional connectivity between cortical motor areas, basal ganglia and thalamus. On the other hand, increased movement velocity ON DBS was associated with stronger pallido-thalamic connectivity. Conclusion These findings suggest that DBS-induced decoupling of a motor cortico-basal ganglia network underlies impaired inhibitory control in PD patients undergoing subthalamic DBS and highlight the concept of functional network modulation through DBS. Understanding the connectivity basis of nonmotor changes in PD patients treated with DBS has a high clinical relevance, since network modulation may be fine-tuned with advancing therapeutic developments such as adaptive stimulation.

Reduced modulation of BOLD variability as a function of cognitive load in healthy aging

BOLD variability, which measures moment-to-moment fluctuations in brain signal, is sensitive to age differences in cognitive performance. However, the effect of aging on BOLD variability in the context of different cognitive demands is still unclear. The current study examined how aging affects brain variability across cognitive loads and the contribution of BOLD variability to working memory abilities. Participants (N = 149, ages 20‒86) completed an fMRI n-back paradigm with 3 loads and 10-minute resting state scan. We found that BOLD variability was greater during rest compared to task and decreased even further as n-back load increased. Older age was associated with smaller load-related modulations of BOLD variability in default mode and fronto-parietal control networks. Increased variability in default mode, fronto-parietal control, and limbic regions and decreased variability in sensori-motor regions during the n-back task was associated with better working memory performance, regardless of age. Our findings suggest that working memory reductions in older ages are related to failure of core cognitive control and default mode regions to modulate dynamic range of activity in the face of increased demands.