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Living in poverty places children at very high risk for problems across a variety of domains, including schooling, behavioral regulation, and health. Aspects of cognitive functioning, such as information processing, may underlie these kinds of problems. How might poverty affect the brain functions underlying these cognitive processes? Here, we address this question by observing and analyzing repeated measures of brain development of young children between five months and four years of age from economically diverse backgrounds (n = 77). In doing so, we have the opportunity to observe changes in brain growth as children begin to experience the effects of poverty. These children underwent MRI scanning, with subjects completing between 1 and 7 scans longitudinally. Two hundred and three MRI scans were divided into different tissue types using a novel image processing algorithm specifically designed to analyze brain data from young infants. Total gray, white, and cerebral (summation of total gray and white matter) volumes were examined along with volumes of the frontal, parietal, temporal, and occipital lobes. Infants from low-income families had lower volumes of gray matter, tissue critical for processing of information and execution of actions. These differences were found for both the frontal and parietal lobes. No differences were detected in white matter, temporal lobe volumes, or occipital lobe volumes. In addition, differences in brain growth were found to vary with socioeconomic status (SES), with children from lower-income households having slower trajectories of growth during infancy and early childhood. Volumetric differences were associated with the emergence of disruptive behavioral problems.

Social anxiety disorder (SAD) is a common and disabling condition characterized by excessive fear and avoidance of public scrutiny. Psychoradiology studies have suggested that the emotional and behavior deficits in SAD are associated with abnormalities in regional brain function and functional connectivity. However, little is known about whether intrinsic functional brain networks in patients with SAD are topologically disrupted. Here, we collected resting-state fMRI data from 33 drug-naive patients with SAD and 32 healthy controls (HC), constructed functional networks with 34 predefined regions based on previous meta-analytic research with task-based fMRI in SAD, and performed network-based statistic and graph-theory analyses. The network-based statistic analysis revealed a single connected abnormal circuitry including the frontolimbic circuit (termed the “fear circuit”, including the dorsolateral prefrontal cortex, ventral medial prefrontal cortex and insula) and posterior cingulate/occipital areas supporting perceptual processing. In this single altered network, patients with SAD had higher functional connectivity than HC. At the global level, graph-theory analysis revealed that the patients exhibited a lower normalized characteristic path length than HC, which suggests a disorder-related shift of network topology toward randomized configurations. SAD-related deficits in nodal degree, efficiency and participation coefficient were detected in the parahippocampal gyrus, posterior cingulate cortex, dorsolateral prefrontal cortex, insula and the calcarine sulcus. Aspects of abnormal connectivity were associated with anxiety symptoms. These findings highlight the aberrant topological organization of functional brain network organization in SAD, which provides insights into the neural mechanisms underlying excessive fear and avoidance of social interactions in patients with debilitating social anxiety. •We defined 34 network nodes based on task-based SAD fMRI meta-analytic studies.•SAD had higher functional connectivity in a single connected component.•SAD had a shift of brain network topology toward randomized configurations.•Abnormal connectivity in SAD was significantly associated with anxiety symptoms.

The molecular architecture of amyloids formed in vivo can be interrogated using luminescent conjugated oligothiophenes (LCOs), a unique class of amyloid dyes. When bound to amyloid, LCOs yield fluorescence emission spectra that reflect the 3D structure of the protein aggregates. Given that synthetic amyloid-β peptide (Aβ) has been shown to adopt distinct structural conformations with different biological activities, we asked whether Aβ can assume structurally and functionally distinct conformations within the brain. To this end, we analyzed the LCO-stained cores of β-amyloid plaques in postmortem tissue sections from frontal, temporal, and occipital neocortices in 40 cases of familial Alzheimer’s disease (AD) or sporadic (idiopathic) AD (sAD). The spectral attributes of LCO-bound plaques varied markedly in the brain, but the mean spectral properties of the amyloid cores were generally similar in all three cortical regions of individual patients. Remarkably, the LCO amyloid spectra differed significantly among some of the familial and sAD subtypes, and between typical patients with sAD and those with posterior cortical atrophy AD. Neither the amount of Aβ nor its protease resistance correlated with LCO spectral properties. LCO spectral amyloid phenotypes could be partially conveyed to Aβ plaques induced by experimental transmission in a mouse model. These findings indicate that polymorphic Aβ-amyloid deposits within the brain cluster as clouds of conformational variants in different AD cases. Heterogeneity in the molecular architecture of pathogenic Aβ among individuals and in etiologically distinct subtypes of AD justifies further studies to assess putative links between Aβ conformation and clinical phenotype.

Second-generation antipsychotics are utilized extensively in the treatment of psychotic disorders and other psychiatric conditions, but the effects of these medications on human brain white matter are not well understood. We thus investigated the effects of second-generation antipsychotics on white matter integrity using tract-based spatial statistics in patients experiencing a first episode of psychosis with little or no prior antipsychotic exposure, and how potential changes were associated with metabolic side effects. Thirty-five (26 men/9 women) patients experiencing a first episode of psychosis received diffusion tensor imaging (DTI) exams, clinical assessments, and provided fasting blood samples at the onset of antipsychotic treatment, and then again after 12 weeks of treatment with either risperidone or aripiprazole in a double-blind randomized clinical trial. In addition, 35 (26 men/9 women) healthy volunteers received DTI exams at a baseline time point and then after 12 weeks. Patients demonstrated significant (p<0.05; family-wise error corrected) fractional anisotropy reductions within the parietal and occipital white matter following antipsychotic treatment. Greater overall fractional anisotropy reduction was significantly correlated with greater increases in low-density lipoprotein. There were no significant fractional anisotropy increases among patients following treatment. Moreover, healthy volunteers did not demonstrate either significant increases or decreases in fractional anisotropy across a comparable 12-week interval. The use of antipsychotics may be associated with a subtle loss of white matter integrity that is related to greater side effects, thus raising potentially important considerations regarding risk/benefit in their usage. Limitations of the current study, however, include a prior history of substance use among patients and our inability to exclude the possibility of disease progression.

Abstract The dopamine hypothesis of schizophrenia implies that alterations in the dopamine system cause functional abnormalities in the brain that may converge to aberrant salience attribution and eventually lead to psychosis. Indeed, widespread brain disconnectivity across the psychotic spectrum has been revealed by resting-state functional magnetic resonance imaging (rs-fMRI). However, the dopaminergic involvement in intrinsic functional connectivity (iFC) and its putative relationship to the development of psychotic spectrum disorders remains partly unclear—in particular at the low-end of the psychosis continuum. Therefore, we investigated dopamine-induced changes in striatal iFC and their modulation by psychometrically assessed schizotypy. Our randomized, double-blind placebo-controlled study design included 54 healthy, right-handed male participants. Each participant was assessed with the Schizotypal Personality Questionnaire (SPQ) and underwent 10 minutes of rs-fMRI scanning. Participants then received either a placebo or 200 mg of L-DOPA, a dopamine precursor. We analyzed iFC of 6 striatal seeds that are known to evoke modulation of dopamine-related networks. The main effect of L-DOPA was a significant functional decoupling from the right ventral caudate to both occipital fusiform gyri. This dopamine-induced decoupling emerged primarily in participants with low SPQ scores, while participants with high positive SPQ scores showed decoupling indifferently of the L-DOPA challenge. Taken together, these findings demonstrate that schizotypal traits may be the result of dopamine-induced striato-occipital decoupling.

The human ventral visual stream consists of several areas that are considered processing stages essential for perception and recognition. A fundamental microanatomical feature differentiating areas is cytoarchitecture, which refers to the distribution, size, and density of cells across cortical layers. Because cytoarchitectonic structure is measured in 20-micron-thick histological slices of postmortem tissue, it is difficult to assess (a) how anatomically consistent these areas are across brains and (b) how they relate to brain parcellations obtained with prevalent neuroimaging methods, acquired at the millimeter and centimeter scale. Therefore, the goal of this study was to (a) generate a cross-validated cytoarchitectonic atlas of the human ventral visual stream on a whole brain template that is commonly used in neuroimaging studies and (b) to compare this atlas to a recently published retinotopic parcellation of visual cortex (Wang et al., 2014). To achieve this goal, we generated an atlas of eight cytoarchitectonic areas: four areas in the occipital lobe (hOc1-hOc4v) and four in the fusiform gyrus (FG1-FG4), then we tested how the different alignment techniques affect the accuracy of the resulting atlas. Results show that both cortex-based alignment (CBA) and nonlinear volumetric alignment (NVA) generate an atlas with better cross-validation performance than affine volumetric alignment (AVA). Additionally, CBA outperformed NVA in 6/8 of the cytoarchitectonic areas. Finally, the comparison of the cytoarchitectonic atlas to a retinotopic atlas shows a clear correspondence between cytoarchitectonic and retinotopic areas in the ventral visual stream. The successful performance of CBA suggests a coupling between cytoarchitectonic areas and macroanatomical landmarks in the human ventral visual stream, and furthermore, that this coupling can be utilized for generating an accurate group atlas. In addition, the coupling between cytoarchitecture and retinotopy highlights the potential use of this atlas in understanding how anatomical features contribute to brain function. We make this cytoarchitectonic atlas freely available in both BrainVoyager and FreeSurfer formats (http://vpnl.stanford.edu/vcAtlas). The availability of this atlas will enable future studies to link cytoarchitectonic organization to other parcellations of the human ventral visual stream with potential to advance the understanding of this pathway in typical and atypical populations. •We provide a cross-validated cytoarchitectonic atlas of the human ventral stream.•The atlas is publically available in BrainVoyager and FreeSurfer formats.•Study compared how alignment methods affect atlas cross-validation performance.•Cortex-based alignment outperforms both affine and nonlinear volume alignments.•Coupling between cytoarchitectonic and retinotopic parcellations of ventral stream.

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder characterized by atypical social communication and repetitive behaviors. In this study, we applied a multimodal approach to investigate brain structural connectivity, resting state activity, and surface area, as well as their associations with the core symptoms of ASD. Data from forty boys with ASD (mean age, 11.5 years; age range, 5.5–19.5) and forty boys with typical development (TD) (mean age, 12.3; age range, 5.8–19.7) were extracted from the Autism Brain Imaging Data Exchange II (ABIDE II) for data analysis. We found significantly decreased structural connectivity, resting state brain activity, and surface area at the occipital cortex in boys with ASD compared to boys with TD. In addition, we found that resting state brain activity and surface area in the lateral occipital cortex was negatively correlated with communication scores in boys with ASD. Our results suggest that decreased structural connectivity and resting-state brain activity in the occipital cortex may impair the integration of verbal and non-verbal communication cues in boys with ASD, thereby impacting their social development. •We applied a multimodal approach to investigate the neuropathology of ASD.•ASD showed decreased fALFF and surface area at the occipital cortex.•ASD is associated with decreased FA and track length in left CCG and right UNC.•Functional and structural changes were associated with ASD communication scores.

Working memory is imprecise, and these imprecisions can be explained by the combined influences of random diffusive error and systematic drift toward a set of stable states (\"attractors\"). However, the neural correlates of diffusion and drift remain unknown. Here, we investigated how delay-period activity in frontal and parietal cortex, which is known to correlate with the decline in behavioral memory precision observed with increasing memory load, might relate to diffusion and drift. We analyzed data from an existing experiment in which subjects performed delayed recall for line orientation, at different loads, during functional magnetic resonance imaging (fMRI) scanning. To quantify the influence of drift and diffusion, we modeled subjects' behavior using a discrete attractor model and calculated within-subject correlation between frontal and parietal delay-period activity and whole-trial estimates of drift and diffusion. We found that although increases in frontal and parietal activity were associated with increases in both diffusion and drift, diffusion explained the most variance in frontal and parietal delay-period activity. In comparison, a subsequent whole-brain regression analysis showed that drift, rather than diffusion, explained the most variance in delay-period activity in lateral occipital cortex. These results are consistent with a model of the differential recruitment of general frontoparietal mechanisms in response to diffusive noise and of stimulus-specific biases in occipital cortex.

Resting-state fMRI is a novel approach to measure spontaneous brain activity in patients with major depressive disorder (MDD). Although most resting-state fMRI studies have focused on the examination of temporal correlations between low-frequency oscillations (LFOs), few studies have explored the amplitude of these LFOs in MDD. In this study, we applied the approaches of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF to examine the amplitude of LFOs in MDD. A total of 36 subjects, 18 first-episode, treatment-naive patients with MDD matched with 18 healthy controls (HCs) completed the fMRI scans. Compared with HCs, MDD patients showed increased ALFF in the right fusiform gyrus and the right anterior and posterior lobes of the cerebellum but decreased ALFF in the left inferior temporal gyrus, bilateral inferior parietal lobule, and right lingual gyrus. The fALFF in patients was significantly increased in the right precentral gyrus, right inferior temporal gyrus, bilateral fusiform gyrus, and bilateral anterior and posterior lobes of the cerebellum but was decreased in the left dorsolateral prefrontal cortex, bilateral medial orbitofrontal cortex, bilateral middle temporal gyrus, left inferior temporal gyrus, and right inferior parietal lobule. After taking gray matter (GM) volume as a covariate, the results still remained. These findings indicate that MDD patients have altered LFO amplitude in a number of regions distributed over the frontal, temporal, parietal, and occipital cortices and the cerebellum. These aberrant regions may be related to the disturbances of multiple emotion- and cognition-related networks observed in MDD and the apparent heterogeneity in depressive symptom domains. Such brain functional alteration of MDD may contribute to further understanding of MDD-related network imbalances demonstrated in previous fMRI studies.

Parkinson's disease (PD) is a neurodegenerative disorder affecting dopaminergic neurons in the substantia nigra leading to dysfunctional cortico-striato-thalamic-cortical loops. In addition to the characteristic motor symptoms, PD patients often show cognitive impairments, affective changes and other non-motor symptoms, suggesting system-wide effects on brain function. Here, we used functional magnetic resonance imaging and graph-theory based analysis methods to investigate altered whole-brain intrinsic functional connectivity in PD patients (n = 37) compared to healthy controls (n = 20). Global network properties indicated less efficient processing in PD. Analysis of brain network modules pointed to increased connectivity within the sensorimotor network, but decreased interaction of the visual network with other brain modules. We found lower connectivity mainly between the cuneus and the ventral caudate, medial orbitofrontal cortex and the temporal lobe. To identify regions of altered connectivity, we mapped the degree of intrinsic functional connectivity both on ROI- and on voxel-level across the brain. Compared to healthy controls, PD patients showed lower connectedness in the medial and middle orbitofrontal cortex. The degree of connectivity was also decreased in the occipital lobe (cuneus and calcarine), but increased in the superior parietal cortex, posterior cingulate gyrus, supramarginal gyrus and supplementary motor area. Our results on global network and module properties indicated that PD manifests as a disconnection syndrome. This was most apparent in the visual network module. The higher connectedness within the sensorimotor module in PD patients may be related to compensation mechanism in order to overcome the functional deficit of the striato-cortical motor loops or to loss of mutual inhibition between brain networks. Abnormal connectivity in the visual network may be related to adaptation and compensation processes as a consequence of altered motor function. Our analysis approach proved sensitive for detecting disease-related localized effects as well as changes in network functions on intermediate and global scale.