scholarly journals Intrinsic network activity in human brain organoids

2021 ◽  
Author(s):  
Tal Sharf ◽  
Tjitse van der Molen ◽  
Elmer Guzman ◽  
Stella M.K. Glasauer ◽  
Gabriel Luna ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Network Activity ◽  
Field Potentials ◽  
Network Graph ◽  
Developmental Anatomy ◽  
Functional Connections ◽  
Phase Alignment ◽  
Neuropsychiatric Diseases ◽  
Spiking Activity

AbstractHuman brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we probed broadband and three-dimensional spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single unit activity. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Increasing the intrinsic inhibitory tone with a benzodiazepine altered the functional network graph of the organoid by suppressing the network skeleton. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. An ensemble of spikes phase-locked to theta frequency oscillations were strongly interconnected as a sub-network within the larger network in which they were embedded. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.

scholarly journals Genetically defined cellular correlates of the baseline brain MRI signal

2018 ◽  
Vol 115 (41) ◽  
pp. E9727-E9736 ◽  
Author(s):  
Jie Wen ◽  
Manu S. Goyal ◽  
Serguei V. Astafiev ◽  
Marcus E. Raichle ◽  
Dmitriy A. Yablonskiy
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Brain Activity ◽  
Brain Mri ◽  
Blood Oxygenation ◽  
Brain Atlas ◽  
Functional Connections ◽  
Fmri Signal ◽  
Useful Signal

fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease.

scholarly journals Dissect Relationships Between Gene Co-expression and Functional Connectivity in Human Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Xue Zhang ◽  
Yingying Xie ◽  
Jie Tang ◽  
Wen Qin ◽  
Feng Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Functional Connectivity ◽  
Human Brain ◽  
Functional Networks ◽  
Expression Data ◽  
Biological Functions ◽  
Functional Connections ◽  
Postmortem Brains ◽  
Specific Association ◽  
Cortical Regions

Although recent evidence indicates an association between gene co-expression and functional connectivity in human brain, specific association patterns remain largely unknown. Here, using neuroimaging-based functional connectivity data of living brains and brain-wide gene expression data of postmortem brains, we performed comprehensive analyses to dissect relationships between gene co-expression and functional connectivity. We identified 125 connectivity-related genes (20 novel genes) enriched for dendrite extension, signaling pathway and schizophrenia, and 179 gene-related functional connections mainly connecting intra-network regions, especially homologous cortical regions. In addition, 51 genes were associated with connectivity in all brain functional networks and enriched for action potential and schizophrenia; in contrast, 51 genes showed network-specific modulatory effects and enriched for ion transportation. These results indicate that functional connectivity is unequally affected by gene expression, and connectivity-related genes with different biological functions are involved in connectivity modulation of different networks.

scholarly journals Abnormal interhemispheric functional connectivity in patients with strabismic amblyopia: a resting-state fMRI study using voxel-mirrored homotopic connectivity

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shuang Zhang ◽  
Gui-Ping Gao ◽  
Wen-Qing Shi ◽  
Biao Li ◽  
Qi Lin ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Brain Activity ◽  
Characteristic Curve ◽  
Clinical Manifestations ◽  
Resting State Fmri ◽  
Diagnostic Value ◽  
Functional Connections ◽  
Receiver Operating

Abstract Background Previous studies have demonstrated that strabismus amblyopia can result in markedly brain function alterations. However, the differences in spontaneous brain activities of strabismus amblyopia (SA) patients still remain unclear. Therefore, the current study intended to employthe voxel-mirrored homotopic connectivity (VMHC) method to investigate the intrinsic brain activity changes in SA patients. Purpose To investigate the changes in cerebral hemispheric functional connections in patients with SA and their relationship with clinical manifestations using the VMHC method. Material and methods In the present study, a total of 17 patients with SA (eight males and nine females) and 17 age- and weight-matched healthy control (HC) groups were enrolled. Based on the VMHC method, all subjects were examined by functional magnetic resonance imaging. The functional interaction between cerebral hemispheres was directly evaluated. The Pearson’s correlation test was used to analyze the clinical features of patients with SA. In addition, their mean VMHC signal values and the receiver operating characteristic curve were used to distinguish patients with SA and HC groups. Results Compared with HC group, patients with SA had higher VMHC values in bilateral cingulum ant, caudate, hippocampus, and cerebellum crus 1. Moreover, the VMHC values of some regions were positively correlated with some clinical manifestations. In addition, receiver operating characteristic curves presented higher diagnostic value in these areas. Conclusion SA subjects showed abnormal brain interhemispheric functional connectivity in visual pathways, which might give some instructive information for understanding the neurological mechanisms of SA patients.

scholarly journals Regional abnormality of functional connectivity is associated with clinical manifestations in individuals with intractable focal epilepsy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yasuo Nakai ◽  
Hiroki Nishibayashi ◽  
Tomohiro Donishi ◽  
Masaki Terada ◽  
Naoyuki Nakao ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Focal Epilepsy ◽  
Clinical Manifestations ◽  
Eigenvector Centrality ◽  
Functional Connections ◽  
Duration Of Illness ◽  
Healthy Control ◽  
Matched Data ◽  
Clinical Conditions ◽  
Age And Sex

AbstractWe explored regional functional connectivity alterations in intractable focal epilepsy brains using resting-state functional MRI. Distributions of the network parameters (corresponding to degree and eigenvector centrality) measured at each brain region for all 25 patients were significantly different from age- and sex-matched control data that were estimated by a healthy control dataset (n = 582, 18–84 years old). The number of abnormal regions whose parameters exceeded the mean + 2 SD of age- and sex-matched data for each patient were associated with various clinical parameters such as the duration of illness and seizure severity. Furthermore, abnormal regions for each patient tended to have functional connections with each other (mean ± SD = 58.6 ± 20.2%), the magnitude of which was negatively related to the quality of life. The abnormal regions distributed within the default mode network with significantly higher probability (p < 0.05) in 7 of 25 patients. We consider that the detection of abnormal regions by functional connectivity analysis using a large number of control datasets is useful for the numerical assessment of each patient’s clinical conditions, although further study is necessary to elucidate etiology-specific abnormalities.

scholarly journals The brain timewise: how timing shapes and supports brain function

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Generative Models ◽  
Network Activity ◽  
Brain Diseases ◽  
Specific Information ◽  
Non Invasive ◽  
The Brain

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

scholarly journals Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory Simchick ◽  
Kelly M. Scheulin ◽  
Wenwu Sun ◽  
Sydney E. Sneed ◽  
Madison M. Fagan ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Coefficients ◽  
Brain Network ◽  
Network Activity ◽  
Anatomical Structures ◽  
Healthy Control ◽  
And Task

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

scholarly journals Development and Emergence of Individual Variability in the Functional Connectivity Architecture of the Preterm Human Brain

2018 ◽  
Vol 29 (10) ◽  
pp. 4208-4222 ◽  
Author(s):  
Yuehua Xu ◽  
Miao Cao ◽  
Xuhong Liao ◽  
Mingrui Xia ◽  
Xindi Wang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Network Architecture ◽  
Brain Networks ◽  
Individual Variability ◽  
Distance Constraint ◽  
Behavioral Differences ◽  
Sensorimotor Network ◽  
Middle Range ◽  
Brain Functional Connectivity

Abstract Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31–42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.

Sign in / Sign up

Export Citation Format

Share Document