Model Of Human Brain Research Articles

Localization of the epileptogenic network from scalp EEG using a patient-specific whole-brain model

ABSTRACT Computational modeling is a key tool for elucidating the neuronal mechanisms underlying epileptic activity. Despite considerable progress, existing models often lack realistic accuracy in representing electrophysiological epileptic activity. In this study, we used a comprehensive human brain model based on a neural mass model, which is tailored to the layered structure of the neocortex and incorporates patient-specific imaging data. This approach allowed the simulation of scalp EEGs in an epileptic patient suffering from type 2 focal cortical dysplasia (FCD). The simulation specifically addressed epileptic activity induced by FCD, faithfully reproducing intracranial interictal epileptiform discharges (IEDs) recorded with electrocorticography. For constructing the patient-specific scalp EEG, we carefully defined a clear delineation of the epileptogenic zone by numerical simulations to ensure fidelity to the topography, polarity, and diffusion characteristics of IEDs. This nuanced approach improves the accuracy of the simulated EEG signal, provides a more accurate representation of epileptic activity, and enhances our understanding of the mechanism behind the epileptogenic networks. The accuracy of the model was confirmed by a postoperative reevaluation with a secondary EEG simulation that was consistent with the lesion’s removal. Ultimately, this personalized approach may prove instrumental in optimizing and tailoring epilepsy treatment strategies.

Brain Tumor Detection and Size Estimation using Microwave Imaging

This project focuses on developing an antenna that utilising microwave imaging technology for visualising, detecting, and estimating the size of human tumors using simulation approach. A rectangular microstrip patch antenna is chosen for its advantages of low cost, convenience, efficiency, and compactness, offering a non-ionised alternative. To meet the antenna specifications, rectangular slots are incorporated into the design. The antenna performs effectively at 7.5 GHz, exhibiting a return loss of -24.20383 dB, well below the -10 dB threshold. Placing the antenna 15 mm away from the human brain model results in a specific absorption rate (SAR) value of 0.2 W/kg for 10g, indicating its safety for brain imaging. By scanning a human head phantom with and without a tumor, the antenna captures reflected signals from different locations, enabling the generation of tumour images. A 10-mm-radius tumor is introduced to the phantom, and the unique reflected signal serves as an indicator for tumor detection, using the signal without a tumor as a reference. MATLAB software is employed for image processing, allowing the generation of tumour images and the estimation of tumor size. The simulation results demonstrate 63% accuracy in tumor size estimation. In conclusion, the antenna proves to be a safe and effective brain imaging system for tumor detection.

Two-Step Iterative Medical Microwave Tomography.

In the field of medical imaging, microwave tomography (MWT) is based on the scattering and absorption characteristics of different tissues to microwaves and can reconstruct the electromagnetic property distribution of biological tissues non-invasively and without ionizing radiation. However, due to the inherently nonlinear and ill-posed characteristics of MWT calculations, actual imaging is prone to overfitting or artifacts. To address this, this paper proposes a two-step iterative imaging approach for rapid medical microwave tomography. This method establishes corresponding objective functions for microwave imaging across multiple frequencies and conducts iterative calculations on images at varying resolutions. This effectively enhances image clarity and accuracy while alleviating the issue of prolonged computational time associated with imaging complex structures at high resolution due to insufficient prior information during iterative processes. In the electromagnetic simulation section, we simulated a three-layer brain model and conducted imaging experiments. The results demonstrate that the algorithm significantly enhances imaging resolution, accurately pinpointing cerebral hemorrhages at different locations using an eight-antenna array and successfully reconstructs tomography images with a hemorrhage area radius of 1 cm. Lastly, experiments were conducted using a medical microwave tomography platform and four simplified human brain models, achieving millimeter-level accuracy in MWT.

On human nanoscale synaptome: Morphology modeling and storage estimation.

One of the key challenges in neuroscience is to generate the human nanoscale connectome which requires comprehensive knowledge of synaptome forming the neural microcircuits. The synaptic architecture determines limits of individual mental capacity and provides the framework for understanding neurologic disorders. Here, I address morphology modeling and storage estimation for the human synaptome at the nanoscale. A synapse is defined as a pair of pairs [(presynaptic_neuron),(presynaptic_axonal_terminal);(postsynaptic_neuron),(postsynaptic_dendritic_terminal)]. Center coordinates, radius, and identifier characterize a dendritic or axonal terminal. A synapse comprises topology with the paired neuron and terminal identifiers, location with terminal coordinates, and geometry with terminal radii. The storage required for the synaptome depends on the number of synapses and storage necessary for a single synapse determined by a synaptic model. I introduce three synaptic models: topologic with topology, point with topology and location, and geometric with topology, location, and geometry. To accommodate for a wide range of variations in the numbers of neurons and synapses reported in the literature, four cases of neurons (30;86;100;138 billion) and three cases of synapses per neuron (1,000;10,000;30,000) are considered with three full and simplified (to reduce storage) synaptic models resulting in total 72 cases of storage estimation. The full(simplified) synaptic model of the entire human brain requires from 0.21(0.14) petabytes (PB) to 28.98(18.63) PB for the topologic model, from 0.57(0.32) PB to 78.66(43.47) PB for the point model, and from 0.69(0.38) PB to 95.22(51.75) PB for the geometric model. The full(simplified) synaptic model of the cortex needs from 86.80(55.80) TB to 2.60(1.67) PB for the topologic model, from 235.60(130.02) TB to 7.07(3.91) PB for the point model, and from 285.20(155.00) TB to 8.56(4.65) PB for the geometric model. The topologic model is sufficient to compute the connectome's topology, but it is still too big to be stored on today's top supercomputers related to neuroscience. Frontier, the world's most powerful supercomputer for 86 billion neurons can handle the nanoscale synaptome in the range of 1,000-10,000 synapses per neuron. To my best knowledge, this is the first big data work attempting to provide storage estimation for the human nanoscale synaptome.

Recent advances and applications of human brain models.

Recent advances in human pluripotent stem cell (hPSC) technologies have prompted the emergence of new research fields and applications for human neurons and brain organoids. Brain organoids have gained attention as an in vitro model system that recapitulates the higher structure, cellular diversity and function of the brain to explore brain development, disease modeling, drug screening, and regenerative medicine. This progress has been accelerated by abundant interactions of brain organoid technology with various research fields. A cross-disciplinary approach with human brain organoid technology offers a higher-ordered advance for more accurately understanding the human brain. In this review, we summarize the status of neural induction in two- and three-dimensional culture systems from hPSCs and the modeling of neurodegenerative diseases using brain organoids. We also highlight the latest bioengineered technologies for the assembly of spatially higher-ordered neural tissues and prospects of brain organoid technology toward the understanding of the potential and abilities of the human brain.

Study on human brain protection from electromagnetic radiation of mobile phone by plasma

The propagation characteristics of electromagnetic waves (EMW) in plasma with the plural dielectric properties (real and imaginary parts of the relative dielectric constant) were investigated in the virtual human brain (VHB) model by the full-wave solution. Simulation results indicate that the value of the electric and magnetic field amplitude of EMW with the frequency of 5 GHz and the value of specific absorption ratio within VHB can be reduced by more than 60% and 80%, respectively. After the secondary absorption of the plasma layer, the reflected wave amplitude is attenuated by 33.066 dB. The amplitude attenuation of EMW from 2.45 to 6 GHz can be exceeded 10 dB. Compared to the traditional absorbing materials for the electromagnetic protection, the plasma layer, as an absorbing medium, possesses wide frequency characteristics. These results have important reference value for reducing the high-frequency electromagnetic radiation to VHB.

Single-cell epigenomic reconstruction of developmental trajectories from pluripotency in human neural organoid systems

Cell fate progression of pluripotent progenitors is strictly regulated, resulting in high human cell diversity. Epigenetic modifications also orchestrate cell fate restriction. Unveiling the epigenetic mechanisms underlying human cell diversity has been difficult. In this study, we use human brain and retina organoid models and present single-cell profiling of H3K27ac, H3K27me3 and H3K4me3 histone modifications from progenitor to differentiated neural fates to reconstruct the epigenomic trajectories regulating cell identity acquisition. We capture transitions from pluripotency through neuroepithelium to retinal and brain region and cell type specification. Switching of repressive and activating epigenetic modifications can precede and predict cell fate decisions at each stage, providing a temporal census of gene regulatory elements and transcription factors. Removing H3K27me3 at the neuroectoderm stage disrupts fate restriction, resulting in aberrant cell identity acquisition. Our single-cell epigenome-wide map of human neural organoid development serves as a blueprint to explore human cell fate determination.

Human Brain In Vitro Model for Pathogen Infection-Related Neurodegeneration Study.

Recent advancements in stem cell biology and tissue engineering have revolutionized the field of neurodegeneration research by enabling the development of sophisticated in vitro human brain models. These models, including 2D monolayer cultures, 3D organoids, organ-on-chips, and bioengineered 3D tissue models, aim to recapitulate the cellular diversity, structural organization, and functional properties of the native human brain. This review highlights how these in vitro brain models have been used to investigate the effects of various pathogens, including viruses, bacteria, fungi, and parasites infection, particularly in the human brain cand their subsequent impacts on neurodegenerative diseases. Traditional studies have demonstrated the susceptibility of different 2D brain cell types to infection, elucidated the mechanisms underlying pathogen-induced neuroinflammation, and identified potential therapeutic targets. Therefore, current methodological improvement brought the technology of 3D models to overcome the challenges of 2D cells, such as the limited cellular diversity, incomplete microenvironment, and lack of morphological structures by highlighting the need for further technological advancements. This review underscored the significance of in vitro human brain cell from 2D monolayer to bioengineered 3D tissue model for elucidating the intricate dynamics for pathogen infection modeling. These in vitro human brain cell enabled researchers to unravel human specific mechanisms underlying various pathogen infections such as SARS-CoV-2 to alter blood-brain-barrier function and Toxoplasma gondii impacting neural cell morphology and its function. Ultimately, these in vitro human brain models hold promise as personalized platforms for development of drug compound, gene therapy, and vaccine. Overall, we discussed the recent progress in in vitro human brain models, their applications in studying pathogen infection-related neurodegeneration, and future directions.

Storage estimation in morphology modeling of the human whole brain at the nanoscale

The human brain is an enormous scientific challenge. Knowledge of the complete map of neuronal connections (connectome) is essential for understanding how neuronal circuits encode information and the brain works in health and disease. Nanoscale connectomes are created for a few small animals but not yet for the human. The key challenges in the development of a whole human brain model at the nanoscale are data acquisition and computing including big data and high performance computing. This work focuses on big data and volumetric and geometric modeling of brain morphology at the micro- and nanoscales. It presents the volumetric and four geometric neuronal models and estimates the storage required for them. It introduces four geometric neuronal models: straight wireframe, enhanced wireframe, straight polygonal, and enhanced polygonal. The volumetric model requires approximately from 4.2 to 33.6 petabytes (PB) at the microscale up to 5,600,000 exabytes (EB) at the nanoscale. The straight wireframe model requires 18 PB at the microscale and 24 PB at the nanoscale. The enhanced parabolic wireframe model needs 36 PB at the microscale and 48 PB at the nanoscale, whereas the enhanced cubic model requires 54 PB at the microscale and 72 PB at the nanoscale. The straight polygonal model requires 24 PB at the microscale and 32 PB at the nanoscale. The enhanced parabolic polygonal model needs 48 PB at the microscale and 64 PB at the nanoscale, while the enhanced cubic model needs 72 PB at the microscale and 96 PB at the nanoscale. The straight wireframe model of 18 PB is sufficient to enable computing of the human synaptome and subsequently the connectome. The only operational supercomputer able to provide such storage is the world’s first exascale supercomputer Frontier. The sizes of the volumetric and geometric models are comparable at the microscale, however, their difference is dramatic at the nanoscale; for the 10 nm resolution the geometric models are smaller approximately from 58 to 233 thousand times, and for the 1 nm resolution from 58 to 233 million times. This novel work is an extended version of a conference paper [15] and it represents a step forward toward the development of the human whole brain model at the nanoscale.

Evaluation of DAMAGE Algorithm in Frontal Crashes.

With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 - BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world. Although DAMAGE correlates well with MPS in the human brain model across several test scenarios, the predicted risk of AIS2+ brain injuries are too high compared to real-world experience. The prediction of AIS4+ brain injury risk in lower velocity crashes is good, but too high in NCAP-like and high speed angular frontal crashes.

Development of a 3D Brain Model to Study Sex-Specific Neuroinflammation After Hemorrhagic Stroke.

Subarachnoid hemorrhage (SAH) accounts for 5% of stroke, with women having a decreased inflammatory response compared to men; however, this mechanism has yet to be identified. One hurdle in SAH research is the lack of human brain models. Studies in murine models are helpful, but human models should be used in conjunction for improved translatability. These observations lead us to develop a 3D system to study the sex-specific microglial and neuroglial function in a novel in vitro human SAH model and compare it to our validated in vivo SAH model. Our lab has developed a 3D, membrane-based in vitro cell culture system with human astrocytes, microglia, and neurons from both sexes. The 3D cultures were incubated with male and female cerebrospinal fluid from SAH patients in the Neuro-ICU. Furthermore, microglial morphology, erythrophagocytosis, microglial inflammatory cytokine production, and neuronal apoptosis were studied and compared with our murine SAH models. The human 3D system demonstrated intercellular interactions and proportions of the three cell types similar to the adult human brain. In vitro and in vivo models of SAH showed concordance in male microglia being more inflammatory than females via morphology and flow cytometry. On the contrary, both in vitro and in vivo models revealed that female microglia were more phagocytic and less prone to damaging neurons than males. One possible explanation for the increased phagocytic ability of female microglia was the increased expression of CD206 and MerTK. Our in vitro, human, 3D cell culture SAH model showed similar results to our in vivo murine SAH model with respect to microglial morphology, inflammation, and phagocytosis when comparing the sexes. A human 3D brain model of SAH may be a useful adjunct to murine models to improve translation to SAH patients.

268 Integrative Genomics Identifies Evolutionary, Temporal, and Cell-lineage Origin of Hydrocephalus Risk Gene

INTRODUCTION: Our previous work identified MAEL, a gene involved in regulation of DNA transposon activity and histone methylation, as a transcriptome-wide predictor of pediatric hydrocephalus (Hale et al., Cell Reports, 2021). Here we aim to characterize the function of MAEL across timescales and cell-lineages in the developing human brain to understand the pathophysiological basis of hydrocephalus. METHODS: We performed taxonomic analysis of MAEL across species using Ensemble. Analysis of single-cell RNA sequencing (scRNA-seq) of 49 brain regions across the prenatal period from the Developing Human Brain Atlas (Allen Institute) and an atlas of late-prenatal cortical tissue identified temporospatial MAEL expression patterns. Finally, to estimate the degree to which in vitro models recapitulate expression patterns of MAEL in the developing brain, we analyzed scRNA-seq from human neural and choroid-plexus organoids. RESULTS: We performed taxonomic evolutionary gene-mapping to define the evolutionary origin of MAEL to assess suitability for mechanistic characterization in model systems. MAEL is among the top 0.01% human-specific genes and shares < 50% sequence homology with mammalian model organisms. scRNA-seq identified MAEL first detected in the telencephalon at 9 weeks post-conception, highest expressed in the sub-ventricular zone at 16 weeks, and lowest expressed in the hippocampus at 21 weeks post conception. Temporospatial expression of MAEL in the late-prenatal cortex identifies MAEL expression largely restricted to the neural progenitor cells before reaching steady-state expression throughout the cortical layers at 39 weeks gestation. Finally, spatial MAEL expression is largely preserved in brain organoids and robustly expressed in choroid plexus organoids highlighting the utility of these models in future mechanistic studies. CONCLUSIONS: We delineate the evolutionary origin and temporospatial patterns of MAEL expression in the developing human brain and organoid models. These data provide the premise for understanding the detailed molecular-genetic underpinnings of hydrocephalus.

Brain organoid protocols and limitations.

Stem cell-derived organoid technology is a powerful tool that revolutionizes the field of biomedical research and extends the scope of our understanding of human biology and diseases. Brain organoids especially open an opportunity for human brain research and modeling many human neurological diseases, which have lagged due to the inaccessibility of human brain samples and lack of similarity with other animal models. Brain organoids can be generated through various protocols and mimic whole brain or region-specific. To provide an overview of brain organoid technology, we summarize currently available protocols and list several factors to consider before choosing protocols. We also outline the limitations of current protocols and challenges that need to be solved in future investigation of brain development and pathobiology.

A theory of emotion based on a universal model

The complexity of emotions has thus far limited our understanding of them. To obtain a clear understanding of the nature of emotion, this paper proposes a novel emotion theory and establishes a universal model of the conscious world in the human brain, the substanguage and interaction model (SIM). Based on an analysis of the possibilities of the interaction process in the SIM, two basic emotions that are indecomposable factors within all emotions—hope and fear—are identified. A questionnaire survey reveals that this basic emotion exhibits high acceptability. Based on emotion theory, this paper reasonably explains the phenomena of facial attraction and infantile facial preference and discusses the psychological reasons for phonocentrism, the phenomenon of preferring the spoken word over the written word. In addition, this paper explores the possibility of artificial intelligence possessing self-emotions. Emotions are relevant to many areas of human knowledge, as well as to everyone’s daily lives, and the simple, clear way to understand emotions provided in this paper may be instructive for everyone.

Imitating and exploring the human brain's resting and task-performing states via brain computing: scaling and architecture.

A computational human brain model with the voxel-wise assimilation method was established based on individual structural and functional imaging data. We found that the more similar the brain model is to the biological counterpart in both scale and architecture, the more similarity was found between the assimilated model and the biological brain both in resting states and during tasks by quantitative metrics. The hypothesis that resting state activity reflects internal body states was validated by the interoceptive circuit's capability to enhance the similarity between the simulation model and the biological brain. We identified that the removal of connections from the primary visual cortex (V1) to downstream visual pathways significantly decreased the similarity at the hippocampus between the model and its biological counterpart, despite a slight influence on the whole brain. In conclusion, the model and methodology present a solid quantitative framework for a digital twin brain for discovering the relationship between brain architecture and functions, and for digitally trying and testing diverse cognitive, medical and lesioning approaches that would otherwise be unfeasible in real subjects.

Design and performance analysis of an L-shaped radiator and defected ground antenna for enhancing wireless connectivity in brain implants

Brain implantable wireless microsystems has potential to treat neurological diseases and maintain the quality of life. Highly efficient miniaturized antenna is the fundamental part of BID (brain implantable device) for reliable signaling of data through dissipative intracranial material. In this paper, a patch antenna with L-shaped defected ground is demonstrated. L-shaped radiator contributed to achieve the resonance at 2.45 GHz industrial scientific and medical (ISM) band. Antenna size is reduced to 10 × 10 × 0.25 mm3. The proposed L-shaped ground plane geometry is contributing in improving the radiation performance. |S11| value shifts from 15 dB to 30 dB after modifying the ground plane. Proposed structure attained the gain of −14 dBi when located between the Dura and CSF layers at the depth of 12 mm in human brain model. Full wave simulated antenna prototype is fabricated and measured for performance verification. Impedance bandwidth of 270 MHz and broadside radiation pattern (for transferring maximum electromagnetic energy away from tissue) are maintained by the proposed antenna. Brain tissue safety is ensured by specific absorption rate which is 0.709 W/kg and in compliance with the safety limits of 1.6 W/kg for 1-g averaged tissue. Proposed antenna structure is the promising candidate for medical implant technology.

Implantation of Flexible Electrodes for Simultaneous in-vivo Extracellular Recording and Two-Photon Imaging

Introduction: Rigid silicon electrodes like Utah array grids and Neuropixel probes have been used in human and animal brain models to understand the dynamics of neural computation, treat neurodegenerative disorders, and act as brain-machine-interfaces. However, when implanted chronically, glial proliferation can rapidly disrupt the interaction between neurons and electrodes, drastically reducing recording fidelity. The development of flexible electrodes has the potential to minimize tissue damage and inflammation, which allows for long-term recordings over several months. In line with this objective, the Nano-neurotechnology Lab at Purdue University has developed a 6-µm thick, flexible, and biocompatible Parylene probe to facilitate chronic recordings in awake mice. However, flexible electrodes present a unique engineering challenge as the force required to insert into the brain causes the probe to buckle and fail during insertion. 
 Methods and Results: Here, I designed a micropipette shuttle using a glass micropipette and custom insertion system which provided reproducible probe implantation into the cortex. The implantation device was designed in CAD software and 3D-printed for rapid prototyping. The procedure was developed on brain phantoms made of 0.6% agarose with a comparable Young’s modulus to mouse brain tissue. Utilizing 3D-printed pieces and the surface tension of diluted poly-vinyl-acrylate adhesive to align the probe to a micropipette, insertion of the electrode and retraction of the shuttle was accomplished in awake mice. 
 Conclusion: The implications of flexible recording electrodes are extensive. Long-term implantation opens the door for understanding behavioral and learning dynamics over time. Moreover, the flexibility of these probes allows for the combination of 2-photon optical microscopy, thus enabling multi-modal investigation of neuronal physiology. A low-cost, consistent procedure is the first step in the implementation of these flexible probes for further advancements in fundamental neuroscience research and its potential applications in human and animal studies.

Generating Homogeneous Brain Organoids from Human iPSCs.

There is a high demand for the development of in vitro models for human brain development and diseases due to the inaccessibility of human brain tissues. The human iPSC-derived brain organoids provide a promising in vitro model for studying human brain development and disorders. However, it is challenging to generate a large number of brain organoids with highconsistency for modeling human neurological diseases. Here, we describe a method for generating high-yield brain organoids with highconsistency by combining large-scale embryoid body (EB) generation and incorporating a quality controlscreening step duringdifferentiation. The method described in this chapter provides a robust way to generate brain organoids for studying human brain development and modeling neurological diseases.

Understanding molecular and cellular mechanisms of APOE4‐mediated susceptibility to tau‐related cognitive impairments in the miBrain model

AbstractBackgroundAPOE4 is the strongest genetic risk factor for Alzheimer’s disease with Tau pathology, namely hyperphosphorylation (p‐Tau) and aggregation of Tau into neurofibrillary tangles (NFTs) being correlated with poor cognitive outcomes in AD. Instances of mild traumatic brain injury (TBI) have been associated with increased susceptibility to neurodegenerative diseases such as AD and related dementias. We hypothesize that human APOE4 carriers’ brains are more susceptible to increased tau pathology with instances of TBI further increasing the severity.MethodUsing the 3D multi‐cellular integrated human brain (miBrain) model, which recapitulates key brain tissues through the co‐culturing of all hiPSC‐derived major brain cell‐types, Tau pathology can be induced with treatment of Tau fibrils or by increasing endogenous phosphorylated Tau with methotrexate.ResultAPOE4/4 miBrain cultures exhibit increased Tau pathology compared to isogenic APOE3/3 miBrains. Combinatorial genetic mixing experiments revealed that the increase of Tau hyperphosphorylation is dependent on the presence of APOE4 microglia.ConclusionData suggests that microglia facilitate the accumulation of p‐tau in APOE4 genetic backgrounds in an in vitro 3D model.

Patient-specific modeling for guided rehabilitation of stroke patients: the BrainX3 use-case

BrainX3 is an interactive neuroinformatics platform that has been thoughtfully designed to support neuroscientists and clinicians with the visualization, analysis, and simulation of human neuroimaging, electrophysiological data, and brain models. The platform is intended to facilitate research and clinical use cases, with a focus on personalized medicine diagnostics, prognostics, and intervention decisions. BrainX3 is designed to provide an intuitive user experience and is equipped to handle different data types and 3D visualizations. To enhance patient-based analysis, and in keeping with the principles of personalized medicine, we propose a framework that can assist clinicians in identifying lesions and making patient-specific intervention decisions. To this end, we are developing an AI-based model for lesion identification, along with a mapping of tract information. By leveraging the patient's lesion information, we can gain valuable insights into the structural damage caused by the lesion. Furthermore, constraining whole-brain models with patient-specific disconnection masks can allow for the detection of mesoscale excitatory-inhibitory imbalances that cause disruptions in macroscale network properties. Finally, such information has the potential to guide neuromodulation approaches, assisting in the choice of candidate targets for stimulation techniques such as Transcranial Ultrasound Stimulation (TUS), which modulate E-I balance, potentiating cortical reorganization and the restoration of the dynamics and functionality disrupted due to the lesion.