This study is an observational study that takes the existing longitudinal data from Alzheimer's disease Neuroimaging Initiative to examine the spatial correlation map of hippocampal subfield atrophy with CSF biomarkers and cognitive decline in the course of AD. This study included 421 healthy controls (HC), 557 patients of stable mild cognitive impairment (s-MCI), 304 Alzheimer's Disease (AD) patients, and 241 subjects who converted to be AD from MCI (c-MCI), and 6,525 MRI scans in a period from 2004 to 2019. Our findings revealed that all the hippocampal subfields showed their accelerated atrophy rate from cognitively normal aging to stable MCI and AD. The presubiculum, dentate gyrus, and fimbria showed greater atrophy beyond the whole hippocampus in the HC, s-MCI, and AD groups and corresponded to a greater decline of memory and attention in the s-MCI group. Moreover, the higher atrophy rates of the subiculum and CA2/3, CA4 were also associated with a greater decline in attention in the s-MCI group. Interestingly, patients with c-MCI showed that the presubiculum atrophy was associated with CSF tau levels and corresponded to the onset age of AD and a decline in attention in patients with c-MCI. These spatial correlation findings of the hippocampus suggested that the hippocampal subfields may not be equally impacted by normal aging, MCI, and AD, and their atrophy was selectively associated with declines in specific cognitive domains. The presubiculum atrophy was highlighted as a surrogate marker for the AD prognosis along with tau pathology and attention decline.

In vivo mapping of cerebrovascular oscillations in the 0.05-0.15 Hz remains difficult. Oscillations in the cerebrospinal fluid (CSF) represent a possible avenue for noninvasively tracking these oscillations using resting-state functional MRI (rs-fMRI), and have been used to correct for vascular oscillations in rs-fMRI functional connectivity. However, the relationship between low-frequency CSF and vascular oscillations remains unclear. In this study, we investigate this relationship using fast simultaneous rs-fMRI and photoplethysmogram (PPG), examining the 0.1 Hz PPG signal, heart-rate variability (HRV), pulse-intensity ratio (PIR), and the second derivative of the PPG (SDPPG). The main findings of this study are: (a) signals in different CSF regions are not equivalent in their associations with vascular and tissue rs-fMRI signals; (b) the PPG signal is maximally coherent with the arterial and CSF signals at the cardiac frequency, but coherent with brain tissue at ~0.2 Hz; (c) PIR is maximally coherent with the CSF signal near 0.03 Hz; and (d) PPG-related vascular oscillations only contribute to ~15% of the CSF (and arterial) signal in rs-fMRI. These findings caution against averaging all CSF regions when extracting physiological nuisance regressors in rs-fMRI applications, and indicate the drivers of the CSF signal are more than simply cardiac. Our study is an initial attempt at the refinement and standardization of how the CSF signal in rs-fMRI can be used and interpreted. It also paves the way for using rs-fMRI in the CSF as a potential tool for tracking cerebrovascular health through, for instance, the potential relationship between PIR and the CSF signal.

While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL, n = 41) and sporadic SVD (n = 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test-retest reliability of functional network measures in sporadic SVD patients participating in a high-frequency (monthly) serial imaging study (RUN DMC-InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN; fronto-parietal task control network, FPCN; visual network, VN; hand somatosensory-motor network, HSMN) were constructed based on resting-state multi-band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = -.44; p [corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = -.20, p = .047; direct path: std. beta = -.19, p = .25; total effect: std. beta = -.39, p = .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high-frequency serial MRI dataset of the sporadic SVD patients revealed poor test-retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD-related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age-related comorbidities, impedes the analysis in elderly SVD patients.

The habenula is a hub for cognitive and emotional signals that are relayed to the aminergic centers in the midbrain and, thus, plays an important role in goal-oriented behaviors. Although it is well described in rodents and non-human primates, the habenula functional network remains relatively uncharacterized in humans, partly because of the methodological challenges associated with the functional magnetic resonance imaging of small structures in the brain. Using high-resolution cardiac-gated resting state imaging in healthy humans and precisely identifying each participants' habenula, we show that the habenula is functionally coupled with the insula, parahippocampus, thalamus, periaqueductal grey, pons, striatum and substantia nigra/ventral tegmental area complex. Furthermore, by separately examining and comparing the functional maps from the left and right habenula, we provide the first evidence of an asymmetry in the functional connectivity of the habenula in humans. Hum Brain Mapp 37:2602-2615, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Two basic neuroimaging-based characterizations of white matter tracts are the magnitude of water diffusion along the principal tract orientation (axial diffusivity, AD) and water diffusion perpendicular to the principal orientation (radial diffusivity, RD). It is generally accepted that decreases in AD reflect disorganization, damage, or loss of axons, whereas increases in RD are indicative of disruptions to the myelin sheath. Previous reports have detailed the heritability of individual AD and RD measures, but have not examined the extent to which the same or different genetic or environmental factors influence these two phenotypes (except for corpus callosum). We implemented bivariate twin analyses to examine the shared and independent genetic influences on AD and RD. In the Vietnam Era Twin Study of Aging, 393 men (mean age = 61.8 years, SD = 2.6) underwent diffusion-weighted magnetic resonance imaging. We derived fractional anisotropy (FA), mean diffusivity (MD), AD, and RD estimates for 11 major bilateral white matter tracts and the mid-hemispheric corpus callosum, forceps major, and forceps minor. Separately, AD and RD were each highly heritable. In about three-quarters of the tracts, genetic correlations between AD and RD were >.50 (median = .67) and showed both unique and common variance. Genetic variance of FA and MD were predominately explained by RD over AD. These findings are important for informing genetic association studies of axonal coherence/damage and myelination/demyelination. Thus, genetic studies would benefit from examining the shared and unique contributions of AD and RD.

There is evidence that differences among individuals in white matter microstructure, as measured with diffusion tensor imaging (DTI), are under genetic control. However, little is known about the relative contribution of genetic and environmental effects on different diffusivity indices among late middle-aged adults. Here, we examined the magnitude of genetic influences for fractional anisotropy (FA), and mean (MD), axial (AD), and radial (RD) diffusivities in male twins aged 56-66 years old. Using an atlas-based registration approach to delineate individual white matter tracts, we investigated mean DTI-based indices within the corpus callosum, 12 bilateral tracts and all these regions of interest combined. All four diffusivity indices had high heritability at the global level (72%-80%). The magnitude of genetic effects in individual tracts varied from 0% to 82% for FA, 0% to 81% for MD, 8% to 77% for AD, and 0% to 80% for RD with most of the tracts showing significant heritability estimates. Despite the narrow age range of this community-based sample, age was correlated with all four diffusivity indices at the global level. In sum, all diffusion indices proved to have substantial heritability for most of the tracts and the heritability estimates were similar in magnitude for different diffusivity measures. Future studies could aim to discover the particular set of genes that underlie the significant heritability of white matter microstructure. Hum Brain Mapp 38:2026-2036, 2017. © 2017 Wiley Periodicals, Inc.

Studies linking meditation and brain structure are still relatively sparse, but the hippocampus is consistently implicated as one of the structures altered in meditation practitioners. To explore hippocampal features in the framework of meditation, we analyzed high-resolution structural magnetic resonance imaging data from 30 long-term meditators and 30 controls, closely matched for sex, age, and handedness. Hippocampal formations were manually traced following established protocols. In addition to calculating left and right hippocampal volumes (global measures), regional variations in surface morphology were determined by measuring radial distances from the hippocampal core to spatially matched surface points (local measures). Left and right hippocampal volumes were larger in meditators than in controls, significantly so for the left hippocampus. The presence and direction of this global effect was confirmed locally by mapping the exact spatial locations of the group differences. Altogether, radial distances were larger in meditators compared to controls, with up to 15% difference. These local effects were observed in several hippocampal regions in the left and right hemisphere though achieved significance primarily in the left hippocampal head. Larger hippocampal dimensions in long-term meditators may constitute part of the underlying neurological substrate for cognitive skills, mental capacities, and/or personal traits associated with the practice of meditation. Alternatively, given that meditation positively affects autonomic regulation and immune activity, altered hippocampal dimensions may be one result of meditation-induced stress reduction. However, given the cross-sectional design, the lack of individual stress measures, and the limited resolution of brain data, the exact underlying neuronal mechanisms remain to be established.

Cognitive control is a critical executive function. Many studies have combined general linear modeling and the stop signal task (SST) to delineate the component processes of cognitive control. For instance, by contrasting stop success (SS) and stop error (SE) trials in the SST, investigators examined regional responses to stop signal inhibition. In contrast to this parameterized approach, independent component analysis (ICA) elucidates brain networks subserving cognitive control. In our earlier work of 59 adults performing the SST during fMRI, we characterized six independent components (ICs). However, none of these ICs correlated with stop signal performance, raising questions about their behavioral validity. Here, in a larger sample (n = 100), we identified and explored 23 ICs for correlation with the stop signal reaction time (SSRT), a measure of the efficiency of response inhibition. At a corrected threshold (P < 0.0005), a paracentral lobule-midcingulate network and a left inferior parietal-supplementary motor-somatomotor network showed a positive correlation between SE beta weight and SSRT. In contrast, a midline cerebellum-thalamus-pallidum network showed a negative correlation between SE beta weight and SSRT. These findings suggest that motor preparation and execution prolongs the SSRT, likely via an interaction between the go and stop processes as suggested by the race model. Behaviorally, consistent with this hypothesis, the difference in G and SE reaction times is positively correlated with SSRT across subjects. These new results highlight the importance of cognitive motor regions in response inhibition and support the utility of ICA in uncovering functional networks for cognitive control in the SST.

Electroencephalography (EEG) is a common and inexpensive method to record neural activity in humans. However, it lacks spatial resolution making it difficult to determine which areas of the brain are responsible for the observed EEG response. Here we present a new easy-to-use method that relies on EEG topographical templates. Using MRI and fMRI scans of 50 participants, we simulated how the activity in each visual area appears on the scalp and averaged this signal to produce functionally defined EEG templates. Once created, these templates can be used to estimate how much each visual area contributes to the observed EEG activity. We tested this method on extensive simulations and on real data. The proposed procedure is as good as bespoke individual source localization methods, robust to a wide range of factors, and has several strengths. First, because it does not rely on individual brain scans, it is inexpensive and can be used on any EEG data set, past or present. Second, the results are readily interpretable in terms of functional brain regions and can be compared across neuroimaging techniques. Finally, this method is easy to understand, simple to use and expandable to other brain sources.

Autism spectrum disorder is a heterogeneous disorder of brain development with wide ranging cognitive deficits. Typically diagnosed before age 3, autism spectrum disorder is behaviorally defined but patients are thought to have protracted alterations in brain maturation. With longitudinal magnetic resonance imaging (MRI), we mapped an anomalous developmental trajectory of the brains of autistic compared with those of typically developing children and adolescents. Using tensor-based morphometry, we created 3D maps visualizing regional tissue growth rates based on longitudinal brain MRI scans of 13 autistic and seven typically developing boys (mean age/interscan interval: autism 12.0 ± 2.3 years/2.9 ± 0.9 years; control 12.3 ± 2.4/2.8 ± 0.8). The typically developing boys demonstrated strong whole brain white matter growth during this period, but the autistic boys showed abnormally slowed white matter development (P = 0.03, corrected), especially in the parietal (P = 0.008), temporal (P = 0.03), and occipital lobes (P = 0.02). We also visualized abnormal overgrowth in autism in gray matter structures such as the putamen and anterior cingulate cortex. Our findings reveal aberrant growth rates in brain regions implicated in social impairment, communication deficits and repetitive behaviors in autism, suggesting that growth rate abnormalities persist into adolescence. Tensor-based morphometry revealed persisting growth rate anomalies long after diagnosis, which has implications for evaluation of therapeutic effects.

Antisocial behavior (ASB) is believed to have neural substrates; however, the association between ASB and functional brain networks remains unclear. The temporal variability of the functional connectivity (or dynamic FC) derived from resting-state functional MRI has been suggested as a useful metric for studying abnormal behaviors including ASB. This is the first study using low-frequency fluctuations of the dynamic FC to unravel potential system-level neural correlates with ASB. Specifically, we individually associated the dynamic FC patterns with the ASB scores (measured by Antisocial Process Screening Device) of the male offenders (age: 23.29 ± 3.36 years) based on machine learning. Results showed that the dynamic FCs were associated with individual ASB scores. Moreover, we found that it was mainly the inter-network dynamic FCs that were negatively associated with the ASB severity. Three major high-order cognitive functional networks and the sensorimotor network were found to be more associated with ASB. We further found that impaired behavior in the ASB subjects was mainly associated with decreased FC dynamics in these networks, which may explain why ASB subjects usually have impaired executive control and emotional processing functions. Our study shows that temporal variation of the FC could be a promising tool for ASB assessment, treatment, and prevention.

Cerebellar morphology and function have been implicated in a variety of developmental disorders, and in healthy aging. Although recent work has sought to characterize the relationships between volume and age in this structure during adolescence, young, and older adulthood, there have been no investigations of regional cerebellar volume from adolescence through late middle age. Middle age in particular has been largely understudied, and investigating this period of the lifespan may be especially important for our understanding of senescence. Understanding regional patterns of cerebellar volume with respect to age during this portion of the lifespan may provide important insight into healthy aging and cognitive function as well as pathology from adolescence into later life. We investigated regional cerebellar volume using a highly novel lobular segmentation approach in conjunction with a battery of cognitive tasks in a cross-sectional sample of 123 individuals from 12 to 65 years old. Our results indicated that regional cerebellar volumes show different patterns with respect to age. In particular, the more posterior aspect of the neocerebellum follows a quadratic "inverse-U" pattern while the vermis and anterior cerebellum follow logarithmic patterns. In addition, we quantified the relationships between age and a variety of cognitive assessments and found relationships between regional cerebellar volumes and performance. Finally, exploratory analyses of sex differences in the relationships between regional cerebellar volume, age, and cognition were investigated. Taken together, these results provide key insights into the development and aging of the human cerebellum, and its role in cognitive function across the lifespan.

Executive function (EF) is a set of cognitive capabilities considered essential for successful daily living, and is negatively affected by ageing and neurodegenerative conditions. Underpinning EF performance are functional nodes in the executive control network (ECN), while the structural connectivity underlying this network is not well understood. In this paper, we evaluated the structural white matter tracts that interconnect the ECN and investigated their relationship to the EF performance. Using high-angular resolution diffusion MRI data, we performed tractography analysis of structural connectivity in a cognitively normal cohort (n = 140), specifically targeting the connectivity between ECN nodes. Our data revealed the presence of a strongly-connected "structural core" of the ECN comprising three components: interhemispheric frontal connections, a fronto-parietal subnetwork and fronto-striatal connections between right dorsolateral prefrontal cortex and right caudate. These pathways were strongly correlated with EF performance (p = .003). Post-hoc analysis of subregions within the significant ECN connections showed that these effects were driven by a highly specific subset of interconnected cortical regions. The structural core subnetwork of the functional ECN may be an important feature crucial to a better future understanding of human cognition and behaviour.

In day-to-day life, we need to apply strategies to cascade different actions for efficient unfolding of behavior. While deficits in action cascading are examined extensively, almost nothing is known about the neuronal mechanisms mediating superior performance above the normal level. To examine this question, we investigate action control in airplane pilot trainees. We use a stop-change paradigm that is able to estimate the efficiency of action cascading on the basis of mathematical constraints. Behavioral and EEG data is analyzed along these constraints and integrated with neurochemical data obtained using Magnetic Resonance Spectroscopy (MRS) from the striatal gamma-aminobutyric acid (GABA) -ergic system. We show that high performance in action cascading, as exemplified in airplane pilot trainees, can be driven by intensified attentional processes, circumventing response selection processes. The results indicate that the efficiency of action cascading and hence the speed of responding as well as attentional gating functions are modulated by striatal GABA and Glutamate + Glutamine concentrations. In superior performance in action cascading similar increases in the concentrations of GABA and Glutamate + Glutamine lead to stronger neurophysiological and behavioral effects as compared to subjects with normal performance in action cascading.

Following long-duration spaceflight, some astronauts exhibit ophthalmic structural changes referred to as Spaceflight Associated Neuro-ocular Syndrome (SANS). Optic disc edema is a common sign of SANS. The origin and effects of SANS are not understood as signs of SANS have not manifested in previous spaceflight analog studies. In the current spaceflight analog study, 11 subjects underwent 30 days of strict head down-tilt bed rest in elevated ambient carbon dioxide (HDBR+CO2 ). Using functional magnetic resonance imaging (fMRI), we acquired resting-state fMRI data at 6 time points: before (2), during (2), and after (2) the HDBR+CO2 intervention. Five participants developed optic disc edema during the intervention (SANS subgroup) and 6 did not (NoSANS group). This occurrence allowed us to explore whether development of signs of SANS during the spaceflight analog impacted resting-state functional connectivity during HDBR+CO2 . In light of previous work identifying genetic and biochemical predictors of SANS, we further assessed whether the SANS and NoSANS subgroups exhibited differential patterns of resting-state functional connectivity prior to the HDBR+CO2 intervention. We found that the SANS and NoSANS subgroups exhibited distinct patterns of resting-state functional connectivity changes during HDBR+CO2 within visual and vestibular-related brain networks. The SANS and NoSANS subgroups also exhibited different resting-state functional connectivity prior to HDBR+CO2 within a visual cortical network and within a large-scale network of brain areas involved in multisensory integration. We further present associations between functional connectivity within the identified networks and previously identified genetic and biochemical predictors of SANS. Subgroup differences in resting-state functional connectivity changes may reflect differential patterns of visual and vestibular reweighting as optic disc edema develops during the spaceflight analog. This finding suggests that SANS impacts not only neuro-ocular structures, but also functional brain organization. Future prospective investigations incorporating sensory assessments are required to determine the functional significance of the observed connectivity differences.

Gamma-hydroxybutyrate acid (GHB) is a recreational drug with a high addictive potential. Severe side effects such as GHB-induced coma are common and linked to increased emergency room attendances. Task-based functional-imaging studies have revealed an association between the regular use of GHB and multiple GHB-induced comas, and altered neurocognitive function. However the effects of multiple GHB-induced comas and regular GHB-use on intrinsic brain connectivity during rest remain unknown. The study population consisted of 23 GHB-users with ≥4 GHB-induced comas (GHB-Coma), 22 GHB-users who never experienced a GHB-induced coma (GHB-NoComa) and 24 polydrug users who never used GHB (No-GHB). Resting-state scans were collected to assess resting-state functional-connectivity within and between the default mode network (DMN), the bilateral central executive network (CEN) and the salience network (SN). The GHB-NoComa group showed decreased rsFC of the right CEN with a region in the anterior cingulate cortex (pFWE  = 0.048) and decreased rsFC between the right CEN and the DMN (pFWE  = 0.048) when compared with the No-GHB group. These results suggest that regular GHB-use is associated with decreased rsFC within the right CEN and between the right CEN and the DMN. The presence of multiple GHB-induced comas is not associated with (additional) alterations in rsFC.

Temporal lobe epilepsy (TLE) is a network disorder with a high incidence of memory impairment. Memory processing ability highly depends on the dynamic coordination between distinct modules within the hippocampal network. Here, we investigate the relationship between memory phenotypes and modular alterations of dynamic functional connectivity (FC) in the hippocampal network in TLE patients. Then, 31 healthy controls and 66 TLE patients with hippocampal sclerosis were recruited. The patients were classified into memory-intact (MI, 35 cases) group and memory-deficit (MD, 31 cases) group, each based on individual's Wechsler Memory Scale-Revised score. The sliding-windows approach and graph theory analysis were used to analyze the hippocampal network based on resting state functional magnetic resonance imaging. Temporal properties and modular metrics were calculated. Two discrete and switchable states were revealed: a high modularized state (State I) and a low modularized state (State II), which corresponded to either anterior or posterior hippocampal network dominated pattern. TLE was prone to drive less State I but more State II, and the tendency was more obvious in TLE-MD. Additionally, TLE-MD showed more widespread alterations of modular properties compared with TLE-MI across two states. Furthermore, the dynamic modularity features had unique superiority in discriminating TLE-MD from TLE-MI. These findings demonstrated that state transitions and modular function of dissociable hippocampal networks were altered in TLE and more importantly, they could reflect different memory phenotypes. The trend revealed potential values of dynamic FC in elucidating the mechanism underlying memory impairments in TLE.

Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition.

Internet gaming disorder (IGD) and tobacco use disorder (TUD) are globally common, non-substance-related disorders and substance-related disorders worldwide, respectively. Recognizing the commonalities between IGD and TUD will deepen understanding of the underlying mechanisms of addictive behavior and excessive online gaming. Using node strength, 141 resting-state data were collected in this study to compute network homogeneity. The participants included participants with IGD (PIGD: n = 34, male = 29, age: 15-25 years), participants with TUD (PTUD: n = 33, male = 33, age: 19-42 years), and matched healthy controls (control-for-IGD: n = 41, male = 38, age: 17-32 years; control-for-TUD: n = 33, age: 21-27 years). PIGD and PTUD exhibited common enhanced node strength between the subcortical and motor networks. Additionally, a common enhanced resting-state functional connectivity (RSFC) was found between the right thalamus and right postcentral gyrus in PIGD and PTUD. Node strength and RSFC were used to distinguish PIGD and PTUD from their respective healthy controls. Interestingly, models trained on PIGD versus controls could classify PTUD versus controls and vice versa, suggesting that these disorders share common neurological patterns. Enhanced connectivity may indicate a greater association between rewards and behaviors, inducing addiction behaviors without flexible and complex regulation. This study discovered that the connectivity between the subcortical and motor networks is a potential biological target for developing addiction treatment in the future.

Attention deficit is a critical symptom that impairs social functioning in adolescents with major depressive disorder (MDD). In this study, we aimed to explore the dynamic neural network activity associated with attention deficits and its relationship with clinical outcomes in adolescents with MDD. We included 188 adolescents with MDD and 94 healthy controls. By combining psychophysics, resting-state electroencephalography (EEG), and functional magnetic resonance imaging (fMRI) techniques, we aimed to identify dynamic network features through the investigation of EEG microstate characteristics and related temporal network features in adolescents with MDD. At baseline, microstate analysis revealed that the occurrence of Microstate C in the patient group was lower than that in healthy controls, whereas the duration and coverage of Microstate D increased in the MDD group. Mediation analysis revealed that the probability of transition from Microstate C to D mediated anhedonia and attention deficits in the MDD group. fMRI results showed that the temporal variability of the dorsal attention network (DAN) was significantly weaker in patients with MDD than in healthy controls. Importantly, the temporal variability of DAN mediated the relationship between anhedonia and attention deficits in the patient group. After acute-stage treatment, the response prediction group (RP) showed improvement in Microstates C and D compared to the nonresponse prediction group (NRP). For resting-state fMRI data, the temporal variability of DAN was significantly higher in the RP group than in the NRP group. Overall, this study enriches our understanding of the neural mechanisms underlying attention deficits in patients with MDD and provides novel clinical biomarkers.