Brain multiphysics最新文献

{"title":"Super-resolved shear shock focusing in the human head","authors":"Bharat B. Tripathi ,&nbsp;Sandhya Chandrasekaran ,&nbsp;Gianmarco F. Pinton","doi":"10.1016/j.brain.2021.100033","DOIUrl":"10.1016/j.brain.2021.100033","url":null,"abstract":"<div><p>Shear shocks, which exist in a completely different regime from compressional shocks, were recently observed in the brain. These low phase speed (<span><math><mo>≈</mo></math></span> 2 m/s) high Mach number (<span><math><mo>≈</mo></math></span> 1) waves could be the primary mechanism behind diffuse axonal injury due to a very high local acceleration at the shock front. The extreme nonlinearity of these waves results in unique behaviors that are different from more commonly studied nonlinear compressional waves. Here we show the first observation of super-resolved shear shock wave focusing. Shear shock wave imaging and numerical simulations in a human head phantom over a range of frequencies/amplitudes shows the super-resolution of shock waves in the low strain and high strain-rate regime. These results suggest that even for mild accelerations injuries as small as a grain of rice on the scale of mm<span><math><msup><mrow></mrow><mn>2</mn></msup></math></span> can be easily created deep inside the brain.</p></div><div><h3>Statement of Significance</h3><p>The relationship between brain motion and traumatic brain injury remains poorly understood despite many decades of investigation. We have developed high frame-rate ultrasound imaging techniques combined with motion tracking sequences that can capture a previously unobtainable high strain and high strain-rate regime. This quantitative imaging method has led to the discovery that shear waves can develop into shear shocks. To the best of our knowledge, we are the only group in the world that has observed these shear shocks in soft tissue. In this manuscript we demonstrate that shear waves are focused into destructive shocks deep inside the human head where rate-dependent metrics, such as acceleration and strain-rate, are amplified by an order of magnitude. Furthermore, it is shown that the destructive power of these shear shocks is superresolved into tiny areas about the size of a grain of rice. To achieve these results, we have made technical innovations in the field of ultrasound by designing shock-capturing imaging sequences, and simulations tools that can model shear shocks. There is an overwhelming amount of evidence that shear shock wave physics is a necessary and primary component of brain biomechanics and, we hypothesize, brain injury. Local measurements and simulations of this shock wave behavior, which are absent from current biomechanical models of the brain, may fundamentally change the way we approach the design of protective equipment in transportation, sports, playground safety, falls and our understanding of the extreme biomechanical environment to which our brains can be subjected.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100033"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666522021000137/pdfft?md5=9566b06d1b467e2639638a94d96d53df&pid=1-s2.0-S2666522021000137-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54405858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single cell electrophysiological alterations under dynamic loading at ultrasonic frequencies","authors":"M. Tamayo-Elizalde,&nbsp;C. Kayal,&nbsp;H. Ye,&nbsp;A. Jérusalem","doi":"10.1016/j.brain.2021.100031","DOIUrl":"10.1016/j.brain.2021.100031","url":null,"abstract":"<div><p>The use of ultrasound as a non-invasive means to modulate neuronal electrophysiological signals in experimental <em>in vivo</em> and <em>in vitro</em> models has recently been gaining momentum. Paradoxically, the intrinsic mechanisms linking high-frequency minute mechanical vibrations to electrophysiological alterations at the cellular scale are yet to be identified in this context. To this end, this work combines patch clamp and nanoindentation to study the action potential alterations induced by direct mechanical vibrations at ultrasonic frequencies of dorsal root ganglion-derived neuronal single cells. The characteristics of the action potentials are studied under oscillatory shear loadings of 25 and 50 nm displacement amplitudes at frequencies ranging from 250 kHz to 1 MHz. Results show significantly narrower action potentials, with faster depolarisations and shorter rising and falling phases when induced after 1 MHz. The faster action potential dynamics appearing once the oscillation is removed points towards a cumulative or lagged effect of mechanical stimulation at ultrasonic frequencies, also observed in ultrasound neuromodulation studies. It is hypothesised here that this action potential modulation arises as a consequence of remarkable membrane properties changes induced above a threshold frequency, situated between 370 kHz and 960 kHz, and possibly related to membrane stiffening and membrane phase state alterations. These observations demonstrate the ability of mechanical cues at the cellular level to modify the neuronal signal and assert the importance of the direct mechanical vibrations induced by ultrasound stimulation protocols in assisting the observed neuromodulatory effects.</p></div><div><h3>Statement of Significance</h3><p>In the last few decades, transcranial ultrasound stimulation (TUS) has established itself as one of the most promising non-invasive neuromodulating techniques. In particular, by avoiding both the lack of spatial specificity and surgical needs plaguing other established techniques, TUS offers new avenues for the treatment of neurological diseases. In order to enhance its specificity and efficacy, and, ultimately, optimise the sonication parameters for a given application, a better understanding of the underlying mechanisms linking mechanical vibrations to electrophysiological alterations is needed. By focusing on this coupling down to the cellular scale, this work demonstrates at the cellular scale that a transition between <span><math><mo>∼</mo></math></span> 400 kHz and <span><math><mo>∼</mo></math></span> 1 MHz exists above which mechanical vibrations are able to modulate the neuronal action potential by accelerating its dynamics.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100031"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brain.2021.100031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43421419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Awareness and confidence in perceptual decision-making","authors":"Joshua Skewes ,&nbsp;Chris Frith ,&nbsp;Morten Overgaard","doi":"10.1016/j.brain.2021.100030","DOIUrl":"10.1016/j.brain.2021.100030","url":null,"abstract":"<div><p>Perceptual decision-making employs a range of higher order metacognitive processes. Two of the most important of these are perceptual awareness; or the clarity with which one reports seeing a perceptual stimulus, and response confidence; or the certainty one has about the correctness of one's own perceptual categorizations. We used a novel false feedback paradigm to investigate the relationships between these two processes. We asked people to perform a standard psychophysical detection task. We used feedback to selectively intervene either on our participants’ trust in their own perceptual awareness of the stimulus, or on their confidence in their own responses. We measured the effects of these interventions on response accuracy; on reports of perceptual awareness; and on response confidence. We found that by undermining people's trust in their awareness of the sensory stimulus, we could reliably reduce their accuracy on the task. We suggest that the reason this occurred is that people came to rely less on evidence from their senses when making perceptual decisions. We conclude by suggesting that there is a not a one-to-one mapping between content in conscious experience and how that content is used in perceptual decision making, and that one's perception of the reliability of content also plays a role.</p></div><div><h3>Statement of Significance</h3><p>This paper explores how different kinds of metacognitive state are related to one another and to perceptual decision making. Our focus is on the states of metacognitive confidence and perceptual awareness. We examine how an intervention on the reliability of these states influences performance in a perceptual detection task. We also examine how the intervention influences reports of the states themselves. The intervention we use is false feedback. For one group of participants, we tell them their perceptual judgement is wrong whenever they report they are uncertain in their choice (confidence intervention). For another group, we tell them their judgement is wrong whenever they report that their experience of the stimulus is unclear (awareness intervention). We find that both interventions reduce the accuracy of people's judgements, but that the awareness intervention is more effective. Also, we find that only the awareness intervention reduces reports of both metacognitive confidence in the response, and awareness of the stimuli. The confidence intervention does not influence either metacognitive state. These results suggest that we should understand confidence and awareness as separate higher level cognitive states, and that we should understand awareness as having a stronger causal role than confidence in perception and performance.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100030"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brain.2021.100030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54405761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractal and multifractal characterization of in vitro respiratory recordings of the pre-Bötzinger complex","authors":"Ulises Paredes-Hernández ,&nbsp;Patricia Pliego-Pastrana ,&nbsp;Enrique Vázquez-Mendoza ,&nbsp;Consuelo Morgado-Valle ,&nbsp;Luis Beltran-Parrazal ,&nbsp;Arturo Criollo-Perez ,&nbsp;Erika Elizabeth Rodriguez-Torres","doi":"10.1016/j.brain.2021.100026","DOIUrl":"https://doi.org/10.1016/j.brain.2021.100026","url":null,"abstract":"<div><p>The pre-Bötzinger complex is a neural network located in the ventrolateral brainstem that generates the respiratory rhythm. Under normoxic conditions, this area shows two inspiratory burst patterns, sigh and non-sigh. Several studies have shown that in vitro application of peptides, such as bombesin, stimulates the respiratory rate and increases the appearance of sighs. However, it is difficult to distinguish between sighs and non-sighs waveforms, which makes it difficult to study their properties under experimental conditions. The fractal and multifractal analysis have proven to be valuable tools for studying physiological time series, thus in this study, we applied this methodology to characterize sighs and non-sighs. Our results regarding fractality, shown that the sighs and non-sighs have similar Hurst exponents and that the application of bombesin only decreased the Hurst exponent of non-sighs. On the other hand, our results on multifractality parameters scaling exponent (<span><math><mrow><mi>τ</mi><mo>(</mo><mi>q</mi><mo>)</mo></mrow></math></span>) and generalized Hurst exponent (<span><math><mrow><mi>H</mi><mo>(</mo><mi>q</mi><mo>)</mo></mrow></math></span>) shown that both sighs and non-sighs were multifractal and this remained even after the application of bombesin. Further analysis showed that sighs and non-sighs had different <span><math><mrow><mi>H</mi><mo>(</mo><mi>q</mi><mo>)</mo></mrow></math></span> values, which changed after the bombesin application. To quantitatively analyzed the multifractal spectrum, we calculated the area of the spectrum (<span><math><msub><mi>I</mi><mi>α</mi></msub></math></span>), which was similar between sighs and non-sighs and the application of bombesin did not change this. Altogether, these results show that the analysis of fractal and multifractal parameters allows to characterize and find statistical differences of sighs and non-sighs within and between different experimental conditions.</p></div><div><h3>Statement of Significance</h3><p>The characterization of the respiratory recordings is very difficult and time consuming when is done manually by a researcher. An automated software that can aid this can be very useful. Furthermore, this gives some parameters that can help to statistically differentiate between sighs and non sighs. One interesting finding was that multifractality show differences in the same condition between sighs and non sighs. Also, we found that the neuropeptide bombesin increases the number of sighs without changing the intrinsic structure of the respiration system. This is important to avoid the collapse of the lungs that can be incorporated in mechanical ventilators. We hope that you will find our paper suitable for publication in Brain Multiphysics and will look forward to receiving your response.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100026"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brain.2021.100026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92071546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A quantitative relationship between rotational head kinematics and brain tissue strain from a 2-D parametric finite element analysis","authors":"Rika Wright Carlsen ,&nbsp;Alice Lux Fawzi ,&nbsp;Yang Wan ,&nbsp;Haneesh Kesari ,&nbsp;Christian Franck","doi":"10.1016/j.brain.2021.100024","DOIUrl":"10.1016/j.brain.2021.100024","url":null,"abstract":"<div><p>Given the complex nature of traumatic brain injury (TBI), assessment of injury risk directly from kinematic measures of head motion remains a challenge. Despite this challenge, kinematic-based measures of injury continue to be widely used to guide the design of protective equipment. In an effort to provide more insight into the relationship between rotational head kinematics and injury risk, we have conducted a large scale parametric finite element analysis (FEA) to investigate the role of angular acceleration, angular velocity, and angular jerk on the brain tissue strains and strain rates. The peak strains and strain rates resulting from rotational head accelerations were obtained for peak angular accelerations ranging from 0.5 - 25 krad/s<span><math><msup><mrow></mrow><mn>2</mn></msup></math></span> and peak angular velocities ranging from 10 - 100 rad/s. The results of this study show that both angular acceleration and angular velocity have a significant effect on the peak tissue strains and strain rates, reinforcing the importance of accounting for both of these kinematic measures when evaluating injury risk. For a given magnitude of peak angular acceleration and angular velocity, increases in angular jerk are shown to have minimal effect on the peak tissue strains but can lead to an increase in the peak tissue strain rates. This advancement in our understanding of the relationship between angular head kinematics, tissue strain, and tissue strain rate is an important step toward developing improved kinematic-based measures of injury.</p></div><div><h3>Statement of Significance</h3><p>To reduce the risk of traumatic brain injury, we must first fully understand the relationship between impact-induced head motions and the brain deformation response. Large deformations of the brain have been shown to cause damage to neural cells and can result in long-term neurocognitive deficits. This study investigates the role of angular acceleration, angular velocity, and angular jerk on the tissue strains and strain rates that develop in the brain. By providing further insight into how each of these kinematic parameters affect the brain deformation response, we can begin to identify the types of head motions that are the most injurious and develop new targeted approaches to reduce the risk of injury.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100024"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brain.2021.100024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54405712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating material properties from magnetic resonance elastography into subject-specific computational models for the human brain","authors":"Ahmed Alshareef ,&nbsp;Andrew K. Knutsen ,&nbsp;Curtis L. Johnson ,&nbsp;Aaron Carass ,&nbsp;Kshitiz Upadhyay ,&nbsp;Philip V. Bayly ,&nbsp;Dzung L. Pham ,&nbsp;Jerry L. Prince ,&nbsp;K.T. Ramesh","doi":"10.1016/j.brain.2021.100038","DOIUrl":"10.1016/j.brain.2021.100038","url":null,"abstract":"<div><p>Advances in brain imaging and computational methods have facilitated the creation of subject-specific computational brain models that aid researchers in investigating brain trauma using simulated impacts. The emergence of magnetic resonance elastography (MRE) as a non-invasive mechanical neuroimaging tool has enabled in vivo estimation of material properties at low-strain, harmonic loading. An open question in the field has been how this data can be integrated into computational models. The goals of this study were to use a novel MRI dataset acquired in human volunteers to generate models with subject-specific anatomy and material properties, and then to compare simulated brain deformations to subject-specific brain deformation data under non-injurious loading. Models of five subjects were simulated with linear viscoelastic (LVE) material properties estimated directly from MRE data. Model predictions were compared to experimental brain deformation acquired in the same subjects using tagged MRI. Outcomes from the models matched the spatial distribution and magnitude of the measured peak strain components as well as the 95^th percentile in-plane peak strains within 0.005 mm/mm and maximum principal strain within 0.012 mm/mm. Sensitivity to material heterogeneity was also investigated. Simulated brain deformations from a model with homogenous brain properties and a model with brain properties discretized with up to ten regions were very similar (a mean absolute difference less than 0.0015 mm/mm in peak strains). Incorporating material properties directly from MRE into a biofidelic subject-specific model is an important step toward future investigations of higher-order model features and simulations under more severe loading conditions.</p></div><div><h3>Statement of Significance</h3><p>The study presents a method to calibrate and evaluate subject-specific finite element brain models using a combination of advanced magnetic resonance imaging (MRI) data. The imaging data is acquired in human volunteers and includes anatomical MRI, magnetic resonance elastography (MRE), and tagged MRI to generate subject-specific geometry, calibrate subject-specific material properties, and evaluate simulation response using subject-specific brain deformation. This dataset of MRE and tagged MRI allows for a unique evaluation of whether material properties from MRE can be used to create biofidelic computational models of the human brain. The study develops a calibration procedure to readily calculate linear viscoelastic material parameters from MRE data and then provides a sensitivity study of the effect of mechanical heterogeneity of the brain on simulation response. The calibrated computational models are used to simulate each subject's tagged MRI experiment; the results show good agreement between the simulated and experimental strain fields. The presented study and results will be informative in guiding the calibration of subject-specific computati","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100038"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/6e/22/nihms-1895473.PMC10168673.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9468830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of axonal fibers in the cortical folding patterns: A tale of variability and regularity","authors":"Poorya Chavoshnejad ,&nbsp;Xiao Li ,&nbsp;Songyao Zhang ,&nbsp;Weiying Dai ,&nbsp;Lana Vasung ,&nbsp;Tianming Liu ,&nbsp;Tuo Zhang ,&nbsp;Xianqiao Wang ,&nbsp;Mir Jalil Razavi","doi":"10.1016/j.brain.2021.100029","DOIUrl":"https://doi.org/10.1016/j.brain.2021.100029","url":null,"abstract":"<div><p>Cortical folding is one of the most complex processes that occur during the normal development of the human brain. Despite variability in folding patterns of different individuals, there are a few specific types of preserved folding patterns within individuals or across species. The origin and formation mechanism of variable or regular folding patterns in the human brain yet remains to be thoroughly explored. This study aims to delineate how the interplay between the differential tangential growth of cerebral cortex and axonal fiber tension induces and regulates the folding patterns in a developing human brain. To achieve this aim, an image-based multiscale mechanical model on the basis of the embedded nonlinear finite element method is employed to investigate a set of growth and folding scenarios. Our results show that the differential growth between cortical and subcortical layers is the main inducer of cortical folding. In addition, the gyrification of the cortex pulls the areas with a high density of stiff axonal fiber bundles towards gyri rather than sulci; therefore, axonal fiber bundles induce symmetry breaking, and regulate the folding patterns. In particular, spatial distribution of axonal fiber bundles is the determinant factor to control the locations of gyri and sulci. In conclusion, we propose that neural wiring might be the main regulator of folding patterns responsible for the formation of regular cortical folding patterns. This study provides a deeper understanding of cortical folding and its morphogenesis which are the key to interpreting normal brain development and growth.</p></div><div><h3>Statement of Significance</h3><p>There is a vital need to discover the role of axonal fibers of the brain’s connectivity on the formation and modulation of folding patterns in the developing human brain. The lack of knowledge of the physical interplay between cortical folding and neural wiring is a critical barrier to the fundamental understanding of the relationship between cortical folding, brain connectivity, and brain function in different neurodevelopmental stages. This study by using image-based multiscale mechanical models investigates the role of the differential tangential growth of cerebral cortex and axonal fibers in the formation and regulation of the folding patterns in the developing human brain. This is the first study to explain why despite variation in folding patterns, there are some specific types of regular shapes within individuals or across species and why axonal fibers connected to gyri in the human brain are typically denser than those connected to sulci. The study has a positive impact on the deeper understanding of cortical folding and its morphogenesis that is the key to interpreting the normal development of the human brain during the early stages of growth.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100029"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brain.2021.100029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92063973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-field computational model couples cellular brain development with cortical folding","authors":"M.S. Zarzor ,&nbsp;S. Kaessmair ,&nbsp;P. Steinmann ,&nbsp;I. Blümcke ,&nbsp;S. Budday","doi":"10.1016/j.brain.2021.100025","DOIUrl":"https://doi.org/10.1016/j.brain.2021.100025","url":null,"abstract":"<div><p>The convoluted macroscopic shape of the mammalian brain plays an important role for brain function. To date, the link between the cellular processes during brain development and normal or abnormal cortical folding on the macroscopic scale remains insufficiently understood. Disruption of cellular division, migration, or connectivity may lead to malformations of cortical development associated with neurological disorders like schizophrenia, autism, or epilepsy. Here, we use a computational model, which couples an advection-diffusion model with finite growth, to assess the link between cellular division and migration on the cell scale and growth and cortical folding on the tissue or organ scale. It introduces the cell density as independent field controlling volumetric growth. This allows us to numerically study the influence of cell migration velocity, cell diffusivity, and the temporally changing local stiffness of brain tissue on the cortical folding process during normal brain development. We show that the model is capable of capturing the local distribution of cells through the comparison with histologically stained sections of the developing human brain. Our results further demonstrate that it is important to take temporal changes in tissue stiffness into account, which naturally occur during brain development. The present study constitutes an important step towards a computational model that could help to better understand, diagnose, and, eventually, treat neurological disorders arising from abnormal cellular development and cortical malformations.</p></div><div><h3>Statement of Significance</h3><p>While it is now well established that mechanical instabilities play an important role for cortical folding in the developing human brain, the mechanisms on the cellular scale leading to those macroscopic structural changes remain insufficiently understood. Here, we demonstrate that a two-field mechanical model coupling cell division and migration with volume growth is capable of capturing the spatial and temporal distribution of the cell density and the corresponding cortical folding pattern observed in the human fetal brain. The presented model provides a platform to obtain important insights into the cellular mechanisms underlying normal cortical folding and, even more importantly, malformations of cortical development.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100025"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brain.2021.100025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92063972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A sensitivity analysis of a mathematical model for the synergistic interplay of amyloid beta and tau on the dynamics of Alzheimer’s disease","authors":"Michiel Bertsch ,&nbsp;Bruno Franchi ,&nbsp;Valentina Meschini ,&nbsp;Maria Carla Tesi ,&nbsp;Andrea Tosin","doi":"10.1016/j.brain.2020.100020","DOIUrl":"https://doi.org/10.1016/j.brain.2020.100020","url":null,"abstract":"<div><p>We propose a mathematical model for the onset and progression of Alzheimer’s disease based on transport and diffusion equations. We treat brain neurons as a continuous medium and structure them by their degree of malfunctioning. Three different mechanisms are assumed to be relevant for the temporal evolution of the disease: i) diffusion and agglomeration of soluble Amyloid beta, ii) effects of phosphorylated tau protein and iii) neuron-to-neuron prion-like transmission of the disease. We model these processes by a system of Smoluchowski equations for the Amyloid beta concentration, an evolution equation for the dynamics of tau protein and a kinetic-type transport equation for the distribution function of the degree of malfunctioning of neurons. The latter equation contains an integral term describing the random onset of the disease as a jump process localized in particularly sensitive areas of the brain. We are particularly interested in investigating the effects of the synergistic interplay of Amyloid beta and tau on the dynamics of Alzheimer’s disease. The output of our numerical simulations, although in 2D with an over-simplified geometry, is in good qualitative agreement with clinical findings concerning both the disease distribution in the brain, which varies from early to advanced stages, and the effects of tau on the dynamics of the disease.</p></div><div><h3>Statement of Significance</h3><p>We propose an in silico study of the onset and progression of Alzheimer’s disease (AD) in the brain by means of a mathematical model formulated in terms of kinetic and macroscopic integro-differential equations. From the biological side, our model takes into account the synergistic effect of Amiloid beta and phosphorylated tau protein and investigates the impact of their interplay on AD dynamics. From the mathematical side, unlike several other models present in the literature, our model does not focus on the detailed description of specific intra-cellular biochemical processes. It takes instead an aggregate point of view and, thanks to a multiscale approach inspired by statistical mechanics, describes the spatio-temporal patterns of the degree of neuronal malfunctioning due to AD in macroscopic portions of the brain tissue.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100020"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brain.2020.100020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92063971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyperelastic material properties of axonal fibers in brain white matter","authors":"Poorya Chavoshnejad ,&nbsp;Guy K. German ,&nbsp;Mir Jalil Razavi","doi":"10.1016/j.brain.2021.100035","DOIUrl":"10.1016/j.brain.2021.100035","url":null,"abstract":"<div><p>Accurate characterization of the mechanical properties of the human brain at both microscopic and macroscopic length scales is a critical requirement for modeling of traumatic brain injury and brain folding. To date, most experimental studies that employ classical tension/compression/shear tests report the mechanical properties of the brain averaged over both the gray and white matter within the macroscopic regions of interest. As a result, there is a missing correlation between the independent mechanical properties of the microscopic constituent elements and the composite bulk macroscopic mechanical properties of the tissue. This microstructural computational study aims to inversely predict the hyperelastic mechanical properties of the axonal fibers and their surrounding extracellular matrix (ECM) from the bulk tissue's mechanical properties. We develop a representative volume element (RVE) model of the bulk tissue consisting of axonal fibers and ECM with the embedded element technique. A multiobjective optimization technique is implemented to calibrate the model and establish the independent mechanical properties of axonal fibers and ECM based on seven previously reported experimental mechanical tests for bulk white matter tissue from the corpus callosum. The result of the study shows that the discrepancy between the reported values for the elastic behavior of white matter in literature stems from the anisotropy of the tissue at the microscale. The shear modulus of the axonal fiber is seven times larger than the ECM, with axonal fibers that also show greater nonlinearity, contrary to the common assumption that both components exhibit identical nonlinear characteristics.</p></div><div><h3>Statement of significance</h3><p>The reported mechanical properties of white matter microstructure used in traumatic brain injury or brain mechanics studies vary widely, in some cases by up to two orders of magnitude. Currently, the material parameters of the white matter microstructure are identified by a single loading mode or ultimately two modes of the bulk tissue. The presented material models only define the response of the bulk and homogenized white matter at a macroscopic scale and cannot explicitly capture the connection between the material properties of microstructure and bulk structure. To fill this knowledge gap, our study characterizes the hyperelastic material properties of axonal fibers and ECM using microscale computational modeling and multiobjective optimization. The hyperelastic material properties for axonal fibers and ECM presented in this study are more accurate than previously proposed because they have been optimized using seven or six loading modes of the bulk tissue, which were previously limited to only two of the seven possible loading modes. As such, the predicted values with high accuracy could be used in various computational modeling studies. The systematic characterization of the material properties of the human brain t","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"2 ","pages":"Article 100035"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666522021000150/pdfft?md5=d47dafeedf7d2fc8f41120599c459ced&pid=1-s2.0-S2666522021000150-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54405887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}