Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis

Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly understood.Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain injury.This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function.However,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional connectivity.Given that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is critical.In the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury.In this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy controls.Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis.In the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network.More than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 patients.Furthermore,better cognitive function was associated with more efficient networks.Finally,our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury.These findings highlight the importance of integrating structural and functional connectivity in unde rstanding the occurrence and evolution of mild traumatic brain injury.Additionally,exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.

Structural and functional connectivity in traumatic brain injury

Traumatic brain injury survivors often experience cognitive deficits and neuropsychiatric symptoms.However,the neurobiological mechanisms underlying specific impairments are not fully understood.Advances in neuroimaging techniques（such as diffusion tensor imaging and functional MRI）have given us new insights on structural and functional connectivity patterns of the human brain in both health and disease.The connectome derived from connectivity maps reflects the entire constellation of distributed brain networks.Using these powerful neuroimaging approaches,changes at the microstructural level can be detected through regional and global properties of neuronal networks.Here we will review recent developments in the study of brain network abnormalities in traumatic brain injury,mainly focusing on structural and functional connectivity.Some connectomic studies have provided interesting insights into the neurological dysfunction that occurs following traumatic brain injury.These techniques could eventually be helpful in developing imaging biomarkers of cognitive and neurobehavioral sequelae,as well as predicting outcome and prognosis.

The development of brain functional connectivity networks revealed by resting-state functional magnetic resonance imaging

Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.

Changes in brain functional network connectivity after stroke

Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.

Functional connectivity of paired default mode network subregions in patients with eye trauma

AIM:To study functional brain abnormalities in patients with eye trauma(ET)and to discuss the pathophysiological mechanisms of ET.METHODS:Totally 31 ET patients and 31 healthy controls(HCs)were recruited.The age,gender,and educational background characteristics of the two groups were similar.After functional magnetic resonance imaging(fMRI)scanning,the subjects’spontaneous brain activity was evaluated with the functional connectivity(FC)method.Receiver operating characteristic(ROC)curve analysis was used to classify the data.Pearson’s correlation analysis was used to explore the relationship between FC values in specific brain regions and clinical behaviors in patients with ET.RESULTS:Significantly increased FC between several regions was identified including the medial prefrontal cortex(MPFC)and left hippocampus formations(HF),the MPFC and left inferior parietal lobule(IPL),the left IPL and left medial temporal lobe(MTL),the left IPL and right MTL,and the right IPL and left MTL.No decreased region-to-region connectivity was detected in default mode network(DMN)sub-regions in patients with ET.Compared with HCs,ET patients exhibited significantly increased FC between several paired DMN regions,as follows:posterior cingulate cortex(PCC)and right HF(HF.R,t=2.196,P=0.032),right inferior parietal cortices(IPC.R)and left MTL(MTL.L,t=2.243,P=0.029),and right MTL(MTL.R)and HF.R(t=2.236,P=0.029).CONCLUSION:FC values in multiple brain regions of ET patients are abnormal,suggesting that these brain regions in ET patients may be dysfunctional,which may help to reveal the pathophysiological mechanisms of ET.

Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we inves-tigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state.Z-values in the vision-related brain regions were calculated, conifrming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental ifndings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.

The Gut Brain Connection

The gut-brain connection is a bidirectional communication system that links the gut microbiome to the central nervous system (CNS). The gut-brain axis communicates through a variety of mechanisms, including the release of hormones, neurotransmitters, and cytokines. These signaling molecules can travel from the gut to the brain and vice versa, influencing various physiological and cognitive functions. Emerging therapeutic strategies targeting the gut-brain connection include probiotics, prebiotics, and faecal microbiota transplantation (FMT). Probiotics are live microorganisms that are similar to the beneficial bacteria that are naturally found in the gut. Prebiotics are non-digestible fibers that feed the beneficial bacteria in the gut. FMT is a procedure in which faecal matter from a healthy donor is transplanted into the gut of a person with a diseased microbiome. Probiotics, prebiotics, and FMT have been shown to be effective in treating a variety of gastrointestinal disorders, and there is growing evidence that they may also be effective in treating neurological and psychiatric disorders. This review explores the emerging field of the gut-brain connection, focusing on the communication pathways between the gut microbiome and the central nervous system. We summarize the potential roles of gut dysbiosis in various neurological and psychiatric disorders. Additionally, we discuss potential therapeutic strategies, research limitations, and future directions in this exciting area of research. More research is needed to fully understand the mechanisms underlying the gut-brain connection and to develop safe and effective therapies that target this pathway. However, the findings to date are promising, and there is the potential to revolutionize the way we diagnose and treat a variety of neurological and psychiatric disorders.

Adaptation to Fluctuating Neuronal Signal Traffic for Brain Connectivity

Brain connectivity is commonly studied in terms of causal interaction or statistical dependency between brain regions. In this analysis paper, we draw attention to the constraining effect the dynamics of fiber tract connections may impose on neuronal signal traffic. We propose a model developed by Copelli and Kinouchi (l.c.) for a different purpose to safeguard signal transmission for brain connectivity by ensuring dynamic adaptation of signal reception to a wide frequency range of traffic flow over connecting fiber tracts. Gap junction connectivity would confer to neuronal groups the capacity of acting as collectives for dynamical adaptability to impinging neural traffic thereby forestalling traffic congestion and overload. It is suggested that applying this model to signal reception in brain connectivity would deliver the required functionality as a collective achievement of the interrelations between neurons and gap junctions, the latter regulated by glia.

Structural Connectivity Enhanced Anisotropic 3D Network for Brain Midline Delineation

Brain midline delineation can facilitate the clinical evaluation of brain midline shift,which has a pivotal role in the diagnosis and prognosis of various brain pathology.However,there are still challenges for brain midline delineation:1)the largely deformed midline is hard to localize if mixed with severe cerebral hemorrhage;2)the predicted midlines of recent methods are not smooth and continuous which violates the structural priority.To overcome these challenges,we propose an anisotropic three dimensional(3D)network with context-aware refinement(A3D-CAR)for brain midline modeling.The proposed network fuses 3D context from different two dimensional(2D)slices through asymmetric context fusion.To exploit the elongated structure of the midline,an anisotropic block is designed to balance the difference between the adjacent pixels in the horizontal and vertical directions.For maintaining the structural priority of a brain midline,we present a novel 3D connectivity regular loss(3D CRL)to penalize the disconnectivity between nearby coordinates.Extensive experiments on the CQ dataset and one in-house dataset show that the proposed method outperforms three state-of-the-art methods on four evaluation metrics without excessive computational burden.

Research on resting spontaneous brain activity and functional connectivity of acupuncture at uterine acupoints

Objective The resting-state functional magnetic resonance imaging(rs-f MRI)method was used to observe brain activity and its functional connection upon electroacupuncture stimulation at bilateral uterine acupoints(EX-CA1),as well as to investigate the mechanism of acupuncture in the treatment of gynecological diseases.Methods Twenty-two healthy female subjects were stimulated by electroacupuncture at bilateral uterine acupoints;rs-f MRI data of the brain were acquired and standardized.Degree centrality(DC),amplitude of low-frequency fluctuation(ALFF),and regional homogeneity(ReHo)were used to analyze local spontaneous brain activity via acupuncture.An independent component analysis was used to evaluate the functional connectivity of the resting brain networks after acupuncture.Results Analytical results showed that the neural activity intensity of the precuneus lobe,orbitofrontal cortex,lingual gyrus,amygdala,and posterior central gyrus decreased after acupuncture(voxel P<0.001,cluster P<0.05).Functional connectivity analysis revealed weakened auditory and right frontal-parietal networks(voxel P<0.001,cluster P<0.05),enhanced visual network(voxel P<0.001,cluster P<0.05),and synergistic auditory network and hypothalamic-pituitary system.Conclusion Significant differences in neural activity and functional connectivity in specific brain regions were observed after acupuncture intervention at uterine acupoints;the hypothalamic-pituitary system also showed various active states in different brain regions.It is speculated that the effective mechanism of acupuncture at uterine acupoints is related to the regulation of reproductive hormones,emotional changes,and somatic sensations.Therefore,the methods used in this study could clarify the neural mechanism of uterine-point acupuncture in the treatment of gynecological diseases and may serve as a reference for other studies pertaining to acupuncture.

Neural Mechanisms of Mental Fatigue Revisited: New Insights from the Brain Connectome

Maintaining sustained attention during a prolonged cognitive task often comes at a cost: high levels of mental fatigue. Heuristically, mental fatigue refers to a feeling of tiredness or exhaustion, and a disengagement from the task at hand;it manifests as impaired cognitive and behavioral performance. In order to effectively reduce the undesirable yet preventable consequences of mental fatigue in many real-world workspaces, a better understanding of the underlying neural mechanisms is needed, and continuous efforts have been devoted to this topic. In comparison with conventional univariate approaches, which are widely utilized in fatigue studies, convergent evidence has shown that multivariate functional connectivity analysis may lead to richer information about mental fatigue. In fact, mental fatigue is increasingly thought to be related to the deviated reorganization of functional connectivity among brain regions in recent studies. In addition, graph theoretical analysis has shed new light on quantitatively assessing the reorganization of the brain functional networks that are modulated by mental fatigue. This review article begins with a brief introduction to neuroimaging studies on mental fatigue and the brain connectome, followed by a thorough overview of connectome studies on mental fatigue. Although only a limited number of studies have been published thus far, it is believed that the brain connectome can be a useful approach not only for the elucidation of underlying neural mechanisms in the nascent field of neuroergonomics, but also for the automatic detection and classification of mental fatigue in order to address the prevention of fatigue-related human error in the near future.

Age-related changes in resting-state functional connectivity in older adults

Age-related changes in the brain connectivity of healthy older adults have been widely studied in recent years,with some differences in the obtained results.Most of these studies showed decreases in general functional connectivity,but they also found increases in some particular regions and areas.Frequently,these studies compared young individuals with older subjects,but few studies compared different age groups only in older populations.The purpose of this study is to analyze whole-brain functional connectivity in healthy older adult groups and its network characteristics through functional segregation.A total of 114 individuals,48 to 89 years old,were scanned using resting-state functional magnetic resonance imaging in a resting state paradigm and were divided into six different age groups(<60,60–64,65–69,70–74,75–79,≥80 years old).A partial correlation analysis,a pooled correlation analysis and a study of 3-cycle regions with prominent connectivity were conducted.Our results showed progressive diminution in the functional connectivity among different age groups and this was particularly pronounced between 75 and 79 years old.The oldest group(≥80 years old)showed a slight increase in functional connectivity compared to the other groups.This occurred possibly because of compensatory mechanism in brain functioning.This study provides information on the brain functional characteristics of every age group,with more specific information on the functional progressive decline,and supplies methodological tools to study functional connectivity characteristics.Approval for the study was obtained from the ethics committee of the Comision de Bioetica de la Universidad de Barcelona(approval No.PSI2012-38257)on June 5,2012,and from the ethics committee of the Barcelona’s Hospital Clinic(approval No.2009-5306 and 2011-6604)on October 22,2009 and April 7,2011 respectively.

Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity

The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.

Visual Analysis of Epilepsy Diagnosis Based on Brain Functional Connections

Epilepsy is a transient neurological disorder associated with changes in the functional connections of the brain. Abnormal electrical discharges can be observed during an epileptic seizure. However, in the absence of an epileptic seizure, the anatomical structure of the brain and the electrical waves of the brain are not observed, making it difficult to explain the cause. This paper deals with together weighted imaging (DWI) sequence data in functional magnetic resonance imaging (FMRI) of epileptic patients before seizure, using Anatomical Automatic Labeling (AAL) template extracted 116 brain regions and the introduction of time series, a matrix of 116 × 116. Pearson correlation coefficient was calculated to investigate the pathological condition of brain function in epilepsy patients, using of neural network visualization system of innovative visual display and compared with the normal epileptic brain function to connect the image, with 38 cases of epilepsy by 187 cases of normal DWI experiment data, and can confirm the existence of brain function in patients with epilepsy connections. Cerebral neural network visualization system showed partial functional connection loss between frontal lobe and temporal lobe in epileptic group compared with normal control group.

Exploring the Abnormal Brain Regions and Abnormal Functional Connections in SZ by Multiple Hypothesis Testing Technique

Schizophrenia(SZ)is one of the most common mental diseases.Its main characteristics are abnormal social behavior and inability to correctly understand real things.In recent years,the magnetic resonance imaging(MRI)technique has been popularly utilized to study SZ.However,it is still a great challenge to reveal the essential information contained in the MRI data.In this paper,we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data,in which biomarkers represent both abnormal brain functional connectivity and abnormal brain regions.By implementing the biomarker selection approach,six abnormal brain regions and twenty-three abnormal functional connectivity in the brains of SZ are explored.It is discovered that compared with healthy controls,the significantly reduced gray matter volumes are mainly distributed in the limbic lobe and the basal ganglia,and the significantly increased gray matter volumes are distributed in the frontal gyrus.Meanwhile,it is revealed that the significantly strengthened connections are those between the middle frontal gyrus and the superior occipital gyrus,the superior occipital gyrus and the middle occipital gyrus as well as the middle occipital gyrus and the fusiform gyrus,and the rest connections are significantly weakened.

Localizing the Language Network with fMRI and Functional Connectivity: Implications for Pre-Surgical Planning

Object: Functional MRI is frequently applied to lateralize language in pre-surgical planning, with potential to localize functionally important cortex too. Here we present BOLD signal activation maps and related functional connectivity, in response to three commonly administered fMRI language tasks. Methods: Datasets from 55 pre-surgical fMRI studies were analyzed. Verbal response naming, covert word generation and passive listening tasks were administered in all studies. Single-subject analyses, group analyses and region-of-interest analyses were conducted, and a multi-subject functional connectivity analysis was performed. Results: Single-subject analyses revealed that clinically important language regions were activated in all but three patients using the panel of tasks. Group analyses revealed significant bilateral BOLD signal increases in anterior and posterior language regions in response to verbal response naming and bilateral signal increase in posterior language regions only in response to passive listening. Covert word generation activated anterior language regions bilaterally and posterior language cortex in the dominant hemisphere. Functional connectivity analyses confirmed that activated regions were significantly correlated in all tasks. Conclusion: The findings of single-subject and group analyses add to the evidence supporting the use of a panel of fMRI tasks to map the language network for pre-surgical planning. Our findings support the additional use of functional connectivity analysis in routine language mapping to add to the localization value to fMRI. In addition, the results of our investigation demonstrate these three commonly applied tasks reliably activate unique aspects of the language network, which advocates closer individual inspection, guided by the surgical intervention planned.

Age-related connectivity differences between attention deficit and hyperactivity disorder patients and typically developing subjects：a resting-state functional MRI study

Attention deficit and hyperactivity disorder（ADHD） is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing（TD） subjects using resting state f MRI（rs-f MRI） for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals（27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults）.The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status（i.e.,ADHD or TD） and age（i.e.,child,adolescent,or adult）（P 0.001）.Additional regions were identified at a relaxed threshold（P 0.05）.Many of the identified regions（the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus） were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.

Brain networks in newborns and infants with and without sensorineural hearing loss:A functional near-infrared spectroscopy study

BACKGROUND Understanding the impact of early sensory deficits on brain development is essential for understanding developmental processes and developing potential interventions.While previous studies have looked into the impact of prenatal experiences on language development,there is a lack of research on how these experiences affect early language and brain function development in individuals with sensorineural hearing loss(SNHL).AIM To investigate SNHL effects on early brain development and connectivity in 4-month-olds vs healthy newborns and controls.METHODS The research involved analyzing the functional brain networks of 65 infants,categorized into three groups:28 healthy newborns,224-month-old participants with SNHL,and 15 age-matched healthy participants.The resting-state functional connectivity was measured and compared between the groups using functional near-infrared spectroscopy and graph theory to assess the brain network properties.RESULTS Significant differences were found in resting-state functional connectivity between participants with SNHL and age-matched controls,indicating a developmental lag in brain connectivity for those with SNHL.Surprisingly,SNHL participants showed better connectivity development compared to healthy newborns,with connectivity strengths of 0.13±0.04 for SNHL,0.16±0.08 for controls,and 0.098±0.04 for newborns.Graph theory analysis revealed enhanced global brain network properties for the SNHL group,suggesting higher communication efficiency at 4 months.No significant differences were noted in network properties between 4-month-old SNHL participants and neonates.A unique pattern of central hubs was observed in the SNHL group,with 2 hubs in the left hemisphere compared to 6 in controls.CONCLUSION 4-month-old infants with SNHL have a distinct brain network pattern with efficient long-distance information transmission but less effective local communication compared to age-matched controls.

Multimodal Nature of the Single-cell Primate Brain Atlas:Morphology,Transcriptome,Electrophysiology,and Connectivity

Primates exhibit complex brain structures that augment cognitive function.The neocortex fulfills high-cognitive functions through billions of connected neurons.These neurons have distinct transcriptomic,morphological,and electrophysiological properties,and their connectivity principles vary.These features endow the primate brain atlas with a multimodal nature.The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex,enabling a multimodal neuronal atlas to be established in great detail:(1)single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references,covering all major transcriptomic cell types;(2)patch-seq links the morphological and electrophysiological features to the transcriptomic reference;(3)multicell patch-clamp delineates the principles of local connectivity.Here,we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.