Individual Brain Regions Research Articles

The Effects of a TMS Double Perturbation to a Cortical Network.

Transcranial magnetic stimulation (TMS) is often used to understand the function of individual brain regions, but this ignores the fact that TMS may affect network-level rather than nodal-level processes. We examine the effects of a double perturbation to two frontoparietal network nodes, compared with the effects of single lesions to either node. We hypothesized that Bayesian evidence for the absence of effects that build upon one another indicates that a single perturbation is consequential to network-level processes. Twenty-three humans performed pro-saccades (look toward) and anti-saccades (look away) after receiving continuous theta-burst stimulation (cTBS) to right frontal eye fields (FEFs), dorsolateral prefrontal cortex (DLPFC), or somatosensory cortex (S1; the control region). On a subset of trials, a TMS pulse was applied to right posterior parietal cortex (PPC). FEF, DLPFC, and PPC are important frontoparietal network nodes for generating anti-saccades. Bayesian t tests were used to test hypotheses for enhanced double perturbation effects (cTBS plus TMS pulse) on saccade behaviors, against the alternative hypothesis that double perturbation effects to a network are not greater than single perturbation effects. In one case, we observed strong evidence [Bayes factor (BF10) = 325] that PPC TMS following DLPFC cTBS enhanced impairments in ipsilateral anti-saccade amplitudes over DLPFC cTBS alone, and not over the effect of the PPC pulse alone (BF10 = 0.75), suggesting that double perturbation effects do not augment one another. Rather, this suggests that computations are distributed across the network, and in some cases there can be compensation for cTBS perturbations.

Focal left prefrontal lesions and cognitive impairment: A multivariate lesion-symptom mapping approach

Despite network studies of the human brain have brought consistent evidence of brain regions with diverse functional roles, the neuropsychological approach has mainly focused on the functional specialization of individual brain regions. Relatively few neuropsychological studies try to understand whether the severity of cognitive impairment across multiple cognitive abilities can be related to focal brain injuries. Here we approached this issue by applying a latent variable modeling of the severity of cognitive impairment in brain tumor patients, followed by multivariate lesion-symptom methods identifying brain regions critically involved in multiple cognitive abilities. We observed that lesions in confined left lateral prefrontal areas including the inferior frontal junction produced the most severe cognitive deficits, above and beyond tumor histology. Our findings support the recently suggested integrated albeit modular view of brain functional organization, according to which specific brain regions are highly involved across different sub-networks and subserve a vast range of cognitive abilities. Defining such brain regions is relevant not only theoretically but also clinically, since it may facilitate tailored tumor resections and improve cognitive surgical outcomes.

Multiscale Imaging Reveals Aberrant Functional Connectome Organization and Elevated Dorsal Striatal Arc Expression in Advanced Age.

The functional connectome reflects a network architecture enabling adaptive behavior that becomes vulnerable in advanced age. The cellular mechanisms that contribute to altered functional connectivity in old age, however, are not known. Here we used a multiscale imaging approach to link age-related changes in the functional connectome to altered expression of the activity-dependent immediate-early gene Arc as a function of training to multitask on a working memory (WM)/biconditional association task (BAT). Resting-state fMRI data were collected from young and aged rats longitudinally at three different timepoints during cognitive training. After imaging, rats performed the WM/BAT and were immediately sacrificed to examine expression levels of Arc during task performance. Aged behaviorally impaired, but not young, rats had a subnetwork of increased connectivity between the anterior cingulate cortex (ACC) and dorsal striatum (DS) that was correlated with the use of a suboptimal response-based strategy during cognitive testing. Moreover, while young rats had stable rich-club organization across three scanning sessions, the rich-club organization of old rats increased with cognitive training. In a control group of young and aged rats that were longitudinally scanned at similar time intervals, but without cognitive training, ACC-DS connectivity and rich-club organization did not change between scans in either age group. These findings suggest that aberrant large-scale functional connectivity in aged animals is associated with altered cellular activity patterns within individual brain regions.

Network-based Responses to the Psychomotor Vigilance Task during Lapses in Adolescents after Short and Extended Sleep

Neuroimaging studies of the Psychomotor Vigilance Task (PVT) have revealed brain regions involved in attention lapses in sleep-deprived and well-rested adults. Those studies have focused on individual brain regions, rather than integrated brain networks, and have overlooked adolescence, a period of ongoing brain development and endemic short sleep. This study used functional MRI (fMRI) and a contemporary analytic approach to assess time-resolved peri-stimulus response of key brain networks when adolescents complete the PVT, and test for differences across attentive versus inattentive periods and after short sleep versus well-rested states. Healthy 14–17-year-olds underwent a within-subjects randomized protocol including 5-night spans of extended versus short sleep. PVT was performed during fMRI the morning after each sleep condition. Event-related independent component analysis (eICA) identified coactivating functional networks and corresponding time courses. Analysis of salient time course characteristics tested the effects of sleep condition, lapses, and their interaction. Seven eICA networks were identified supporting attention, executive control, motor, visual, and default-mode functions. Attention lapses, after either sleep manipulation, were accompanied by broadly increased response magnitudes post-stimulus and delayed peak responses in some networks. Well-circumscribed networks respond during the PVT in adolescents, with timing and intensity impacted by attentional lapses regardless of experimentally shortened or extended sleep.

Development of Human Emotion Circuits Investigated Using a Big-Data Analytic Approach: Stability, Reliability, and Robustness.

Emotion perception is fundamental to affective and cognitive development and is thought to involve distributed brain circuits. Efforts to chart neurodevelopmental changes in emotion have been severely hampered by narrowly focused approaches centered on activation of individual brain regions and small sample sizes. Here we investigate the maturation of human functional brain circuits associated with identification of fearful, angry, sad, happy, and neutral faces using a large sample of 759 children, adolescents, and adults (ages 8-23; female/male = 419/340). Network analysis of emotion-related brain circuits revealed three functional modules, encompassing lateral frontoparietal, medial prefrontal-posterior cingulate, and subcortical-posterior insular cortices, with hubs in medial prefrontal, but not posterior cingulate, cortex. This overall network architecture was stable by age 8, and it anchored maturation of circuits important for salience detection and cognitive control, as well as dissociable circuit patterns across distinct emotion categories. Our findings point to similarities and differences in functional circuits associated with identification of fearful, angry, sad, happy, and neutral faces, and reveal aspects of brain circuit organization underlying emotion perception that are stable over development as well as features that change with age. Reliability analyses demonstrated the robustness of our findings and highlighted the importance of large samples for probing functional brain circuit development. Our study emphasizes a need to focus beyond amygdala circuits and provides a robust neurodevelopmental template for investigating emotion perception and identification in psychopathology.SIGNIFICANCE STATEMENT Emotion perception is fundamental to cognitive and affective development. However, efforts to chart neurodevelopmental changes in emotion perception have been hampered by narrowly focused approaches centered on the amygdala and prefrontal cortex and small sample sizes. Using a large sample of 759 children, adolescents, and adults and a multipronged analytical strategy, we investigated the development of brain network organization underlying identification and categorization of fearful, happy, angry, sad, and neutral facial expressions. Results revealed a developmentally stable modular architecture that anchored robust age-related and emotion category-related changes in brain connectivity across multiple brain systems that extend far beyond amygdala circuits and provide a new template for investigation of emotion processing in the developing brain.

Effects of Diurnal Intermittent Fasting on Daytime Sleepiness Reflected by EEG Absolute Power.

We hypothesized that diurnal intermittent fasting would not increase slow frequency EEG waves, which reflect increased sleepiness. Therefore, this study aimed at performing a quantitative EEG analysis of young healthy volunteers with and without diurnal intermittent fasting while controlling for potential confounders. Eight young healthy volunteers (mean age: 24.4 ± 3.7 years) reported to the laboratory during the following five occasions: (1) adaptation, (2) 4 weeks before Ramadan while performing diurnal intermittent fasting (fasting from dawn to sunset) for 1 week (fasting outside Ramadan), (3) 1 week before Ramadan (nonfasting baseline), (4) during the second week of Ramadan while fasting (Ramadan), and (5) 2 weeks after Ramadan (recovery). Frontal, central, and occipital EEG signals were monitored four times (09:15, 11:15, 13:15, and 15:15 for 15 minutes each time) while the participants were awake to assess EEG spectral power of the delta, theta, alpha, and beta frequency bands. During wakefulness, no difference in EEG slowing was observed between nonfasting baseline and fasting during and outside Ramadan. There were no differences in the mean absolute power of each band in any studied brain region in any of the four study periods. Moreover, there was no difference in EEG absolute powers in the delta, theta, alpha, and beta frequency bands for any individual brain region during the four study periods. Spectral analysis of EEG power indicates that diurnal intermittent fasting does not increase sleepiness. Future larger studies are needed to confirm the current findings.

Moving beyond neurons: the role of cell type-specific gene regulation in Parkinson\u2019s disease heritability

Parkinson’s disease (PD), with its characteristic loss of nigrostriatal dopaminergic neurons and deposition of α-synuclein in neurons, is often considered a neuronal disorder. However, in recent years substantial evidence has emerged to implicate glial cell types, such as astrocytes and microglia. In this study, we used stratified LD score regression and expression-weighted cell-type enrichment together with several brain-related and cell-type-specific genomic annotations to connect human genomic PD findings to specific brain cell types. We found that PD heritability attributable to common variation does not enrich in global and regional brain annotations or brain-related cell-type-specific annotations. Likewise, we found no enrichment of PD susceptibility genes in brain-related cell types. In contrast, we demonstrated a significant enrichment of PD heritability in a curated lysosomal gene set highly expressed in astrocytic, microglial, and oligodendrocyte subtypes, and in LoF-intolerant genes, which were found highly expressed in almost all tested cellular subtypes. Our results suggest that PD risk loci do not lie in specific cell types or individual brain regions, but rather in global cellular processes detectable across several cell types.

Clozapine impact on FosB/ΔFosB expression in stress preconditioned rats: response to a novel stressor

Prolonged treatment with neuroleptics has been shown to induce FosB/ΔFosB expression in several brain regions including the medial prefrontal cortex, dorsomedial and dorsolateral striatum, ventrolateral and dorsolateral septum, nucleus accumbens shell and core, and the hypothalamic paraventricular nucleus (PVN). Some of these regions are known to be also stress responsive. This study was designed to determine whether repeated clozapine (CLZ) administration for 7 consecutive days to Wistar rats may modify FosB/ΔFosB expression in the above-mentioned brain areas induced by acute stress or novel stressor that followed 13-day chronic mild stress preconditioning. Following experimental groups were used: unstressed animals treated with vehicle/ CLZ for 7 days; 7-day vehicle/CLZ-treated animals on the last day exposed to acute stress - forced swimming (FSW); and animals preconditioned with stress for 13 days treated from the 8th day with vehicle/CLZ and on the 14th day exposed to novel stress - FSW. In the unstressed animals CLZ markedly increased FosB/ΔFosB immunoreactivity in the ventrolateral septum and PVN. FSW elevated FosB/ΔFosB expression in the medial prefrontal cortex, striatum, and septum. CLZ markedly potentiated the effect of the FSW on FosB/ΔFosB expression in the PVN, but suppressed it in the dorsomedial striatum. Novel stress with stress preconditioning increased FosB/ΔFosB immunoreactivity in the prefrontal cortex, striatum, ventrolateral septum, and the PVN. In the nucleus accumbens the effect of the novel stressor was potentiated by CLZ. Our data indicate that CLZ may modulate the acute as well as novel stress effects on FosB/ΔFosB expression but its effect differs within the individual brain regions.

Increased signal intensities and gadolinium levels in the brain after administration of gadolinium-based MR contrast agents : Clinical observations and results from preclinical research

Numerous clinical MRI studies have been published that describe an association between the repeated administration of (linear) gadolinium-based contrast agents and increased signal intensity in certain brain areas. In November 2017, the European Commission suspended the use of some of these contrast agents. The background for this decision, both regulatory and scientific, are presented and discussed. The regulatory decisions are evaluated and the clinical and preclinical literature is discussed. Differences in the structure and stability of gadolinium-based contrast agent molecules explain the observed increased signal intensities in individual brain regions (e. g. dentate nucleus) after administration of multiple doses of linear contrast agents. This phenomenon was not observed after administration of multiple doses of macrocyclic contrast agents. Preclinical studies have confirmed these results. To date, no clinical symptoms have been confirmed to be associated with the increased signal intensity or gadolinium presence in the brain.

Activation-based association profiles differentiate network roles across cognitive loads.

Working memory (WM) is a complex and pivotal cognitive system underlying the performance of many cognitive behaviors. Although individual differences in WM performance have previously been linked to the blood oxygenation level-dependent (BOLD) response across several large-scale brain networks, the unique and shared contributions of each large-scale brain network to efficient WM processes across different cognitive loads remain elusive. Using a WM paradigm and functional magnetic resonance imaging (fMRI) from the Human Connectome Project, we proposed a framework to assess the association and shared-association strength between imaging biomarkers and behavioral scales. Association strength is the capability of individual brain regions to modulate WM performance and shared-association strength measures how different regions share the capability of modulating performance. Under higher cognitive load (2-back), the frontoparietal executive control network (FPN), dorsal attention network (DAN), and salience network showed significant positive activation and positive associations, whereas the default mode network (DMN) showed the opposite pattern, namely, significant deactivation and negative associations. Comparing the different cognitive loads, the DMN and FPN showed predominant associations and globally shared-associations. When investigating the differences in association from lower to higher cognitive loads, the DAN demonstrated enhanced association strength and globally shared-associations, which were significantly greater than those of the other networks. This study characterized how brain regions individually and collaboratively support different cognitive loads.

Whole-brain white matter organization, intelligence, and educational attainment.

General cognitive ability, sometimes referred to as intelligence, is associated with educational attainment throughout childhood. Most studies that have explored the neural correlates of intelligence in childhood focus on individual brain regions. This analytical approach is designed to identify restricted sets of voxels that overlap across participants. By contrast, we explored the relationship between white matter connectome organization, intelligence, and education. In both a sample of typically-developing children (N = 63) and a sample of struggling learners (N = 139), the white matter connectome efficiency was strongly associated with intelligence and educational attainment. Further, intelligence partially mediated the relationship between connectome efficiency and educational attainment. In contrast, a canonical voxel-wise analysis failed to identify any significant relationships. The results emphasize the importance of distributed brain network properties for cognitive or educational ability in childhood. Our findings are interpreted in the context of a developmental theory, which emphasizes the interaction between different subsystems over developmental time.

Automated ROI-Based Labeling for Multi-Voxel Magnetic Resonance Spectroscopy Data Using FreeSurfer.

Purpose: Advanced analysis methods for multi-voxel magnetic resonance spectroscopy (MRS) are crucial for neurotransmitter quantification, especially for neurotransmitters showing different distributions across tissue types. So far, only a handful of studies have used region of interest (ROI)-based labeling approaches for multi-voxel MRS data. Hence, this study aims to provide an automated ROI-based labeling tool for 3D-multi-voxel MRS data.Methods: MRS data, for automated ROI-based labeling, was acquired in two different spatial resolutions using a spiral-encoded, LASER-localized 3D-MRS imaging sequence with and without MEGA-editing. To calculate the mean metabolite distribution within selected ROIs, masks of individual brain regions were extracted from structural T1-weighted images using FreeSurfer. For reliability testing of automated labeling a comparison to manual labeling and single voxel selection approaches was performed for six different subcortical regions.Results: Automated ROI-based labeling showed high consistency [intra-class correlation coefficient (ICC) > 0.8] for all regions compared to manual labeling. Higher variation was shown when selected voxels, chosen from a multi-voxel grid, uncorrected for voxel composition, were compared to labeling methods using spatial averaging based on anatomical features within gray matter (GM) volumes.Conclusion: We provide an automated ROI-based analysis approach for various types of 3D-multi-voxel MRS data, which dramatically reduces hands-on time compared to manual labeling without any possible inter-rater bias.

Adaptive Identification of Cortical and Subcortical Imaging Markers of Early Life Stress and Posttraumatic Stress Disorder.

Posttraumatic stress disorder (PTSD) is a heterogeneous condition associated with a range of brain imaging abnormalities. Early life stress (ELS) contributes to this heterogeneity, but we do not know how a history of ELS influences traditionally defined brain signatures of PTSD. Here, we used a novel machine learning method - evolving partitions to improve classification (EPIC) - to identify shared and unique structural neuroimaging markers of ELS and PTSD in 97 combat-exposed military veterans. We used EPIC with repeated cross-validation (CV) to determine how combinations of cortical thickness, surface area, and subcortical brain volumes could contribute to classification of PTSD (n=40) versus controls (n=57), and classification of ELS within the PTSD (ELS+ n=16; ELS- n=24) and control groups (ELS+ n=16; ELS- n=41). Additional inputs included intracranial volume, age, sex, adult trauma, and depression. On average, EPIC classified PTSD with 69% accuracy (SD=5%), and ELS with 64% accuracy in the PTSD group (SD=10%), and 62% accuracy in controls (SD=6%). EPIC selected unique sets of individual features that classified each group with 75-85% accuracy in post hoc analyses; combinations of regions marginally improved classification from the individual atlas-defined brain regions. Across analyses, surface area in the right posterior cingulate was the only variable that was repeatedly selected as an important feature for classification of PTSD and ELS. EPIC revealed unique patterns of features that distinguished PTSD and ELS in this sample of combat-exposed military veterans, which may represent distinct biotypes of stress-related neuropathology.

Polygenic Adaptation Underlies Evolution of Brain Structures and Behavioral Traits

Many of the characteristics of psychiatric disorders, including their early age of onset, moderate to high prevalence (i.e., 1% for schizophrenia, >15% for major depression), reduced fecundity, and high heritability have led many to speculate on how risk alleles have persisted throughout evolutionary history. While several potential mechanisms for maintaining high allele frequency of risk variants have been hypothesized (e.g., weak positive selection, balancing selection), few have been empirically tested. Given the recent analytic advancements in detecting polygenic adaptation, we systematically evaluated evidence for selection across a total of twenty-five complex traits including ten neuropsychiatric disorders, three personality traits, total intracranial volume, seven subcortical brain structure volume traits, and four complex traits with no known neuropsychiatric associations. We tested each set of trait-associated variants for evidence of classical hard sweeps (i.e., extreme integrated haplotype scores, iHS), partial sweeps (i.e., extreme population differentiation, Fst), rapid evolution since divergence from Neanderthal (i.e., Neanderthal depletion score, NDS), ancient polygenic selection (i.e., Qx scores), and very recent polygenic selection within the past 2,000 years (i.e., trait singleton density scores, tSDS). Variants associated with schizophrenia (Qx = 208.36, p < 0.001), extraversion (Qx = 88.04, p = 0.001), subjective well-being (Qx = 113.90, p < 0.001), hippocampus volume (Qx = 108.98, p < 0.001), and putamen volume (Qx = 115.76, p < 0.001) were enriched for signatures of weak polygenic adaptation after accounting for genetic drift. However, a limitation of this approach is that the null model of neutral drift is computed with respect to ancestral and derived allelic annotations, therefore it is not possible to determine whether polygenic adaptation has favored risk/trait-increasing alleles or protective/trait-decreasing alleles. Thus, we also employed a directional test of selection (tSDS) which overcomes this limitation. Remarkably, tSDS is powered to detect very recent selection that has been active only in the past ~2,000 years. Here, we find that signatures of recent polygenic adaptation are enriched among SCZ-protective alleles (Z=-3.06, p=0.002) total intracranial volume-increasing alleles (Z=3.09, p = 0.002), but putamen (Z=-4.93, p < 0.001), amygdala (Z=-3.49, p<0.001) and pallidum (Z=-3.39, p<0.001) volume-decreasing alleles. These results provide the first genome-wide genetic evidence in support of the mosaic theory of brain evolution in humans, suggesting that individual brain regions can evolve and vary in size independent of one another. No trait studied displayed significant consistent evidence of classical hard sweeps or partial sweeps. To characterize the biological processes and functional elements potentially targeted by polygenic adaptation, we conducted expression Quantitative Trait Locus (eQTL) and gene set enrichment analyses. SNPs associated with schizophrenia were enriched for eQTLs in brain (p = 0.007) while immune eQTLs were overrepresented among putamen (p = 0.001) and intracranial volume (p = 0.001) associated variants. Our results suggest that alleles associated with behavioral and brain structure volume traits have experienced polygenic adaptation acting through neurodevelopmental and immune-mediated pathways.

Divergent patterns of loss of interpersonal warmth in frontotemporal dementia syndromes are predicted by altered intrinsic network connectivity.

Loss of warmth is well-documented in behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA) at a group level, and has been linked to salience (SN) and semantic-appraisal (SAN) network atrophy. However, clinical observations of individual patients show much greater heterogeneity, thus measuring this clinical variability and identifying the underlying neurologic mechanisms is a critical step for understanding the symptom profile of any one patient. We used reliable change indexes with premorbid and current informant-based evaluations to characterize patterns of change on the warmth subscale of the Interpersonal Adjective Scale (IAS) questionnaire in 132 patients (21 bvFTD, 19 svPPA, 22 nonfluent variant primary progressive aphasia [nfvPPA], 37 Alzheimer's disease [AD]) and 33 healthy older adults. We investigated whether individual differences in warmth change were reflected in SN or SAN functional connectivity, or structural volume of individual brain regions in these two networks. Though one subset of patients showed significant drop in warmth to abnormally low levels (bvFTD: 38%; svPPA: 21%; nfvPPA: 5%; AD: 11%), a second subset significantly dropped but remained within the clinically normal range (bvFTD: 33%; svPPA: 21%; nfvPPA: 9%; AD: 5%), and a third subset did not drop and stayed in the clinically normal range (bvFTD: 29%; svPPA: 58%; nfvPPA: 86%; AD: 84%). Furthermore, interpersonal warmth score was strongly predicted by SN functional connectivity (p < .01), but not by SAN functional connectivity or by structural volume in these networks. Our results extend earlier group-level findings by showing wide individual variability in degree of disease-related reduction of interpersonal warmth and SN functional connectivity in bvFTD and svPPA, and highlight new approaches to revealing how brain connectivity predicts behavior on an individual patient level. Our findings suggest that measures of interpersonal warmth can provide important clinical information about changes in underlying brain networks, and help clinicians and clinical researchers better identify which bvFTD and svPPA patients are at greater risk for interpersonal disruption.

Mass Spectrometric Quantification of Arousal Associated Neurochemical Changes in Single Honey Bee Brains and Brain Regions.

Honey bee foragers show a strong diurnal rhythm of foraging activity, and such behavioral changes are likely under the control of specific neuromodulators. To identify and quantify neuromodulators involved in regulating rest and arousal in honey bees, we established a mass spectrometric method for quantifying 14 different neurochemicals and precursor molecules. We measured forager type and brain region specific differences in amine levels from individual honey bee brains and brain regions. The observed differences in amine levels between resting and aroused foragers resemble findings in other species indicating a conserved molecular mechanism by glutamate and GABA in regulating arousal. Subesophageal ganglion specific changes in the histaminergic system and global increases in aspartate during arousal suggest a possible role of histamine and aspartate in feeding and arousal, respectively. More aminergic systems were significantly affected due to arousal in nectar foragers than in pollen foragers, implying that forager phenotypes differ not only in their food preference but also in their neuromodulatory signaling systems (brain states). Finally, we found that neurotransmitter precursors were better at distinguishing brain states in the central brain, while their end products correlated with arousal associated changes in sensory regions like the optic and antennal lobes.

Disrupted Functional Network Topology in Children and Adolescents With Post-traumatic Stress Disorder.

Neuroimaging studies in children and adolescents with post-traumatic stress disorder (PTSD) have focused on abnormal structures and the functionality of a few individual brain regions. However, little is known about alterations to the topological organization of whole-brain functional networks in children and adolescents with PTSD. To this end, we investigated the topological properties of brain functional networks derived from resting-state functional magnetic resonance imaging (r-fMRI) in patients suffering from PTSD. The r-fMRI data were obtained from 10 PTSD patients and 16 trauma-exposed non-PTSD subjects. Graph theory analysis was used to investigate the topological properties of the two groups, and group comparisons of topological metrics were performed using nonparametric permutation tests. Both the PTSD and non-PTSD groups showed the functional brain network to have a small-world architecture. However, the PTSD group exhibited alterations in global properties characterized by higher global efficiency, lower clustering coefficient, and characteristic path length, implying a shift toward randomization of the networks. The PTSD group also showed increased nodal centralities, predominately in the left middle frontal gyrus, caudate nucleus, and hippocampus, and decreased nodal centralities in the left anterior cingulate cortex, left paracentral lobule, and bilateral thalami. In addition, the clustering coefficient and nodal betweenness of the left paracentral lobule were found to be negatively and positively correlated with the re-experiencing and hyper-arousal symptoms of PTSD respectively. The findings of disrupted topological properties of functional brain networks may help to better understand the pathophysiological mechanism of PTSD in children and adolescents.

Acoustically targeted chemogenetics for the non-invasive control of neural circuits.

Neurological and psychiatric disorders are often characterized by dysfunctional neural circuits in specific regions of the brain. Existing treatment strategies, including the use of drugs and implantable brain stimulators, aim to modulate the activity of these circuits. However, they are not cell-type-specific, lack spatial targeting or require invasive procedures. Here, we report a cell-type-specific and non-invasive approach based on acoustically targeted chemogenetics that enables the modulation of neural circuits with spatiotemporal specificity. The approach uses ultrasound waves to transiently open the blood-brain barrier and transduce neurons at specific locations in the brain with virally encoded engineered G-protein-coupled receptors. The engineered neurons subsequently respond to systemically administered designer compounds to activate or inhibit their activity. In a mouse model of memory formation, the approach can modify and subsequently activate or inhibit excitatory neurons within the hippocampus, with selective control over individual brain regions. This technology overcomes some of the key limitations associated with conventional brain therapies.

Transcriptional profiling and biomarker identification reveal tissue specific effects of expanded ataxin-3 in a spinocerebellar ataxia type 3 mouse model

BackgroundSpinocerebellar ataxia type 3 (SCA3) is a progressive neurodegenerative disorder caused by expansion of the polyglutamine repeat in the ataxin-3 protein. Expression of mutant ataxin-3 is known to result in transcriptional dysregulation, which can contribute to the cellular toxicity and neurodegeneration. Since the exact causative mechanisms underlying this process have not been fully elucidated, gene expression analyses in brains of transgenic SCA3 mouse models may provide useful insights.MethodsHere we characterised the MJD84.2 SCA3 mouse model expressing the mutant human ataxin-3 gene using a multi-omics approach on brain and blood. Gene expression changes in brainstem, cerebellum, striatum and cortex were used to study pathological changes in brain, while blood gene expression and metabolites/lipids levels were examined as potential biomarkers for disease.ResultsDespite normal motor performance at 17.5 months of age, transcriptional changes in brain tissue of the SCA3 mice were observed. Most transcriptional changes occurred in brainstem and striatum, whilst cerebellum and cortex were only modestly affected. The most significantly altered genes in SCA3 mouse brain were Tmc3, Zfp488, Car2, and Chdh. Based on the transcriptional changes, α-adrenergic and CREB pathways were most consistently altered for combined analysis of the four brain regions. When examining individual brain regions, axon guidance and synaptic transmission pathways were most strongly altered in striatum, whilst brainstem presented with strongest alterations in the pi-3 k cascade and cholesterol biosynthesis pathways. Similar to other neurodegenerative diseases, reduced levels of tryptophan and increased levels of ceramides, di- and triglycerides were observed in SCA3 mouse blood.ConclusionsThe observed transcriptional changes in SCA3 mouse brain reveal parallels with previous reported neuropathology in patients, but also shows brain region specific effects as well as involvement of adrenergic signalling and CREB pathway changes in SCA3. Importantly, the transcriptional changes occur prior to onset of motor- and coordination deficits.

Brainstem-cortical functional connectivity for speech is differentially challenged by noise and reverberation

Everyday speech perception is challenged by external acoustic interferences that hinder verbal communication. Here, we directly compared how different levels of the auditory system (brainstem vs. cortex) code speech and how their neural representations are affected by two acoustic stressors: noise and reverberation. We recorded multichannel (64 ch) brainstem frequency-following responses (FFRs) and cortical event-related potentials (ERPs) simultaneously in normal hearing individuals to speech sounds presented in mild and moderate levels of noise and reverb. We matched signal-to-noise and direct-to-reverberant ratios to equate the severity between classes of interference. Electrode recordings were parsed into source waveforms to assess the relative contribution of region-specific brain areas [i.e., brainstem (BS), primary auditory cortex (A1), inferior frontal gyrus (IFG)]. Results showed that reverberation was less detrimental to (and in some cases facilitated) the neural encoding of speech compared to additive noise. Inter-regional correlations revealed associations between BS and A1 responses, suggesting subcortical speech representations influence higher auditory-cortical areas. Functional connectivity analyses further showed that directed signaling toward A1 in both feedforward cortico-collicular (BS→A1) and feedback cortico-cortical (IFG→A1) pathways were strong predictors of degraded speech perception and differentiated “good” vs. “poor” perceivers. Our findings demonstrate a functional interplay within the brain's speech network that depends on the form and severity of acoustic interference. We infer that in addition to the quality of neural representations within individual brain regions, listeners' success at the “cocktail party” is modulated based on how information is transferred among subcortical and cortical hubs of the auditory-linguistic network.