Model Of Human Brain Research Articles

Development of 3D printed human brain models using thermoplastic Polyurethane/Rubber blends for anatomy teaching promoting kinesthetic learning purposes

Kinesthetic appreciation of anatomy models serves to activate a concrete sensory experience that enhances 3D visuospatial mental mapping of anatomical structures. However, most commercially available plastic anatomy models are costly and do not provide tactile sensation similar to the organ or structures. Polymeric materials have been used widely in additive manufacturing to produce human brain models, however, none of the models resembles accurate feeling. The aim of this study is to produce 3D printed anatomical models using customized soft 3D printing filament from thermoplastic Polyurethane (TPU) and two types of rubber, which are ethylene propylene diene monomer (EPDM) and styrene butadiene rubber (SBR) compounds. Actual human brain MRI scans are used to form 3D-printed anatomy models. The MRI image obtained was in DICOM format, exported into 3D slicer software for specific brain parts extraction (whole brain, brain ventricles, circle of Willis, and dural venous sinuses), and converted into STL format for 3D printing. For material processing, the blending of TPU/EPDM and TPU/SBR were successfully fabricated using an internal mixer (Haake) and extruded into filament using a single screw extruder with the aid of a filament winder. The human brain model was then printed using 3D Printer (Ender 3). It was found that all TPU blends were able to be printed into brain anatomy models but the properties of the materials were greatly affected by rubber types and compositions of the added fillers. The addition of more than 30% of the fillers gave difficulties in processing, probably due to inconsistent viscosity that led to phase separation.

Deletion of Abi3/Gngt2 influences age-progressive amyloid β and tau pathologies in distinctive ways

BackgroundThe S209F variant of Abelson Interactor Protein 3 (ABI3) increases risk for Alzheimer’s disease (AD), but little is known about its function in relation to AD pathogenesis.MethodsHere, we use a mouse model that is deficient in Abi3 locus to study how the loss of function of Abi3 impacts two cardinal neuropathological hallmarks of AD—amyloid β plaques and tau pathology. Our study employs extensive neuropathological and transcriptomic characterization using transgenic mouse models and adeno-associated virus-mediated gene targeting strategies.ResultsAnalysis of bulk RNAseq data confirmed age-progressive increase in Abi3 levels in rodent models of AD-type amyloidosis and upregulation in AD patients relative to healthy controls. Using RNAscope in situ hybridization, we localized the cellular distribution of Abi3 in mouse and human brains, finding that Abi3 is expressed in both microglial and non-microglial cells. Next, we evaluated Abi3−/− mice and document that both Abi3 and its overlapping gene, Gngt2, are disrupted in these mice. Using multiple transcriptomic datasets, we show that expression of Abi3 and Gngt2 are tightly correlated in rodent models of AD and human brains, suggesting a tight co-expression relationship. RNAseq of the Abi3-Gngt2−/− mice revealed upregulation of Trem2, Plcg2, and Tyrobp, concomitant with induction of an AD-associated neurodegenerative signature, even in the absence of AD-typical neuropathology. In APP mice, loss of Abi3-Gngt2 resulted in a gene dose- and age-dependent reduction in Aβ deposition. Additionally, in Abi3-Gngt2−/− mice, expression of a pro-aggregant form of human tau exacerbated tauopathy and astrocytosis. Further, using in vitro culture assays, we show that the AD-associated S209F mutation alters the extent of ABI3 phosphorylation.ConclusionsThese data provide an important experimental framework for understanding the role of Abi3-Gngt2 function and early inflammatory gliosis in AD. Our studies also demonstrate that inflammatory gliosis could have opposing effects on amyloid and tau pathology, highlighting the unpredictability of targeting immune pathways in AD.

A diffeomorphic aging model for adult human brain from cross-sectional data

Normative aging trends of the brain can serve as an important reference in the assessment of neurological structural disorders. Such models are typically developed from longitudinal brain image data—follow-up data of the same subject over different time points. In practice, obtaining such longitudinal data is difficult. We propose a method to develop an aging model for a given population, in the absence of longitudinal data, by using images from different subjects at different time points, the so-called cross-sectional data. We define an aging model as a diffeomorphic deformation on a structural template derived from the data and propose a method that develops topology preserving aging model close to natural aging. The proposed model is successfully validated on two public cross-sectional datasets which provide templates constructed from different sets of subjects at different age points.

Human Brain Models of Intellectual Disability: Experimental Advances and Novelties.

Intellectual disability (ID) is characterized by deficits in conceptual, social and practical domains. ID can be caused by both genetic defects and environmental factors and is extremely heterogeneous, which complicates the diagnosis as well as the deciphering of the underlying pathways. Multiple scientific breakthroughs during the past decades have enabled the development of novel ID models. The advent of induced pluripotent stem cells (iPSCs) enables the study of patient-derived human neurons in 2D or in 3D organoids during development. Gene-editing tools, such as CRISPR/Cas9, provide isogenic controls and opportunities to design personalized gene therapies. In practice this has contributed significantly to the understanding of ID and opened doors to identify novel therapeutic targets. Despite these advances, a number of areas of improvement remain for which novel technologies might entail a solution in the near future. The purpose of this review is to provide an overview of the existing literature on scientific breakthroughs that have been advancing the way ID can be studied in the human brain. The here described human brain models for ID have the potential to accelerate the identification of underlying pathophysiological mechanisms and the development of therapies.

Nature inspired fault tolerant task allocation in cloud computing using neural network model

Cloud computing in the current scenario comes with a large pool of resources, pay-per-use model and reliable infrastructure. Cloud optimization relies on resource optimization to improve the performance and reliability of the cloud. Fault in the cloud places an important role in defining the reliability of the cloud. The identification of fault is a challenging issue in a modular cloud environment. The researchers have developed various methods for the fault-aware scheduling of cloud resources. The fault-aware resource allocation includes static, dynamic, meta-heuristic, and learning-based approaches. In this article, we primarily focused on existing fault-aware resource allocation techniques and then we proposed a model that will primarily focus on fault forecast in tasks allocation. The projected model is based nature-inspired heuristic approach and intelligent artificial neural network. The fault-tolerant aware ANN-based proposed model focuses on performance improvement and reliability testing proactively. The proposed model surpasses the existing state of art methods for proactive and reactive fault-aware scheduling techniques in a large scale datacenter. The results and discussions section support the reliability assertion of the fault-tolerant aware human brain and nature-inspired model.

Acute Antioxidant and Cytoprotective Effects of Caffeine in the Model of Neurovascular Injury by Oxidative Stress

Caffeine is commonly used in the neonatal intensive care units for respiratory disorders, but the effects of this medication in the neonatal cerebral circulation remain largely unexplored. We used newborn pigs as a clinically relevant model of the neonatal human brain to investigate the effects of caffeine on cerebral arterioles and primary neurovascular cells. First, we examined dose‐dependent cerebrovascular and systemic effects of water‐soluble anhydrous caffeine in anesthetized newborn pigs equipped with closed cranial windows. Caffeine administered systemically at therapeutic concentrations (20‐40 mg/kg i.v.) had no significant effects on diameter of pial arterioles, mean arterial blood pressure (MABP), and heart rate within 10‐60 min after the injection. When used at a higher concentration (70 mg/kg i.v.), caffeine produced dilation of pial arterioles (15‐20%) accompanied by an increased heart rate, without any effect on MABP. Topical application of caffeine (10‐5‐10‐3M) under the cranial window produced a dose‐dependent dilation of pial cerebral arterioles (15‐30%) that was fully reversed by a brief flushing with artificial cerebrospinal fluid. These in vivo data indicate that cerebral vascular cells are potential targets for caffeine. Next, we tested the hypothesis that caffeine exhibits cytoprotective properties in cerebral circulation during oxidative stress conditions. We used an in vitro model of acute oxidative stress‐induced neurovascular injury caused by excitotoxic and inflammatory conditions concomitant with epileptic seizures, asphyxia, and cerebral ischemia. Endothelial cells and cortical astrocytes are the key components of the neurovascular unit that are most vulnerable to oxidative stress injury. Primary cultures of cerebral vascular endothelial cells (CVEC) and cortical astrocytes from newborn pigs responded to pro‐inflammatory cytokine TNF‐alpha (30 ng/ml) and excitotoxic glutamate (1‐2 mM) by a surge in reactive oxygen species (ROS) production leading to apoptosis. NADPH oxidase is the major ROS‐generating system in the neurovascular unit during inflammation and excitotoxicity. We examined the acute effects of caffeine on oxidative stress‐induced neurovascular cell death caused by TNF‐alpha and excitotoxic glutamate. Caffeine (0.1‐10 µM) inhibited NADPH oxidase activation, reduced overall ROS generation, and attenuated major key events of apoptosis (caspase‐3 activation, DNA fragmentation, and loss of cell‐cell contacts) in CVEC and astrocytes exposed to TNF‐a and glutamate. These data demonstrate, for the first time, that caffeine exhibits acute antioxidant and cytoprotective effects in cerebral vascular endothelial cells and astrocytes. Overall, endothelial and astrocytic components of the neurovascular unit represent target cells for caffeine cytoprotective therapy in the neonatal cerebral circulation during oxidative stress.

Human IPSC 3D brain model as a tool to study chemical-induced dopaminergic neuronal toxicity

Oxidative stress is caused by an imbalance between the generation and detoxification of reactive oxygen and nitrogen species (ROS/RNS). This imbalance plays an important role in brain aging and age-related neurodegenerative diseases. In the context of Parkinson's disease (PD), the sensitivity of dopaminergic neurons in the substantia nigra pars compacta to oxidative stress is considered a key factor of PD pathogenesis. Here we study the effect of different oxidative stress-inducing compounds (6-OHDA, MPTP or MPP+) on the population of dopaminergic neurons in an iPSC-derived human brain 3D model (aka BrainSpheres). Treatment with 6-OHDA, MPTP or MPP+ at 4 weeks of differentiation disrupted the dopaminergic neuronal phenotype in BrainSpheres at (50, 5000, 1000 μM respectively). 6-OHDA increased ROS production and decreased mitochondrial function most efficiently. It further induced the greatest changes in gene expression and metabolites related to oxidative stress and mitochondrial dysfunction. Co-culturing BrainSpheres with an endothelial barrier using a transwell system allowed the assessment of differential penetration capacities of the tested compounds and the damage they caused in the dopaminergic neurons within the BrainSpheres In conclusion, treatment with compounds known to induce PD-like phenotypes in vivo caused molecular deficits and loss of dopaminergic neurons in the BrainSphere model. This approach therefore recapitulates common animal models of neurodegenerative processes in PD at similarly high doses. The relevance as tool for drug discovery is discussed.

Development and Testing of SPIDER-NET: An Interactive Tool for Brain Connectogram Visualization, Sub-Network Exploration and Graph Metrics Quantification.

Brain connectomics consists in the modeling of human brain as networks, mathematically represented as numerical connectivity matrices. However, this representation may result in difficult interpretation of the data. To overcome this limitation, graphical representation by connectograms is currently used via open-source tools, which, however, lack user-friendly interfaces and options to explore specific sub-networks. In this context, we developed SPIDER-NET (Software Package Ideal for Deriving Enhanced Representations of brain NETworks), an easy-to-use, flexible, and interactive tool for connectograms generation and sub-network exploration. This study aims to present SPIDER-NET and to test its potential impact on pilot cases. As a working example, structural connectivity (SC) was investigated with SPIDER-NET in a group of 17 healthy controls (HCs) and in two subjects with stroke injury (Case 1 and Case 2, both with a focal lesion affecting part of the right frontal lobe, insular cortex and subcortical structures). 165 parcels were determined from individual structural magnetic resonance imaging data by using the Destrieux atlas, and defined as nodes. SC matrices were derived with Diffusion Tensor Imaging tractography. SC matrices of HCs were averaged to obtain a single group matrix. SC matrices were then used as input for SPIDER-NET. First, SPIDER-NET was used to derive the connectogram of the right hemisphere of Case 1 and Case 2. Then, a sub-network of interest (i.e., including gray matter regions affected by the stroke lesions) was interactively selected and the associated connectograms were derived for Case 1, Case 2 and HCs. Finally, graph-based metrics were derived for whole-brain SC matrices of Case 1, Case 2 and HCs. The software resulted effective in representing the expected (dis) connectivity pattern in the hemisphere affected by the stroke lesion in Cases 1 and 2. Furthermore, SPIDER-NET allowed to test an a priori hypothesis by interactively extracting a sub-network of interest: Case 1 showed a sub-network connectivity pattern different from Case 2, reflecting the different clinical severity. Global and local graph-based metrics derived with SPIDER-NET were different between cases with stroke injury and HCs. The tool proved to be accessible, intuitive, and interactive in brain connectivity investigation and provided both qualitative and quantitative evidence.

Electrophysiological Monitoring of Neurochemical-Based Neural Signal Transmission in a Human Brain-Spinal Cord Assembloid.

Combining human brain organoids holds great potential in recapitulating the human brain's histological features and modeling neural disorders. However, current combined-brain organoid models focus on the internal interactions between different brain regions. In this study, we develop an engineered brain-spinal cord assembloid (eBSA) by coculturing cerebral organoids (COs) and motor neuron spheroids (MNSs). By connecting COs and MNSs, we generate a terminal for signal transfer from the brain to the whole body by mimicking the brain-spinal cord connection. After the formation of COs from human induced pluripotent stem cells and MNSs from human neural stem cells, MNSs are prepatterned into specific CO regions and assembled to form an eBSA. Caffeine serves as a neurochemical model to demonstrate neural signal transmission. When the MNSs in the eBSA contact the multielectrode array, the eBSA successfully shows an increased neural spiking speed on the motor neuron region by caffeine treatment, which means that neural stimulation signals transfer from the COs to MNSs. The neural stimulation effects of caffeine are tested on the MNSs only to prove the eBSA system's neural signal transmission, and there were no stimulus effects. Our results demonstrate that the eBSA system can monitor a caffeine-mediated excitatory signal as an output signal from the brain to the spinal cord. We believe that the eBSA system can be utilized as a screening platform to validate the stimulus signal transfer by neurochemicals. In addition, the accumulation of understanding of the neural signal transfer from CNS to PNS will provide better knowledge for controlling muscle actuators with the nervous system.

Arterial Collapse during Thrombectomy for Stroke: Clinical Evidence and Experimental Findings in Human Brains and In Vivo Models.

Aspiration thrombectomy has become a preferred approach to recanalize large-vessel occlusion in stroke with a growing trend toward using larger-bore catheters and stronger vacuum pumps. However, the mechanical response of the delicate cerebral arteries to aspiration force has not been evaluated. Here, we provide preclinical and clinical evidence of intracranial arterial collapse in aspiration thrombectomy. We presented a clinical case of arterial collapse with previously implanted flow diverters. We then evaluated the effect of vacuum with conventional aspiration catheters (with and without stent retrievers) in a rabbit model (n = 3) using fluoroscopy and intravascular optical coherence tomography. Then, in a validated human cadaveric brain model, we conducted 168 tests of direct aspiration thrombectomy following an experimental design modifying the catheter inner diameter (0.064 inch, 0.068 inch, and 0.070 inch), cerebral perfusion pressures (mean around 60 and 90 mm Hg), and anterior-versus-posterior circulation. Arterial wall response was recorded and graded via direct transluminal observation. Arterial collapse was observed in both the patient and preclinical experimental models. In the human brain model, arterial collapse was observed in 98% of cases in the M2 and in all the cases with complete proximal flow arrest. A larger bore size of the aspiration catheter, a lower cerebral perfusion pressure, and the posterior circulation in comparison with the anterior circulation were associated with a higher probability of arterial collapse. Arterial collapse does occur during aspiration thrombectomy and is more likely to happen with larger catheters, lower perfusion pressure, and smaller arteries.

Design of rectangular coaxial slot antenna for ultra‐high‐field magnetic resonance imaging

AbstractRectangular coaxial slot arrays (RCSAs) are antennas designed to ensure superior field penetration depth with a high signal‐to‐noise ratio (S/N) in the deeper imaging region of ultra‐high magnetic resonance imaging (MRI). The RCSA consists of a transmission line of λ/4 length surrounded by a dielectric material, and a ground plate that resembles a rectangular coaxial line. We extended this antenna to eight elements. The simulation indicates that a single RCSA has a distribution similar to that of the generally used dipole antenna for traveling RF waves. However, the of the RCSA in an array configuration was stronger in the deep brain region of the human brain model and its specific absorption rate was lower compared to the dipole and monopole antenna arrays. The proposed RSCA array can be adapted to acquire MR signals with high sensitivity in a deeper imaging region in an ultra‐high field MRI scanner.

An Air Particulate Pollutant Induces Neuroinflammation and Neurodegeneration in Human Brain Models (Adv. Sci. 21/2021)

Human Brain Model In article number 2101251 by Hansang Cho and co-workers, PM2.5-polluted human brain models (PMBs) are created in a 3D microfluidic platform reconstituting key aspects of human brain immunity under the PM2.5 exposure. The cover artwork shows the potential risk of neuroinflammation on brain health induced by air pollutants from diesel exhaust. Cover illustration by You Jung Kang. CT images of organs kindly provided by NIH.

Pallidothalamic neurotransmission model in human brain: a pilot study through deep brain stimulation

Pallidothalamic neurotransmission model in human brain: a pilot study through deep brain stimulation

Effects of the Selective Serotonin Reuptake Inhibitor Fluoxetine on Developing Neural Circuits in a Model of the Human Fetal Cortex.

The developing prenatal brain is particularly susceptible to environmental disturbances. During prenatal brain development, synapses form between neurons, resulting in neural circuits that support complex cognitive functions. In utero exposure to environmental factors such as pharmaceuticals that alter the process of synapse formation increases the risk of neurodevelopmental abnormalities. However, there is a lack of research into how specific environmental factors directly impact the developing neural circuitry of the human brain. For example, selective serotonin reuptake inhibitors are commonly used throughout pregnancy to treat depression, yet their impact on the developing fetal brain remains unclear. Recently, human brain models have provided unprecedented access to the critical window of prenatal brain development. In the present study, we used human neurons and cortical spheroids to determine whether the selective serotonin reuptake inhibitor fluoxetine alters neurite and synapse formation and the development of spontaneous activity within neural circuits. We demonstrate that cortical spheroids express serotonin transporter, thus recapitulating the early developmental expression of serotonin transporter associated with cortical pyramidal neurons. Cortical spheroids also appropriately express serotonin receptors, such as synaptic 5-HT2A and glial 5-HT5A. To determine whether fluoxetine can affect developing neural circuits independent of serotonergic innervation from the dorsal and medial raphe nuclei, we treated cortical neurons and spheroids with fluoxetine. Fluoxetine alters neurite formation in a dose-dependent fashion. Intriguingly, in cortical spheroids, neither acute nor chronic fluoxetine significantly altered excitatory synapse formation. However, only acute, but not chronic fluoxetine exposure altered inhibitory synaptogenesis. Finally, fluoxetine reversibly suppresses neuronal activity in a dose-dependent manner. These results demonstrate that fluoxetine can acutely alter synaptic function in developing neural circuits, but the effects were not long-lasting. This work provides a foundation for future studies to combine serotonergic innervation with cortical spheroids and assess the contributions of fluoxetine-induced alterations in serotonin levels to brain development.

An Air Particulate Pollutant Induces Neuroinflammation and Neurodegeneration in Human Brain Models.

Fine particulate matter (PM2.5), a major component among air pollutants, highlights as a global health concern. Several epidemiological studies show the correlation between chronical PM2.5 exposure and incidents of neurological disorders including Alzheimer's disease. However, the mechanisms have not been well understood, partly due to the lack of model systems that reflect the physiologically relevant innate immunity in human brains. Here, PM2.5‐polluted human brain models (PMBs) are created in a 3D microfluidic platform reconstituting key aspects of human brain immunity under the PM2.5 exposure. PM2.5 penetration across a blood–brain barrier (BBB) model and accumulation in the brain tissue side of the model are first validated. Second, the PMB model shows that the BBB‐penetrating PM2.5 initiates astrogliosis, resulting in slight neuronal loss and microglial infiltration. Third, it is demonstrated that the infiltrating microglia obtain M1 phenotype induced by interleukin‐1β and interferon‐γ from neurons and reactive astrocytes under the PM2.5 exposure. Finally, it is observed that additional proinflammatory mediators and nitric oxide released from the M1 microglia exacerbate neuronal damages, such as synaptic impairment, phosphoric tau accumulation, and neuronal death. This study suggests that PM2.5 can be a potential environmental risk factor for dementia mediated by the detrimental neuroinflammation.

Human 3D brain model to study developmental neurotoxicity

Human 3D brain model to study developmental neurotoxicity

TurboBC: A Memory Efficient and Scalable GPU Based Betweenness Centrality Algorithm in the Language of Linear Algebra.

Betweenness centrality (BC) is a shortest path centrality metric used to measure the influence of individual vertices or edges on huge graphs that are used for modeling and analysis of human brain, omics data, or social networks. The application of the BC algorithm to modern graphs must deal with the size of the graphs, as well with highly irregular data-access patterns. These challenges are particularly important when the BC algorithm is implemented on Graphics Processing Units (GPU), due to the limited global memory of these processors, as well as the decrease in performance due to the load unbalance resulting from processing irregular data structures. In this paper, we present the first GPU based linear-algebraic formulation and implementation of BC, called TurboBC, a set of memory efficient BC algorithms that exhibits good performance and high scalability on unweighted, undirected or directed sparse graphs of arbitrary structure. Our experiments demonstrate that our TurboBC algorithms obtain more than 18 GTEPs and an average speedup of 31.9x over the sequential version of the BC algorithm, and are on average 1.7x and 2.2x faster than the state-of-the-art algorithms implemented on the high performance, GPU-based, gunrock, and CPU-based, ligra libraries, respectively. These experiments also show that by minimizing their memory footprint, the TurboBC algorithms are able to compute the BC of relatively big graphs, for which the gunrock algorithms ran out of memory.

Position-Based Dynamics Simulator of Brain Deformations for Path Planning and Intra-Operative Control in Keyhole Neurosurgery

Many tasks in robot-assisted surgery require planning and controlling manipulators' motions that interact with highly deformable objects. This study proposes a realistic, time-bounded simulator based on Position-based Dynamics (PBD) simulation that mocks brain deformations due to catheter insertion for pre-operative path planning and intra-operative guidance in keyhole surgical procedures. It maximizes the probability of success by accounting for uncertainty in deformation models, noisy sensing, and unpredictable actuation. The PBD deformation parameters were initialized on a parallelepiped-shaped simulated phantom to obtain a reasonable starting guess for the brain white matter. They were calibrated by comparing the obtained displacements with deformation data for catheter insertion in a composite hydrogel phantom. Knowing the gray matter brain structures' different behaviors, the parameters were fine-tuned to obtain a generalized human brain model. The brain structures' average displacement was compared with values in the literature. The simulator's numerical model uses a novel approach with respect to the literature, and it has proved to be a close match with real brain deformations through validation using recorded deformation data of in-vivo animal trials with a mean mismatch of 4.73$\pm$2.15%. The stability, accuracy, and real-time performance make this model suitable for creating a dynamic environment for KN path planning, pre-operative path planning, and intra-operative guidance.

TMEM106B modifies TDP-43 pathology in human ALS brain and cell-based models of TDP-43 proteinopathy.

The neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with TAR DNA-binding protein-43 (TDP-43) inclusions (FTLD-TDP) share the neuropathological hallmark of aggregates of TDP-43. However, factors governing the severity and regional distribution of TDP-43 pathology, which may account for the divergent clinical presentations of ALS and FTLD-TDP, are not well understood. Here, we investigated the influence of genotypes at TMEM106B, a locus associated with risk for FTLD-TDP, and hexanucleotide repeat expansions in C9orf72, a known genetic cause for both ALS and FTLD-TDP, on global TDP-43 pathology and regional distribution of TDP-43 pathology in 899 postmortem cases from a spectrum of neurodegenerative diseases. We found that, among the 110 ALS cases, minor (C)-allele homozygotes at the TMEM106B locus sentinel SNP rs1990622 had more TDP-43 pathology globally, as well as in select brain regions. C9orf72 expansions similarly associated with greater TDP-43 pathology in ALS. However, adjusting for C9orf72 expansion status did not affect the relationship between TMEM106B genotype and TDP-43 pathology. To elucidate the direction of causality for this association, we directly manipulated TMEM106B levels in an inducible cell system that expresses mislocalized TDP-43 protein. We found that partial knockdown of TMEM106B, to levels similar to what would be expected in rs1990622 C allele carriers, led to development of more TDP-43 cytoplasmic aggregates, which were more insoluble, in this system. Taken together, our results support a causal role for TMEM106B in modifying the development of TDP-43 proteinopathy.

Simulation of Blast Induced Traumatic Brain Injury using Finite Element Method

Because of increase in threat from militant groups and during war exposure to blast wave from improvised explosive devices, Traumatic Brain Injury (TBI), a signature injury is on rise worldwide. During blast, the biological system is exposed to a sudden blast over pressure which is several times higher than the ambient pressure causing the damage in the brain. The severity of TBI due to air blast may vary from brief change in mental status or consciousness (termed as mild) to extended period of unconsciousness or memory loss after injuries (termed as severe). The blast wave induced impact on head propagates as shock wave with the broad spectrum of frequencies and stress concentrations in the brain. The primary blast TBI is directly induced by pressure differentials across the skull/fluid/soft tissue interfaces and is further reinforced by the reflected stress waves within the cranial cavity, leading to stress concentrations in certain regions of the brain. In this paper, an attempt has been made to study the behaviour of a human brain model subjected to blast wave based on finite element model using LSDYNA code. The parts of a typical human head such as skull, scalp, CSF, brain are modelled using finite element with properties assumed based on available literature. The model is subjected to blast from frontal lobe, occipital lobe, temporal lobe of the brain. The interaction of the blast wave with the head and subsequent transformation of various forms of shock energy internally have been demonstrated in the human head model. The brain internal pressure levels and the shear stress distribution in the various lobes of the brain such as frontal, parietal, temporal and occipital are determined and presented.