Neurite outgrowth deficits caused by rare PLXNB1 mutation in pediatric bipolar disorder.

Pediatric bipolar disorder (PBD) is a severe mood dysregulation condition that affects 0.5-1% of children and teens in the United States. It is associated with recurrent episodes of mania and depression and an increased risk of suicidality. However, the genetics and neuropathology of PBD are largely unknown. Here, we used a combinatorial family-based approach to characterize cellular, molecular, genetic, and network-level deficits associated with PBD. We recruited a PBD patient and three unaffected family members from a family with a history of psychiatric illnesses. Using resting-state functional magnetic resonance imaging (rs-fMRI), we detected altered resting-state functional connectivity in the patient as compared to an unaffected sibling. Using transcriptomic profiling of patient and control induced pluripotent stem cell (iPSC)-derived telencephalic organoids, we found aberrant signaling in the molecular pathways related to neurite outgrowth. We corroborated the presence of neurite outgrowth deficits in patient iPSC-derived cortical neurons and identified a rare homozygous loss-of-function PLXNB1 variant (c.1360C>C; p.Ser454Arg) responsible for the deficits in the patient. Expression of wild-type PLXNB1, but not the variant, rescued neurite outgrowth in patient neurons, and expression of the variant caused the neurite outgrowth deficits in cortical neurons from PlxnB1 knockout mice. These results indicate that dysregulated PLXNB1 signaling may contribute to an increased risk of PBD and other mood dysregulation-related disorders by disrupting neurite outgrowth and functional brain connectivity. Overall, this study established and validated a novel family-based combinatorial approach for studying cellular and molecular deficits in psychiatric disorders and identified dysfunctional PLXNB1 signaling and neurite outgrowth as potential risk factors for PBD.

Sleepy without stimulation: subjective and objective sleepiness in actigraphy-verified natural short sleepers.

Natural short sleepers (NSS)-individuals who report minimal sleepiness or daytime dysfunction despite habitually sleeping less than the recommended amount (i.e., <7 h)-are a focus of growing interest in sleep research. Yet, the predominance of research on NSS has relied on subjective reports of functionality. The present study examined subjective and objective sleepiness among actigraphy-verified NSS in comparison with recommended (7-9 h/day) length sleepers (RLS) who reported similarly minimal daytime dysfunction. The study tested the hypothesis that under conditions of low environmental stimulation, NSS have increased risk of drowsiness and sleep onset, regardless of perceived alertness. The NSS and RLS groups were identified via screening and verified with a 14 day assessment with actigraphy, sleep diaries, and morning ratings of sleep restoration. In-laboratory resting electroencephalography (EEG) data were analysed using a computerised EEG-based algorithm (Vigilance Algorithm Leipzig; VIGALL) to classify second-by-second changes in objective sleepiness ranging from cognitively active alertness to sleep onset. Results demonstrated that NSS exhibited significantly higher drowsiness and sleep onset ('microsleeps') across 15 min of resting EEG despite perceptions of lower subjective sleepiness compared to RLS. Findings suggest that irrespective of perceived sleep restoration and alertness, NSS appear to be at high risk of objective sleepiness that is rapidly unmasked under conditions of low environmental stimulation. Such apparent discrepancy between subjective and objective sleepiness has potentially important public health implications. Future research directions, including tests of mechanisms and tailored sleep extension intervention, are discussed.

Individual differences in aesthetic engagement are reflected in resting-state fMRI connectivity: Implications for stress resilience.

OBJECTIVE: Individual differences in aesthetic engagement-the propensity to be moved by art, nature, and beauty-are associated with positive health outcomes, as well as stress resilience. The purpose of the current study was to identify potential neural substrate mechanisms underlying individual differences in aesthetic engagement and reported proneness to aesthetic chill. METHODS: Data from the Human Connectome Project (HCP) 1200 Subjects Release were utilized. Resting-state fMRI connectivity was extracted for 361 regions in the brain including cortical, subcortical and cerebellar regions for each participant, using participant-specific segmentation and parcellation of subcortical gray matter nuclei and a network-based statistics analytical approach. The Aesthetic Interests subcluster of the Openness to Experience scale (NEO-Five Factor Inventory; NEO-FFI) was used to characterize individual differences in aesthetic engagement and chill. RESULTS: Participants reporting higher aesthetic engagement, particularly proneness to aesthetic chill responses, exhibited significantly higher connectivity between the default network and sensory and motor cortices, higher connectivity between the ventral default and salience networks, and decreased connectivity between the cerebellum and somatomotor cortex. CONCLUSIONS: Current findings suggest that greater integration of the default mode network, involving processing of internal narrative, with neural representations of sensory perception and salience detection may be a mechanism underlying individual differences in aesthetic engagement. Thus, these individual differences may reflect general integration of environmental perception with internal emotional experience, which in turn may facilitate comfort with novelty, self-regulation, and positive adaptation to potentially stressful experiences.

Sustained versus instantaneous connectivity differentiates cognitive functions of processing speed and episodic memory.

Synchrony of brain activity over time describes the functional connectivity between brain regions but does not address the temporal component of this relationship. We propose a complementary method of analysis by introducing the width of cross-correlation curves between functional MRI (fMRI) time series as a metric of the relative duration of synchronous activity between brain regions, or "sustained connectivity". Using resting-state fMRI, cognitive, and demographics data from 1,003 subjects included in the Human Connectome Project, we find that sustained connectivity is a reproducible trait in individuals, heritable, more transient in females, and shows changes with age in early adulthood. Sustained connectivity in sensory brain regions is specifically associated with differences in processing speed across subjects, particularly in men. In contrast, traditional functional connectivity was correlated with a measure of episodic memory, but not with processing speed. Individual differences in hemodynamic response function (HRF) are closely approximated by sustained connectivity and width of the HRF is also correlated with processing speed across individuals, suggesting that variability in hemodynamic response may be influenced by transient versus sustained neural activity rather than simply differences in vascularity and signal transduction. Sustained connectivity may provide new opportunities to study brain dynamics in clinical populations.

Decreased anterior cingulate activation in a motor task in youths with bipolar disorder.

BACKGROUND: Bipolar disorder (BP) is characterized by abnormal shifts in mood between episodes of mania and severe depression, both of which have been linked with psychomotor disturbances. This study compares brain activation patterns in motor networks between euthymic youths with BP and healthy controls (HC) during the completion of a simple motor task. METHODS: Thirty-five youths with BP and 35 HC (aged 10-19) completed a self-paced sequential bilateral finger-tapping task, consisting of a 4-minute scan block with alternating 20-second periods of either the tapping task (six blocks) or rest (six blocks), while undergoing functional magnetic resonance imaging. Clinical and behavioral symptoms were assessed using the Child Behavior Checklist (CBCL). A between-group whole-brain analysis compared activation pattern differences while controlling for effects of age and sex. Clusters meeting whole-brain false discovery rate (FDR) correction (qFDR < .05) were considered statistically significant. Post hoc analyses evaluating comorbid attention-deficit/hyperactivity disorder (ADHD) in the BP group were also conducted. RESULTS: Significantly decreased activation was found in the anterior cingulate cortex (ACC) in youths with BP compared to HC. Furthermore, ACC activation was negatively correlated with CBCL mood dysregulation profile scores in the BP group. No significant differences in functional activation patterns were found between youths with BP and comorbid ADHD and those with only BP. CONCLUSIONS: These findings suggest a potential common mechanism of impaired ACC modulation between emotion dysregulation and motor processing in youths with BP.

Low b-value diffusion weighted imaging is promising in the diagnosis of brain death and hypoxic-ischemic injury secondary to cardiopulmonary arrest.

BACKGROUND: Cardiorespiratory arrest can result in a spectrum of hypoxic ischemic brain injury leading to global hypoperfusion and brain death (BD). Because up to 40% of patients with BD are viable organ donors, avoiding delayed diagnosis of this condition is critical. High b-value diffusion weighted imaging (DWI) measures primarily molecular self-diffusion; however, low b-values are sensitive to perfusion. We investigated the feasibility of low b-value DWI in discriminating the global hypoperfusion of BD and hypoxic ischemic encephalopathy (HIE). METHODS: We retrospectively reviewed cardiorespiratory arrest subjects with a diagnosis of HIE or BD. Inclusion criteria included brain DWI acquired at both low (50 s/mm2) and high (1000-2000 s/mm2) b-values. Automated segmentation was used to determine mean b50 apparent diffusion coefficient (ADC) values in gray and white matter regions. Normal subjects with DWI at both values were used as age- and sex-matched controls. RESULTS: We evaluated 64 patients (45 with cardiorespiratory arrest and 19 normal). Cardiorespiratory arrest patients with BD had markedly lower mean b50 ADC in gray matter regions compared with HIE (0.70 ± 0.18 vs. 1.95 ± 0.25 × 10-3 mm2/s, p < 0.001) and normal subjects (vs. 1.79 ± 0.12 × 10-3 mm2/s, p < 0.001). HIE had higher mean b50 ADC compared with normal (1.95 ± 0.25 vs. 1.79 ± 0.12 × 10-3 mm2/s, p = 0.016). There was wide separation of gray matter ADC values in BD subjects compared with age matched normal and HIE subjects. White matter values were also markedly decreased in the BD population, although they were less predictive than gray matter. CONCLUSION: Low b-value DWI is promising for the discrimination of HIE with maintained perfusion and brain death in cardiorespiratory arrest.

Brain connectivity and psychiatric comorbidity in adolescents with Internet gaming disorder.

Prolonged Internet video game play may have multiple and complex effects on human cognition and brain development in both negative and positive ways. There is not currently a consensus on the principle effects of video game play neither on brain development nor on the relationship to psychiatric comorbidity. In this study, 78 adolescents with Internet gaming disorder (IGD) and 73 comparison subjects without IGD, including subgroups with no other psychiatric comorbid disease, with major depressive disorder and with attention deficit hyperactivity disorder (ADHD), were included in a 3 T resting state functional magnetic resonance imaging analysis. The severity of Internet gaming disorder, depression, anxiety and ADHD symptoms were assessed with the Young Internet Addiction Scale, the Beck Depression Inventory, the Beck Anxiety Inventory and the Korean ADHD rating scales, respectively. Patients with IGD showed an increased functional correlation between seven pairs of regions, all satisfying q < 0.05 False discovery rates in light of multiple statistical tests: left frontal eye field to dorsal anterior cingulate, left frontal eye field to right anterior insula, left dorsolateral prefrontal cortex (DLPFC) to left temporoparietal junction (TPJ), right DLPFC to right TPJ, right auditory cortex to right motor cortex, right auditory cortex to supplementary motor area and right auditory cortex to dorsal anterior cingulate. These findings may represent a training effect of extended game play and suggest a risk or predisposition in game players for over-connectivity of the default mode and executive control networks that may relate to psychiatric comorbidity.

Longitudinal changes in cortical thickness in autism and typical development.

The natural history of brain growth in autism spectrum disorders remains unclear. Cross-sectional studies have identified regional abnormalities in brain volume and cortical thickness in autism, although substantial discrepancies have been reported. Preliminary longitudinal studies using two time points and small samples have identified specific regional differences in cortical thickness in the disorder. To clarify age-related trajectories of cortical development, we examined longitudinal changes in cortical thickness within a large mixed cross-sectional and longitudinal sample of autistic subjects and age- and gender-matched typically developing controls. Three hundred and forty-five magnetic resonance imaging scans were examined from 97 males with autism (mean age = 16.8 years; range 3-36 years) and 60 males with typical development (mean age = 18 years; range 4-39 years), with an average interscan interval of 2.6 years. FreeSurfer image analysis software was used to parcellate the cortex into 34 regions of interest per hemisphere and to calculate mean cortical thickness for each region. Longitudinal linear mixed effects models were used to further characterize these findings and identify regions with between-group differences in longitudinal age-related trajectories. Using mean age at time of first scan as a reference (15 years), differences were observed in bilateral inferior frontal gyrus, pars opercularis and pars triangularis, right caudal middle frontal and left rostral middle frontal regions, and left frontal pole. However, group differences in cortical thickness varied by developmental stage, and were influenced by IQ. Differences in age-related trajectories emerged in bilateral parietal and occipital regions (postcentral gyrus, cuneus, lingual gyrus, pericalcarine cortex), left frontal regions (pars opercularis, rostral middle frontal and frontal pole), left supramarginal gyrus, and right transverse temporal gyrus, superior parietal lobule, and paracentral, lateral orbitofrontal, and lateral occipital regions. We suggest that abnormal cortical development in autism spectrum disorders undergoes three distinct phases: accelerated expansion in early childhood, accelerated thinning in later childhood and adolescence, and decelerated thinning in early adulthood. Moreover, cortical thickness abnormalities in autism spectrum disorders are region-specific, vary with age, and may remain dynamic well into adulthood.

A functional network estimation method of resting-state fMRI using a hierarchical Markov random field.

We propose a hierarchical Markov random field model for estimating both group and subject functional networks simultaneously. The model takes into account the within-subject spatial coherence as well as the between-subject consistency of the network label maps. The statistical dependency between group and subject networks acts as a regularization, which helps the network estimation on both layers. We use Gibbs sampling to approximate the posterior density of the network labels and Monte Carlo expectation maximization to estimate the model parameters. We compare our method with two alternative segmentation methods based on K-Means and normalized cuts, using synthetic and real fMRI data. The experimental results show that our proposed model is able to identify both group and subject functional networks with higher accuracy on synthetic data, more robustness, and inter-session consistency on the real data.

Complexity of low-frequency blood oxygen level-dependent fluctuations covaries with local connectivity.

Very low-frequency blood oxygen level-dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generating such fluctuations are poorly understood. Using publicly available data from 1,019 subjects of age 7-30, we show that BOLD fluctuations exhibit temporal complexity that is linearly related to local connectivity (regional homogeneity), consistently and significantly covarying across subjects and across gray matter regions. This relationship persisted independently of covariance with gray matter density or standard deviation of BOLD signal. During late neurodevelopment, BOLD fluctuations were unchanged with age in association cortex while becoming more random throughout the rest of the brain. These data suggest that local interconnectivity may play a key role in establishing the complexity of low-frequency BOLD fluctuations underlying functional magnetic resonance imaging connectivity. Stable low-frequency power dynamics may emerge through segmentation and integration of connectivity during development of distributed large-scale brain networks.

Topographic maps of multisensory attention.

The intraparietal sulcus (IPS) region is uniquely situated at the intersection of visual, somatosensory, and auditory association cortices, ideally located for processing of multisensory attention. We examined the internal architecture of the IPS region and its connectivity to other regions in the dorsal attention and cinguloinsular networks using maximal connectivity clustering. We show with resting state fMRI data from 58 healthy adolescent and young adult volunteers that points of maximal connectivity between the IPS and other regions in the dorsal attention and cinguloinsular networks are topographically organized, with at least seven maps of the IPS region in each hemisphere. Distinct clusters of the IPS exhibited differential connectivity to auditory, visual, somatosensory, and default mode networks, suggesting local specialization within the IPS region for different sensory modalities. In an independent task activation paradigm with 16 subjects, attention to different sensory modalities showed similar functional specialization within the left intraparietal sulcus region. The default mode network, in contrast, did not show a topographical relationship between regions in the network, but rather maximal connectivity in each region to a single central cluster of the other regions. The topographical architecture of multisensory attention may represent a mechanism for specificity in top-down control of attention from dorsolateral prefrontal and lateral orbitofrontal cortex and may represent an organizational unit for multisensory representations in the brain.

Dynamical stability of intrinsic connectivity networks.

Functional connectivity MRI (fcMRI) has become a widely used technique in recent years for measuring the static correlation of activity between cortical regions. Using a publicly available resting state dataset (n = 961 subjects), we obtained high spatial-resolution maps of functional connectivity between a lattice of 7266 regions covering the gray matter. Average whole brain functional correlations were calculated, with high reproducibility within the dataset and across sites. Since correlation measures not only represent pairwise connectivity information, but also shared inputs from other brain regions, we approximate pairwise connection strength by representing each region as a linear combination of the others by performing a Cholesky decomposition of the pairwise correlation matrix. We then used this weighted connection strength between regions to iterate relative brain activity in discrete temporal steps, beginning both with random initial conditions, and with initial conditions reflecting intrinsic connectivity networks using each region as a seed. In whole brain simulations based on weighted connectivity from healthy adult subjects (mean age 27.3), there was consistent convergence to one of two inverted states, one representing high activity in the default mode network, the other representing low relative activity in the default mode network. Metastable intermediate states in our simulation corresponded to combinations of characterized functional networks. Convergence to a final state was slowest for initial conditions on the borders of the default mode network.

Functional connectivity magnetic resonance imaging classification of autism.

Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.

Decreased interhemispheric functional connectivity in autism.

The cortical underconnectivity theory asserts that reduced long-range functional connectivity might contribute to a neural mechanism for autism. We examined resting-state blood oxygen level-dependent interhemispheric correlation in 53 males with high-functioning autism and 39 typically developing males from late childhood through early adulthood. By constructing spatial maps of correlation between homologous voxels in each hemisphere, we found significantly reduced interhemispheric correlation specific to regions with functional relevance to autism: sensorimotor cortex, anterior insula, fusiform gyrus, superior temporal gyrus, and superior parietal lobule. Observed interhemispheric connectivity differences were better explained by diagnosis of autism than by potentially confounding neuropsychological metrics of language, IQ, or handedness. Although both corpus callosal volume and gray matter interhemispheric connectivity were significantly reduced in autism, no direct relationship was observed between them, suggesting that structural and functional metrics measure different aspects of interhemispheric connectivity. In the control but not the autism sample, there was decreasing interhemispheric correlation with subject age. Greater differences in interhemispheric correlation were seen for more lateral regions in the brain. These findings suggest that long-range connectivity abnormalities in autism are spatially heterogeneous and that transcallosal connectivity is decreased most in regions with functions associated with behavioral abnormalities in autism. Autism subjects continue to show developmental differences in interhemispheric connectivity into early adulthood.

Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images.

Background and purpose: Large MRI studies often pool data gathered from widely varying imaging sequences. Pooled data creates a potential source of variation in structural analyses which may cause misinterpretation of findings. The purpose of this study is to determine if data acquired using different scan sequences, head coils and scanners offers consistent structural measurements. Materials and methods: Participants (163 right-handed males: 82 typically developing controls, 81 participants with autism spectrum disorder) were scanned on the same day using an MPRAGE sequence with a 12-channel headcoil on a Siemens 3T Trio scanner and an MP2RAGE sequence with a 64-channel headcoil on a Siemens 3T Prisma scanner. Segmentation was performed using FreeSurfer to identify regions exhibiting variation between sequences on measures of volume, surface area, and cortical thickness. Intraclass correlation coefficient (ICC) and mean percent difference (MPD) were used as test-retest reproducibility measures. Results: ICC for total brain segmented volume yielded a 0.99 intraclass correlation, demonstrating high overall volumetric reproducibility. Comparison of individual regions of interest resulted in greater variation. Volumetric variability, although low overall, was greatest in the entorhinal cortex (ICC = 0.71), frontal (ICC = 0.60) and temporal (ICC = 0.60) poles. Surface area variability was greatest in the insula (ICC = 0.65), temporal (ICC = 0.64) and frontal (ICC = 0.68) poles. Cortical thickness was most variable in the frontal (ICC = 0.41) and temporal (ICC = 0.35) poles. Conclusion: Data collected on different scanners and head coils using MPRAGE and MP2RAGE are generally consistent for surface area and volume estimates. However, regional variability may constrain accuracy in some regions and cortical thickness measurements exhibit higher generalized variability.

Network anticorrelations, global regression, and phase-shifted soft tissue correction.

Synchronized low-frequency BOLD fluctuations are observed in dissociable large-scale, distributed networks with functional specialization. Two such networks, referred to as the task-positive network (TPN) and the task-negative network (TNN) because they tend to be active or inactive during cognitively demanding tasks, show reproducible anticorrelation of resting BOLD fluctuations after removal of the global brain signal. Because global signal regression mandates that anticorrelated regions to a given seed region must exist, it is unclear whether such anticorrelations are an artifact of global regression or an intrinsic property of neural activity. In this study, we demonstrate from simulated data that spurious anticorrelations are introduced during global regression for any two networks as a linear function of their size. Using actual resting state data, we also show that both the TPN and TNN become anticorrelated with the orbits when soft tissues are included in the global regression algorithm. Finally, we propose a technique using phase-shifted soft tissue regression (PSTCor) that allows improved correction of global physiological artifacts without global regression that shows improved anatomic specificity to global regression but does not show significant network anticorrelations. These results imply that observed anticorrelations between TNN and TPN may be largely or entirely artifactual in the resting state. These results also imply that differences in network anticorrelations attributed to pathophysiological or behavioral states may be due to differences in network size or recruitment rather than actual anticorrelations.

"Fully automated segmentation of the corticospinal tract using the TractSeg algorithm in patients with brain tumors".

OBJECTIVE: Tractography has been used to define the presurgical location of white matter tracts, but this is subjective and time-intensive, making incorporation to imaging workflow at scale problematic. The objective is to validate a fully automated pipeline using the TractSeg algorithm (Wasserthal et al. NeuroImage 2018;183:239-253) to segment the corticospinal tract in patients with brain tumors adjacent to the corticospinal tract. METHODS: The process of importing a structural MPRAGE sequence and raw diffusion weighted images from PACS, executing the TractSeg algorithm, overlaying the resulting bilateral corticospinal tracts on the MPRAGE image, and exporting this composite image to PACS was automated. This procedure was used to segment the corticospinal tract in 28 patients with brain masses adjacent to or displacing the corticospinal tract. These segmentations were compared with both manual deterministic tractography performed with DSI Studio using seeds placed in the pons and an automated tractography method in DSI Studio. RESULTS: The automated algorithm was able to segment the bilateral corticospinal tracts in all 28 patients whereas the manual reference method and DSI Studio based automated tractography were unsuccessful in 2 and 1 patients, respectively. In all cases, the TractSeg segmentations very closely matched the manual segmentations. Also, TractSeg appeared to include larger portions of the lateral corticospinal tract fibers than the other 2 methods. CONCLUSION: The TractSeg algorithm demonstrated robust performance in segmenting the corticospinal tract in patients with brain tumors adjacent to this tract. The algorithm is fast to perform and has great potential for optimizing and streamlining neurosurgical planning.

Left Ear Hearing Predicts Functional Activity in the Brains of Patients with Alzheimer's Disease Dementia.

OBJECTIVES: To determine whether central speech processing ability, as measured by hearing in noise, differs between right and left ears in adults with Alzheimer's disease related dementia (AD) as well as whether differences in central speech processing ability correlate with an fMRI-based measurement of global functional brain connectivity. METHODS: This prospective study was carried out at a tertiary referral center. Patients with an AD diagnosis and pure tone averages 40 dB HL or better were included. They were examined using resting-state fMRI and underwent central audiometric testing using the Dichotic Sentence Identification Test (DSI), the Dichotic Digits Test (DD), and the Synthetic Sentence Identification Test (SS), which test hearing in noise. DSI scores were correlated with resting-state fMRI connectivity between 361 distinct gray matter brain regions of interest (ROIs). Average global connectivity was calculated as mean functional connectivity between an ROI and the other 360 regions, a quantitative marker representing overall functional connectivity in the brain. RESULTS: Sixteen subjects had adequate fMRI and hearing data. The average age was 71.5 years old (±6.0). The average DSI score for the left ear was 40% (±34%) compared to 90% (±10%) in the right ear (P < .001). No difference between ears was noted on the DD. SS does not differentiate between ears, but worsening scores were noted with increasing background noise. Of the fMRI ROIs, 269 of the 361 had multiple comparison corrected significant correlations between global connectivity and DSI of the left ear (P = .004, r = .673), and all 269 showed higher functional connectivity for individuals with higher left DSI score. No correlations between DSI of the right ear and functional connectivity were found. CONCLUSIONS: Correlation was noted between left sided DSI and functional connectivity in patients with AD. Auditory input from the left ear was more susceptible to impairment, suggesting that side-specific auditory input may influence central auditory processing.

Predicting biomarkers in intact older adults and those with amnestic Mild Cognitive Impairment, and mild Alzheimer's Disease using the Repeatable Battery for the Assessment of Neuropsychological Status.

INTRODUCTION: The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has been associated, to varying degrees, with commonly used biomarkers of Alzheimer's disease (AD). Given the ease of RBANS administration as a screening tool for clinical trials and other applications, a better understanding of how RBANS performance is associated with presence of APOE ε4 allele[s], cerebral amyloid burden, and hippocampal volume is warranted. METHOD: One hundred twenty-one older adults who were classified as intact, amnestic Mild Cognitive Impairment, or mild AD underwent cognitive assessment with the RBANS, genetic analysis, and quantitative brain imaging. APOE ε4 carrier status, 18F-Flutemetamol composite standardized uptake value ratio (SUVR), and hippocampal volume were each regressed on demographic variables and RBANS Total Scale score, Index scores, and subtest scores. RESULTS: Lower RBANS Total Scale score or Delayed Memory Index (DMI) predicted the presence of APOE ε4 allele[s], higher cerebral amyloid burden, and lower hippocampal volumes. DMI was a slightly better predictor than Total Scale score for most AD biomarkers. No demographic variables consistently contributed to these models. CONCLUSIONS: The RBANS - DMI in particular - is sensitive to AD pathology. As such, it could be used as a predictive tool, particularly in clinical drug trials to enrich samples prior to less accessible AD biomarker investigation.

Understanding heterosexual women's erotic flexibility: the role of attention in sexual evaluations and neural responses to sexual stimuli.

Many women experience desires, arousal and behavior that run counter to their sexual orientation (orientation inconsistent, 'OI'). Are such OI sexual experiences cognitively and neurobiologically distinct from those that are consistent with one's sexual orientation (orientation consistent, 'OC')? To address this question, we employed a mindful attention intervention-aimed at reducing judgment and enhancing somatosensory attention-to examine the underlying attentional and neurobiological processes of OC and OI sexual stimuli among predominantly heterosexual women. Women exhibited greater neural activity in response to OC, compared to OI, sexual stimuli in regions associated with implicit visual processing, volitional appraisal and attention. In contrast, women exhibited greater neural activity to OI, relative to OC, sexual stimuli in regions associated with complex visual processing and attentional shifting. Mindfully attending to OC sexual stimuli reduced distraction, amplified women's evaluations of OC stimuli as sexually arousing and deactivated the superior cerebellum. In contrast, mindfully attending to OI sexual stimuli amplified distraction, decreased women's evaluations of OI stimuli as sexually arousing and augmented parietal and temporo-occipital activity. Results of the current study constrain hypotheses of female erotic flexibility, suggesting that sexual orientation may be maintained by differences in attentional processing that cannot be voluntarily altered.