Whole-brain resting-state connectivity underlying impaired inhibitory control during early versus longer-term abstinence in cocaine addiction.

Lapses in inhibitory control have been linked to relapse in human drug addiction. Evidence suggests differences in inhibitory control depending on abstinence duration, but the underlying neural mechanisms remain unknown. We hypothesized that early abstinence (2-5 days) would be characterized by the strongest impairments of inhibitory control and most wide-spread deviations in resting-state functional connectivity of brain networks, while longer-term abstinence (>30 days) would be characterized by weaker impairments as compared to healthy controls. In this laboratory-based cross-sectional study, we compared individuals with Cocaine Use Disorder (iCUD) during early (cocaine urine-positive: N = 19, iCUD+; 32% female; mean age: 46.8 years) and longer-term abstinence (cocaine urine-negative: N = 29, iCUD-; 15% female; mean age: 46.6 years) to healthy controls (N = 33; 24% female; mean age: 40.9 years). We compared the groups on inhibitory control performance (Stop-Signal Task) and, using a whole-brain graph theory analysis (638 region parcellation) of functional magnetic resonance imaging (fMRI) data, we tested for group differences in resting-state brain function (local/global efficiency). We characterized how resting-state brain function was associated with inhibitory control performance within iCUD. Inhibitory control performance was worst in the early abstinence group, and intermediate in the longer-term abstinence group, as compared to the healthy control group (P < 0.01). More recent use of cocaine (CUD+ > CUD- > healthy controls) was characterized by decreased efficiency in fronto-temporal and subcortical networks (primarily in the salience, semantic, and basal ganglia networks) and increased efficiency in visual networks. Importantly, a similar functional connectivity pattern characterized impaired inhibitory control performance within iCUD (all brain analyses P < 0.05, FWE-corrected). Together, we demonstrated that a similar pattern of systematic and widespread deviations in resting-state brain efficiency, extending beyond the networks commonly investigated in human drug addiction, is linked to both abstinence duration and inhibitory control deficits in iCUD.

Age differences in the functional architecture of the human brain.

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience-dependent changes, or both, is uncertain. We employed a multimethod strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n = 181) and older (n = 120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multiscale, multimethod approaches to characterize the architecture of functional brain aging.

Neurocognitive aging data release with behavioral, structural and multi-echo functional MRI measures.

Central to understanding human behavior is a comprehensive mapping of brain-behavior relations within the context of lifespan development. Reproducible discoveries depend upon well-powered samples of reliable data. We provide to the scientific community two, 10-minute, multi-echo functional MRI (ME-fMRI) runs, and structural MRI (T1-MPRAGE), from 181 healthy younger (ages 18-34 y) and 120 older adults (ages 60-89 y). T2-FLAIR MRIs and behavioral assessments are available in a majority subset of over 250 participants. Behavioral assessments include fluid and crystallized cognition, self-reported measures of personality, and socioemotional functioning. Initial quality control and validation of these data is provided. This dataset will be of value to scientists interested in BOLD signal specifically isolated from ME-fMRI, individual differences in brain-behavioral associations, and cross-sectional aging effects in healthy adults. Demographic and behavioral data are available within the Open Science Framework project "Goal-Directed Cognition in Older and Younger Adults" ( http://osf.io/yhzxe/ ), which will be augmented over time; neuroimaging data are available on OpenNeuro ( https://openneuro.org/datasets/ds003592 ).

Bedside detection of intracranial midline shift using portable magnetic resonance imaging.

Neuroimaging is crucial for assessing mass effect in brain-injured patients. Transport to an imaging suite, however, is challenging for critically ill patients. We evaluated the use of a low magnetic field, portable MRI (pMRI) for assessing midline shift (MLS). In this observational study, 0.064 T pMRI exams were performed on stroke patients admitted to the neuroscience intensive care unit at Yale New Haven Hospital. Dichotomous (present or absent) and continuous MLS measurements were obtained on pMRI exams and locally available and accessible standard-of-care imaging exams (CT or MRI). We evaluated the agreement between pMRI and standard-of-care measurements. Additionally, we assessed the relationship between pMRI-based MLS and functional outcome (modified Rankin Scale). A total of 102 patients were included in the final study (48 ischemic stroke; 54 intracranial hemorrhage). There was significant concordance between pMRI and standard-of-care measurements (dichotomous, κ = 0.87; continuous, ICC = 0.94). Low-field pMRI identified MLS with a sensitivity of 0.93 and specificity of 0.96. Moreover, pMRI MLS assessments predicted poor clinical outcome at discharge (dichotomous: adjusted OR 7.98, 95% CI 2.07-40.04, p = 0.005; continuous: adjusted OR 1.59, 95% CI 1.11-2.49, p = 0.021). Low-field pMRI may serve as a valuable bedside tool for detecting mass effect.

Lateralisation of subcortical functional connectivity during and after general anaesthesia.

BACKGROUND: Arousal and awareness are two important components of consciousness states. Functional neuroimaging has furthered our understanding of cortical and thalamocortical mechanisms of awareness. Investigating the relationship between subcortical functional connectivity and arousal has been challenging owing to the relatively small size of brainstem structures and thalamic nuclei, and their depth in the brain. METHODS: Resting state functional MRI scans of 72 healthy volunteers were acquired before, during, 1 h after, and 1 day after sevoflurane general anaesthesia. Functional connectivity of subcortical regions of interest vs whole brain and homotopic functional connectivity for assessment of left-right symmetry analyses of both cortical and subcortical regions of interest were performed. Both analyses used high resolution atlases generated from deep brain stimulation applications. RESULTS: Functional connectivity in subcortical loci within the thalamus and of the ascending reticular activating system was sharply restricted under anaesthesia, featuring a general lateralisation of connectivity. Similarly, left-right homology was sharply reduced under anaesthesia. Subcortical bilateral functional connectivity was not fully restored after emergence from anaesthesia, although greater restoration was seen between ascending reticular activating system loci and specific thalamic nuclei thought to be involved in promoting and maintaining arousal. Functional connectivity was fully restored to baseline by the following day. CONCLUSIONS: Functional connectivity in the subcortex is sharply restricted and lateralised under general anaesthesia. This restriction may play a part in loss and return of consciousness. CLINICAL TRIAL REGISTRATION: NCT02275026.

Advances in resting state fMRI acquisitions for functional connectomics.

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry.

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.

Resting-state functional connectivity in early postanaesthesia recovery is characterised by globally reduced anticorrelations.

BACKGROUND: A growing body of literature addresses the possible long-term cognitive effects of anaesthetics, but no study has delineated the normal trajectory of neural recovery attributable to anaesthesia alone in adults. We obtained resting-state functional MRI scans on 72 healthy human volunteers between ages 40 and 80 (median: 59) yr before, during, and after general anaesthesia with sevoflurane, in the absence of surgery, as part of a larger study on cognitive function postanaesthesia. METHODS: Region-of-interest analysis, independent component analysis, and seed-to-voxel analysis were used to characterise resting-state functional connectivity and to differentiate between correlated and anticorrelated connectivity before, during, and after general anaesthesia. RESULTS: Whilst positively correlated functional connectivity remained essentially unchanged across these perianaesthetic states, anticorrelated functional connectivity decreased globally by 35% 1 h after emergence from general anaesthesia compared with baseline, as seen by the region-of-interest analysis. This decrease corresponded to a consistent reduction in expression of canonical resting-state networks, as seen by independent component analysis. All measures returned to baseline 1 day later. CONCLUSIONS: The normal perianaesthesia trajectory of resting-state connectivity in healthy adults is characterised by a transient global reduction in anticorrelated activity shortly after emergence from anaesthesia that returns to baseline by the following day. CLINICAL TRIAL REGISTRATION: NCT02275026.

Self-awareness of problematic drug use: Preliminary validation of a new fMRI task to assess underlying neurocircuitry.

BACKGROUND: Multiple psychopathologies feature impaired clinical insight. Emerging evidence suggests that insight problems may similarly characterize addiction, perhaps due to aberrant functioning of self-referential brain circuitry, including the rostral anterior cingulate and ventromedial prefrontal cortices (rACC/vmPFC). We developed a new fMRI task to probe whether rACC/vmPFC abnormalities in cocaine use disorder (CUD) constitute neural correlates of readiness to change, one facet of insight. METHODS: Eighteen individuals with current CUD and 15 healthy controls responded about their own need to change their drug use and eating behavior (control condition) and the need for a named acquaintance to do the same (two additional control conditions). Measures of simulated drug-choice behavior, addiction severity, and neuropsychological function were collected outside the scanner. RESULTS: CUD participants perceived a greater need for behavior change than controls (as expected, given their diagnosis), but fell short of "agreeing" to a need for change; in CUD, lower perceived need correlated with higher simulated drug-choice behavior, a proxy measure of drug-seeking. During drug-related insight judgments, CUD participants had higher activation than controls in an anatomically-defined region of interest (ROI) in the medial orbitofrontal cortex, part of the rACC/vmPFC. Although not showing group differences, activation in an anatomically-defined ACC ROI correlated with insight-related task behavior (in all participants) and memory performance (in CUD). CONCLUSIONS: As a group, individuals with current CUD appear to show mild insight problems and rACC/vmPFC abnormalities vis-à-vis readiness to change behavior. With replication and extension of these results, insight-related circuitry may emerge as a novel therapeutic target.

Sub-millimeter variation in human locus coeruleus is associated with dimensional measures of psychopathology: An in vivo ultra-high field 7-Tesla MRI study.

The locus coeruleus (LC) has a long-established role in the attentional and arousal response to threat, and in the emergence of pathological anxiety in pre-clinical models. However, human evidence of links between LC function and pathological anxiety has been restricted by limitations in discerning LC with current neuroimaging techniques. We combined ultra-high field 7-Tesla and 0.4 × 0.4 × 0.5 mm quantitative MR imaging with a computational LC localization and segmentation algorithm to delineate the LC in 29 human subjects including subjects with and without an anxiety or stress-related disorder. Our automated, data-driven LC segmentation algorithm provided LC delineations that corresponded well with postmortem anatomic definitions of the LC. There was variation of LC size in healthy subjects (125.7 +/- 59.3 mm3), which recapitulates histological reports. Patients with an anxiety or stress-related disorder had larger LC compared to controls (Cohen's d = 1.08, p = 0.024). Larger LC was additionally associated with poorer attentional and inhibitory control and higher anxious arousal (FDR-corrected p's<0.025), trans-diagnostically across the full sample. This study combined high-resolution and quantitative MR with a mixture of supervised and unsupervised computational techniques to provide robust, sub-millimeter measurements of the LC in vivo, which were additionally related to common psychopathology. This work has wide-reaching applications for a range of neurological and psychiatric disorders characterized by expected LC dysfunction.

Conservative and disruptive modes of adolescent change in human brain functional connectivity.

Adolescent changes in human brain function are not entirely understood. Here, we used multiecho functional MRI (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in 298 healthy adolescents scanned 520 times. Participants were aged 14 to 26 y and were scanned on 1 to 3 occasions at least 6 mo apart. We found 2 distinct modes of age-related change in FC: "conservative" and "disruptive." Conservative development was characteristic of primary cortex, which was strongly connected at 14 y and became even more connected in the period from 14 to 26 y. Disruptive development was characteristic of association cortex and subcortical regions, where connectivity was remodeled: connections that were weak at 14 y became stronger during adolescence, and connections that were strong at 14 y became weaker. These modes of development were quantified using the maturational index (MI), estimated as Spearman's correlation between edgewise baseline FC (at 14 y, [Formula: see text]) and adolescent change in FC ([Formula: see text]), at each region. Disruptive systems (with negative MI) were activated by social cognition and autobiographical memory tasks in prior fMRI data and significantly colocated with prior maps of aerobic glycolysis (AG), AG-related gene expression, postnatal cortical surface expansion, and adolescent shrinkage of cortical thickness. The presence of these 2 modes of development was robust to numerous sensitivity analyses. We conclude that human brain organization is disrupted during adolescence by remodeling of FC between association cortical and subcortical areas.

Sex-specific impact of prenatal androgens on social brain default mode subsystems.

Early-onset neurodevelopmental conditions (e.g., autism) affect males more frequently than females. Androgens may play a role in this male-bias by sex-differentially impacting early prenatal brain development, particularly neural circuits that later develop specialized roles in social cognition. Here, we find that increasing prenatal testosterone in humans is associated with later reduction of functional connectivity between social brain default mode (DMN) subsystems in adolescent males, but has no effect in females. Since testosterone can work directly via the androgen receptor (AR) or indirectly via the estrogen receptor through aromatase conversion to estradiol, we further examined how a potent non-aromatizable androgen, dihydrotestosterone (DHT), acts via the AR to influence gene expression in human neural stem cells (hNSC)-particularly for genes of high-relevance for DMN circuitry. DHT dysregulates a number of genes enriched for syndromic causes of autism and intellectual disability and for genes that in later development are expressed in anatomical patterns that highly correspond to the cortical midline DMN subsystem. DMN-related and DHT-affected genes (e.g., MEF2C) are involved in a number of synaptic processes, many of which impact excitation-inhibition balance. Androgens have male-specific prenatal influence over social brain circuitry in humans and may be relevant towards explaining some component of male-bias in early-onset neurodevelopmental conditions.

Altered Connectivity Between Cerebellum, Visual, and Sensory-Motor Networks in Autism Spectrum Disorder: Results from the EU-AIMS Longitudinal European Autism Project.

BACKGROUND: Resting-state functional magnetic resonance imaging-based studies on functional connectivity in autism spectrum disorder (ASD) have generated inconsistent results. Interpretation of findings is further hampered by small samples and a focus on a limited number of networks, with networks underlying sensory processing being largely underexamined. We aimed to comprehensively characterize ASD-related alterations within and between 20 well-characterized resting-state networks using baseline data from the EU-AIMS (European Autism Interventions-A Multicentre Study for Developing New Medications) Longitudinal European Autism Project. METHODS: Resting-state functional magnetic resonance imaging data was available for 265 individuals with ASD (7.5-30.3 years; 73.2% male) and 218 typically developing individuals (6.9-29.8 years; 64.2% male), all with IQ > 70. We compared functional connectivity within 20 networks-obtained using independent component analysis-between the ASD and typically developing groups, and related functional connectivity within these networks to continuous (overall) autism trait severity scores derived from the Social Responsiveness Scale Second Edition across all participants. Furthermore, we investigated case-control differences and autism trait-related alterations in between-network connectivity. RESULTS: Higher autism traits were associated with increased connectivity within salience, medial motor, and orbitofrontal networks. However, we did not replicate previously reported case-control differences within these networks. The between-network analysis did reveal case-control differences showing on average 1) decreased connectivity of the visual association network with somatosensory, medial, and lateral motor networks, and 2) increased connectivity of the cerebellum with these sensory and motor networks in ASD compared with typically developing subjects. CONCLUSIONS: We demonstrate ASD-related alterations in within- and between-network connectivity. The between-network alterations broadly affect connectivity between cerebellum, visual, and sensory-motor networks, potentially underlying impairments in multisensory and visual-motor integration frequently observed in ASD.

Ultra-high field MRI reveals mood-related circuit disturbances in depression: a comparison between 3-Tesla and 7-Tesla.

Ultra-high field 7-Tesla (7 T) MRI has the potential to advance our understanding of neuropsychiatric disorders, including major depressive disorder (MDD). To date, few studies have quantified the advantage of resting state functional MRI (fMRI) at 7 T compared to 3-Tesla (3 T). We conducted a series of experiments that demonstrate the improvement in temporal signal-to-noise ratio (TSNR) of a multi-echo multi-band fMRI protocol with ultra-high field 7 T MRI, compared to a similar protocol using 3 T MRI in healthy controls (HC). We also directly tested the enhancement in ultra-high field 7 T fMRI signal power by examining the ventral tegmental area (VTA), a small midbrain structure that is critical to the expected neuropathology of MDD but difficult to discern with standard 3 T MRI. We demonstrate up to 300% improvement in TSNR and resting state functional connectivity coefficients provided by ultra-high field 7 T fMRI compared to 3 T, indicating enhanced power for detection of functional neural architecture. A multi-echo based acquisition protocol and signal denoising pipeline afforded greater gain in signal power compared to classic acquisition and denoising pipelines. Furthermore, ultra-high field fMRI revealed mood-related neurocircuit disturbances in patients with MDD compared to HC, which were not detectable with 3 T fMRI. Ultra-high field 7 T fMRI may provide an effective tool for studying functional neural architecture relevant to MDD and other neuropsychiatric disorders.

Neural Correlates of Drug-Biased Choice in Currently Using and Abstinent Individuals With Cocaine Use Disorder.

BACKGROUND: The choice for drugs over alternative reinforcers is a translational hallmark feature of drug addiction. The neural basis of such drug-biased choice is not well understood, particularly in individuals with protracted drug abstinence who cannot ethically participate in studies that offer drug-using opportunities. METHODS: We developed a functional magnetic resonance imaging drug-choice task to examine the choice for viewing drug-related images, rather than for actually consuming a drug. Actively using (n = 18) and abstaining (n = 19) individuals with a history of cocaine use disorder (CUD: dependence or abuse) and matched healthy control subjects (n = 26) participated. RESULTS: Individuals with CUD, especially those actively using cocaine outside the laboratory, made more choices than control subjects to view images depicting cocaine (especially when directly compared against images depicting an alternative appetitive reinforcer [food]). Functional magnetic resonance imaging data revealed that in individuals with CUD, the act of making drug-related choices engaged brain regions implicated in choice difficulty or ambivalence (i.e., dorsal anterior cingulate cortex, which was higher in all individuals with CUD than control subjects). Drug-related choices in CUD also engaged brain regions implicated in reward (e.g., midbrain/ventral tegmental area, which was most activated in active users, although this region was not hypothesized a priori). CONCLUSIONS: These results help clarify the neural mechanisms underlying drug-biased choice in human addiction, which, beyond mechanisms involved in value assignment or reward, may critically involve mechanisms that contribute to resolving difficult decisions. Future studies are needed to validate these behavioral and neural abnormalities as markers of drug seeking and relapse in treatment contexts.

The Integration of Functional Brain Activity from Adolescence to Adulthood.

Age-related changes in human functional neuroanatomy are poorly understood. This is partly due to the limits of interpretation of standard fMRI. These limits relate to age-related variation in noise levels in data from different subjects, and the common use of standard adult brain parcellations for developmental studies. Here we used an emerging MRI approach called multiecho (ME)-fMRI to characterize functional brain changes with age. ME-fMRI acquires blood oxygenation level-dependent (BOLD) signals while also quantifying susceptibility-weighted transverse relaxation time (T2*) signal decay. This approach newly enables reliable detection of BOLD signal components at the subject level as opposed to solely at the group-average level. In turn, it supports more robust characterization of the variability in functional brain organization across individuals. We hypothesized that BOLD components in the resting state are not stable with age, and would decrease in number from adolescence to adulthood. This runs counter to the current assumptions in neurodevelopmental analyses of brain connectivity that the number of BOLD signal components is a random effect. From resting-state ME-fMRI of 51 healthy subjects of both sexes, between 8.3 and 46.2 years of age, we found a highly significant (r = -0.55, p ≪ 0.001) exponential decrease in the number of BOLD components with age. The number of BOLD components were halved from adolescence to the fifth decade of life, stabilizing in middle adulthood. The regions driving this change were dorsolateral prefrontal cortices, parietal cortex, and cerebellum. The functional network of these regions centered on the cerebellum. We conclude that an age-related decrease in BOLD component number concurs with the hypothesis of neurodevelopmental integration of functional brain activity. We show evidence that the cerebellum may play a key role in this process.SIGNIFICANCE STATEMENT Human brain development is ongoing from childhood to at least 30 years of age. Functional MRI (fMRI) is key for characterizing changes in brain function that accompany development. However, developmental fMRI studies have relied on reference maps of adult brain organization in the analysis of data from younger subjects. This approach may limit the characterization of functional activity patterns that are particular to children and adolescents. Here we used an emerging fMRI approach called multi-echo fMRI that is not susceptible to such biases when analyzing the variation in functional brain organization over development. We hypothesized an integration of the components of brain activity over development, and found that the number of components decreases exponentially, halving from 8 to 35 years of age. The brain regions most affected underlie executive function and coordination. In summary, we show major changes in the organization and integration of functional networks over development into adulthood, with both methodological and neurobiological implications for future lifespan and disease studies on brain connectivity.

Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.

"Functional connectivity" techniques are commonplace tools for studying brain organization. A critical element of these analyses is to distinguish variance due to neurobiological signals from variance due to nonneurobiological signals. Multiecho fMRI techniques are a promising means for making such distinctions based on signal decay properties. Here, we report that multiecho fMRI techniques enable excellent removal of certain kinds of artifactual variance, namely, spatially focal artifacts due to motion. By removing these artifacts, multiecho techniques reveal frequent, large-amplitude blood oxygen level-dependent (BOLD) signal changes present across all gray matter that are also linked to motion. These whole-brain BOLD signals could reflect widespread neural processes or other processes, such as alterations in blood partial pressure of carbon dioxide (pCO2) due to ventilation changes. By acquiring multiecho data while monitoring breathing, we demonstrate that whole-brain BOLD signals in the resting state are often caused by changes in breathing that co-occur with head motion. These widespread respiratory fMRI signals cannot be isolated from neurobiological signals by multiecho techniques because they occur via the same BOLD mechanism. Respiratory signals must therefore be removed by some other technique to isolate neurobiological covariance in fMRI time series. Several methods for removing global artifacts are demonstrated and compared, and were found to yield fMRI time series essentially free of motion-related influences. These results identify two kinds of motion-associated fMRI variance, with different physical mechanisms and spatial profiles, each of which strongly and differentially influences functional connectivity patterns. Distance-dependent patterns in covariance are nearly entirely attributable to non-BOLD artifacts.

Brain-behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder.

BACKGROUND: Childhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD. METHODS: We first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naïve adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype. RESULTS: Adults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain-symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD. CONCLUSIONS: Overall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain-symptom mediators.