Aging modulates large-scale neural network interactions during speech comprehension

Speech comprehension in noisy environments constitutes a critical challenge in everyday life and affects people of all ages. This challenging listening situation can be alleviated using semantic context to predict upcoming words (i.e., predictability gain)-a process associated with the domain-specific semantic network. When no such context can be used, speech comprehension in challenging listening conditions relies on cognitive control functions, underpinned by domain-general networks. Most previous studies focused on regional activity of pre-selected cortical regions or networks in healthy young listeners. Thus, it remains unclear how domain-specific and domain-general networks interact during speech comprehension in noise and how this may change across the lifespan. Here, we used correlational psychophysiological interaction (cPPI) to investigate functional network interactions during sentence comprehension under noisy conditions with varying predictability in healthy young and older listeners. Relative to young listeners, older adults showed increased task-related activity in several domain-general networks but reduced between-network connectivity. Across groups, higher predictability was associated with increased positive coupling between semantic and attention networks and increased negative coupling between semantic and control networks. These results highlight the complex interplay between the semantic network and several domain-general networks underlying the predictability gain. The observed differences in connectivity profiles with age inform the current debate on whether age-related changes in neural activity and functional connectivity reflect compensation or dedifferentiation.

Neurovascular coupling alterations related to cognitive impairment in cerebral small vessel disease: A multiscale brain network perspective

Evidence suggests that neurovascular coupling (NVC) dysfunction in cerebral small vessel disease (CSVD) may precede typical clinical and imaging manifestations. Here, we explored the underlying brain alterations of multiscale networks in CSVD patients related to cognitive impairment based on the method of NVC. We investigated 124 CSVD patients, including 70 patients with mild cognitive impairment (MCI) and 54 patients with no cognitive impairment (NCI). Functional MRI and arterial spin labeling were employed to estimate the coupling of spontaneous neuronal activity and cerebral blood perfusion based on the regional homogeneity and cerebral blood flow at the whole-brain, modular, and regional levels. We showed that the NVC of the dorsal attention network (DOR), ventral attention network (VEN) and default mode network (DMN) in the MCI were significantly lower than those in the NCI. The NVC of the DOR, VEN, and DMN in the NCI group exhibited correlations with the executive function. Furthermore, mediation effect of CSVD lesion load was observed for the association between NVC alterations and cognitive function. The abnormal NVC features achieved effective classification performance for MCI and NCI. These findings underscore the significance of specific modular and regional NVC dysfunction in the cognitive outcomes of CSVD. This study revealed the potential of NVC as a focal point for future research on cognitive impairment in CSVD, particularly from the perspective of multiscale brain network analysis.

Novel Genes Associated With Working Memory Are Identified by Combining Connectome, Transcriptome, and Genome

Working memory (WM) plays a crucial role in human cognition. Previous candidate and genome-wide association studies have reported many genetic variations associated with WM. However, little research has examined genetic basis of WM by using transcriptome, even though it reflects gene function more directly than does the genome. Here we propose a new approach to exploring the genetic mechanisms of WM by integrating connectome, transcriptome, and genome data in a high-quality dataset comprising 481 Chinese healthy adults. First, relevance vector regression was used to define WM-related brain regions. Second, genes differentially expressed within these regions were identified using the Allen Human Brain Atlas (AHBA) dataset. Finally, two independent datasets were used to validate these genes' contributions to WM. With this method, we identified 24 novel genes and 20 of them were confirmed in the large-scale datasets of ABCD and UK Biobank. These novel genes were enriched in the cellular component of collagen-containing extracellular matrix and the CCL18 signaling pathway. Our method offers an effective approach to integrating multimodal gene discovery and demonstrates the superiority of expression data. This new method and the newly identified genes deserve more attention in the future.

Investigation of white matter functional networks in young smokers

AIMS

This study investigated the changes in the organizational and intrinsical activities of the white matter functional networks (WMFNs) in young smokers using resting-state functional magnetic resonance imaging.

METHODS

A data-driven approach was used to characterize the WMFNs of 30 young smokers and 30 non-smokers. We applied K-means clustering to the neuroimaging data to delineate the WMFNs. Functional neural activities of the WMFNs were compared between the two groups. Correlation analyses were also conducted for the WMFNs neural activities of and clinical indicators of smoking.

RESULTS

Eight WMFNs were identified in both groups. Compared to non-smokers, young smokers demonstrated a different dorsal attention network and lack of a frontostriatal network. The neural activities in the frontal network, deep frontoparietal network, and visual network were reduced in young smokers. Further correlation analyses showed that the decreased neural activity in the deep frontal network and deep frontoparietal network were significantly negatively correlated with the Fagerström Test for Nicotine Dependence.

CONCLUSION

Young smokers exhibited differences in the organizational structure and neural activity intensities of the WMFNs. The present findings may indicate the importance of WMFNs in young smokers, which can help in obtaining a comprehensive understanding of the neural mechanisms underlying smoking addiction.

The dynamic reconfiguration of the functional network during episodic memory task predicts the memory performance

Episodic memory is essential for forming and retaining personal experiences, representing a fundamental aspect of human cognition. Traditional studies of episodic memory have typically used static analysis methods, viewing the brain as an unchanging entity and overlooking its dynamic properties over time. In this study, we utilized dynamic functional connectivity analysis on fMRI data from healthy adults performing an episodic memory task. We quantified integration and recruitment metrics and examined their correlation with memory performance using Pearson correlation. During encoding, integration across the entire brain, especially within the frontoparietal subnetwork, was significantly correlated with memory performance. During retrieval, recruitment becomes significantly associated with memory performance in visual subnetwork, somatomotor subnetwork, and ventral attention subnetwork. At the nodal level, a significant negative correlation was observed between memory scores and integration of the anterior cingulate gyrus, precentral gyrus, and inferior frontal gyrus within the frontoparietal network during encoding task. During retrieval task, a significant negative correlation was found between memory scores and recruitment in the left progranular cortex and right transverse gyral ventral, whereas positive correlations were seen in the right posterior inferior temporal, left middle temporal, right frontal operculum, and left operculum nodes. Moreover, the dynamic reconfiguration of the functional network was predictive of predict memory performance, as demonstrated by a significant correlation between actual and predicted memory scores. These findings advance our understanding network mechanisms underlying memory processes and developing intervention approaches for memory-related disorders as they shed light on critical factors involved in cognitive processes and provide a deeper understanding of the underlying mechanisms driving cognitive function.

Switching between External and Internal Attention in Hippocampal Networks

Everyday experience requires processing external signals from the world around us and internal information retrieved from memory. To do both, the brain must fluctuate between states that are optimized for external versus internal attention. Here, we focus on the hippocampus as a region that may serve at the interface between these forms of attention and ask how it switches between prioritizing sensory signals from the external world versus internal signals related to memories and thoughts. Pharmacological, computational, and animal studies have identified input from the cholinergic basal forebrain as important for biasing the hippocampus toward processing external information, whereas complementary research suggests the dorsal attention network (DAN) may aid in allocating attentional resources toward accessing internal information. We therefore tested the hypothesis that the basal forebrain and DAN drive the hippocampus toward external and internal attention, respectively. We used data from 29 human participants (17 female) who completed two attention tasks during fMRI. One task (memory-guided) required proportionally more internal attention, and proportionally less external attention, than the other (explicitly instructed). We discovered that background functional connectivity between the basal forebrain and hippocampus was stronger during the explicitly instructed versus memory-guided task. In contrast, DAN-hippocampus background connectivity was stronger during the memory-guided versus explicitly instructed task. Finally, the strength of DAN-hippocampus background connectivity was correlated with performance on the memory-guided but not explicitly instructed task. Together, these results provide evidence that the basal forebrain and DAN may modulate the hippocampus to switch between external and internal attention.SIGNIFICANCE STATEMENT How does the brain balance the need to pay attention to internal thoughts and external sensations? We focused on the human hippocampus, a region that may serve at the interface between internal and external attention, and asked how its functional connectivity varies based on attentional states. The hippocampus was more strongly coupled with the cholinergic basal forebrain when attentional states were guided by the external world rather than retrieved memories. This pattern flipped for functional connectivity between the hippocampus and dorsal attention network, which was higher for attention tasks that were guided by memory rather than external cues. Together, these findings show that distinct networks in the brain may modulate the hippocampus to switch between external and internal attention.

Resting State Dynamic Reconfiguration of Spatial Attention Cortical Networks and Visuospatial Functioning in Non-Verbal Learning Disability (NVLD): A HD-EEG Investigation

Nonverbal learning disability (NVLD) is a neurodevelopmental disorder characterized by deficits in visuospatial processing but spared verbal competencies. Neurocognitive markers may provide confirmatory evidence for characterizing NVLD as a separate neurodevelopmental disorder. Visuospatial performance and high-density electroencephalography (EEG) were measured in 16 NLVD and in 16 typically developing (TD) children. Cortical source modeling was applied to assess resting-state functional connectivity (rs-FC) in spatial attention networks (dorsal (DAN) and ventral attention networks (VAN)) implicated in visuospatial abilities. A machine-learning approach was applied to investigate whether group membership could be predicted from rs-FC maps and if these connectivity patterns were predictive of visuospatial performance. Graph theoretical measures were applied to nodes inside each network. EEG rs-FC maps in the gamma and beta band differentiated children with and without NVLD, with increased but more diffuse and less efficient functional connections bilaterally in the NVLD group. While rs-FC of the left DAN in the gamma range predicted visuospatial scores for TD children, in the NVLD group rs-FC of the right DAN in the delta range predicted impaired visuospatial performance, confirming that NVLD is a disorder with a predominant dysfunction in right hemisphere connectivity patterns.

Training allows switching from limited-capacity manipulations to large-capacity perceptual processing

In contrast to perceptual tasks, which enable concurrent processing of many stimuli, working memory (WM) tasks have a very small capacity, limiting cognitive skills. Training on WM tasks often yields substantial improvement, suggesting that training might increase the general WM capacity. To understand the underlying processes, we trained a test group with a newly designed tone manipulation WM task and a control group with a challenging perceptual task of pitch pattern discrimination. Functional magnetic resonance imaging (fMRI) scans confirmed that pretraining, manipulation was associated with a dorsal fronto-parietal WM network, while pitch comparison was associated with activation of ventral auditory regions. Training induced improvement in each group, which was limited to the trained task. Analyzing the behavior of the group trained with tone manipulation revealed that participants learned to replace active manipulation with a perceptual verification of the position of a single salient tone in the sequence presented as a tentative reply. Posttraining fMRI scans revealed modifications in ventral activation of both groups. Successful WMtrained participants learned to utilize auditory regions for the trained task. These observations suggest that the huge task-specific enhancement of WM capacity stems from a task-specific switch to perceptual routines, implemented in perceptual regions.

The neural coding of tonal working memory load: An functional magnetic resonance imaging study

Tonal working memory load refers to the number of pitches held in working memory. It has been found that different verbal working memory loads have different neural coding (local neural activity pattern). However, whether there exists a comparable phenomenon for tonal working memory load remains unclear. In this study, we used a delayed match-to-sample paradigm to evoke tonal working memory. Neural coding of different tonal working memory loads was studied with a surface space and convolution neural network (CNN)-based multivariate pattern analysis (SC-MVPA) method. We found that first, neural coding of tonal working memory was significantly different from that of the control condition in the bilateral superior temporal gyrus (STG), supplement motor area (SMA), and precentral gyrus (PCG). Second, neural coding of nonadjacent tonal working memory loads was distinguishable in the bilateral STG and PCG. Third, neural coding is gradually enhanced as the memory load increases. Finally, neural coding of tonal working memory was encoded in the bilateral STG in the encoding phase and shored in the bilateral PCG and SMA in the maintenance phase.

Evidence of familial confounding of the association between cannabis use and cerebellar-cortical functional connectivity using a twin study

Cerebellar-cortical resting-state functional connectivity (rsFC) has been reported to be altered in cannabis users. However, this association may be due to genetic and environmental confounding rather than a causal relationship between cannabis use and changes in rsFC. In this co-twin control study, linear mixed models were used to assess relationships between the number of lifetime cannabis uses (NLCU) and age of cannabis onset (ACO) with cerebellar-cortical rsFC. The rsFC with seven functional networks was evaluated in 147 monozygotic and 82 dizygotic twin pairs. Importantly, the use of genetically informed models in this twin sample facilitated examining whether shared genetic or environmental effects underlie crude associations between cannabis measures and connectivity. Individual-level phenotypic analyses (i.e., accounting for twin-pair non-independence) showed that individuals in the full sample with earlier ACO and higher NLCU had lower cerebellar rsFC within the VA, DA, and FP networks. Yet, there were no significant differences in cerebellar-cortical rsFC between monozygotic twins who were discordant for cannabis measures. These findings suggest shared genetic or environmental confounds contribute to associations between cannabis use and altered cerebellar-cortical rsFC, rather than unique causal impacts of cannabis use on cerebellar-cortical rsFC.

Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders that are highly heritable and are associated with impaired dynamic functional connectivity (DFC). However, the molecular mechanisms behind DFC alterations remain largely unknown. Eighty-eight patients with ASDs and 87 demographically matched typical controls (TCs) from the Autism Brain Imaging Data Exchange II database were included in this study. A seed-based sliding window approach was then performed to investigate the DFC changes in each of the 29 seeds in 10 classic resting-state functional networks and the whole brain. Subsequently, the relationships between DFC alterations in patients with ASDs and their symptom severity were assessed. Finally, transcription-neuroimaging association analyses were conducted to explore the molecular mechanisms of DFC disruptions in patients with ASDs. Compared with TCs, patients with ASDs showed significantly increased DFC between the right dorsolateral prefrontal cortex (DLPFC) and left fusiform/lingual gyrus, between the DLPFC and the superior temporal gyrus, between the right frontal eye field (FEF) and left middle frontal gyrus, between the FEF and the right angular gyrus, and between the left intraparietal sulcus and the right middle temporal gyrus. Moreover, significant relationships between DFC alterations and symptom severity were observed. Furthermore, the genes associated with DFC changes in ASDs were identified by performing gene-wise across-sample spatial correlation analysis between gene expression extracted from six donors’ brain of the Allen Human Brain Atlas and case-control DFC difference. In enrichment analysis, these genes were enriched for processes associated with synaptic signaling and voltage-gated ion channels and calcium pathways; also, these genes were highly expressed in autistic disorder, chronic alcoholic intoxication and several disorders related to depression. These results not only demonstrated higher DFC in patients with ASDs but also provided novel insight into the molecular mechanisms underlying these alterations.

The Neural Representation of Ordinal Information: Domain-Specific or Domain-General?

Ordinal processing allows for the representation of the sequential relations between stimuli and is a fundamental aspect of different cognitive domains such as verbal working memory (WM), language and numerical cognition. Several studies suggest common ordinal coding mechanisms across these different domains but direct between-domain comparisons of ordinal coding are rare and have led to contradictory evidence. This fMRI study examined the commonality of ordinal representations across the WM, the number, and the letter domains by using a multivoxel pattern analysis approach and by focusing on triplet stimuli associated with robust ordinal distance effects. Neural patterns in fronto-parietal cortices distinguished ordinal distance in all domains. Critically, between-task predictions of ordinal distance in fronto-parietal cortices were robust between serial order WM, alphabetical order judgment but not when involving the numerical order judgment tasks. Moreover, frontal ROIs further supported between-task prediction of distance for the luminance judgment control task, the serial order WM, and the alphabetical tasks. These results suggest that common neural substrates characterize processing of ordinal information in WM and alphabetical but not numerical domains. This commonality, particularly in frontal cortices, may however reflect attentional control processes involved in judging ordinal distances rather than the intervention of domain-general ordinal codes.

Individualized video recommendation modulates functional connectivity between large scale networks

With the emergence of AI‐powered recommender systems and their extensive use in the video streaming service, questions and concerns also arise. Why can recommended video content continuously capture users' attention? What is the impact of long‐term exposure to personalized video content on one's behaviors and brain functions? To address these questions, we designed an fMRI experiment presenting participants with personally recommended videos and generally recommended ones. To examine how large‐scale networks were modulated by personalized video content, graph theory analysis was applied to investigate the interaction between seven networks, including the ventral and dorsal attention networks (VAN, DAN), frontal–parietal network (FPN), salience network (SN), and three subnetworks of default mode network (dorsal medial prefrontal (dMPFC), Core, and medial temporal lobe (MTL)). Our results showed that viewing nonpersonalized video content mainly enhanced the connectivity in the DAN‐FPN‐Core pathway, whereas viewing personalized ones increased not only the connectivity in this pathway but also the DAN‐VAN‐dMPFC pathway. In addition, both personalized and nonpersonalized short videos decreased the couplings between SN and VAN as well as between two DMN subsystems, Core and MTL. Collectively, these findings uncovered distinct patterns of network interactions in response to short videos and provided insights into potential neural mechanisms by which human behaviors are biased by personally recommended content.

Transcranial Direct Current Stimulation (tDCS) over the Intraparietal Sulcus Does Not Influence Working Memory Performance

Mixed results of the impact of transcranial direct current stimulation (tDCS) on working memory have been reported. Contrarily to previous studies who focused mainly on stimulating the dorsolateral prefrontal cortex, we modulated the left intraparietal sulcus (IPS) area which is considered to support attentional control aspects of working memory. Using a within-participant experimental design, participants completed three different conditions: anodal stimulation of the IPS, cathodal stimulation of the IPS, and sham stimulation of the IPS. Both visual and verbal working memory tasks were administered. In the visual task, participants had to memorize a random set of colored figures. In the verbal task, participants had to memorize a string of letters. Working memory load was manipulated in both tasks (six figures/letters vs. two figures/letters). No significant differences in accuracy or reaction time between the anodal, cathodal and sham conditions were found. Bayesian analysis supported evidence for an absence of effect. The results of the present study add to the growing body of contradictory evidence regarding the modulatory effects of single session tDCS on working memory performance.

Gotcha: Working memory prioritization from automatic attentional biases

Attention is an important resource for prioritizing information in working memory (WM), and it can be deployed both strategically and automatically. Most research investigating the relationship between WM and attention has focused on strategic efforts to deploy attentional resources toward remembering relevant information. However, such voluntary attentional control represents a mere subset of the attentional processes that select information to be encoded and maintained in WM (Theeuwes, Journal of Cognition, 1[1]: 29, 1-15, 2018). Here, we discuss three ways in which information becomes prioritized automatically in WM-physical salience, statistical learning, and reward learning. This review integrates findings from perception and working memory studies to propose a more sophisticated understanding of the relationship between attention and working memory.

Developing Multimodal Dynamic Functional Connectivity as a Neuroimaging Biomarker

Background: In spite of increasing evidence highlighting the role of dynamic functional connectivity (FC) in characterizing mental disorders, there is a lack of (a) reliable statistical methods to compute dynamic connectivity and (b) rigorous dynamic FC-based approaches for predicting mental health outcomes in heterogeneous disorders such as post-traumatic stress disorder (PTSD). Methods: In one of the first such efforts, we develop a reliable and accurate approach for estimating dynamic FC guided by brain structural connectivity (SC) computed using diffusion tensor imaging data and investigate the potential of the proposed multimodal dynamic FC to predict continuous mental health outcomes. We develop concrete measures of temporal network variability that are predictive of PTSD resilience, and identify regions whose temporal connectivity fluctuations are significantly related to resilience. Results: Our results illustrate that the multimodal approach is more sensitive to connectivity change points, it can clearly detect localized brain regions with the dynamic network features such as small-worldedness, clustering coefficients, and efficiency associated with resilience, and that it has superior predictive performance compared with existing static and dynamic network models when modeling PTSD resilience. Discussion: While the majority of resting-state network modeling in psychiatry has focused on static FC, our novel multimodal dynamic network analyses that are sensitive to network fluctuations allowed us to provide a model of neural correlates of resilience with high accuracy compared with existing static connectivity approaches or those that do not use brain SC information, and provided us with an expanded understanding of the neurobiological causes for PTSD. Impact statement The methods developed in this article provide reliable and accurate dynamic functional connectivity (FC) approaches by fusing multimodal imaging data that are highly predictive of continuous clinical phenotypes in heterogeneous mental disorders. Currently, there is very little theoretical work to explain how network dynamics might contribute to individual differences in behavior or psychiatric symptoms. Our analysis conclusively discovers localized brain resting-state networks, regions, and connections where variations in dynamic FC (that is estimated after incorporating brain structural connectivity information) are associated with post-traumatic stress disorder resilience, which could potentially provide valuable tools for the development of neural circuit modeling in psychiatry in the future.

Distinct functional and structural connections predict crystallised and fluid cognition in healthy adults

White matter pathways between neurons facilitate neuronal coactivation patterns in the brain. Insight into how these structural and functional connections underlie complex cognitive functions provides an important foundation with which to delineate disease‐related changes in cognitive functioning. Here, we integrate neuroimaging, connectomics, and machine learning approaches to explore how functional and structural brain connectivity relate to cognition. Specifically, we evaluate the extent to which functional and structural connectivity predict individual crystallised and fluid cognitive abilities in 415 unrelated healthy young adults (202 females) from the Human Connectome Project. We report three main findings. First, we demonstrate functional connectivity is more predictive of cognitive scores than structural connectivity, and, furthermore, integrating the two modalities does not increase explained variance. Second, we show the quality of cognitive prediction from connectome measures is influenced by the choice of grey matter parcellation, and, possibly, how that parcellation is derived. Third, we find that distinct functional and structural connections predict crystallised and fluid abilities. Taken together, our results suggest that functional and structural connectivity have unique relationships with crystallised and fluid cognition and, furthermore, studying both modalities provides a more comprehensive insight into the neural correlates of cognition.

Lesions that do or do not impair digit span: a study of 816 stroke survivors

Prior studies have reported inconsistency in the lesion sites associated with verbal short-term memory impairments. Here we asked: How many different lesion sites can account for selective impairments in verbal short-term memory that persist over time, and how consistently do these lesion sites impair verbal short-term memory? We assessed verbal short-term memory impairments using a forward digit span task from the Comprehensive Aphasia Test. First, we identified the incidence of digit span impairments in a sample of 816 stroke survivors (541 males/275 females; age at stroke onset 56 ± 13 years; time post-stroke 4.4 ± 5.2 years). Second, we studied the lesion sites in a subgroup of these patients (n = 39) with left hemisphere damage and selective digit span impairment-defined as impaired digit span with unimpaired spoken picture naming and spoken word comprehension (tests of speech production and speech perception, respectively). Third, we examined how often these lesion sites were observed in patients who either had no digit span impairments or digit span impairments that co-occurred with difficulties in speech perception and/or production tasks. Digit span impairments were observed in 222/816 patients. Almost all (199/222 = 90%) had left hemisphere damage to five small regions in basal ganglia and/or temporo-parietal areas. Even complete damage to one or more of these five regions was not consistently associated with persistent digit span impairment. However, when the same regions were spared, only 5% (23/455) presented with digit span impairments. These data suggest that verbal short-term memory impairments are most consistently associated with damage to left temporo-parietal and basal ganglia structures. Sparing of these regions very rarely results in persistently poor verbal short-term memory. These findings have clinical implications for predicting recovery of verbal short-term memory after stroke.

Exercise alters brain activation in Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Gulf War Illness affects 25-30% of American veterans deployed to the 1990-91 Persian Gulf War and is characterized by cognitive post-exertional malaise following physical effort. Gulf War Illness remains controversial since cognitive post-exertional malaise is also present in the more common Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. An objective dissociation between neural substrates for cognitive post-exertional malaise in Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome would represent a biological basis for diagnostically distinguishing these two illnesses. Here, we used functional magnetic resonance imaging to measure neural activity in healthy controls and patients with Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome during an N-back working memory task both before and after exercise. Whole brain activation during working memory (2-Back > 0-Back) was equal between groups prior to exercise. Exercise had no effect on neural activity in healthy controls yet caused deactivation within dorsal midbrain and cerebellar vermis in Gulf War Illness relative to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients. Further, exercise caused increased activation among Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients within the dorsal midbrain, left operculo-insular cortex (Rolandic operculum) and right middle insula. These regions-of-interest underlie threat assessment, pain, interoception, negative emotion and vigilant attention. As they only emerge post-exercise, these regional differences likely represent neural substrates of cognitive post-exertional malaise useful for developing distinct diagnostic criteria for Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Neural Patterns in Linguistic Cortices Discriminate the Content of Verbal Working Memory

An influential theoretical account of working memory (WM) considers that WM is based on direct activation of long-term memory knowledge. While there is empirical support for this position in the visual WM domain, direct evidence is scarce in the verbal WM domain. This question is critical for models of verbal WM, as the question of whether short-term maintenance of verbal information relies on direct activation within the long-term linguistic knowledge base or not is still debated. In this study, we examined the extent to which short-term maintenance of lexico-semantic knowledge relies on neural activation patterns in linguistic cortices, and this by using a fast encoding running span task for word and nonword stimuli minimizing strategic encoding mechanisms. Multivariate analyses showed specific neural patterns for the encoding and maintenance of word versus nonword stimuli. These patterns were not detectable anymore when participants were instructed to stop maintaining the memoranda. The patterns involved specific regions within the dorsal and ventral pathways, which are considered to support phonological and semantic processing to various degrees. This study provides novel evidence for a role of linguistic cortices in the representation of long-term memory linguistic knowledge during WM processing.

Targeting age-related differences in brain and cognition with multimodal imaging and connectome topography profiling

Aging is characterized by accumulation of structural and metabolic changes in the brain. Recent studies suggest transmodal brain networks are especially sensitive to aging, which, we hypothesize, may be due to their apical position in the cortical hierarchy. Studying an open‐access healthy cohort (n = 102, age range = 30–89 years) with MRI and Aβ PET data, we estimated age‐related cortical thinning, hippocampal atrophy and Aβ deposition. In addition to carrying out surface‐based morphological and metabolic mapping experiments, we stratified effects along neocortical and hippocampal resting‐state functional connectome gradients derived from independent datasets. The cortical gradient depicts an axis of functional differentiation from sensory‐motor regions to transmodal regions, whereas the hippocampal gradient recapitulates its long‐axis. While age‐related thinning and increased Aβ deposition occurred across the entire cortical topography, increased Aβ deposition was especially pronounced toward higher‐order transmodal regions. Age‐related atrophy was greater toward the posterior end of the hippocampal long‐axis. No significant effect of age on Aβ deposition in the hippocampus was observed. Imaging markers correlated with behavioral measures of fluid intelligence and episodic memory in a topography‐specific manner, confirmed using both univariate as well as multivariate analyses. Our results strengthen existing evidence of structural and metabolic change in the aging brain and support the use of connectivity gradients as a compact framework to analyze and conceptualize brain‐based biomarkers of aging.

Alzheimer's disease patients activate attention networks in a short-term memory task

Network functioning during cognitive tasks is of major interest in Alzheimer's disease (AD). Cognitive functioning in AD includes variable performance in short-term memory (STM). In most studies, the verbal STM functioning in AD patients has been interpreted within the phonological loop subsystem of Baddeley's working memory model. An alternative account considers that domain-general attentional processes explain the involvement of frontoparietal networks in verbal STM beside the functioning of modality-specific subsystems. In this study, we assessed the functional integrity of the dorsal attention network (involved in task-related attention) and the ventral attention network (involved in stimulus-driven attention) by varying attentional control demands in a STM task. Thirty-five AD patients and twenty controls in the seventies performed an fMRI STM task. Variation in load (five versus two items) allowed the dorsal (DAN) and ventral attention networks (VAN) to be studied. ANOVA revealed that performance decreased with increased load in both groups. AD patients performed slightly worse than controls, but accuracy remained above 70% in all patients. Statistical analysis of fMRI brain images revealed DAN activation for high load in both groups. There was no between-group difference or common activation for low compared to high load conditions. Psychophysiological interaction showed a negative relationship between the DAN and the VAN for high versus low load conditions in patients. In conclusion, the DAN remained activated and connected to the VAN in mild AD patients who succeeded in performing an fMRI verbal STM task. DAN was necessary for the task, but not sufficient to reach normal performance. Slightly lower performance in early AD patients compared to controls might be related to maintained bottom-up attention to distractors, to decrease in executive functions, to impaired phonological processing or to reduced capacity in serial order processing.

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Patients with early AD succeeded in performing an fMRI short-term memory task.

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Dorsal attention network activation did not differ between patients and controls.

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Dorsal and ventral attention networks remained connected in high load task in AD.

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DAN was necessary for the task, but not sufficient to reach normal performance.

Stimulus-driven attention and cognitive control during encoding: An event related brain potentials study

Stimulus-driven attention drawn to relevant items can improve working memory (WM) whether attentional capture is driven by salient, low level features or by contingent salience from shared features with targets. In the current work, we examined the time course of enhanced attention to contingently salient information in a non-spatial WM task using event related brain potentials (ERPs). In line with previous work, we predicted that the encoding of contingently salient stimuli would be associated with an enhancement of cognitive control processes rather than low-level salience detection. The results of this study supported this hypothesis, evidenced by a posterior P3 component of greater amplitude for contingently salient stimuli relative to stimuli of a control color, which is thought to reflect enhanced attention to information that matches a target held in WM. However, P3 amplitude during encoding was unrelated to subsequent memory accuracy. As an exploratory follow up on these results, we conducted a regression analysis including beliefs about ability to focus attention as a moderator, which interacted with P3 amplitude to predict WM recall of salient letters. Furthermore, source localization analyses implicated a significant contribution of regions in the salience network to the detection of target stimuli, but only frontal control regions showed a greater response to salient than control letters. Thus, the results of this experiment suggest that participants enhance cognitive control during the encoding of contingently salient stimuli, but that the relationship between this neural process during encoding and subsequent benefits to WM recall might depend on individual differences in attentional focus.

Shared and Distinct Neural Bases of Large- and Small-Scale Spatial Ability: A Coordinate-Based Activation Likelihood Estimation Meta-Analysis

Background: Spatial ability is vital for human survival and development. However, the relationship between large-scale and small-scale spatial ability remains poorly understood. To address this issue from a novel perspective, we performed an activation likelihood estimation (ALE) meta-analysis of neuroimaging studies to determine the shared and distinct neural bases of these two forms of spatial ability. Methods: We searched Web of Science, PubMed, PsycINFO, and Google Scholar for studies regarding "spatial ability" published within the last 20 years (January 1988 through June 2018). A final total of 103 studies (Table 1) involving 2,085 participants (male = 1,116) and 2,586 foci were incorporated into the meta-analysis. Results: Large-scale spatial ability was associated with activation in the limbic lobe, posterior lobe, occipital lobe, parietal lobe, right anterior lobe, frontal lobe, and right sub-lobar area. Small-scale spatial ability was associated with activation in the parietal lobe, occipital lobe, frontal lobe, right posterior lobe, and left sub-lobar area. Furthermore, conjunction analysis revealed overlapping regions in the sub-gyrus, right superior frontal gyrus, right superior parietal lobule, right middle occipital gyrus, right superior occipital gyrus, left inferior occipital gyrus, and precuneus. The contrast analysis demonstrated that the parahippocampal gyrus, left lingual gyrus, culmen, right middle temporal gyrus, left declive, left superior occipital gyrus, and right lentiform nucleus were more strongly activated during large-scale spatial tasks. In contrast, the precuneus, right inferior frontal gyrus, right precentral gyrus, left inferior parietal lobule, left supramarginal gyrus, left superior parietal lobule, right inferior occipital gyrus, and left middle frontal gyrus were more strongly activated during small-scale spatial tasks. Our results further indicated that there is no absolute difference in the cognitive strategies associated with the two forms of spatial ability (egocentric/allocentric). Conclusion: The results of the present study verify and expand upon the theoretical model of spatial ability proposed by Hegarty et al. Our analysis revealed a shared neural basis between large- and small-scale spatial abilities, as well as specific yet independent neural bases underlying each. Based on these findings, we proposed a more comprehensive version of the behavioral model.

The developmental neural substrates of item and serial order components of verbal working memory

Behavioral and developmental studies have made a critical distinction between item and serial order processing components of verbal working memory (WM). This functional magnetic resonance imaging (fMRI) study determined the extent to which item and serial order WM components are characterized by specialized neural networks already in young children or whether this specialization emerges at a later developmental stage. Total of 59 children aged 7-12 years performed item and serial order short-term probe recognition tasks in an fMRI experiment. While a left frontoparietal network was recruited in both item and serial order WM conditions, the right intraparietal sulcus was selectively involved in the serial order WM condition. This neural segregation was modulated by age, with both networks becoming increasingly separated in older children. Our results indicate a progressive specialization of networks involved in item and order WM processes during cognitive development.

Role of the left hemisphere in visuospatial working memory

Visuospatial processing deficits are typically associated with damage to the right hemisphere. However, deficits on spatial working memory have been reported among some individuals with focal left hemisphere damage (LHD). It has been suggested that the left hemisphere may play a role in such non-verbal working memory tasks due to the use of subvocal, verbally-mediated strategies. The current study investigated the role of the left hemisphere in spatial working memory by testing spatial span performance, both forward and backward, in a large group of individuals with a history of left hemisphere stroke. Our first aim was to establish whether individuals with LHD are indeed impaired on spatial span tasks using standardized span tasks with published normative data. Our second aim was to identify the role that language plays in supporting spatial working memory by comparing LHD individuals with and without aphasia, and by relating spatial span performance to performance on a series of language measures. Our third aim was to identify left hemisphere brain regions that contribute to spatial working memory using voxel-based lesion symptom mapping (VLSM), a whole-brain statistical approach that identifies regions critical to a particular behavior on a voxel-by-voxel basis. We found that 28% of individuals with LHD performed in the clinically-impaired range on forward spatial span and 16% performed in the clinically-impaired range on backward spatial span. There were no significant differences in performance between individuals with and without aphasia, and there were no correlations between spatial span performance and language functions such as repetition and comprehension. The VLSM analysis showed that backward spatial span was associated with a left fronto-parietal network consisting of somatosensory cortex, the supramarginal gyrus, lateral prefrontal cortex, and the frontal eye fields. Regions identified in the VLSM analysis of forward spatial span did not reach the conservative statistical threshold for significance. Overall, these results suggest that spatial working memory, as measured by spatial span, can be significantly disrupted in a subset of individuals with LHD whose lesions infringe on a network of regions in the left hemisphere that have been implicated in domain-general working memory and attentional control mechanisms.

Task-unrelated thought depends on the phonological short-term memory system more than the visual short-term memory system

This study examined which type of short-term memory (STM), phonological or visual, is involved in and more important for representing contents of task-unrelated thoughts (TUTs). Three experiments consistently showed that TUTs were less likely to be reported during phonological STM tasks than either visual STM or control tasks. In contrast, the number of TUT responses did not considerably differ between visual STM tasks and control tasks even for TUTs with many visual images. This difference cannot be explained by the differential involvement of executive control processes because task difficulty was controlled for in the multi-level logistic regression analysis. These results, together with the finding that most TUT responses contained verbal images, suggest that phonological STM plays an important role in representing verbal images in TUTs, while visual STM is less or not involved in representing TUTs, even for those with many visual images.

Contralateral delay activity tracks the storage of visually presented letters and words

Electrophysiological studies have demonstrated that the maintenance of items in visual working memory (VWM) is indexed by the contralateral delay activity (CDA), which increases in amplitude as the number of objects to remember increases, plateauing at VWM capacity. Previous work has primarily utilized simple visual items, such as colored squares or picture stimuli. Despite the frequent use of verbal stimuli in seminal investigations of visual attention and memory, it is unknown whether temporary storage of letters and words also elicit a typical load-sensitive CDA. Given their close associations with language and phonological codes, it is possible that participants store these stimuli phonologically, and not visually. Participants completed a standard visual change-detection task while their ERPs were recorded. Experiment 1 compared the CDA elicited by colored squares compared to uppercase consonants, and Experiment 2 compared the CDA elicited by words compared to colored bars. Behavioral accuracy of change detection decreased with increasing set size for colored squares, letters, and words. We found that a capacity-limited CDA was present for colored squares, letters, and word arrays, suggesting that the visual codes for letters and words were maintained in VWM, despite the potential for transfer to verbal working memory. These results suggest that, despite their verbal associations, letters and words elicit the electrophysiological marker of VWM encoding and storage.

Investigating the Correspondence of Clinical Diagnostic Grouping With Underlying Neurobiological and Phenotypic Clusters Using Unsupervised Machine Learning

Many brain-based disorders are traditionally diagnosed based on clinical interviews and behavioral assessments, which are recognized to be largely imperfect. Therefore, it is necessary to establish neuroimaging-based biomarkers to improve diagnostic precision. Resting-state functional magnetic resonance imaging (rs-fMRI) is a promising technique for the characterization and classification of varying disorders. However, most of these classification methods are supervised, i.e., they require a priori clinical labels to guide classification. In this study, we adopted various unsupervised clustering methods using static and dynamic rs-fMRI connectivity measures to investigate whether the clinical diagnostic grouping of different disorders is grounded in underlying neurobiological and phenotypic clusters. In order to do so, we derived a general analysis pipeline for identifying different brain-based disorders using genetic algorithm-based feature selection, and unsupervised clustering methods on four different datasets; three of them-ADNI, ADHD-200, and ABIDE-which are publicly available, and a fourth one-PTSD and PCS-which was acquired in-house. Using these datasets, the effectiveness of the proposed pipeline was verified on different disorders: Attention Deficit Hyperactivity Disorder (ADHD), Alzheimer's Disease (AD), Autism Spectrum Disorder (ASD), Post-Traumatic Stress Disorder (PTSD), and Post-Concussion Syndrome (PCS). For ADHD and AD, highest similarity was achieved between connectivity and phenotypic clusters, whereas for ASD and PTSD/PCS, highest similarity was achieved between connectivity and clinical diagnostic clusters. For multi-site data (ABIDE and ADHD-200), we report site-specific results. We also reported the effect of elimination of outlier subjects for all four datasets. Overall, our results suggest that neurobiological and phenotypic biomarkers could potentially be used as an aid by the clinician, in additional to currently available clinical diagnostic standards, to improve diagnostic precision. Data and source code used in this work is publicly available at https://github.com/xinyuzhao/identification-of-brain-based-disorders.git.

Neural Mechanisms for the Benefits of Stimulus-Driven Attention

Stimulus-driven attention can improve working memory (WM) when drawn to behaviorally relevant information, but the neural mechanisms underlying this effect are unclear. The present study used functional magnetic resonance imaging (fMRI) to test competing hypotheses regarding the nature of the benefits of stimulus-driven attention to WM: that stimulus-driven attention benefits WM directly via salience detection, that stimulus-driven attention benefits WM incidentally via cognitive control mechanisms recruited to reduce interference from salient features, or that both mechanisms are co-involved in enhancing WM for salient information. To test these hypotheses, we observed activation in brain regions associated with cognitive control and salience detection. We found 2 cognitive control regions that were associated with enhanced memory for salient stimuli: a region in the right superior parietal lobule and a region in the right inferior frontal junction. No regions associated with salience detection were found to show this effect. These fMRI results support the hypothesis that benefits to WM from stimulus-driven attention occur primarily as a result of cognitive control and top-down factors rather than pure bottom-up aspects of stimulus-driven attention.

Asymmetric Spatial Processing Under Cognitive Load

Spatial attention allows us to selectively process information within a certain location in space. Despite the vast literature on spatial attention, the effect of cognitive load on spatial processing is still not fully understood. In this study we added cognitive load to a spatial processing task, so as to see whether it would differentially impact upon the processing of visual information in the left versus the right hemispace. The main paradigm consisted of a detection task that was performed during the maintenance interval of a verbal working memory task. We found that increasing cognitive working memory load had a more negative impact on detecting targets presented on the left side compared to those on the right side. The strength of the load effect correlated with the strength of the interaction on an individual level. The implications of an asymmetric attentional bias with a relative disadvantage for the left (vs the right) hemispace under high verbal working memory (WM) load are discussed.

The Dorsal Attention Network Reflects Both Encoding Load and Top–down Control during Working Memory

The dorsal attention network is consistently involved in verbal and visual working memory (WM) tasks and has been associated with task-related, top–down control of attention. At the same time, WM capacity has been shown to depend on the amount of information that can be encoded in the focus of attention independently of top–down strategic control. We examined the role of the dorsal attention network in encoding load and top–down memory control during WM by manipulating encoding load and memory control requirements during a short-term probe recognition task for sequences of auditory (digits, letters) or visual (lines, unfamiliar faces) stimuli. Encoding load was manipulated by presenting sequences with small or large sets of memoranda while maintaining the amount of sensory stimuli constant. Top–down control was manipulated by instructing participants to passively maintain all stimuli or to selectively maintain stimuli from a predefined category. By using ROI and searchlight multivariate analysis strategies, we observed that the dorsal attention network encoded information for both load and control conditions in verbal and visuospatial modalities. Decoding of load conditions was in addition observed in modality-specific sensory cortices. These results highlight the complexity of the role of the dorsal attention network in WM by showing that this network supports both quantitative and qualitative aspects of attention during WM encoding, and this is in a partially modality-specific manner.

Spontaneous brain oscillations as neural fingerprints of working memory capacities: A resting-state MEG study

Short-term storage and mental information manipulation capacities in the human brain are key to healthy cognition. These brain processes collectively known as working memory (WM) are associated with modulations of rhythmic brain activity across multiple brain areas and frequencies. Yet, it is not clear whether - and, if so, how-intrinsic resting-state neuronal oscillations are related to individual WM capacities, as measured by standard neuropsychological tests. We addressed this question by probing the correlation between resting-state brain activity, recorded with magnetoencephalography (MEG), and verbal and visuo-spatial WM indices obtained from the standardized Wechsler Adult Intelligence Scale (WAIS-IV) and the Wechsler Memory Scale (WMS-IV). To this end, 5-min eyes-open resting-state MEG data were acquired in 28 healthy participants. Source-reconstructed spectral power estimates were then computed in standard frequency bands and their correlation with neuropsychological indices across individuals was assessed using Pearson correlation and cluster-level statistics. We found statistically significant positive correlations between spectral amplitudes measured at rest and standardized scores on both verbal and visuo-spatial WM performance. The correlation clusters primarily involved key medial and dorsolateral components within the parietal and prefrontal regions. In addition, while the correlation in some clusters was frequency selective (e.g., alpha-band oscillations), other areas showed correlations with WM across a wide range of frequencies reflecting a broadband effect. These results provide the first evidence for a positive correlation between neuromagnetic signals measured at rest and WM performance separately assessed by standardized neuropsychological tests. Our results advance our understanding of the link between WM capacities and intrinsic oscillatory dynamics networks. They also suggest that individual differences in baseline spectral power might need to be taken into account when probing differences in brain responses during the execution of WM tasks.

Fluctuations of Attentional Networks and Default Mode Network during the Resting State Reflect Variations in Cognitive States: Evidence from a Novel Resting-state Experience Sampling Method

Neuroimaging studies have revealed the recruitment of a range of neural networks during the resting state, which might reflect a variety of cognitive experiences and processes occurring in an individual's mind. In this study, we focused on the default mode network (DMN) and attentional networks and investigated their association with distinct mental states when participants are not performing an explicit task. To investigate the range of possible cognitive experiences more directly, this study proposes a novel method of resting-state fMRI experience sampling, informed by a phenomenological investigation of the fluctuation of mental states during the resting state. We hypothesized that DMN activity would increase as a function of internal mentation and that the activity of dorsal and ventral networks would indicate states of top–down versus bottom–up attention at rest. Results showed that dorsal attention network activity fluctuated as a function of subjective reports of attentional control, providing evidence that activity of this network reflects the perceived recruitment of controlled attentional processes during spontaneous cognition. Activity of the DMN increased when participants reported to be in a subjective state of internal mentation, but not when they reported to be in a state of perception. This study provides direct evidence for a link between fluctuations of resting-state neural activity and fluctuations in specific cognitive processes.

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task.

Finding the answer in space: the mental whiteboard hypothesis on serial order in working memory

Various prominent models on serial order coding in working memory (WM) build on the notion that serial order is achieved by binding the various items to-be-maintained to fixed position markers. Despite being relatively successful in accounting for empirical observations and some recent neuro-imaging support, these models were largely formulated on theoretical grounds and few specifications have been provided with respect to the cognitive and/or neural nature of these position markers. Here we outline a hypothesis on a novel candidate mechanism to substantiate the notion of serial position markers. Specifically, we propose that serial order WM is grounded in the spatial attention system: (I) The position markers that provide multi-item WM with a serial context should be understood as coordinates within an internal, spatially defined system; (II) internal spatial attention is involved in searching through the resulting serial order representation; and (III) retrieval corresponds to selection by spatial attention. We sketch the available empirical support and discuss how the hypothesis may provide a parsimonious framework from which to understand a broad range of observations across behavioral, neural and neuropsychological domains. Finally, we pinpoint what we believe are major questions for future research inspired by the hypothesis.

Central and peripheral components of working memory storage

This study reexamines the issue of how much of working memory storage is central, or shared across sensory modalities and verbal and nonverbal codes, and how much is peripheral, or specific to a modality or code. In addition to the exploration of many parameters in 9 new dual-task experiments and reanalysis of some prior evidence, the innovations of the present work compared to previous studies of memory for 2 stimulus sets include (a) use of a principled set of formulas to estimate the number of items in working memory and (b) a model to dissociate central components, which are allocated to very different stimulus sets depending on the instructions, from peripheral components, which are used for only 1 kind of material. We consistently find that the central contribution is smaller than was suggested by Saults and Cowan (2007) and that the peripheral contribution is often much larger when the task does not require the binding of features within an object. Previous capacity estimates are consistent with the sum of central plus peripheral components observed here. We consider the implications of the data as constraints on theories of working memory storage and maintenance.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM.

Functional specialization of the left ventral parietal cortex in working memory

The function of the ventral parietal cortex (VPC) is subject to much debate. Many studies suggest a lateralization of function in the VPC, with the left hemisphere facilitating verbal working memory and the right subserving stimulus-driven attention. However, many attentional tasks elicit activity in the VPC bilaterally. To elucidate the potential divides across the VPC in function, we assessed the pattern of activity in the VPC bilaterally across two tasks that require different demands, an oddball attentional task with low working memory demands and a working memory task. An anterior region of the VPC was bilaterally active during novel targets in the oddball task and during retrieval in WM, while more posterior regions of the VPC displayed dissociable functions in the left and right hemisphere, with the left being active during the encoding and retrieval of WM, but not during the oddball task and the right showing the reverse pattern. These results suggest that bilateral regions of the anterior VPC subserve non-mnemonic processes, such as stimulus-driven attention during WM retrieval and oddball detection. The left posterior VPC may be important for speech-related processing important for both working memory and perception, while the right hemisphere is more lateralized for attention.

Long-term memory-based control of attention in multi-step tasks requires working memory: evidence from domain-specific interference

Evidence for long-term memory (LTM)-based control of attention has been found during the execution of highly practiced multi-step tasks. However, does LTM directly control for attention or are working memory (WM) processes involved? In the present study, this question was investigated with a dual-task paradigm. Participants executed either a highly practiced visuospatial sensorimotor task (speed stacking) or a verbal task (high-speed poem reciting), while maintaining visuospatial or verbal information in WM. Results revealed unidirectional and domain-specific interference. Neither speed stacking nor high-speed poem reciting was influenced by WM retention. Stacking disrupted the retention of visuospatial locations, but did not modify memory performance of verbal material (letters). Reciting reduced the retention of verbal material substantially whereas it affected the memory performance of visuospatial locations to a smaller degree. We suggest that the selection of task-relevant information from LTM for the execution of overlearned multi-step tasks recruits domain-specific WM.

Brain networks disconnection in early multiple sclerosis cognitive deficits: an anatomofunctional study

Severe cognitive impairment involving multiple cognitive domains can occur early during the course of multiple sclerosis (MS). We investigated resting state functional connectivity changes in large-scale brain networks and related structural damage underlying cognitive dysfunction in patients with early MS. Patients with relapsing MS (3-5 years disease duration) were prospectively assigned to two groups based on a standardized neuropsychological evaluation: (1) cognitively impaired group (CI group, n = 15), with abnormal performances in at least 3 tests; (2) cognitively preserved group (CP group, n = 20) with normal performances in all tests. Patients and age-matched healthy controls underwent a multimodal 3T magnetic resonance imaging (MRI) including anatomical T1 and T2 images, diffusion imaging and resting state functional MRI. Structural MRI analysis revealed that CI patients had a higher white matter lesion load compared to CP and a more severe atrophy in gray matter regions highly connected to networks involved in cognition. Functional connectivity measured by integration was increased in CP patients versus controls in attentional networks (ATT), while integration was decreased in CI patients compared to CP both in the default mode network (DMN) and ATT. An anatomofunctional study within the DMN revealed that functional connectivity was mostly altered between the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) in CI patients compared to CP and controls. In a multilinear regression model, functional correlation between MPFC and PCC was best predicted by PCC atrophy. Disconnection in the DMN and ATT networks may deprive the brain of compensatory mechanisms required to face widespread structural damage.