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Entropy is an important trait for life as well as the human brain. Characterizing brain entropy (BEN) may provide an informative tool to assess brain states and brain functions. Yet little is known about the distribution and regional organization of BEN in normal brain. The purpose of this study was to examine the whole brain entropy patterns using a large cohort of normal subjects. A series of experiments were first performed to validate an approximate entropy measure regarding its sensitivity, specificity, and reliability using synthetic data and fMRI data. Resting state fMRI data from a large cohort of normal subjects (n = 1049) from multi-sites were then used to derive a 3-dimensional BEN map, showing a sharp low-high entropy contrast between the neocortex and the rest of brain. The spatial heterogeneity of resting BEN was further studied using a data-driven clustering method, and the entire brain was found to be organized into 7 hierarchical regional BEN networks that are consistent with known structural and functional brain parcellations. These findings suggest BEN mapping as a physiologically and functionally meaningful measure for studying brain functions.

Consistent resting brain activity patterns have been repeatedly demonstrated using measures derived from resting BOLD fMRI data. While those metrics are presumed to reflect underlying spontaneous brain activity (SBA), it is challenging to prove that association because resting BOLD fMRI metrics are purely model-free and scale-free variables. Cerebral blood flow (CBF) is typically closely coupled to brain metabolism and is used as a surrogate marker for quantifying regional brain function, including resting function. Assessing the correlations between resting BOLD fMRI measures and CBF correlation should provide a means of linking of those measures to the underlying SBA, and a means to quantify those scale-free measures. The purpose of this paper was to examine the CBF correlations of 3 widely used neuroimaging-based SBA measures, including seed-region based functional connectivity (FC), regional homogeneity (ReHo), and amplitude of low frequency fluctuation (ALFF). Test-retest data were acquired to check the stability of potential correlations across time. Reproducible posterior cingulate cortex (PCC) FC vs regional CBF correlations were found in much of the default mode network and visual cortex. Dorsal anterior cingulate cortex (ACC) FC vs CBF correlations were consistently found in bilateral prefrontal cortex. Both ReHo and ALFF were found to be reliably correlated with CBF in most of brain cortex. None of the assessed SBA measures was correlated with whole brain mean CBF. These findings suggest that resting BOLD fMRI-derived measures are coupled with regional CBF and are therefore linked to regional SBA.

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.QSIPrep is a software platform for processing of most diffusion MRI datasets and ensures that adequate workflows are used.

Although the hippocampus is one of the most studied structures in the human brain, limited quantitative data exist on its 3D organization, anatomical variability, and effects of disease on its subregions. Histological studies provide restricted reference information due to their 2D nature. In this paper, high-resolution (∼200 × 200 × 200 μm³) ex vivo MRI scans of 31 human hippocampal specimens are combined using a groupwise diffeomorphic registration approach into a 3D probabilistic atlas that captures average anatomy and anatomic variability of hippocampal subfields. Serial histological imaging in 9 of the 31 specimens was used to label hippocampal subfields in the atlas based on cytoarchitecture. Specimens were obtained from autopsies in patients with a clinical diagnosis of Alzheimer’s disease (AD; 9 subjects, 13 hemispheres), of other dementia (nine subjects, nine hemispheres), and in subjects without dementia (seven subjects, nine hemispheres), and morphometric analysis was performed in atlas space to measure effects of age and AD on hippocampal subfields. Disproportional involvement of the cornu ammonis (CA) 1 subfield and stratum radiatum lacunosum moleculare was found in AD, with lesser involvement of the dentate gyrus and CA2/3 subfields. An association with age was found for the dentate gyrus and, to a lesser extent, for CA1. Three-dimensional patterns of variability and disease and aging effects discovered via the ex vivo hippocampus atlas provide information highly relevant to the active field of in vivo hippocampal subfield imaging.

During sustained periods of a taxing cognitive workload, humans typically display time-on-task (TOT) effects, in which performance gets steadily worse over the period of task engagement. Arterial spin labeling (ASL) perfusion functional magnetic resonance imaging (fMRI) was used in this study to investigate the neural correlates of TOT effects in a group of 15 subjects as they performed a 20-min continuous psychomotor vigilance test (PVT). Subjects displayed significant TOT effects, as seen in progressively slower reaction times and significantly increased mental fatigue ratings after the task. Perfusion data showed that the PVT activates a right lateralized fronto-parietal attentional network in addition to the basal ganglia and sensorimotor cortices. The fronto-parietal network was less active during post-task rest compared to pre-task rest, and regional CBF decrease in this network correlated with performance decline. These results demonstrate the persistent effects of cognitive fatigue in the fronto-parietal network after a period of heavy mental work and indicate the critical role of this attentional network in mediating TOT effects. Furthermore, resting regional CBF in the thalamus and right middle frontal gyrus prior to task onset was predictive of subjects' subsequent performance decline, suggesting that resting CBF quantified by ASL perfusion fMRI may be a useful indicator of performance potential and a marker of the level of fatigue in the neural attentional system.

Increasing effort has been devoted to understanding the neural mechanisms underlying decision making during risk, yet little is known about the effect of voluntary choice on risk taking. The Balloon Analog Risk Task (BART), in which subjects inflate a virtual balloon that can either grow larger or explode [Lejuez, C.W., Read, J.P., Kahler, C.W., Richards, J.B., Ramsey, S.E., Stuart, G.L., Strong, D.R., Brown, R.A., 2002. Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task BART. J. Exp. Psychol. Appl. 8, 75–84.], provides an ecologically valid model to assess human risk taking propensity and behaviour. In the present study, we modified this task for use during functional magnetic resonance imaging (fMRI) and administered it in both an active choice mode and a passive no-choice mode in order to examine the neural correlates of voluntary and involuntary risk taking in the human brain. Voluntary risk in the active choice task is associated with robust activation in mesolimbic-frontal regions, including the midbrain, ventral and dorsal striatum, anterior insula, dorsal lateral prefrontal cortex (DLPFC), and anterior cingulate/medial frontal cortex (ACC/MFC), in addition to activation in visual pathway regions. However, these mesolimbic-frontal activation patterns were not observed for involuntary risk in the passive no-choice task. Decision making was associated with neural activity in the right DLPFC. These findings demonstrate the utility of the modified BART paradigms for using during fMRI to assess risk taking in the human brain, and suggest that recruitment of the brain mesolimbic-frontal pathway during risk-taking is contingent upon the agency of the risk taker. The present paradigm may be extended to pathological populations to determine the specific neural components of their impaired risk behavior.

Arterial spin labeling (ASL) can be implemented by combining different labeling schemes and readout sequences. In this study, the performance of 2D and 3D single-shot pulsed-continuous ASL (pCASL) sequences was assessed in a group of young healthy volunteers undergoing a baseline perfusion and a functional study with a sensory-motor activation paradigm. The evaluated sequences were 2D echo-planar imaging (2D EPI), 3D single-shot fast spin-echo with in-plane spiral readout (3D FSE spiral), and 3D single-shot gradient-and-spin-echo (3D GRASE). The 3D sequences were implemented with and without the addition of an optimized background suppression (BS) scheme. Labeling efficiency, signal-to-noise ratio (SNR), and gray matter (GM) to white matter (WM) contrast ratio were assessed in baseline perfusion measurements. 3D acquisitions without BS yielded 2-fold increments in spatial SNR, but no change in temporal SNR. The addition of BS to the 3D sequences yielded a 3-fold temporal SNR increase compared to the unsuppressed sequences. 2D EPI provided better GM-to-WM contrast ratio than the 3D sequences. The analysis of functional data at the subject level showed a 3-fold increase in statistical power for the BS 3D sequences, although the improvement was attenuated at the group level. 3D without BS did not increase the maximum t-values, however, it yielded larger activation clusters than 2D. These results demonstrate that BS 3D single-shot imaging sequences improve the performance of pCASL in baseline and activation studies, particularly for individual subject analyses where the improvement in temporal SNR translates into markedly enhanced power for task activation detection. ► 3D pCASL sequences increased perfusion spatial SNR by a factor of 2. ► The addition of BS to 3D readouts increased perfusion temporal SNR by a factor of 3. ► 2D EPI showed higher GM-to-WM CBF contrast ratio. ► Statistical power to detect functional activation was higher in 3D BS sequences. ► 3D BS single-shot sequences appear as the preferable readout choice in pCASL fMRI.

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across the lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we find the emergence of the cortical hierarchy revealed by the highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increases in a biphasic pattern featured by initial rapid and subsequently slower rate, and break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices are associated with enhanced language and motor skills, and frontoparietal association cortices with cognitive skills. The study discovers emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning. Here, the authors show the emergence of limbic-sensorimotor-association cortical hierarchy along with behavioral development during human infancy is underlaid by the spatiotemporal dynamics of cerebral blood flow meeting brain energy change demand.

Human risk tolerance is highly idiosyncratic and individuals often show distinctive preferences when faced with similar risky situations. However, the neural underpinnings of individual differences in risk-taking remain unclear. Here we combined structural and perfusion MRI and examined the associations between brain anatomy and individual risk-taking behavior/risk tolerance in a sample of 115 healthy participants during the Balloon Analogue Risk Task, a well-established sequential risky decision paradigm. Both whole brain and region-of-interest analyses showed that the left cerebellum gray matter volume (GMV) has a strong association with individual risk-taking behavior and risk tolerance, outperforming the previously reported associations with the amygdala and right posterior parietal cortex (PPC) GMV. Left cerebellum GMV also accounted for risk tolerance and risk-taking behavior changes with aging. However, regional cerebral blood flow (CBF) provided no additional predictive power. These findings suggest a novel cerebellar anatomical contribution to individual differences in risk tolerance. Further studies are necessary to elucidate the underestimated important role of cerebellum in risk-taking.

Puberty is the defining biological process of adolescent development, yet its effects on fundamental properties of brain physiology such as cerebral blood flow (CBF) have never been investigated. Capitalizing on a sample of 922 youths ages 8–22 y imaged using arterial spin labeled MRI as part of the Philadelphia Neurodevelopmental Cohort, we studied normative developmental differences in cerebral perfusion in males and females, as well as specific associations between puberty and CBF. Males and females had conspicuously divergent nonlinear trajectories in CBF evolution with development as modeled by penalized splines. Seventeen brain regions, including hubs of the executive and default mode networks, showed a robust nonlinear age-by-sex interaction that surpassed Bonferroni correction. Notably, within these regions the decline in CBF was similar between males and females in early puberty and only diverged in midpuberty, with CBF actually increasing in females. Taken together, these results delineate sex-specific growth curves for CBF during youth and for the first time to our knowledge link such differential patterns of development to the effects of puberty.