Brain Structure & Function最新文献

The influence of regional brain vasculature on resting-state fMRI BOLD signals is well documented. However, the role of brain vasculature is often overlooked in functional connectivity research. In the present report, utilizing publicly available whole-brain vasculature data in the mouse, we investigate the relationship between functional connectivity and brain vasculature. This is done by assessing interregional variations in vasculature through a novel metric termed vascular similarity. First, we identify features to describe the regional vasculature. Then, we employ multiple linear regression models to predict functional connectivity, incorporating vascular similarity alongside metrics from structural connectivity and spatial topology. Our findings reveal a significant correlation between functional connectivity strength and regional vasculature similarity, especially in anesthetized mice. We also show that multiple linear regression models of functional connectivity using standard predictors are improved by including vascular similarity. We perform this analysis at the cerebrum and whole-brain levels using data from both male and female mice. Our findings regarding the relation between functional connectivity and the underlying vascular anatomy may enhance our understanding of functional connectivity based on fMRI and provide insights into its disruption in neurological disorders.

Synapse formation is a critical step in neuronal development. Current knowledge is largely based on altricial rodents where synapse formation and maturation proceed largely postnatally. In precocially born mammals such as guinea pig presynapse and spine formation start well before birth. Here, we analysed the developmental expression of proteins associated with synapse formation and maturation together with the development of basal dendritic spines of pyramidal neurons of visual and somatosensory cortex of the pig, an emerging translational model for human neurodegenerative disorders. A total of 23 selected proteins was quantified with Western blots. Most were detectable from midgestation embryonal day (E) 65 onwards. About half reached the expression level seen at postnatal day (P) 90 pig already two weeks before birth (gestation 114 days) in somatosensory, albeit not yet in visual cortex. For instance, major molecular components of synaptic plasticity such as GluN2B, CamKIIα, α-actinin-2, synaptopodin and T286 phosphorylated CamKIIα were expressed at E100 in somatosensory cortex. Dendritic spine type quantification with DiI-labeled material revealed an increase of total dendritic protrusions from E70 onwards. The increase was steepest in somatosensory cortex which had, at E110, a proportion of mushroom spines equal to the proportion present at P90. Together, matching the ungulate life history, a rapid development of functional synaptic connectivity in prenatal somatosensory cortex serves the somatomotor abilities essentially required by the newborn nest-fledgling.

Significant culture and ethnic diversity play an important role in shaping brain structure and function. Many attempts have been undertaken to connect ethnic variations with brain function, which, however, fluctuates over time and is costly, limiting its utility to identify consistent brain markers as well as its application to a broad population. In contrast, brain anatomy is less altered during a short period of time, but it is not fully understood whether it could serve as the ethnicity-sensitive landmark, or its variation is associated with functional one. In this study, We utilized gyral peaks, a set of early cortical folds, as cortical landmarks to explore the role of ethnic factors in brain anatomy and their relationship to brain function. Comparative experiments were conducted using the Human Connectome Project and the Chinese Human Connectome Project. In populations with similar ethnic backgrounds, gyral peak patterns showed greater consistency. For groups with significantly different ethnic backgrounds, we identified both shared peaks and peaks unique to each group. Compared to shared peaks, unique peaks showed significant differences in anatomical and functional network attributes and were spatially associated with working memory networks, which exhibited increased activation in their presence. Gene enrichment analysis provided additional support, suggesting that the unique peaks are associated with genes linked to working memory functions. These findings could provide new knowledge to understanding how ethnic diversity interplay with brain functions and associate with brain shapes.

The brain entropy (BEN) reflects the randomness of brain activity and is inversely related to its temporal coherence. In recent years, BEN has been found to be associated with a number of neurocognitive, biological, and sociodemographic variables such as fluid intelligence, age, sex, and education. However, evidence regarding the potential relationship between BEN and brain structure is still lacking. In this study, we use resting-state fMRI (rsfMRI) data to estimate BEN and investigate its associations with three structural brain metrics: gray matter volume (GMV), surface area (SA), and cortical thickness (CT). We performed separate analyses on BEN maps derived from four distinct rsfMRI runs, and used a voxelwise as well as a regions-of-interest (ROIs) approach. Our findings consistently showed that lower BEN was related to increased GMV and SA in the lateral frontal and temporal lobes, inferior parietal lobules, and precuneus. We hypothesize that lower BEN and higher SA might reflect higher brain reserve as well as increased information processing capacity.

A significant proportion of patients who have recovered from COVID-19 suffer from persistent symptoms, referred to as "post-acute sequelae of SARS-CoV-2 infection (PASC)". Abnormal brain intrinsic activity has been observed in PASC patients, but the patterns of frequency-dependent intrinsic activity in the PASC and non-PASC (recovered COVID-19 patients without persistent symptoms) groups and their association with neuropsychiatric sequelae remain unclear in PASC. Twenty-nine PASC patients, 27 non-PASC subjects, and 31 healthy controls (HCs) were recruited. The voxel-level fractional amplitude of low-frequency fluctuation (fALFF) was calculated in different frequency bands (typical frequency band: 0.01-0.10 Hz; slow 5: 0.01-0.023 Hz; slow 4: 0.023-0.073 Hz) to assess regional intrinsic activity patterns within different groups. Correlation analyses were performed to explore the associations between frequency-dependent alterations and clinical variables. Significant frequency-dependent alterations in intrinsic activity patterns were observed in both the PASC and non-PASC groups, primarily involving regions of the default mode network (DMN). The decreased fALFF values of the DMN in different frequency bands were associated with different symptoms in PASC. For example, decreased fALFF in the left precuneus in the typical frequency band was related to general attention impairment in PASC, whereas decreased fALFF in the left superior frontal gyrus appeared in non-PASC. The fALFF alterations in the left precuneus/posterior cingulate gyrus in the slow 5 band were also related to cognitive performance in PASC. Additionally, in the slow 4 band, decreased fALFF in the right angular gyrus was associated with depressive symptoms in the PASC. Our results may provide insights into the potential neural mechanisms underlying symptoms in PASC patients.

To achieve a better understanding of the evolution of the large brain in humans, a comparative analysis of species differences in the brains of extant primate species is crucial, as it allows direct comparisons of the brains. We developed a method to achieve anatomically precise region-to-region homologous brain transformations across species using computational neuroanatomy. Utilizing three-dimensional neuroimaging data from humans (Homo sapiens), chimpanzees (Pan troglodytes), and Japanese macaques (Macaca fuscata), along with the anatomical labels of their respective brains, we aimed to create a cross-species average template brain that preserves neuroanatomical correspondence across species. Homologous transformation of the brain from one species to another can be computed using the cross-species average brain. Applying this transformation to human and chimpanzee brains revealed that, compared to chimpanzees, humans had significantly larger and more expanded prefrontal cortex, middle and posterior temporal gyrus, angular gyrus, precuneus, and cortical areas associated with mentalization. This neuroanatomically homologous brain transformation enables the systematic investigation of the similarities and differences in brain anatomy and structure across different species.

In this study, we analyzed the spatio-temporal pattern of expression of specific transcription factors (PITX2, FOXA1, BARHL1, FOXP1, FOXP2) in the human fetal subthalamic nucleus and its neighboring structures from 11 postconceptional weeks (PCW) to 3 postnatal months. We found that all analyzed transcription factors are expressed already during the early fetal period (at 11 PCW). Both FOXP1- and FOXP2-immunoreactive cells were found in the subthalamic nucleus as well as in the striatum, thalamus, reticular nucleus, but not in the zona incerta. FOXP2-ir cells were also found in the lateral hypothalamic-supramamillary area (LHA-SMA) and internal pallidal segment.On the other hand, PITX2, FOXA1 and BARHL1 were expressed exclusively in the subthalamic nucleus and LHA-SMA, from 11 PCW until the birth, the only exception being gradual loss of BARHL1 expression in the LHA-SMA during the late fetal period.Our findings present the first evidence in the human fetal brain that neurons of the subthalamic nucleus do not originate in the diencephalon, as was proposed by classical histological studies, but instead share a common hypothalamic (hp1 prosomere) origin with neurons of the LHA-SMA group, as proposed by the prosomeric model of brain development.

The brain undergoes atrophy and cognitive decline with advancing age. The utilization of brain age prediction represents a pioneering methodology in the examination of brain aging. This study aims to develop a deep learning model with high predictive accuracy and interpretability for brain age prediction tasks. The gray matter (GM) density maps obtained from T1 MRI data of 16,377 healthy participants aged 45 to 82 years from the UKB database were included in this study (mean age, $64.27\pm 7.52$ , 7811 men). We propose an innovative deep learning architecture for predicting brain age based on GM density maps. The architecture combines a 3D dual-stream fully convolutional residual network (ds-FCRN) with a Transformer-based global-local feature learning paradigm to enhance prediction accuracy. Moreover, we employed Shapley values to elucidate the influence of various brain regions on prediction precision. On a test set of 3,276 healthy subjects (mean age, $64.15\pm 7.45$ , 1561 men), our 3D ds-FCRN model achieved a mean absolute error of 2.2 years in brain age prediction, outperforming existing models on the same dataset. The posterior interpretation revealed that the temporal lobe plays the most significant role in the brain age prediction process, while frontal lobe aging is associated with the greatest number of lifestyle factors. Our designed 3D ds-FCRN model achieved high predictive accuracy and high decision transparency. The brain age vectors constructed using Shapley values provided brain region-level insights into life factors associated with abnormal brain aging.

Physiological responses derived from audiovisual perception during assisted driving are associated with the regulation of the autonomic nervous system (ANS), especially in emergencies. However, the interaction of event-related brain activity and the ANS regulating peripheral physiological indicators (i.e., heart rate variability (HRV) and respiratory rate) is unknown, making it difficult to study the neural mechanism during takeover from the assistance system. In this paper, we established a mapping between the ANS regulation and brain activations of driving events in function magnetic resonance imaging (fMRI)-conditioned audiovisual warnings experiment to add physiological fingerprints for assisted driving. Firstly, we used the general linear model (GLM) to obtain brain activation clusters of driving events and brain activation clusters of peripheral physiological indicators in different frequency bands. Secondly, we redefined the input parameters based on the driving events to calculate the GLM to obtain the brain activation clusters of event-related physiological indicators. Finally, the relationship between the main activation clusters of driving events and the activation of event-related physiological indicators was quantified by the statistical test of the mean-time course of voxels within the region. The results showed that related areas of the brain responsible for movement, visceral autonomic regulation, auditory, and vision actively responded to the audiovisual warnings of automatic driving. The mappings created using them revealed that the correlation between driving event-related activation of brain regions and respiration worked at the onset of audiovisual warnings, especially between the intermediate (IM) and low frequency (LF) bands. For pre-emergency and takeover in audiovisual warnings, the correlations of HRV were dominant, with significant differences among LF, IM and high frequency (HF) bands. At different periods of audiovisual warnings, HRV and respiration play different roles in physiological fingerprints. Compared to respiratory indicators, HRV has higher sensitivity to emergency situations. This study investigates the interaction between driving-related network activity and ANS regulation, revealing the profound connection between driving behavior and neural activity, and contributing to the research of driving assistance systems.

Theta oscillations of the mammalian amygdala are associated with processing, encoding and retrieval of aversive memories. In the hippocampus, the power of the network theta oscillation is modulated by basal forebrain (BF) GABAergic projections. Here, we combine anatomical and computational approaches to investigate if similar BF projections to the amygdaloid complex provide an analogous modulation of local network activity. We used retrograde tracing with fluorescent immunohistochemistry to identify cholinergic and non-cholinergic parvalbumin- or calbindin-immunoreactive BF neuronal subgroups targeting the input (lateral and basolateral nuclei) and output (central nucleus and the central bed nucleus of the stria terminalis) regions of the amygdaloid complex. We observed a dense non-cholinergic, putative GABAergic projection from the ventral pallidum (VP) and the substantia innominata (SI) to the basolateral amygdala (BLA). The VP/SI axonal projections to the BLA were confirmed using viral anterograde tracing and transsynaptic labeling. We tested the potential function of this VP/SI-BLA pathway in a 1000-cell biophysically realistic network model, which incorporated principal neurons and three major interneuron groups of the BLA, together with extrinsic glutamatergic, cholinergic, and VP/SI GABAergic inputs. We observed in silico that theta-modulation of VP/SI GABAergic projections enhanced theta oscillations in the BLA via their selective innervation of the parvalbumin-expressing local interneurons. Ablation of parvalbumin-, but not somatostatin- or calretinin-expressing, interneurons reduced theta power in the BLA model. These results suggest that long-range BF GABAergic projections may modulate network activity at their target regions through the formation of a common interneuron-type and oscillatory phase-specific disinhibitory motif.