Finite Element Model Of Human Head Research Articles

Influence of Long-Term Use of American Football Helmets on Concussion Risk

In this study, to discuss the influence of concussion risk from the long-term use of American football helmets on collegiate teams, accident cases during the game are replicated based on game videos by simulations using whole-body numerical models and helmeted finite element human head models. The concussion risks caused by collisions were estimated using the mechanical parameters inside the skull obtained from finite element analyses. In the analyses, the different material properties of helmets identified by free-fall experiments using headform impactor-embedded helmets were used to represent brand-new and long-term-use helmets. After analyzing the five cases, it was observed that wearing a new helmet instead of a long-term-use one resulted in a reduction in the risk of concussion by 1 to 44%. More energy is attenuated by the deformation of the liners of the brand-new helmet, so the energy transferred to the head is smaller than that when wearing the long-term-use helmet. Thus, the long-term use of the helmet reduces its ability to protect the head.

A data-mining study on the prediction of head injury in traffic accidents among vulnerable road users with varying body sizes and head anatomical characteristics.

Body sizes and head anatomical characteristics play the major role in the head injuries sustained by vulnerable road users (VRU) in traffic accidents. In this study, in order to study the influence mechanism of body sizes and head anatomical characteristics on head injury, we used age, gender, height, and Body Mass Index (BMI) as characteristic parameters to develop the personalized human body multi-rigid body (MB) models and head finite element (FE) models. Next, using simulation calculations, we developed the VRU head injury dataset based on the personalized models. In the dataset, the dependent variables were the degree of head injury and the brain tissue von Mises value, while the independent variables were height, BMI, age, gender, traffic participation status, and vehicle speed. The statistical results of the dataset show that the von Mises value of VRU brain tissue during collision ranges from 4.4 kPa to 46.9kPa at speeds between 20 and 60km/h. The effects of anatomical characteristics on head injury include: the risk of a more serious head injury of VRU rises with age; VRU with higher BMIs has less head injury in collision accidents; height has very erratic and nonlinear impacts on the von Mises values of the VRU's brain tissue; and the severity of head injury is not significantly influenced by VRU's gender. Furthermore, we developed the classification prediction models of head injury degree and the regression prediction models of head injury response parameter by applying eight different data mining algorithms to this dataset. The classification prediction models have the best accuracy of 0.89 and the best R2 value of 0.85 for the regression prediction models.

Brain Material Properties and Integration of Arachnoid Complex for Biofidelic Impact Response for Human Head Finite Element Model.

Finite element head models offer great potential to study brain-related injuries; however, at present may be limited by geometric and material property simplifications required for continuum-level human body models. Specifically, the mechanical properties of the brain tissues are often represented with simplified linear viscoelastic models, or the material properties have been optimized to specific impact cases. In addition, anatomical structures such as the arachnoid complex have been omitted or implemented in a simple lumped manner. Recent material test data for four brain regions at three strain rates in three modes of loading (tension, compression, and shear) was used to fit material parameters for a hyper-viscoelastic constitutive model. The material model was implemented in a contemporary detailed head finite element model. A detailed representation of the arachnoid trabeculae was implemented with mechanical properties based on experimental data. The enhanced head model was assessed by re-creating 11 ex vivo head impact scenarios and comparing the simulation results with experimental data. The hyper-viscoelastic model faithfully captured mechanical properties of the brain tissue in three modes of loading and multiple strain rates. The enhanced head model showed a high level of biofidelity in all re-created impacts in part due to the improved brain-skull interface associated with implementation of the arachnoid trabeculae. The enhanced head model provides an improved predictive capability with material properties based on tissue level data and is positioned to investigate head injury and tissue damage in the future.

Finite element brain deformation in adolescent soccer heading

Finite element (FE) modeling provides a means to examine how global kinematics of repetitive head loading in sports influences tissue level injury metrics. FE simulations of controlled soccer headers in two directions were completed using a human head FE model to estimate biomechanical loading on the brain by direction. Overall, headers were associated with 95th percentile peak maximum principal strains up to 0.07 and von Mises stresses up to 1450 Pa, and oblique headers trended toward higher values than frontal headers but below typical injury levels. These quantitative data provide insight into repetitive loading effects on the brain.

Development of detailed finite element models for in silico analyses of brain impact dynamics

Background and objectiveIn the last few decades, several studies have been performed to investigate traumatic brain injuries (TBIs) and to understand the biomechanical response of brain tissues, by using experimental and computational approaches. As part of computational approaches, human head finite element (FE) models show to be important tools in the analysis of TBIs, making it possible to estimate local mechanical effects on brain tissue for different accident scenarios. The present study aims to contribute to the computational approach by means of the development of three advanced FE head models for accurately describing the head tissue dynamics, the first step to predict TBIs. MethodsWe have developed three detailed FE models of human heads from magnetic resonance images of three volunteers: an adult female (32 yrs), an adult male (35 yrs), and a young male (16 yrs). These models have been validated against experimental data of post mortem human subjects (PMHS) tests available in the literature. Brain tissue displacements relative to the skull, hydrostatic intracranial pressure, and head acceleration have been used as the parameters to compare the model response with the experimental response for validation. The software CORAplus (CORrelation and Analysis) has been adopted to evaluate the bio-fidelity level of FE models. ResultsNumerical results from the three models agree with experimental data. FE models presented in this study show a good bio-fidelity for hydrostatic pressure (CORA score of 0.776) and a fair bio-fidelity brain tissue displacements relative to the skull (CORA score of 0.443 and 0.535). The comparison among numerical simulations carried out with the three models shows negligible differences in the mechanical state of brain tissue due to the different morphometry of the heads, when the same acceleration history is considered. ConclusionsThe three FE models, thanks to their accurate description of anatomical morphology and to their bio-fidelity, can be useful tools to investigate brain mechanics due to different impact scenarios. Therefore, they can be used for different purposes, such as the investigation of the correlation between head acceleration and tissue damage, or the effectiveness of helmet designs. This work does not address the issue to define injury thresholds for the proposed models.

An in-silico analysis of retinal electric field distribution induced by different electrode design of trans-corneal electrical stimulation

Objective. Trans-corneal electrical stimulation (TcES) produces therapeutic effects on many ophthalmic diseases non-invasively. Existing clinical TcES devices use largely variable design of electrode distribution and stimulation parameters. Better understanding of how electrode configuration paradigms and stimulation parameters influence the electric field distribution on the retina, will be beneficial to the design of next-generation TcES devices. Approach. In this study, we constructed a realistic finite element human head model with fine eyeball structure. Commonly used DTL-Plus and ERG-Jet electrodes were simulated. We then conducted in silico investigations of retina observation surface (ROS) electric field distributions induced by different return electrode configuration paradigms and different stimulus intensities. Main results. Our results suggested that the ROS electric field distribution could be modulated by re-designing TcES electrode settings and stimulus parameters. Under far return location paradigms, either DTL-Plus or ERG-Jet approach could induce almost identical ROS electric field distribution regardless where the far return was located. However, compared with the ERG-Jet mode, DTL-Plus stimulation induced stronger nasal lateralization. In contrast, ERG-Jet stimulation induced relatively stronger temporal lateralization. The ROS lateralization can be further tweaked by changing the DTL-Plus electrode length. Significance. These results may contribute to the understanding of the characteristics of DTL-Plus and ERG-Jet electrodes based electric field distribution on the retina, providing practical implications for the therapeutic application of TcES.

The Protective Performance of Modern Motorcycle Helmets Under Oblique Impacts

Motorcyclists are at high risk of head injuries, including skull fractures, focal brain injuries, intracranial bleeding and diffuse brain injuries. New helmet technologies have been developed to mitigate head injuries in motorcycle collisions, but there is limited information on their performance under commonly occurring oblique impacts. We used an oblique impact method to assess the performance of seven modern motorcycle helmets at five impact locations. Four helmets were fitted with rotational management technologies: a low friction layer (MIPS), three-layer liner system (Flex) and dampers-connected liner system (ODS). Helmets were dropped onto a 45° anvil at 8 m/s at five locations. We determined peak translational and rotational accelerations (PTA and PRA), peak rotational velocity (PRV) and brain injury criteria (BrIC). In addition, we used a human head finite element model to predict strain distribution across the brain and in corpus callosum and sulci. We found that the impact location affected the injury metrics and brain strain, but this effect was not consistent. The rear impact produced lowest PTAs but highest PRAs. This impact produced highest strain in corpus callosum. The front impact produced the highest PRV and BrIC. The side impact produced the lowest PRV, BrIC and strain across the brain, sulci and corpus callosum. Among helmet technologies, MIPS reduced all injury metrics and brain strain compared with conventional helmets. Flex however was effective in reducing PRA only and ODS was not effective in reducing any injury metrics in comparison with conventional helmets. This study shows the importance of using different impact locations and injury metrics when assessing head protection effects of helmets. It also provides new data on the performance of modern motorcycle helmets. These results can help with improving helmet design and standard and rating test methods.

Optimized Load-Independent Hyperelastic Microcharacterization of Human Brain White Matter

Abstract A micromechanical methodology combined with genetic algorithm (GA) as a global optimization method is used to find the material properties of axons and extracellular matrix (ECM) in corpus callosum which is a part of human brain white matter. Studies have shown that axons are highly oriented in the ECM which enables us to approximate brain white matter as a unidirectional fibrous composite model. Using the one-term Ogden hyperelastic constitutive equations for the constituents and knowing the mechanical response of corpus callosum, GA optimization procedure is used in conjunction with finite element (FE) micromechanical analysis to find optimal material parameters for axon and ECM in three uniaxial loading scenarios of tension, compression, and simple shear. Moreover, by simultaneous fitting to the three loading modes' responses and applying Nelder–Mead simplex optimization method, best-fit parameters are found. The best-fit parameters can be used to approximate the behavior of axons and ECM in different uniaxial loading conditions with the minimum error and hence, can be interpreted as load-independent parameters. Micromechanical simulations by best-fit parameters show maximum stress increase of 2% and 29% for tension and shear and less than 1% reduction for compression mode compared to the case where optimal parameters are used. The findings and the methodology of this study can be employed for constitutive modeling of axonal fibers and its implementation in human head FE model where load-independent parameters are needed for simulating different loading scenarios.

Mechanical Strength Study of a Cranial Implant Using Computational Tools

The human head is sometimes subjected to impact loads that lead to skull fracture or other injuries that require the removal of part of the skull, which is called craniectomy. Consequently, the removed portion is replaced using autologous bone or alloplastic material. The aim of this work is to develop a cranial implant to fulfil a defect created on the skull and then study its mechanical performance by integrating it on a human head finite element model. The material chosen for the implant was PEEK, a thermoplastic polymer that has been recently used in cranioplasty. A6 numerical model head coupled with an implant was subjected to analysis to evaluate two parameters: the number of fixation screws that enhance the performance and ensure the structural integrity of the implant, and the implant’s capacity to protect the brain compared to the integral skull. The main findings point to the fact that, among all tested configurations of screws, the model with eight screws presents better performance when considering the von Mises stress field and the displacement field on the interface between the implant and the skull. Additionally, under the specific analyzed conditions, it is observable that the model with the implant offers more efficient brain protection when compared with the model with the integral skull.

Assessment of brain injury biomechanics in soccer heading using finite element analysis

This study presents an in silico finite element (FE) model-based biomechanical analysis of brain injury metrics and associated risks of a soccer ball impact to the head for aware and unaware athletes, considering ball impact velocity and direction. The analysis presented herein implements a validated soccer ball and 50th percentile human head computational FE model for quantifying traumatic brain injury (TBI) metrics. The brain's mechanical properties are designated using a viscoelastic-viscoplastic constitutive material model for the white and gray matter within the human head FE model. FE results show a dynamic human head-soccer ball peak contact area of approximately seven times greater than those documented for helmet-to-helmet hits in American Football. Due to the deformable nature of the soccer ball, the impact dynamics are unique depending on the location and velocity of impact. TBI injury risks also depend on the location of impact and the impact velocity. Impacts to the rear (BrIC:0.48, HIC15:180.7), side (BrIC:0.52, HIC15:176.5), and front (BrIC:0.37, HIC15:129.0) are associated with the highest injury risks. Furthermore, the FE results indicate when an athlete is aware of an incoming ball, HIC15-based Abbreviated Injury Scale 1 (AIS 1) injury risks for the front, side, and rear impacts decrease from 10.5%, 18.5%, and 19.3%, respectively, to approximately 1% in front and side impacts and under 6% in a rear impact. Lastly, the unique contact area between the head and soccer ball produces pressure gradients in the ball that translate into distinguishable stress waves in the skull and the cerebral cortex. Statement of significanceMild traumatic brain injuries (mTBI) are a worrisome aspect of participation in most sports due to difficulties in their diagnosis in competitions and the potential of long-term neurological defects. These types of injuries are not well understood for athletes playing soccer, specifically pertaining to the risks of heading a soccer ball. Studies are warranted which investigate impacts in this game to improve current knowledge. Our computational study uses finite element modeling to investigate contact between a player's head and the soccer ball. The results of this study present potential injury mechanisms and risks caused by this contact interaction to contribute to the current understanding of brain injuries in soccer and the promotion of athlete safety.

Cerebral Vasculature Influences Blast-Induced Biomechanical Responses of Human Brain Tissue.

Multiple finite-element (FE) models to predict the biomechanical responses in the human brain resulting from the interaction with blast waves have established the importance of including the brain-surface convolutions, the major cerebral veins, and using non-linear brain-tissue properties to improve model accuracy. We hypothesize that inclusion of a more detailed network of cerebral veins and arteries can further enhance the model-predicted biomechanical responses and help identify correlates of blast-induced brain injury. To more comprehensively capture the biomechanical responses of human brain tissues to blast-wave exposure, we coupled a three-dimensional (3-D) detailed-vasculature human-head FE model, previously validated for blunt impact, with a 3-D shock-tube FE model. Using the coupled model, we computed the biomechanical responses of a human head facing an incoming blast wave for blast overpressures (BOPs) equivalent to 68, 83, and 104 kPa. We validated our FE model, which includes the detailed network of cerebral veins and arteries, the gyri and the sulci, and hyper-viscoelastic brain-tissue properties, by comparing the model-predicted intracranial pressure (ICP) values with previously collected data from shock-tube experiments performed on cadaver heads. In addition, to quantify the influence of including a more comprehensive network of brain vessels, we compared the biomechanical responses of our detailed-vasculature model with those of a reduced-vasculature model and a no-vasculature model for the same blast-loading conditions. For the three BOPs, the predicted ICP values matched well with the experimental results in the frontal lobe, with peak-pressure differences of 4–11% and phase-shift differences of 9–13%. As expected, incorporating the detailed cerebral vasculature did not influence the ICP, however, it redistributed the peak brain-tissue strains by as much as 30% and yielded peak strain differences of up to 7%. When compared to existing reduced-vasculature FE models that only include the major cerebral veins, our high-fidelity model redistributed the brain-tissue strains in most of the brain, highlighting the importance of including a detailed cerebral vessel network in human-head FE models to more comprehensively account for the biomechanical responses induced by blast exposure.

Anisotropic finite element modelling of traumatic brain injury: A voxel-based approach

A computationally efficient 3D human head finite element model was constructed. The model includes the mesoscale geometrical details of the brain including the distinction between white and grey matter, sulci and gyri, ventricular system, foramen magnum, and the cerebrospinal fluid. We incorporate the heterogeneity and anisotropy from diffusion tensor imaging data by applying a one-to-one voxel-based correspondence between diffusion voxels and finite elements. The voxel resolution of the model was optimized to obtain a trade-off between reduced computational cost and higher geometrical details. Three sets of constitutive material properties were extracted from the literature to validate the model against intra-cranial pressure and relative motion test data within the brain. The model exhibited good agreement at pressure tests in frontal and occipital lobes with peak pressure magnitudes of only 8% and 6% higher which occurred 0.5-3 ms earlier than those of the experimental curves at coup and countercoup sites, respectively. In addition, the evaluation of the relative displacement at six locations within the brain indicated acceptable agreement with experimental data, with our model’s performance exhibiting the highest overall score compared to several previous models by using the correlation and analysis rating method.

The importance of modeling the human cerebral vasculature in blunt trauma

BackgroundMultiple studies describing human head finite element (FE) models have established the importance of including the major cerebral vasculature to improve the accuracy of the model predictions. However, a more detailed network of cerebral vasculature, including the major veins and arteries as well as their branch vessels, can further enhance the model-predicted biomechanical responses and help identify correlates to observed blunt-induced brain injury.MethodsWe used an anatomically accurate three-dimensional geometry of a 50th percentile U.S. male head that included the skin, eyes, sinuses, spine, skull, brain, meninges, and a detailed network of cerebral vasculature to develop a high-fidelity model. We performed blunt trauma simulations and determined the intracranial pressure (ICP), the relative displacement (RD), the von Mises stress, and the maximum principal strain. We validated our detailed-vasculature model by comparing the model-predicted ICP and RD values with experimental measurements. To quantify the influence of including a more comprehensive network of brain vessels, we compared the biomechanical responses of our detailed-vasculature model with those of a reduced-vasculature model and a no-vasculature model.ResultsFor an inclined frontal impact, the predicted ICP matched well with the experimental results in the fossa, frontal, parietal, and occipital lobes, with peak-pressure differences ranging from 2.4% to 9.4%. For a normal frontal impact, the predicted ICP matched the experimental results in the frontal lobe and lateral ventricle, with peak-pressure discrepancies equivalent to 1.9% and 22.3%, respectively. For an offset parietal impact, the model-predicted RD matched well with the experimental measurements, with peak RD differences of 27% and 24% in the right and left cerebral hemispheres, respectively. Incorporating the detailed cerebral vasculature did not influence the ICP but redistributed the brain-tissue stresses and strains by as much as 30%. In addition, our detailed-vasculature model predicted strain reductions by as much as 28% when compared to current reduced-vasculature FE models that only include the major cerebral vessels.ConclusionsOur study highlights the importance of including a detailed representation of the cerebral vasculature in FE models to more accurately estimate the biomechanical responses of the human brain to blunt impact.

The left anterior right temporal (LART) placement for electroconvulsive therapy: A computational modelling study

Electrode placement in electroconvulsive therapy (ECT) has a major impact on treatment efficacy and cognitive side effects. Left Anterior Right Temporal (LART) is a lesser utilised bilateral montage which may produce more optimal clinical outcomes relative to standard bitemporal ECT. In this study we used computational modelling to explore how stimulation effects from LART and two novel variants (LART – F3 and LART – Frontal) compared to the more common bilateral placements of bitemporal and bifrontal ECT. High resolution finite element human head models were generated from MRI scans of three subjects with Major Depressive Disorder. Differences in regional stimulation were examined through parametric tests for regions of interest and subtraction maps. Compared to bitemporal ECT, LART – Original resulted in significantly greater stimulation of the left cingulate gyrus (hypothesised to be associated with treatment efficacy), and relatively reduced stimulation of the bilateral hippocampi (potentially associated with cognitive side effects). No additional clinical benefit was suggested with the novel LART placements compared to the original LART. The original LART placement is a promising montage for further clinical investigation.

A simplified human head finite element model for brain injury assessment of blunt impacts

Blunt impacts contribute more than 95% of brain trauma injuries in Malaysia. Modelling and simulation of these impacts are essential in understanding the mechanics of the injuries to develop a protective equipment that might prevent brain trauma. Various finite element models of human head have been developed, ranging from two-dimensional models to very complex three-dimensional models. The aim of this study is to develop a simplified three-dimensional human head model with low computational cost, yet capable of producing reliable brain responses. The influence of different head-neck boundary conditions on the brain responses were also examined. Our model was validated against an experimental work on human cadaver. The model with free head-neck boundary condition was found to be in good agreement with experimental results. The head-neck joint was found to have a significant influence on the brain responses upon impact. Further investigations on the head-neck joint modelling are needed. Our simplified model was successfully validated against experimental data on human cadaver and could be used in simulating blunt impact scenarios.

The Strain Rates in the Brain, Brainstem, Dura, and Skull under Dynamic Loadings

Knowing the precise material properties of intracranial head organs is crucial for studying the biomechanics of head injury. It has been shown that these biological tissues are significantly rate-dependent; hence, their material properties should be determined with respect to the range of deformation rate they experience. In this paper, a validated finite element human head model is used to investigate the biomechanics of the head in impact and blast, leading to traumatic brain injuries (TBI). We simulate the head under various directions and velocities of impacts, as well as helmeted and unhelmeted head under blast shock waves. It is demonstrated that the strain rates for the brain are in the range of 36 to 241 s−1, approximately 1.9 and 0.86 times the resulting head acceleration under impacts and blast scenarios, respectively. The skull was found to experience a rate in the range of 14 to 182 s−1, approximately 0.7 and 0.43 times the head acceleration corresponding to impact and blast cases. The results of these incident simulations indicate that the strain rates for brainstem and dura mater are respectively in the range of 15 to 338 and 8 to 149 s−1. These findings provide a good insight into characterizing the brain tissue, cranial bone, brainstem and dura mater, and also selecting material properties in advance for computational dynamical studies of the human head.

Brain Strain from Motion of Sparse Markers.

Brain strain secondary to head impact or inertial loading is closely associated with pathologic observations in the brain. The only experimental brain strain dataset under loadings close to traumatic levels was calculated by imposing the experimentally measured motion of markers embedded in the brain to an auxiliary model formed by triad elements (Hardy et al., 2007). However, fidelity of the calculated strain as well as the suitability of using triad elements for three-dimensional (3D) strain estimation remains to be verified. Therefore, this study proposes to use tetrahedron elements as a new approach to estimate the brain strain. Fidelity of this newly-proposed approach along with the previous triad-based approach is evaluated with the aid of three independently-developed finite element (FE) head models by numerically replicating the experimental impacts and strain estimation procedures. Strain in the preselected brain elements obtained from the whole head simulation exhibits good correlation with its tetra estimation and exceeds its triad estimation, indicating that the tetra approach more accurately estimates the strain in the preselected region. The newly calculated brain strain curves using tetra elements provide better approximations for the 3D experimental brain deformation and can be used for strain validation of FE models of human head.

Biomechanical performance of a bicycle helmet design on a six-year-old head impact protection

A previously developed and validated 6-year-old (6YO) Finite Element (FE) human head model was used to evaluate the biomechanical performance of a new bicycle helmet design for children. The cushion structure of the new helmet design is made of honeycomb paperboard and corrugated paperboard instead of Expanded Polystyrene (EPS) foam. Simulation results showed that the EPS foam helmet can effectively resist external shocks in a short period. However, based on biomechanical responses of the 6YO head model, honeycomb and corrugated paperboard helmets also had a promising cushioning performance. From the drop test of the head-helmet model simulations, the effects of paperboard thickness and material parameters on the helmet protection efficiency were further investigated. It was concluded that the EPS foam helmet can be replaced with honeycomb/corrugated paperboard helmets which are made of more environmental friendly manufacturing materials.

Intracranial pressure-based validation and analysis of traumatic brain injury using a new three-dimensional finite element human head model.

Traumatic brain injuries are life-threatening injuries that can lead to long-term incapacitation and death. Over the years, numerous finite element human head models have been developed to understand the injury mechanisms of traumatic brain injuries. Many of these models are erroneous and used ellipsoidal or spherical geometries to represent brain. This work is focused on the development of high-quality, comprehensive three-dimensional finite element human head model with accurate representation of cerebral sulci and gyri structures in order to study traumatic brain injury mechanisms. Present geometry, predicated on magnetic resonance imaging data consist of three rudimentary components, that is, skull, cerebrospinal fluid with the ventricular system, and the soft tissues comprising the cerebrum, cerebellum, and brain stem. The brain is modeled as a hyperviscoelastic material. Meshed model with 10 nodes modified tetrahedral type element (C3D10M) is validated against two cadaver-based impact experiments by comparing the intracranial pressures at different locations of the head. Our results indicate a better agreement with cadaver results, specifically for the case of frontal and parietal intracranial pressure values. Existing literature focuses mostly on intracranial pressure validation, while the effects of von Mises stress on brain injury are not analyzed in detail. In this work, a detailed interpretation of neurological damage resulting from impact injury is performed by analyzing von Mises stress and intracranial pressure distribution across numerous segments of the brain. A reasonably good correlation with experimental data signifies the robustness of the model for predicting injury mechanisms based on clinical predictions of injury tolerance criteria.

Safety Aspects, Tolerability and Modeling of Retinofugal Alternating Current Stimulation.

BackgroundWhile alternating current stimulation (ACS) is gaining relevance as a tool in research and approaching clinical applications, its mechanisms of action remain unclear. A review by Schutter and colleagues argues for a retinal origin of transcranial ACS’ neuromodulatory effects. Interestingly, there is an alternative application form of ACS specifically targeting α-oscillations in the visual cortex via periorbital electrodes (retinofugal alternating current stimulation, rACS). To further compare these two methods and investigate retinal effects of ACS, we first aim to establish the safety and tolerability of rACS.ObjectiveThe goal of our research was to evaluate the safety of rACS via finite-element modeling, theoretical safety limits and subjective report.Methods20 healthy subjects were stimulated with rACS as well as photic stimulation and reported adverse events following stimulation. We analyzed stimulation parameters at electrode level as well as distributed metric estimates from an ultra-high spatial resolution magnetic resonance imaging (MRI)-derived finite element human head model and compared them to existing safety limits.ResultsTopographical modeling revealed the highest current densities in the anterior visual pathway, particularly retina and optic nerve. Stimulation parameters and finite element modeling estimates of rACS were found to be well below existing safety limits. No serious adverse events occurred.ConclusionOur findings are in line with existing safety guidelines for retinal and neural damage and establish the tolerability and feasibility of rACS. In comparison to tACS, retinofugal stimulation of the visual cortex provides an anatomically circumscribed model to systematically study the mechanisms of action of ACS.