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While the literature on aberrant long-distance connectivity in autism spectrum disorder (ASD) has grown fast over the past decade, little is know about local connectivity. We used regional homogeneity (ReHo) and local density approaches at different spatial scales to examine local connectivity in 29 children and adolescents with ASD and 29 matched typically developing participants, using resting state functional MRI data. Across a total of 12 analysis pipelines, the gross pattern of between-group findings was overall stable, with local overconnectivity in the ASD group in occipital and posterior temporal regions and underconnectivity in middle/posterior cingulate and medial prefrontal regions. This general pattern was confirmed in secondary analyses for low-motion subsamples (n=20 per group), in which time series segments with >0.25mm head motion were censored, as well as in an analysis including global signal regression. Local overconnectivity in visual regions appears consistent with preference for local over global visual processing previously reported in ASD, whereas cingulate and medial frontal underconnectivity may relate to aberrant function within the default mode network.

Neural systems activated in a coordinated way during rest, known as the default mode network (DMN), also support autobiographical memory (AM) retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity). Here we examined 18 participants’ spontaneous descriptions of autobiographical memories during a two-hour, private, open-ended interview in which they reacted to a series of true stories about real people’s social situations and responded to the prompt, how does this person’s story make you feel? We classified these descriptions as either containing factual information (semantic AMs) or more elaborate descriptions of emotionally meaningful events (episodic AMs). We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants’ intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

Functional coupling across distributed brain regions varies across task contexts, yet there are stable features. To better understand the range and central tendencies of network configurations, coupling patterns were explored using functional MRI (fMRI) across 14 distinct continuously performed task states ranging from passive fixation to increasingly demanding classification tasks. Mean global correlation profiles across the cortex ranged from 0.69 to 0.82 between task states. Network configurations from both passive fixation and classification tasks similarly predicted task coactivation patterns estimated from meta-analysis of the literature. Thus, even across markedly different task states, central tendencies dominate the coupling configurations. Beyond these shared components, distinct task states displayed significant differences in coupling patterns in response to their varied demands. One possibility is that anatomical connectivity provides constraints that act as attractors pulling network configurations towards a limited number of robust states. Reconfigurable coupling modes emerge as significant modifications to a core functional architecture. [ABSTRACT FROM AUTHOR]

The task-positive network (TPN) is anticorrelated with activity in the default mode network (DMN), and possibly reflects competition between the processing of external and internal information, while the salience network (SN) is pivotal in regulating TPN and DMN activity. Because abnormal functional connectivity in these networks has been related to schizophrenia, we tested whether alterations are also evident in subjects at risk for psychosis. Resting-state functional magnetic resonance imaging was tested in 28 subjects with basic symptoms reporting subjective cognitive-perceptive symptoms; 19 with attenuated or brief, limited psychotic symptoms; and 29 matched healthy controls. We characterized spatial differences in connectivity patterns, as well as internetwork connectivity. Right anterior insula (rAI) was selected as seed region for identifying the SN; medioprefrontal cortex (MPFC) for the DMN and TPN. The 3 groups differed in connectivity patterns between the MPFC and right dorsolateral prefrontal cortex (rDLPFC), and between the rAI and posterior cingulate cortex (PCC). In particular, the typically observed antagonistic relationship in MPFC-rDLPFC, rAI-PCC, and internetwork connectivity of DMN-TPN was absent in both at-risk groups. Notably, those connectivity patterns were associated with symptoms related to reality distortions, whereas enhanced connectivity strengths of MPFC-rDLPFC and TPN-DMN were related to poor performance in cognitive functions. We propose that the loss of a TPN-DMN anticorrelation, accompanied by an aberrant spatial extent in the DMN, TPN, and SN in the psychosis risk state, reflects the confusion of internally and externally focused states and disturbance of cognition, as seen in psychotic disorders. [ABSTRACT FROM PUBLISHER]

An important aspect of adaptive learning is the ability to flexibly use past experiences to guide new decisions. When facing a new decision, some people automatically leverage previously learned associations, while others do not. This variability in transfer of learning across individuals has been demonstrated repeatedly and has important implications for understanding adaptive behavior, yet the source of these individual differences remains poorly understood. In particular, it is unknown why such variability in transfer emerges even among homogeneous groups of young healthy participants who do not vary on other learning-related measures. Here we hypothesized that individual differences in the transfer of learning could be related to relatively stable differences in intrinsic brain connectivity, which could constrain how individuals learn. To test this, we obtained a behavioral measure of memory-based transfer outside of the scanner and on a separate day acquired resting-state functional MRI images in 42 participants. We then analyzed connectivity across independent component analysis-derived brain networks during rest, and tested whether intrinsic connectivity in learning-related networks was associated with transfer. We found that individual differences in transfer were related to intrinsic connectivity between the hippocampus and the ventromedial prefrontal cortex, and between these regions and large-scale functional brain networks. Together, the findings demonstrate a novel role for intrinsic brain dynamics in flexible learning-guided behavior, both within a set of functionally specific regions known to be important for learning, as well as between these regions and the default and frontoparietal networks, which are thought to serve more general cognitive functions. [ABSTRACT FROM AUTHOR]

Abstract: The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. [Copyright &y& Elsevier]

Background: Cocaine-dependent individuals demonstrate neural and behavioral differences compared to healthy comparison subjects when performing the Stroop color-word interference test. Stroop measures also relate to treatment outcome for cocaine dependence. Intrinsic connectivity analyses assess the extent to which task-related regional brain activations are related to each other in the absence of defining a priori regions of interest. Objective: This study examined 1) the extent to which cocaine-dependent and non-addicted individuals differed on measures of intrinsic connectivity during fMRI Stroop performance; and 2) the relationships between fMRI Stroop intrinsic connectivity and treatment outcome in cocaine dependence. Methods: Sixteen treatment-seeking cocaine-dependent patients and matched non-addicted comparison subjects completed an fMRI Stroop task. Between-group differences in intrinsic connectivity were assessed and related to self-reported and urine-toxicology-based cocaine-abstinence measures. Results: Cocaine-dependent patients vs. comparison subjects showed less intrinsic connectivity in cortical and subcortical regions. When adjusting for individual degree of intrinsic connectivity, cocaine-dependent vs. comparison subjects showed relatively greater intrinsic connectivity in the ventral striatum, putamen, inferior frontal gyrus, anterior insula, thalamus and substantia nigra. Non-mean-adjusted intrinsic-connectivity measures in the midbrain, thalamus, ventral striatum, substantia nigra, insula and hippocampus negatively correlated with measures of cocaine abstinence. Conclusion: The diminished intrinsic connectivity in cocaine-dependent vs. comparison subjects suggests poorer communication across brain regions during cognitive-control processes. In mean-adjusted analyses, the cocaine-dependent group displayed relatively greater Stroop-related connectivity in regions implicated in motivational processes in addictions. The relationships between treatment outcomes and connectivity in the midbrain and basal ganglia suggest that connectivity represents a potential treatment target. [ABSTRACT FROM AUTHOR]

Working memory (WM) allows goal-relevant information to be encoded and maintained in mind, even when the contents of WM are incongruent with the immediate environment. While regions of heteromodal cortex are important for WM, the neural mechanisms that relate to individual differences in the encoding and maintenance of goal-relevant information remain unclear. Here, we used behavioral correlates of two large-scale heteromodal networks at rest, the default mode (DMN) and frontoparietal (FPN) networks, to understand their contributions to distinct features of WM. We assessed each individual's ability to resist distracting information during the encoding and maintenance phases of a visuospatial WM task. Individuals with stronger connectivity of DMN with medial visual and retrosplenial cortex were less affected by encoding distraction. Conversely, weaker connectivity of both DMN and FPN with visual regions was associated with better WM performance when target information was no longer in the environment and distractors were presented in the maintenance phase. Our study suggests that stronger coupling between heteromodal cortex and visual-spatial regions supports WM encoding by reducing the influence of concurrently presented distractors, while weaker visual coupling is associated with better maintenance of goal-relevant information because it relates to the capacity to ignore task-irrelevant changes in the environment., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

While the literature on aberrant long-distance connectivity in autism spectrum disorder (ASD) has grown fast over the past decade, little is known about local connectivity. We used regional homogeneity and local density approaches at different spatial scales to examine local connectivity in 29 children and adolescents with ASD and 29 matched typically developing participants, using resting state functional magnetic resonance imaging data. Across a total of 12 analysis pipelines, the gross pattern of between-group findings was overall stable, with local overconnectivity in the ASD group in occipital and posterior temporal regions and underconnectivity in middle/posterior cingulate, and medial prefrontal regions. This general pattern was confirmed in secondary analyses for low-motion subsamples (n = 20 per group), in which time series segments with >0.25 mm head motion were censored, as well as in an analysis including global signal regression. Local overconnectivity in visual regions appears consistent with preference for local over global visual processing previously reported in ASD, whereas cingulate and medial frontal underconnectivity may relate to aberrant function within the default mode network. [ABSTRACT FROM AUTHOR]

Abstract: Functional images of the resting brain can be empirically parsed into intrinsic connectivity networks (ICNs) which closely resemble patterns of evoked task-based brain activity and which have a biological and genetic basis. Recently, ICNs have become popular for investigating brain functioning and brain-behavior relationships. However, the replicability and neurometrics of these networks are only beginning to be reported. Using a meta-level independent component analysis (ICA), we produced ICNs from three data sets collected from two samples of healthy adults. The ICNs from our data sets demonstrated robust and independent replication of 12 intrinsic networks that reflected 17 canonical, task-based, brain networks. We found within-subject reliability of ICNs was modest overall, but ranged from poor to good, and that voxels with the highest measured connectivity rarely had the highest reliability. Networks associated with executive functions, visuospatial reasoning, motor coordination, speech and audition, default mode, vision, and interoception showed moderate to high group-level reproducibility and replicability. However, only the first four of these networks also showed fair or better within-subject reliability over time. Our findings highlight the replicability of ICNs across data sets, the range of within-subject neurometrics across different networks, and the shared characteristics between resting and task-based networks. [Copyright &y& Elsevier]

Abstract: Neural processing is based on interactions between functionally specialized areas that can be described in terms of functional or effective connectivity. Functional connectivity is often assessed by task-free, resting-state functional magnetic resonance imaging (fMRI), whereas effective connectivity is usually estimated from task-based fMRI time-series. To investigate whether different connectivity approaches assess similar network topologies in the same subjects, we scanned 36 right-handed volunteers with resting-state fMRI followed by active-state fMRI involving a hand movement task. Time-series information was extracted from identical locations defined from individual activation maxima derived from the motor task. Dynamic causal modeling (DCM) was applied to the motor task time-series to estimate endogenous and context-dependent effective connectivity. In addition, functional connectivity was computed for both the rest and the motor task condition by means of inter-regional time-series correlations. At the group-level, we found strong interactions between the motor areas of interest in all three connectivity analyses. However, although the sample size warranted 90% power to detect correlations of medium effect size, resting-state functional connectivity was only weakly correlated with both task-based functional and task-based effective connectivity estimates for corresponding region-pairs. By contrast, task-based functional connectivity showed strong positive correlations with DCM effective connectivity parameters. In conclusion, resting-state and task-based connectivity reflect different components of functional integration that particularly depend on the functional state in which the subject is being scanned. Therefore, resting-state fMRI and DCM should be used as complementary measures when assessing functional brain networks. [Copyright &y& Elsevier]

Abstract: Transcranial magnetic stimulation (TMS) to the left dorsolateral prefrontal cortex (DLPFC) is used clinically for the treatment of depression however outcomes vary greatly between patients. We have shown that average clinical efficacy of different left DLPFC TMS sites is related to intrinsic functional connectivity with remote regions including the subgenual cingulate and suggested that functional connectivity with these remote regions might be used to identify optimized left DLPFC targets for TMS. However it remains unclear if and how this connectivity-based targeting approach should be applied at the single-subject level to potentially individualize therapy to specific patients. In this article we show that individual differences in DLPFC connectivity are large, reproducible across sessions, and can be used to generate individualized DLPFC TMS targets that may prove clinically superior to those selected on the basis of group-average connectivity. Factors likely to improve individualized targeting including the use of seed maps and the focality of stimulation are investigated and discussed. The techniques presented here may be applicable to individualized targeting of focal brain stimulation across a range of diseases and stimulation modalities and can be experimentally tested in clinical trials. [Copyright &y& Elsevier]

Functional connectivity (FC) studies have predominantly focused on resting state, where ongoing dynamics are thought to reflect the brain's intrinsic network architecture, which is thought to be broadly relevant because it persists across brain states (i.e., is state-general). However, it is unknown whether resting state is the optimal state for measuring intrinsic FC. We propose that latent FC, reflecting shared connectivity patterns across many brain states, better captures state-general intrinsic FC relative to measures derived from resting state alone. We estimated latent FC independently for each connection using leave-one-task-out factor analysis in seven highly distinct task states (24 conditions) and resting state using fMRI data from the Human Connectome Project. Compared with resting-state connectivity, latent FC improves generalization to held-out brain states, better explaining patterns of connectivity and task-evoked activation. We also found that latent connectivity improved prediction of behavior outside the scanner, indexed by the general intelligence factor ( g ). Our results suggest that FC patterns shared across many brain states, rather than just resting state, better reflect state-general connectivity. This affirms the notion of "intrinsic" brain network architecture as a set of connectivity properties persistent across brain states, providing an updated conceptual and mathematical framework of intrinsic connectivity as a latent factor., (© 2022 Massachusetts Institute of Technology.)

Abstract: We propose a novel reduced-order neuronal network modeling framework that includes an enhanced firing rate model and a corresponding synaptic calcium-based synaptic learning rule. Specifically, we propose enhancements to the Wilson–Cowan firing-rate neuron model that permit full spike-frequency adaptation seen in biological lateral amygdala (LA) neurons, while being sufficiently general to accommodate other spike-frequency patterns. We also report a technique to incorporate calcium-dependent plasticity in the synapses of the network using a regression scheme to link firing rate to postsynaptic calcium. Together, the single-cell model and the synaptic learning scheme constitute a general framework to develop computationally efficient neuronal networks that employ biologically realistic synaptic learning. The reduced-order modeling framework was validated using a previously reported biophysical conductance-based neuronal network model of a rodent LA that modeled features of Pavlovian conditioning and extinction of auditory fear (Li et al., 2009). The framework was then used to develop a larger LA network model to investigate the roles of tone and shock distributions and of intrinsic connectivity in auditory fear learning. The model suggested combinations of tone and shock densities that would provide experimental estimates of tone responsive and conditioned cell proportions. Furthermore, it provided several insights including how intrinsic connectivity might help distribute sensory inputs to produce conditioned responses in cells that do not directly receive both tone and shock inputs, and how a balance between potentiation of excitation and inhibition prevents stimulus generalization during fear learning. [Copyright &y& Elsevier]

Background: Transcranial magnetic stimulation (TMS) to the left dorsolateral prefrontal cortex (DLPFC) is used clinically for the treatment of depression. However, the antidepressant mechanism remains unknown and its therapeutic efficacy remains limited. Recent data suggest that some left DLPFC targets are more effective than others; however, the reasons for this heterogeneity and how to capitalize on this information remain unclear. Methods: Intrinsic (resting state) functional magnetic resonance imaging data from 98 normal subjects were used to compute functional connectivity with various left DLPFC TMS targets employed in the literature. Differences in functional connectivity related to differences in previously reported clinical efficacy were identified. This information was translated into a connectivity-based targeting strategy to identify optimized left DLPFC TMS coordinates. Results in normal subjects were tested for reproducibility in an independent cohort of 13 patients with depression. Results: Differences in functional connectivity were related to previously reported differences in clinical efficacy across a distributed set of cortical and limbic regions. Dorsolateral prefrontal cortex TMS sites with better clinical efficacy were more negatively correlated (anticorrelated) with the subgenual cingulate. Optimum connectivity-based stimulation coordinates were identified in Brodmann area 46. Results were reproducible in patients with depression. Conclusions: Reported antidepressant efficacy of different left DLPFC TMS sites is related to the anticorrelation of each site with the subgenual cingulate, potentially lending insight into the antidepressant mechanism of TMS and suggesting a role for intrinsically anticorrelated networks in depression. These results can be translated into a connectivity-based targeting strategy for focal brain stimulation that might be used to optimize clinical response. [ABSTRACT FROM AUTHOR]

Background: Socio-communicative impairments are salient features of autism spectrum disorder (ASD). Abnormal development of posterior superior temporal sulcus (pSTS)—a key processing area for language, biological motion, and social context—could play a role in these deficits. Methods: Functional connectivity magnetic resonance imaging was used to examine the synchronization of low-frequency blood oxygen level-dependent fluctuations during continuous performance on a visual search task. Twenty-one children and adolescents with ASD and 26 typically developing individuals—matched on age and IQ—participated in the study. Three subregions of pSTS were delineated with a data-driven approach, and differentiation of pSTS was examined by comparing the connectivity of each subregion. Results: In typically developing individuals, differentiation of networks was positively associated with age and anatomical maturation (cortical thinning in pSTS, greater white matter volume). In the ASD group, differentiation of pSTS connectivity was significantly reduced, and correlations with anatomical measures were weak or absent. Moreover, pSTS differentiation was inversely correlated with autism symptom severity. Conclusions: Atypical maturation of pSTS suggests altered trajectories for functional segregation and integration of networks in ASD, potentially related to impaired cognitive and sensorimotor development. Furthermore, our findings provide a novel explanation for atypically increased connectivity in ASD that has been observed in some functional connectivity magnetic resonance imaging studies. [ABSTRACT FROM AUTHOR]

Prematurely born children are at increased risk for cognitive deficits, but the neurobiological basis of these findings remains poorly understood. Because variations in neural circuitry may influence performance on cognitive tasks, recent investigations have explored the impact of preterm birth on connectivity in the developing brain. Diffusion tensor imaging studies demonstrate widespread alterations in fractional anisotropy, a measure of axonal integrity and microstructural connectivity, throughout the developing preterm brain. Functional connectivity studies report that preterm neonates, children and adolescents exhibit alterations in both resting state and task-based connectivity when compared with term control subjects. Taken together, these data suggest that neurodevelopmental impairment following preterm birth may represent a disease of neural connectivity. [Copyright &y& Elsevier]

In mammals, the hippocampus, entorhinal, perirhinal, and parahippocampal cortices (i.e., core regions of the human medial temporal lobes, MTL) are locally interlaced with the adjacent amygdala nuclei at the structural and functional levels. At the global brain level, the human MTL has been described as part of the default mode network and amygdala nuclei as parts of the salience network, with both networks collectively forming a large-scale brain system supporting allostatic-interoceptive functions. We hypothesized (i) that intrinsic functional connectivity of slow activity fluctuations would reveal human MTL subsystems locally extending to the amygdala; and (ii) that these extended local subsystems would be globally embedded in large-scale brain systems supporting allostatic-interoceptive functions. Capitalizing on resting-state fMRI data of three independent samples of cognitively healthy adults (one main and two replication samples: N ​= ​101, 60, and 29, respectively), we analyzed the functional connectivity of fluctuating ongoing BOLD-activity within and outside the amygdala-MTL in a data-driven way using masked independent component and dual-regression analyses. We found that at the local level, MTL subsystems extend to the amygdala and are functionally organized along the longitudinal amygdala-MTL axis. These subsystems are characterized by consistent involvement of amygdala, hippocampus, and entorhinal cortex, but variable participation of perirhinal and parahippocampal regions. At the global level, amygdala-MTL subsystems selectively connect to salience, thalamic-brainstem, and default mode networks – the major cortical and subcortical components of the allostatic-interoceptive system. These findings provide evidence for integrated amygdala-MTL subsystems in humans, which are embedded within a larger allostatic-interoceptive system. [ABSTRACT FROM AUTHOR]

The semantic network is thought to include multiple components, including heteromodal conceptual representations and semantic control processes that shape retrieval to suit the circumstances. Much of this network is strongly left-lateralised; however, work to date has not considered whether separable components of semantic cognition have different degrees of lateralisation. This study examined intrinsic connectivity of four regions implicated in heteromodal semantic cognition, identified using large scale meta-analyses: two sites which have been argued to act as heteromodal semantic hubs in anterior temporal lobe (ATL) and angular gyrus (AG); and two sites implicated in semantic control in inferior frontal (IFG) and posterior middle temporal gyri (pMTG). We compared the intrinsic connectivity of these sites in left hemisphere (LH) and right hemisphere (RH), and linked individual differences in the strength of within- and between-hemisphere connectivity from left-lateralised seeds to performance on semantic tasks, in a sample of 196 healthy volunteers. ATL showed more symmetrical patterns of intrinsic connectivity than the other three sites. The connectivity between IFG and pMTG was stronger in the LH than the RH, suggesting that the semantic control network is strongly left-lateralised. The degree of hemispheric lateralisation also predicted behaviour: participants with stronger intrinsic connectivity within the LH had better semantic performance, while those with stronger intrinsic connectivity between left pMTG and homotopes of semantic regions in the RH performed more poorly on judgements of weak associations, which require greater control. Stronger connectivity between left AG and visual cortex was also linked to poorer perceptual performance. Overall, our results show that hemispheric lateralisation is particularly important for the semantic control network, and that this lateralisation has contrasting functional consequences for the retrieval of dominant and subordinate aspects of knowledge. • Components of semantic cognition are reflected in intrinsic connectivity patterns. • Connectivity of the semantic control network is strongly left-lateralised. • Left and right anterior temporal connectivity is highly similar. • The strength of left-lateralisation relates to semantic processing efficiency. • Left-sided sites couple with lateral default and less with dorsal attention regions. [ABSTRACT FROM AUTHOR]

Contemporary neuroscientific accounts suggest that ventral anterior temporal lobe (ATL) acts as a bilateral heteromodal semantic hub, which is particularly critical for the specific-level knowledge needed to recognise unique entities, such as familiar landmarks and faces. There may also be graded functional differences between left and right ATL, relating to effects of modality (linguistic versus non-linguistic) and category (e.g., knowledge of people and places). Individual differences in intrinsic connectivity from left and right ATL might be associated with variation in semantic categorisation performance across these categories and modalities. We recorded resting-state fMRI in 74 individuals and, in a separate session, examined semantic categorisation. People with greater connectivity between left and right ATL were more efficient at categorising landmarks (e.g., Eiffel Tower), especially when these were presented visually. In addition, participants who showed stronger connectivity from right than left ATL to medial occipital cortex showed more efficient semantic categorisation of landmarks regardless of modality of presentation. These results can be interpreted in terms of graded differences in the patterns of connectivity across left and right ATL, which give rise to a bilateral yet partially segregated semantic 'hub'. More specifically, right ATL connectivity supports the efficient semantic categorisation of landmarks., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Understanding how brain circuitry mediates cognitive control of behavior is crucial for understanding both mental health and disease. Cognitive control describes the group of behaviors that guide goal-directed action such as sustaining attention, processing information and inhibiting impulsive responses. We rely on these behaviors for daily social, occupational and emotional functioning. Two brain networks, the cognitive control network (CCN) and default mode network (DMN), are thought to cooperate in an inverse relationship to support these functions. However, we do not yet know how connectivity within and between these networks directly relates to healthy cognitive control behaviors, and whether these interactions change over time. Here, we employed a longitudinal design to investigate if change in intrinsic connectivity in these networks will correlate with change in a range of cognitive control functions. Over two years, 109 healthy individuals, aged eight to thirty-eight, were tested twice using fMRI to assess intrinsic functional connectivity of the CCN and DMN and a validated cognitive battery. We found that increased within-network connectivity through central and left DMN was associated with increased memory performance. Additionally, decreased connectivity between posterior parietal CCN and DMN nodes and decreased connectivity between left and right dorsolateral prefrontal nodes was associated with increased cognitive performance. These findings were age and gender controlled, suggesting that age-independent plastic change in intrinsic connectivity through these networks directly relate to changing behavior. This has implications for targeting intrinsic connectivity as a possible mechanism to improve cognitive function., Competing Interests: Declaration of competing interest The authors declare no competing financial interests., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Based on the joint investigation in 287 healthy volunteers (150 left-Handers (LH)) of language task-induced asymmetries and intrinsic connectivity strength of the sentence-processing supramodal network, we show that individuals with atypical rightward language lateralization (N = 30, 25 LH) do not rely on an organization that simply mirrors that of typical leftward lateralized individuals. Actually, the resting-state organization in the atypicals showed that their sentence processing was underpinned by left and right networks both wired for language processing and highly interacting by strong interhemispheric intrinsic connectivity and larger corpus callosum volume. Such a loose hemispheric specialization for language permits the hosting of language in either the left and/or right hemisphere as assessed by a very high incidence of dissociations across various language task-induced asymmetries in this group., Competing Interests: LL, BM, MJ, FC, IH, NT No competing interests declared, (© 2020, Labache et al.)

The present chapter offers a report on the recent literature on the neural bases of hemispheric specialization (HS), anatomical and functional developmental timecourse of HS, and on the available knowledge of their relationships with the development of handedness. Strong anatomical asymmetries can be seen located along the end of the sylvian fissure and the superior temporal sulcus (STS) as soon as the 23rd gestational week. They correspond to a leftward sulcal depth asymmetry of the Sylvian fissure coupled with a rightward asymmetry of STS. These neonatal asymmetries targeting speech processing areas do not further change with development. Different from these anatomical asymmetries, the functional asymmetries of language areas develop during childhood. Such a development is characterized at birth by a predominant interhemispheric intrinsic connectivity between homotopic areas that will evolve toward left hemisphere intrahemispheric intrinsic connectivity between anterior and posterior language poles. The development of such a typical architecture of language networks in the left hemisphere dominant for language in more than 90% of humans translates into a continuous increase in the leftward asymmetries of activation during language production throughout childhood. With regard to the rightward cerebral lateralization for visuospatial functions, neuroimaging studies tend to indicate an increase in rightward lateralization of frontal-parietal network with age during visuospatial memory and visuospatial search tasks. In addition, the spatial-attentional behavioral asymmetries emerge early (in preschool children) and, then, can be modulated by factors linked to motor asymmetry and handedness. Finally, the study of manual lateralization in relation to language development has shown the importance of considering several characteristics of manual activities. In particular, the dissociation between manipulative activities and communicative gestures in young children may open further perspectives for future research on HS., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Menstrual cycle-dependent changes have been reported for a variety of functions, including cognition, attention, emotion, inhibition, and perception. For several of these functions, an effect of hormonal contraceptives has also been discussed. Cognitive, attentional, emotional, inhibitory, and perceptual functions have been linked to distinct intrinsic connectivity networks during the resting state. However, changes in resting-state connectivity across the menstrual cycle phase and due to hormonal contraceptive use have only been investigated in two selected networks and without controlling for the type of hormonal contraceptives. In the present study, we demonstrate menstrual cycle and hormonal contraceptive-dependent changes in several intrinsic connectivity networks, including networks that have been related to emotion processing, olfaction, audition, vision, coordination, and two lateralized frontoparietal networks related to a variety of cognitive functions. These changes parallel behavioral changes in the functions associated with these networks. Changes in connectivity and changes in behavior occur during the same cycle phases. Furthermore, hormonal contraceptive-dependent effects were observed in the same networks and same target sites as menstrual cycle-related changes and were dependent on the androgenicity of the progestin component contained in the hormonal contraceptive.

Intrinsic brain activity provides the functional framework for the brain's full repertoire of behavioral responses; that is, a common mechanism underlies intrinsic and extrinsic neural activity, with extrinsic activity building upon the underlying baseline intrinsic activity. The generation of a motor movement in response to sensory stimulation is one of the most fundamental functions of the central nervous system. Since saccadic eye movements are among our most stereotyped motor responses, we hypothesized that individual variability in the ability to inhibit a prepotent saccade and make a voluntary antisaccade would be related to individual variability in intrinsic connectivity. Twenty-three individuals completed the antisaccade task and resting-state functional magnetic resonance imaging (fMRI). A multivariate analysis of covariance identified relationships between fMRI oscillations (0.01-0.2 Hz) of resting-state networks determined using high-dimensional independent component analysis and antisaccade performance (latency, error rate). Significant multivariate relationships between antisaccade latency and directional error rate were obtained in independent components across the entire brain. Some of the relationships were obtained in components that overlapped substantially with the task; however, many were obtained in components that showed little overlap with the task. The current results demonstrate that even in the absence of a task, spectral power in regions showing little overlap with task activity predicts an individual's performance on a saccade task.

To investigate the neuroanatomical and functional brain changes in migraine patients relative to healthy controls, we used a combined analytical approach including voxel- and surface-based morphometry along with resting-state functional connectivity to determine whether areas showing structural alterations in patients also showed abnormal functional connectivity. Additionally, we wanted to assess whether these structural and functional changes were associated with group differences in pain catastrophizing and migraine-related disease variables in patients. We acquired T1-weighted anatomical and functional magnetic resonance imaging scans during rest in human subjects with a diagnosis of migraine and healthy controls. Structural analyses revealed greater left hippocampal gray matter volume and reduced cortical thickness in the left anterior midcingulate in patients compared with controls. We also observed negative associations between pain catastrophizing and migraine disease variables and gray matter in areas implicated in processing the sensory, affective, and cognitive aspects of pain in patients. Functional connectivity analyses showed that migraine patients displayed disrupted connectivity between default mode, salience, cognitive, visuospatial, and sensorimotor networks, which was associated with group differences in pain catastrophizing and migraine-related disease variables in patients. Together, our findings show widespread morphological and functional brain abnormalities in migraineurs in affective, cognitive, visual, and pain-related brain areas, which are associated with increased pain catastrophizing, disease chronicity, and severity of symptoms, suggesting that these structural and functional changes may be a consequence of repeated, long-term nociceptive signaling leading to increased pain sensitivity, mood disturbances, and maladaptive coping strategies to deal with unrelenting pain.

Object: Sagittal nonsyndromic craniosynostosis (sNSC) is the most common form of NSC. The condition is associated with a high prevalence (> 50%) of deficits in executive function. The authors employed diffusion tensor imaging (DTI) and functional MRI to evaluate whether hypothesized structural and functional connectivity differences underlie the observed neurocognitive morbidity of sNSC., Methods: Using a 3-T Siemens Trio MRI system, the authors collected DTI and resting-state functional connectivity MRI data in 8 adolescent patients (mean age 12.3 years) with sNSC that had been previously corrected via total vault cranioplasty and 8 control children (mean age 12.3 years) without craniosynostosis. Data were analyzed using the FMRIB Software Library and BioImageSuite., Results: Analyses of the DTI data revealed white matter alterations approaching statistical significance in all supratentorial lobes. Statistically significant group differences (sNSC < control group) in mean diffusivity were localized to the right supramarginal gyrus. Analysis of the resting-state seed in relation to whole-brain data revealed significant increases in negative connectivity (anticorrelations) of Brodmann area 8 to the prefrontal cortex (Montreal Neurological Institute [MNI] center of mass coordinates [x, y, z]: -6, 53, 6) and anterior cingulate cortex (MNI coordinates 6, 43, 14) in the sNSC group relative to controls. Furthermore, in the sNSC patients versus controls, the Brodmann area 7, 39, and 40 seed had decreased connectivity to left angular gyrus (MNI coordinates -31, -61, 34), posterior cingulate cortex (MNI coordinates 13, -52, 18), precuneus (MNI coordinates 10, -55, 54), left and right parahippocampus (MNI coordinates -13, -52, 2 and MNI coordinates 11, -50, 2, respectively), lingual (MNI coordinates -11, -86, -10), and fusiform gyri (MNI coordinates -30, -79, -18). Intrinsic connectivity analysis also revealed altered connectivity between central nodes in the default mode network in sNSC relative to controls; the left and right posterior cingulate cortices (MNI coordinates -5, -35, 34 and MNI coordinates 6, -42, 39, respectively) were negatively correlated to right hemisphere precuneus (MNI coordinates 6, -71, 46), while the left ventromedial prefrontal cortex (MNI coordinates 6, 34, -8) was negatively correlated to right middle frontal gyrus (MNI coordinates 40, 4, 33). All group comparisons (sNSC vs controls) were conducted at a whole brain-corrected threshold of p < 0.05., Conclusions: This study demonstrates altered neocortical structural and functional connectivity in sNSC that may, in part or substantially, underlie the neuropsychological deficits commonly reported in this population. Future studies combining analysis of multimodal MRI and clinical characterization data in larger samples of participants are warranted.

Neural systems activated in a coordinated way during rest, known as the default mode network (DMN), also support autobiographical memory (AM) retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity). Here we examined 18 participants' spontaneous descriptions of autobiographical memories during a 2 h, private, open-ended interview in which they reacted to a series of true stories about real people's social situations and responded to the prompt, "how does this person's story make you feel?" We classified these descriptions as either containing factual information ("semantic" AMs) or more elaborate descriptions of emotionally meaningful events ("episodic" AMs). We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants' intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.