Neurofibromin regulates corticostriatal inhibitory networks during working memory performance.
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ABSTRACT:
SUBMITTER: Shilyansky C
PROVIDER: S-EPMC2919968 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Convergent evidence suggests that corticostriatal interactions act as a gate to select the input to working memory (WM). However, not all information in WM is relevant for behavior simultaneously. For this reason, a second "output gate" might advantageously govern which contents of WM influence behavior. Here, we test whether frontostriatal circuits previously implicated in input gating also support output gating during selection from WM. fMRI of a hierarchical rule task with dissociable input and output gating demands demonstrated greater lateral prefrontal cortex (PFC) recruitment and frontostriatal connectivity during output gating. Moreover, PFC and striatum correlated with distinct behavioral profiles. Whereas PFC recruitment correlated with mean efficiency of selection from WM, striatal recruitment and frontostriatal interactions correlated with its reliability, as though such dynamics stochastically gate WM's output. These results support the output gating hypothesis, suggesting that contextual representations in PFC influence striatum to select which information in WM drives responding.
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Project description:Impairment of working memory (WM) performance in schizophrenia patients (SZ) is well-established. Compared to healthy controls (HC), SZ patients show aberrant blood oxygen level dependent (BOLD) activations and disrupted functional connectivity during WM performance. In this study, we examined the small-world network metrics computed from functional magnetic resonance imaging (fMRI) data collected as 35 HC and 35 SZ performed a Sternberg Item Recognition Paradigm (SIRP) at three WM load levels. Functional connectivity networks were built by calculating the partial correlation on preprocessed time courses of BOLD signal between task-related brain regions of interest (ROIs) defined by group independent component analysis (ICA). The networks were then thresholded within the small-world regime, resulting in undirected binarized small-world networks at different working memory loads. Our results showed: 1) at the medium WM load level, the networks in SZ showed a lower clustering coefficient and less local efficiency compared with HC; 2) in SZ, most network measures altered significantly as the WM load level increased from low to medium and from medium to high, while the network metrics were relatively stable in HC at different WM loads; and 3) the altered structure at medium WM load in SZ was related to their performance during the task, with longer reaction time related to lower clustering coefficient and lower local efficiency. These findings suggest brain connectivity in patients with SZ was more diffuse and less strongly linked locally in functional network at intermediate level of WM when compared to HC. SZ show distinctly inefficient and variable network structures in response to WM load increase, comparing to stable highly clustered network topologies in HC.
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Project description:The aim was to investigate brain network function during working memory (WM) task performance in patients with uncomplicated mild traumatic brain injury (mTBI) in the sub-acute phase post-injury. We were particularly interested in differences between patients with (PCC-present) and without post-concussive complaints (PCC-absent). Fifty-two patients and twenty healthy controls (HCs) (matched for age, sex, education and handedness) were included. Two patient groups were created based on reported post-concussive complaints at two weeks post-injury: PCC-present (n = 32) and PCC-absent (n = 20). Functional MRI scans were made at approximately four weeks post-injury. Participants performed an n-back task consisting of three conditions (0-, 1- and 2-back) with increasing difficulty. General linear model analysis was performed to investigate activation patterns. Independent component analysis was used to identify brain networks. The frontal executive network (FEN), frontoparietal network (FPN) and default mode network (DMN) were selected for further analyses based on their highest task-relatedness. Task accuracy and reaction times were similar for patients with mTBI and HCs. During high WM load (2-vs.0-back contrast), mTBI patients exhibited lower activation within the medial prefrontal cortex compared to HCs. No differences were found between PCC-present and PCC-absent patients. Regarding network function, PCC-absent patients showed stronger deactivation of the DMN compared to PCC-present patients and HCs, especially during difficult task conditions. Furthermore, functional connectivity between the DMN and FEN was lower in PCC-absent patients compared to PCC-present patients. Interestingly, network function did not differ between PCC-present patients and HCs, suggesting that non-injury related factors may underlie post-concussive complaints after mTBI.
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Project description:The functional network of the brain continually adapts to changing environmental demands. The consequence of behavioral automation for task-related functional network architecture remains far from understood. We investigated the neural reflections of behavioral automation as participants mastered a dual n-back task. In four fMRI scans equally spanning a 6-week training period, we assessed brain network modularity, a substrate for adaptation in biological systems. We found that whole-brain modularity steadily increased during training for both conditions of the dual n-back task. In a dynamic analysis,we found that the autonomy of the default mode system and integration among task-positive systems were modulated by training. The automation of the n-back task through training resulted in non-linear changes in integration between the fronto-parietal and default mode systems, and integration with the subcortical system. Our findings suggest that the automation of a cognitively demanding task may result in more segregated network organization.
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Project description:Excessive brain iron negatively affects working memory and related processes but the impact of cortical iron on task-relevant, cortical brain networks is unknown. We hypothesized that high cortical iron concentration may disrupt functional circuitry within cortical networks supporting working memory performance. Fifty-five healthy older adults completed an N-Back working memory paradigm while functional magnetic resonance imaging (fMRI) was performed. Participants also underwent quantitative susceptibility mapping (QSM) imaging for assessment of non-heme brain iron concentration. Additionally, pseudo continuous arterial spin labeling scans were obtained to control for potential contributions of cerebral blood volume and structural brain images were used to control for contributions of brain volume. Task performance was positively correlated with strength of task-based functional connectivity (tFC) between brain regions of the frontoparietal working memory network. However, higher cortical iron concentration was associated with lower tFC within this frontoparietal network and with poorer working memory performance after controlling for both cerebral blood flow and brain volume. Our results suggest that high cortical iron concentration disrupts communication within frontoparietal networks supporting working memory and is associated with reduced working memory performance in older adults.
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Project description:BACKGROUND:Mounting evidence suggests that autism is a network disorder, characterized by atypical brain connectivity, especially in the context of high level cognitive processes such as working memory (WM). Accordingly, atypical WM processes have been related to the social and cognitive deficits observed in children with autism spectrum disorder (ASD). METHODS:We used magnetoencephalography (MEG) to investigate connectivity differences during a high memory load (2-back) WM task between 17 children with ASD and 20 age-, sex-, and IQ-matched controls. RESULTS:We identified reduced inter-regional alpha-band (9-15 Hz) phase synchronization in children with ASD during the WM task. Reduced WM-related brain synchronization encompassed fronto-temporal networks (ps < 0.04 corrected) previously associated with challenging high-level conditions (i.e. the left insula and the anterior cingulate cortex (ACC)) and memory encoding and/or recognition (i.e. the right middle temporal gyrus and the right fusiform gyrus). Additionally, we found that reduced connectivity processes related to the right fusiform were correlated with the severity of symptoms in children with ASD, suggesting that such atypicalities could be directly related to the behavioural deficits observed. DISCUSSION:This study provides new evidence of atypical long-range synchronization in children with ASD in fronto-temporal areas that crucially contribute to challenging WM tasks, but also emotion regulation and social cognition processes. Thus, these results support the network disorder hypothesis of ASD and argue for a specific pathophysiological contribution of brain processes related to working memory and executive functions on the symptomatology of autism.
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Project description:Previous functional neuroimaging studies on executive function suggested multiple functionally aberrant cortical regions in patients with Huntington's disease (HD). However, little is known about the neural mechanisms of working memory (WM) function in this patient population. The objective of this study was to investigate the functional neuroanatomy of WM in HD patients. We used event-related functional magnetic resonance imaging and a parametric verbal WM task to investigate cerebral function during WM performance in 16 healthy control subjects and 12 mild to moderate stage HD patients. We excluded incorrectly performed trials to control for potential accuracy-related activation confounds. Voxel-based morphometry (VBM) was used to control for confounding cortical and subcortical atrophy. We found that HD patients were slower and less accurate than healthy controls across all WM load levels. In addition, HD patients showed lower activation in the left dorso- and ventrolateral prefrontal cortex, the left inferior parietal cortex, the left putamen, and the right cerebellum at high WM load levels only. VBM revealed gray matter differences in the bilateral caudate nucleus and the thalamus, as well as in inferior parietal and right lateral prefrontal regions. However, volumetric abnormalities in the patient group did not affect the activation differences obtained during WM task performance. These findings demonstrate that WM-related functional abnormalities in HD patients involve distinct WM network nodes associated with cognitive control and subvocal rehearsal. Moreover, aberrant cortical function in HD patients may occur in brain regions, which are relatively well preserved in terms of brain atrophy.
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Project description:Emotional intelligence (EI) is the ability to perceive, use, understand, and regulate emotions. Higher scores on this ability measured through performance tests (but no through self-reports) appears to be related to better performance on "hot" (emotionally laden) cognitive tasks. However, there are relatively few studies concerning how EI may benefit the working memory capacity (WMC). Thus, the objective of this study is to analyse the relationship between EI (as measured through a performance-based ability test, a self-report mixed test, and a self-report ability test) and the WMC during the performance of hot and "cool" (i.e., non-emotionally laden) "2-back" tasks. 203 participants completed three EI tests as well as two 2-back tasks. The results provide evidence for better performance of higher EI participants (specifically in the managing branch) measured through the performance-based ability test, but only on the hot task. For the self-report mixed model, incongruent results were found, and no correlations were obtained using the self-report ability model. The implications of these findings are discussed in terms of the validity of the various EI models.
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Project description:Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship.
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Project description:Survival-relevant information has privileged access to our awareness even during active cognitive engagement. Previous work has demonstrated that during working memory (WM) negative emotional distraction disrupts activation in the lateral prefrontal regions while also engaging the amygdala. Here, using slow event-related fMRI, we replicate and extend previous work examining the effect of negative emotional distraction on WM: (1) We demonstrate that prefrontal regions showed activation differences between correct and incorrect trials during negative, but not neutral, distraction. Specifically, frontopolar prefrontal cortex showed more deactivation for incorrect trials faced with negative distraction, whereas ventrolateral prefrontal regions showed less activation; (2) individual differences in amygdala activity predicted WM performance during negative as well as neutral distraction, such that lower activity predicted better performance; and (3) amygdala showed negative correlations with prefrontal and parietal cortical regions during resting state. However, during negative distraction, amygdala signals were more negatively correlated with prefrontal cortical regions than was found for resting state and neutral distraction. These results provide further evidence for an inverse relationship between dorsal prefrontal cortical regions and the amygdala when processing aversive stimuli competes with ongoing cognitive operations, and further support the importance of the prefrontal cortex in resisting emotional interference. Supplemental materials associated with this article may be downloaded from http://cabn.psychonomic-journals.org/content/supplemental.
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