A precision functional atlas of personalized network topography and probabilities

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Two common and distinct forms of variation in human functional brain networks

The cortex has a characteristic layout with specialized functional areas forming distributed large-scale networks. However, substantial work shows striking variation in this organization across people, which relates to differences in behavior. While most previous work treats individual differences as linked to boundary shifts between the borders of regions, here we show that cortical 'variants' also occur at a distance from their typical position, forming ectopic intrusions. Both 'border' and 'ectopic' variants are common across individuals, but differ in their location, network associations, properties of subgroups of individuals, activations during tasks, and prediction of behavioral phenotypes. Border variants also track significantly more with shared genetics than ectopic variants, suggesting a closer link between ectopic variants and environmental influences. This work argues that these two dissociable forms of variation-border shifts and ectopic intrusions-must be separately accounted for in the analysis of individual differences in cortical systems across people.

Disuse-driven plasticity in the human thalamus and putamen

Motor adaptation in cortico-striato-thalamo-cortical loops has been studied mainly in animals using invasive electrophysiology. Here, we leverage functional neuroimaging in humans to study motor circuit plasticity in the human subcortex. We employed an experimental paradigm that combined two weeks of upper-extremity immobilization with daily resting-state and motor task fMRI before, during, and after the casting period. We previously showed that limb disuse leads to decreased functional connectivity (FC) of the contralateral somatomotor cortex (SM1) with the ipsilateral somatomotor cortex, increased FC with the cingulo-opercular network (CON) as well as the emergence of high amplitude, fMRI signal pulses localized in the contralateral SM1, supplementary motor area and the cerebellum. From our prior observations, it remains unclear whether the disuse plasticity affects the thalamus and striatum. We extended our analysis to include these subcortical regions and found that both exhibit strengthened cortical FC and spontaneous fMRI signal pulses induced by limb disuse. The dorsal posterior putamen and the central thalamus, mainly CM, VLP and VIM nuclei, showed disuse pulses and FC changes that lined up with fmri task activations from the Human connectome project motor system localizer, acquired before casting for each participant. Our findings provide a novel understanding of the role of the cortico-striato-thalamo-cortical loops in human motor plasticity and a potential link with the physiology of sleep regulation. Additionally, similarities with FC observation from Parkinson Disease (PD) questions a pathophysiological link with limb disuse.

Framewise multi-echo distortion correction for superior functional MRI

Functional MRI (fMRI) data are severely distorted by magnetic field (B0) inhomogeneities which currently must be corrected using separately acquired field map data. However, changes in the head position of a scanning participant across fMRI frames can cause changes in the B0 field, preventing accurate correction of geometric distortions. Additionally, field maps can be corrupted by movement during their acquisition, preventing distortion correction altogether. In this study, we use phase information from multi-echo (ME) fMRI data to dynamically sample distortion due to fluctuating B0 field inhomogeneity across frames by acquiring multiple echoes during a single EPI readout. Our distortion correction approach, MEDIC (Multi-Echo DIstortion Correction), accurately estimates B0 related distortions for each frame of multi-echo fMRI data. Here, we demonstrate that MEDIC's framewise distortion correction produces improved alignment to anatomy and decreases the impact of head motion on resting-state functional connectivity (RSFC) maps, in higher motion data, when compared to the prior gold standard approach (i.e., TOPUP). Enhanced framewise distortion correction with MEDIC, without the requirement for field map collection, furthers the advantage of multi-echo over single-echo fMRI.

Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer disease

Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels-a phenomenon termed "activity-dependent degeneration". Yet, two critical issues were unresolved. First, past research hasn't definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence. Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruption's severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in Aβ PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset. Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future.

Structure-Function Coupling in Highly Sampled Individual Brains

Structural connections (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to structural connections may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 minutes of diffusion-weighted MRI for SC and 360 minutes of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas.

SIGNIFICANCE STATEMENT

Structural connections between distant regions of the human brain support networked function that enables cognition and behavior. Improving our understanding of how structure enables function could allow better insight into how brain disconnection injuries impair brain function.Previous work using neuroimaging suggested that structure-function relationships vary systematically across the brain, with structure better explaining function in basic visual/motor areas than in higher-order areas. However, this work was conducted in group-averaged data, which may obscure details of individual-specific structure-function relationships.Using individual-specific densely sampled neuroimaging data, we found that in addition to visual/motor regions, structure strongly predicts function in specific circuits of the higher-order cingulate gyrus. The cingulate's structure-function relationship suggests that its organization may be unique among higher-order cortical regions.

White matter hyperintensity longitudinal morphometric analysis in association with Alzheimer disease

INTRODUCTION

Vascular damage in Alzheimer's disease (AD) has shown conflicting findings particularly when analyzing longitudinal data. We introduce white matter hyperintensity (WMH) longitudinal morphometric analysis (WLMA) that quantifies WMH expansion as the distance from lesion voxels to a region of interest boundary.

METHODS

WMH segmentation maps were derived from 270 longitudinal fluid-attenuated inversion recovery (FLAIR) ADNI images. WLMA was performed on five data-driven WMH patterns with distinct spatial distributions. Amyloid accumulation was evaluated with WMH expansion across the five WMH patterns.

RESULTS

The preclinical group had significantly greater expansion in the posterior ventricular WM compared to controls. Amyloid significantly associated with frontal WMH expansion primarily within AD individuals. WLMA outperformed WMH volume changes for classifying AD from controls primarily in periventricular and posterior WMH.

DISCUSSION

These data support the concept that localized WMH expansion continues to proliferate with amyloid accumulation throughout the entirety of the disease in distinct spatial locations.

Comparison of Resting State Functional Connectivity in Persons With and Without HIV: A Cross-sectional Study

BACKGROUND

This study examined the effects of human immunodeficiency virus (HIV) on resting state functional connectivity (RSFC) in a large cohort of people with HIV (PWH) and healthy controls without HIV (PWoH). Within PWH analyses focused on the effects of viral suppression and cognitive impairment on RSFC.

METHODS

A total of 316 PWH on stable combination antiretroviral therapy and 209 demographically matched PWoH were scanned at a single institution. Effects of the virus were examined by grouping PWH by detectable (viral load > 20 copies/mL; VLD) and undetectable (VLU) viral loads and as being cognitively impaired (CI) (Global Deficit Score ≥ 0.5) or cognitively normal (CN). Regression analysis, object oriented data analysis, and spring embedded graph models were applied to RSFC measures from 298 established brain regions of interest comprising 13 brain networks to examine group differences.

RESULTS

No significant RSFC differences were observed between PWH and PWoH. Within PWH, there were no significant differences in RSFC between VLD and VLU subgroups and CI and CN subgroups.

CONCLUSIONS

There were no significant effects of HIV on RSFC in our relatively large cohort of PWH and PWoH. Future studies could increase the sample size and combine with other imaging modalities.

BOLD cofluctuation 'events' are predicted from static functional connectivity

Recent work identified single time points ("events") of high regional cofluctuation in functional Magnetic Resonance Imaging (fMRI) which contain more large-scale brain network information than other, low cofluctuation time points. This suggested that events might be a discrete, temporally sparse signal which drives functional connectivity (FC) over the timeseries. However, a different, not yet explored possibility is that network information differences between time points are driven by sampling variability on a constant, static, noisy signal. Using a combination of real and simulated data, we examined the relationship between cofluctuation and network structure and asked if this relationship was unique, or if it could arise from sampling variability alone. First, we show that events are not discrete - there is a gradually increasing relationship between network structure and cofluctuation; ∼50% of samples show very strong network structure. Second, using simulations we show that this relationship is predicted from sampling variability on static FC. Finally, we show that randomly selected points can capture network structure about as well as events, largely because of their temporal spacing. Together, these results suggest that, while events exhibit particularly strong representations of static FC, there is little evidence that events are unique timepoints that drive FC structure. Instead, a parsimonious explanation for the data is that events arise from a single static, but noisy, FC structure.

Accuracy and reliability of diffusion imaging models

Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.

Brain function distinguishes female carriers and non-carriers of familial risk for autism

Background

Autism spectrum disorder (ASD) is characterized by high population-level heritability and a three-to-one male-to-female ratio that occurs independent of sex linkage. Prior research in a mixed-sex pediatric sample identified neural signatures of familial risk elicited by passive viewing of point light motion displays, suggesting the possibility that both resilience and risk of autism might be associated with brain responses to biological motion. To confirm a relationship between these signatures and inherited risk of autism, we tested them in families enriched for genetic loading through undiagnosed (“carrier”) females.

Methods

Using functional magnetic resonance imaging, we examined brain responses to passive viewing of point light displays—depicting biological versus non-biological motion—in a sample of undiagnosed adult females enriched for inherited susceptibility to ASD on the basis of affectation in their respective family pedigrees. Brain responses in carrier females were compared to responses in age-, SRS-, and IQ-matched non-carrier-females—i.e., females unrelated to individuals with ASD. We conducted a hypothesis-driven analysis focused on previously published regions of interest as well as exploratory, brain-wide analyses designed to characterize more fully the rich responses to this paradigm.

Results

We observed robust responses to biological motion. Notwithstanding, the 12 regions implicated by prior research did not exhibit the hypothesized interaction between group (carriers vs. controls) and point light displays (biological vs. non-biological motion). Exploratory, brain-wide analyses identified this interaction in three novel regions. Post hoc analyses additionally revealed significant variations in the time course of brain activation in 20 regions spanning occipital and temporal cortex, indicating group differences in response to point light displays (irrespective of the nature of motion) for exploration in future studies.

Limitations

We were unable to successfully eye-track all participants, which prevented us from being able to control for potential differences in eye gaze position.

Conclusions

These methods confirmed pronounced neural signatures that differentiate brain responses to biological and scrambled motion. Our sample of undiagnosed females enriched for family genetic loading enabled discovery of numerous contrasts between carriers and non-carriers of risk of ASD that may index variations in visual attention and motion processing related to genetic susceptibility and inform our understanding of mechanisms incurred by inherited liability for ASD.

Regional, not global, functional connectivity contributes to isolated focal dystonia

OBJECTIVE

To test the hypothesis that there is shared regional or global functional connectivity dysfunction in a large cohort of patients with isolated focal dystonia affecting different body regions compared to control participants. In this case-control study, we obtained resting-state MRI scans (three or four 7.3-minute runs) with eyes closed in participants with focal dystonia (cranial [17], cervical [13], laryngeal [18], or limb [10]) and age- and sex-matched controls.

METHODS

Rigorous preprocessing for all analyses was performed to minimize effect of head motion during scan acquisition (dystonia n = 58, control n = 47 analyzed). We assessed regional functional connectivity by computing a seed-correlation map between putamen, pallidum, and sensorimotor cortex and all brain voxels. We assessed significant group differences on a cluster-wise basis. In a separate analysis, we applied 300 seed regions across the cortex, cerebellum, basal ganglia, and thalamus to comprehensively sample the whole brain. We obtained participant whole-brain correlation matrices by computing the correlation between seed average time courses for each seed pair. Weighted object-oriented data analysis assessed group-level whole-brain differences.

RESULTS

Participants with focal dystonia had decreased functional connectivity at the regional level, within the striatum and between lateral primary sensorimotor cortex and ventral intraparietal area, whereas whole-brain correlation matrices did not differ between focal dystonia and control groups. Rigorous quality control measures eliminated spurious large-scale functional connectivity differences between groups.

CONCLUSION

Regional functional connectivity differences, not global network level dysfunction, contributes to common pathophysiologic mechanisms in isolated focal dystonia. Rigorous quality control eliminated spurious large-scale network differences between patients with focal dystonia and control participants.

Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits

To induce brain plasticity in humans, we casted the dominant upper extremity for 2 weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits.

A Critical, Event-Related Appraisal of Denoising in Resting-State fMRI Studies

This article advances two parallel lines of argument about resting-state functional magnetic resonance imaging (fMRI) signals, one empirical and one conceptual. The empirical line creates a four-part organization of the text: (1) head motion and respiration commonly cause distinct, major, unwanted influences (artifacts) in fMRI signals; (2) head motion and respiratory changes are, confoundingly, both related to psychological and clinical and biological variables of interest; (3) many fMRI denoising strategies fail to identify and remove one or the other kind of artifact; and (4) unremoved artifact, due to correlations of artifacts with variables of interest, renders studies susceptible to identifying variance of noninterest as variance of interest. Arising from these empirical observations is a conceptual argument: that an event-related approach to task-free scans, targeting common behaviors during scanning, enables fundamental distinctions among the kinds of signals present in the data, information which is vital to understanding the effects of denoising procedures. This event-related perspective permits statements like "Event X is associated with signals A, B, and C, each with particular spatial, temporal, and signal decay properties". Denoising approaches can then be tailored, via performance in known events, to permit or suppress certain kinds of signals based on their desirability.

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., 'motion' parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (>0.1 ​Hz, here referred to as 'HF-motion'), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0-2.5 ​s) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 to 2.5 ​s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants.

Correction of respiratory artifacts in MRI head motion estimates

Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison 'single-shot' datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.

Spatial and Temporal Organization of the Individual Human Cerebellum

The cerebellum contains the majority of neurons in the human brain and is unique for its uniform cytoarchitecture, absence of aerobic glycolysis, and role in adaptive plasticity. Despite anatomical and physiological differences between the cerebellum and cerebral cortex, group-average functional connectivity studies have identified networks related to specific functions in both structures. Recently, precision functional mapping of individuals revealed that functional networks in the cerebral cortex exhibit measurable individual specificity. Using the highly sampled Midnight Scan Club (MSC) dataset, we found the cerebellum contains reliable, individual-specific network organization that is significantly more variable than the cerebral cortex. The frontoparietal network, thought to support adaptive control, was the only network overrepresented in the cerebellum compared to the cerebral cortex (2.3-fold). Temporally, all cerebellar resting state signals lagged behind the cerebral cortex (125-380 ms), supporting the hypothesis that the cerebellum engages in a domain-general function in the adaptive control of all cortical processes.

Reward-related regions form a preferentially coupled system at rest

Neuroimaging studies have implicated a set of striatal and orbitofrontal cortex (OFC) regions that are commonly activated during reward processing tasks. Resting-state functional connectivity (RSFC) studies have demonstrated that the human brain is organized into several functional systems that show strong temporal coherence in the absence of goal-directed tasks. Here we use seed-based and graph-theory RSFC approaches to characterize the systems-level organization of putative reward regions of at rest. Peaks of connectivity from seed-based RSFC patterns for the nucleus accumbens (NAcc) and orbitofrontal cortex (OFC) were used to identify candidate reward regions which were merged with a previously used set of regions (Power et al., 2011). Graph-theory was then used to determine system-level membership for all regions. Several regions previously implicated in reward-processing (NAcc, lateral and medial OFC, and ventromedial prefrontal cortex) comprised a distinct, preferentially coupled system. This RSFC system is stable across a range of connectivity thresholds and shares strong overlap with meta-analyses of task-based reward studies. This reward system shares between-system connectivity with systems implicated in cognitive control and self-regulation, including the fronto-parietal, cingulo-opercular, and default systems. Differences may exist in the pathways through which control systems interact with reward system components. Whereas NAcc is functionally connected to cingulo-opercular and default systems, OFC regions show stronger connectivity with the fronto-parietal system. We propose that future work may be able to interrogate group or individual differences in connectivity profiles using the regions delineated in this work to explore potential relationships to appetitive behaviors, self-regulation failure, and addiction.

Loss of white matter integrity reflects tau accumulation in Alzheimer disease defined regions

OBJECTIVE

White matter (WM) projections were assessed from Alzheimer disease (AD) gray matter regions associated with β-amyloid (Aβ), tau, or neurodegeneration to ascertain relationship between WM structural integrity with Aβ and/or tau deposition.

METHODS

Participants underwent diffusion tensor imaging (DTI), PET Aβ ([¹⁸F]AV-45 [florbetapir]), and PET tau ([¹⁸F]AV-1451 [flortaucipir]) imaging. Probabilistic WM summary and individual tracts were created from either a composite or individual gray matter seed regions derived from Aβ, tau, and neurodegeneration. Linear regressions were performed for Aβ, age, tau and WM hyperintensities (WMH) to predict mean diffusivity (MD) or fractional anisotropy (FA) from the corresponding WM summaries or tracts.

RESULTS

Our cohort was composed of 59 cognitively normal participants and 10 cognitively impaired individuals. Aβ was not associated with DTI metrics in WM summary or individual tracts. Age and WMH strongly predicted MD and FA in several WM regions, with tau a significant predictor of MD only in the anterior temporal WM.

CONCLUSION

Tau, not Aβ, was associated with changes in anterior temporal WM integrity. WMH, a proxy for vascular damage, was strongly associated with axonal damage, but tau independently contributed to the model, suggesting an additional degenerative mechanism within tracts projecting from regions vulnerable to AD pathology. WM decline was associated with early tau accumulation, and further decline may reflect tau propagation in more advanced stages of AD.

On the Stability of BOLD fMRI Correlations

Measurement of correlations between brain regions (functional connectivity) using blood oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the functional organization of the brain. Recently, dynamic functional connectivity has emerged as a major topic in the resting-state BOLD fMRI literature. Here, using simulations and multiple sets of empirical observations, we confirm that imposed task states can alter the correlation structure of BOLD activity. However, we find that observations of "dynamic" BOLD correlations during the resting state are largely explained by sampling variability. Beyond sampling variability, the largest part of observed "dynamics" during rest is attributable to head motion. An additional component of dynamic variability during rest is attributable to fluctuating sleep state. Thus, aside from the preceding explanatory factors, a single correlation structure-as opposed to a sequence of distinct correlation structures-may adequately describe the resting state as measured by BOLD fMRI. These results suggest that resting-state BOLD correlations do not primarily reflect moment-to-moment changes in cognitive content. Rather, resting-state BOLD correlations may predominantly reflect processes concerned with the maintenance of the long-term stability of the brain's functional organization.

Individual Variability of the System-Level Organization of the Human Brain

Recent functional magnetic resonance imaging-based resting-state functional connectivity analyses of group average data have characterized large-scale systems that represent a high level in the organizational hierarchy of the human brain. These systems are likely to vary spatially across individuals, even after anatomical alignment, but the characteristics of this variance are unknown. Here, we characterized large-scale brain systems across two independent datasets of young adults. In these individuals, we were able to identify brain systems that were similar to those described in the group average, and we observed that individuals had consistent topological arrangement of the system features present in the group average. However, the size of system features varied across individuals in systematic ways, such that expansion of one feature of a given system predicted expansion of other parts of the system. Individual-specific systems also contained unique topological features not present in group average systems; some of these features were consistent across a minority of individuals. These effects were observed even after controlling for data quality and for the accuracy of anatomical registration. The variability characterized here has important implications for cognitive neuroscience investigations, which often assume the functional equivalence of aligned brain regions across individuals.

Evidence for Two Independent Factors that Modify Brain Networks to Meet Task Goals

Humans easily and flexibly complete a wide variety of tasks. To accomplish this feat, the brain appears to subtly adjust stable brain networks. Here, we investigate what regional factors underlie these modifications, asking whether networks are either altered at (1) regions activated by a given task or (2) hubs that interconnect different networks. We used fMRI "functional connectivity" (FC) to compare networks during rest and three distinct tasks requiring semantic judgments, mental rotation, and visual coherence. We found that network modifications during these tasks were independently associated with both regional activation and network hubs. Furthermore, active and hub regions were associated with distinct patterns of network modification (differing in their localization, topography of FC changes, and variability across tasks), with activated hubs exhibiting patterns consistent with task control. These findings indicate that task goals modify brain networks through two separate processes linked to local brain function and network hubs.

Postoperative seizure freedom does not normalize altered connectivity in temporal lobe epilepsy

OBJECTIVES

Specific changes in the functional connectivity of brain networks occur in patients with epilepsy. Yet whether such changes reflect a stable disease effect or one that is a function of active seizure burden remains unclear. Here, we longitudinally assessed the connectivity of canonical cognitive functional networks in patients with intractable temporal lobe epilepsy (TLE), both before and after patients underwent epilepsy surgery and achieved seizure freedom.

METHODS

Seventeen patients with intractable TLE who underwent epilepsy surgery with Engel class I outcome and 17 matched healthy controls took part in the study. The functional connectivity of a set of cognitive functional networks derived from typical cognitive tasks was assessed in patients, preoperatively and postoperatively, as well as in controls, using stringent methods of artifact reduction.

RESULTS

Preoperatively, functional networks in TLE patients differed significantly from healthy controls, with differences that largely, but not exclusively, involved the default mode and temporal/auditory subnetworks. However, undergoing epilepsy surgery and achieving seizure freedom did not lead to significant changes in network connectivity, with postoperative functional network abnormalities closely mirroring the preoperative state.

SIGNIFICANCE

This result argues for a stable chronic effect of the disease on brain connectivity, with changes that are largely "burned in" by the time a patient with intractable TLE undergoes epilepsy surgery, which typically occurs years after the initial diagnosis. The result has potential implications for the treatment of intractable epilepsy, suggesting that delaying surgical intervention that may achieve seizure freedom may lead to functional network changes that are no longer reversible by the time of epilepsy surgery.

Individual-specific features of brain systems identified with resting state functional correlations

Recent work has made important advances in describing the large-scale systems-level organization of human cortex by analyzing functional magnetic resonance imaging (fMRI) data averaged across groups of subjects. However, new findings have emerged suggesting that individuals' cortical systems are topologically complex, containing small but reliable features that cannot be observed in group-averaged datasets, due in part to variability in the position of such features along the cortical sheet. This previous work has reported only specific examples of these individual-specific system features; to date, such features have not been comprehensively described. Here we used fMRI to identify cortical system features in individual subjects within three large cross-subject datasets and one highly sampled within-subject dataset. We observed system features that have not been previously characterized, but 1) were reliably detected across many scanning sessions within a single individual, and 2) could be matched across many individuals. In total, we identified forty-three system features that did not match group-average systems, but that replicated across three independent datasets. We described the size and spatial distribution of each non-group feature. We further observed that some individuals were missing specific system features, suggesting individual differences in the system membership of cortical regions. Finally, we found that individual-specific system features could be used to increase subject-to-subject similarity. Together, this work identifies individual-specific features of human brain systems, thus providing a catalog of previously unobserved brain system features and laying the foundation for detailed examinations of brain connectivity in individuals.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR.

Multivariate pattern classification of pediatric Tourette syndrome using functional connectivity MRI

Tourette syndrome (TS) is a developmental neuropsychiatric disorder characterized by motor and vocal tics. Individuals with TS would benefit greatly from advances in prediction of symptom timecourse and treatment effectiveness. As a first step, we applied a multivariate method – support vector machine (SVM) classification – to test whether patterns in brain network activity, measured with resting state functional connectivity (RSFC) MRI, could predict diagnostic group membership for individuals. RSFC data from 42 children with TS (8–15 yrs) and 42 unaffected controls (age, IQ, in‐scanner movement matched) were included. While univariate tests identified no significant group differences, SVM classified group membership with ~70% accuracy (p < .001). We also report a novel adaptation of SVM binary classification that, in addition to an overall accuracy rate for the SVM, provides a confidence measure for the accurate classification of each individual. Our results support the contention that multivariate methods can better capture the complexity of some brain disorders, and hold promise for predicting prognosis and treatment outcome for individuals with TS.

Functional System and Areal Organization of a Highly Sampled Individual Human Brain

Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected-considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individual's systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals. VIDEO ABSTRACT.

Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

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SVMs classified 6 versus 12 month-old infants above chance based on fcMRI data alone.

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We carefully accounted for the effects of fcMRI motion artifact.

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These results coincide with a period of dramatic change in infant development.

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Two interpretations about connections supporting this age categorization are given.

Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations

The cortical surface is organized into a large number of cortical areas; however, these areas have not been comprehensively mapped in the human. Abrupt transitions in resting-state functional connectivity (RSFC) patterns can noninvasively identify locations of putative borders between cortical areas (RSFC-boundary mapping; Cohen et al. 2008). Here we describe a technique for using RSFC-boundary maps to define parcels that represent putative cortical areas. These parcels had highly homogenous RSFC patterns, indicating that they contained one unique RSFC signal; furthermore, the parcels were much more homogenous than a null model matched for parcel size when tested in two separate datasets. Several alternative parcellation schemes were tested this way, and no other parcellation was as homogenous as or had as large a difference compared with its null model. The boundary map-derived parcellation contained parcels that overlapped with architectonic mapping of areas 17, 2, 3, and 4. These parcels had a network structure similar to the known network structure of the brain, and their connectivity patterns were reliable across individual subjects. These observations suggest that RSFC-boundary map-derived parcels provide information about the location and extent of human cortical areas. A parcellation generated using this method is available at http://www.nil.wustl.edu/labs/petersen/Resources.html.

Decoding of MSTd population activity accounts for variations in the precision of heading perception

Humans and monkeys use both vestibular and visual motion (optic flow) cues to discriminate their direction of self-motion during navigation. A striking property of heading perception from optic flow is that discrimination is most precise when subjects judge small variations in heading around straight ahead, whereas thresholds rise precipitously when subjects judge heading around an eccentric reference. We show that vestibular heading discrimination thresholds in both humans and macaques also show a consistent, but modest, dependence on reference direction. We used computational methods (Fisher information, maximum likelihood estimation, and population vector decoding) to show that population activity in area MSTd predicts the dependence of heading thresholds on reference eccentricity. This dependence arises because the tuning functions for most neurons have a steep slope for directions near straight forward. Our findings support the notion that population activity in extrastriate cortex limits the precision of both visual and vestibular heading perception.

Identification of an essential molecular contact point on the duck hepatitis B virus reverse transcriptase

The hepadnaviral polymerase (P) functions in a complex with viral nucleic acids and cellular chaperones. To begin to identify contacts between P and its partners, we assessed the exposure of the epitopes of six monoclonal antibodies (MAbs) to the terminal protein domain of the duck hepatitis B virus P protein in a partially denaturing buffer (RIPA) and a physiological buffer (IPP150). All MAbs immunoprecipitated in vitro translated P well in RIPA, but three immunoprecipitated P poorly in IPP150. Therefore, the epitopes for these MAbs were obscured in the native conformation of P but were exposed when P was in RIPA. Epitopes for MAbs that immunoprecipitated P poorly in IPP150 were between amino acids (aa) 138 and 202. Mutation of a highly conserved motif within this region (T3; aa 176 to 183) improved the immunoprecipitation of P by these MAbs and simultaneously inhibited DNA priming by P. Peptides containing the T3 motif inhibited DNA priming in a dose-dependent manner, whereas eight irrelevant peptides did not. T3 function appears to be conserved among the hepadnaviruses because mutating T3 ablated DNA synthesis in both duck hepatitis B virus and hepatitis B virus. These results indicate that (i) the conserved T3 motif is a molecular contact point whose ligand can be competed by soluble T3 peptides, (ii) the occupancy of T3 obscures the epitopes for three MAbs, and (iii) proper occupancy of T3 by its ligand is essential for DNA priming. Therefore, small-molecule ligands that compete for binding to T3 with its natural ligand could form a novel class of antiviral drugs.

Similar kinematic properties for ocular following and smooth pursuit eye movements

Ocular following (OFR) is a short-latency visual stabilization response to the optic flow experienced during self-motion. It has been proposed that it represents the early component of optokinetic nystagmus (OKN) and that it is functionally linked to the vestibularly driven stabilization reflex during translation (translational vestibuloocular reflex, TVOR). Because no single eye movement can eliminate slip from the whole retina during translation, the OFR and the TVOR appear to be functionally related to maintaining visual acuity on the fovea. Other foveal-specific eye movements, like smooth pursuit and saccades, exhibit an eye-position-dependent torsional component, as dictated by what is known as the "half-angle rule" of Listing's law. In contrast, eye movements that stabilize images on the whole retina, such as the rotational vestibuloocular reflex (RVOR) and steady-state OKN do not. Consistent with the foveal stabilization hypothesis, it was recently shown that the TVOR is indeed characterized by an eye-position-dependent torsion, similar to pursuit eye movements. Here we have investigated whether the OFR exhibits three-dimensional kinematic properties consistent with a foveal response (i.e., similar to the TVOR and smooth pursuit eye movements) or with a whole-field stabilization function (similar to steady-state OKN). The OFR was elicited using 100-ms ramp motion of a full-field random dot pattern that moved horizontally at 20, 62, or 83 degrees/s. To study if an eye-position-dependent torsion is generated during the OFR, we varied the initial fixation position vertically within a range of +/-20 degrees . As a control, horizontal smooth pursuit eye movements were also elicited using step-ramp target motion (10, 20, or 30 degrees/s) at similar eccentric positions. We found that the OFR followed kinematic properties similar to those seen in pursuit and the TVOR with the eye-position-dependent torsional tilt of eye velocity having slopes that averaged 0.73 +/- 0.16 for OFR and 0.57 +/- 0.12 (means +/- SD) for pursuit. These findings support the notion that the OFR, like the TVOR and pursuit, are foveal image stabilization systems.