Reaction of human walking to transient block of vision: analysis in the context of indirect, referent control of motor actions.

Human locomotion may result from monotonic shifts in the referent position, R, of the body in the environment. R is also the spatial threshold at which muscles can be quiescent but are activated depending on the deflection of the current body configuration Q from R. Shifts in R are presumably accomplished with the participation of proprioceptive and visual feedback and responsible for transferring stable body balance (equilibrium) from one place in the environment to another, resulting in rhythmic activity of multiple muscles by a central pattern generator (CPG). We tested predictions of this two-level control scheme. In particular, in response to a transient block of vision during locomotion, the system can temporarily slow shifts in R. As a result, the phase of rhythmical movements of all four limbs will be changed for some time, even though the rhythm and other characteristics of locomotion will be fully restored after perturbation, a phenomenon called long-lasting phase resetting. Another prediction of the control scheme is that the activity of multiple muscles of each leg can be minimized reciprocally at specific phases of the gait cycle both in the presence and absence of vision. Speed of locomotion is related to the rate of shifts in the referent body position in the environment. Results confirmed that human locomotion is likely guided by feedforward shifts in the referent body location, with subsequent changes in the activity of multiple muscles by the CPG. Neural structures responsible for shifts in the referent body configuration causing locomotion are suggested.

Visual deprivation is met with active changes in ground reaction forces to minimize worsening balance and stability during walking.

Previous studies suggest that visual information is essential for balance and stability of locomotion. We investigated whether visual deprivation is met with active reactions tending to minimize worsening balance and stability during walking in humans. We evaluated effects of vision on kinetic characteristics of walking on a treadmill-ground reaction forces (GRFs) and shifts in the center of mass (COM). Young adults (n = 10) walked on a treadmill at a comfortable speed. We measured three orthogonal components of GRFs and COM shifts during no-vision (NV) and full-vision (FV) conditions. We also computed the dynamic balance index (DN)-the perpendicular distance from the projection of center of mass (pCOM) to the inter-foot line (IFL) normalized to half of the foot length. Locally weighted regression smoothing with alpha-adjusted serial T tests was used to compare GRFs and DN between two conditions during the entire stance phase. Results showed significant differences in GRFs between FV and NV conditions in vertical and ML directions. Variability of peak forces of all three components of GRF increased in NV condition. We also observed significant increase in DN for NV condition in eight out of ten subjects. The pCOM was kept within BOS during walking, in both conditions, suggesting that body stability was actively controlled by adjusting three components of GRFs during NV walking to minimize stability loss and preserve balance.

A mathematical model to mimic the shape of event related desynchronization/synchronization.

Rhythmic oscillatory activities of the sensory cortex have been observed after a presentation of a stimulus. This activity first drops dramatically and then increases considerably that are respectively named event-related desynchronization (ERD) and event-related synchronization (ERS). There are several effective factors that can alter the ERD and ERS pattern. In this study, a mathematical model was presented that produced ERD and ERS pattern in response to a stimulus. This model works based on the synchronization concepts. The proposed model provided different suggestions about the reason behind the relationship between the encoding of incoming sensory information and the oscillatory activities, effective factors on the characteristics of neuronal units, and how may these factors affect the amplitude and latency of the ERD and ERS.

Cerebellum as a forward but not inverse model in visuomotor adaptation task: a tDCS-based and modeling study.

Despite several pieces of evidence, which suggest that the human brain employs internal models for motor control and learning, the location of these models in the brain is not yet clear. In this study, we used transcranial direct current stimulation (tDCS) to manipulate right cerebellar function, while subjects adapt to a visuomotor task. We investigated the effect of this manipulation on the internal forward and inverse models by measuring two kinds of behavior: generalization of training in one direction to neighboring directions (as a proxy for inverse models) and localization of the hand position after movement without visual feedback (as a proxy for forward model). The experimental results showed no effect of cerebellar tDCS on generalization, but significant effect on localization. These observations support the idea that the cerebellum is a possible brain region for internal forward, but not inverse model formation. We also used a realistic human head model to calculate current density distribution in the brain. The result of this model confirmed the passage of current through the cerebellum. Moreover, to further explain some observed experimental results, we modeled the visuomotor adaptation process with the help of a biologically inspired method known as population coding. The effect of tDCS was also incorporated in the model. The results of this modeling study closely match our experimental data and provide further evidence in line with the idea that tDCS manipulates FM's function in the cerebellum.

The role of internal forward models and proprioception in hand position estimation.

Our ability to properly move and react in different situations is largely dependent on our perception of our limbs' position. At least three sources - vision, proprioception, and internal forward models (FMs) - seem to contribute to this perception. To the best of our knowledge, the effect of each source has not been studied individually. Specifically, role of FM has been ignored in some previous studies. We hypothesized that FM has a critical role in subjects' perception which needs to be considered in the relevant studies to obtain more reliable results. Therefore, we designed an experiment with the goal of investigating FM and proprioception role in subjects' perception of their hand's position. Three groups of subjects were recruited in the study. Based on the experiment design, it was supposed that subjects in different groups relied on proprioception, FM, and both of them for estimating their unseen hand's position. Comparing the results of three groups revealed significant difference between their estimation' errors. FM provided minimum estimation error, while proprioception had a bias error in the tested region. Integrating proprioception with FM decreased this error. Integration of two Gaussian functions, fitted to the error distribution of FM and proprioception groups, was simulated and created a mean error value almost similar to the experimental observation. These results suggest that FM role needs to be considered when studying the perceived position of the limbs. This can lead to gain better insights into the mechanisms underlying the perception of our limbs' position which might have potential clinical and rehabilitation applications, e.g., in the postural control of elderly which are at high risk of falls and injury because of deterioration of their perception with age.

Task-specific stability in muscle activation space during unintentional movements.

We used robot-generated perturbations applied during position-holding tasks to explore stability of induced unintentional movements in a multidimensional space of muscle activations. Healthy subjects held the handle of a robot against a constant bias force and were instructed not to interfere with hand movements produced by changes in the external force. Transient force changes were applied leading to handle displacement away from the initial position and then back toward the initial position. Intertrial variance in the space of muscle modes (eigenvectors in the muscle activations space) was quantified within two subspaces, corresponding to unchanged handle coordinate and to changes in the handle coordinate. Most variance was confined to the former subspace in each of the three phases of movement, the initial steady state, the intermediate position, and the final steady state. The same result was found when the changes in muscle activation were analyzed between the initial and final steady states. Changes in the dwell time between the perturbation force application and removal led to different final hand locations undershooting the initial position. The magnitude of the undershot scaled with the dwell time, while the structure of variance in the muscle activation space did not depend on the dwell time. We conclude that stability of the hand coordinate is ensured during both intentional and unintentional actions via similar mechanisms. Relative equifinality in the external space after transient perturbations may be associated with varying states in the redundant space of muscle activations. The results fit a hierarchical scheme for the control of voluntary movements with referent configurations and redundant mapping between the levels of the hierarchy.

Quantifying Human Gait Symmetry During Blindfolded Treadmill Walking.

Bilateral gait symmetry is an essential requirement for normal walking since asymmetric gait patterns increase the risk of falls and injuries. While human gait control heavily relies on the contribution of sensory inputs, the role of sensory systems in producing symmetric gait has remained unclear. This study evaluated the influence of vision as a dominant sensory system on symmetric gait production. Ten healthy adults performed treadmill walking with and without vision. Twenty-two gait parameters including ground reaction forces, joint range of motion, and other spatial-temporal gait variables were evaluated to quantify gait symmetry and compared between both visual conditions. Visual block caused increased asymmetry in most parameters of ground reaction force, however mainly in the vertical direction. When vision was blocked, symmetry of the ankle and knee joint range of motion decreased, but this change did not occur in the hip joint. Stance and swing time symmetry decreased during no-vision walking while no significant difference was found for step length symmetry between the two conditions. This study provides a comprehensive analysis to reveal how the visual system influences bilateral gait symmetry and highlights the important role of vision in gait control. This approach could be applied to investigate how vision alters gait symmetry in patients with disorders to help better understand the role of vision in pathological gaits.

Preparing to reach: selecting an adaptive long-latency feedback controller.

In a voluntary movement, the nervous system specifies not only the motor commands but also the gains associated with reaction to sensory feedback. For example, suppose that, during reaching, a perturbation tends to push the hand to the left. With practice, the brain not only learns to produce commands that predictively compensate for the perturbation but also increases the long-latency reflex gain associated with leftward displacements of the arm. That is, the brain learns a feedback controller. Here, we wondered whether, during the preparatory period before the reach, the brain engaged this feedback controller in anticipation of the upcoming movement. If so, its signature might be present in how the motor system responds to perturbations in the preparatory period. Humans trained on a reach task in which they adapted to a force field. During the preparatory period before the reach, we measured how the arm responded to a pulse to the hand that was either in the direction of the upcoming field, or in the opposite direction. Reach adaptation produced an increase in the long-latency (45-100 ms delay) feedback gains with respect to baseline, but only for perturbations that were in the same direction as the force field that subjects expected to encounter during the reach. Therefore, as the brain prepares for a reach, it loads a feedback controller specific to the upcoming reach. With adaptation, this feedback controller undergoes a change, increasing the gains for the expected sensory feedback.

A biologically inspired neural model for visual and proprioceptive integration including sensory training.

Humans perceive the surrounding world by integration of information through different sensory modalities. Earlier models of multisensory integration rely mainly on traditional Bayesian and causal Bayesian inferences for single causal (source) and two causal (for two senses such as visual and auditory systems), respectively. In this paper a new recurrent neural model is presented for integration of visual and proprioceptive information. This model is based on population coding which is able to mimic multisensory integration of neural centers in the human brain. The simulation results agree with those achieved by casual Bayesian inference. The model can also simulate the sensory training process of visual and proprioceptive information in human. Training process in multisensory integration is a point with less attention in the literature before. The effect of proprioceptive training on multisensory perception was investigated through a set of experiments in our previous study. The current study, evaluates the effect of both modalities, i.e., visual and proprioceptive training and compares them with each other through a set of new experiments. In these experiments, the subject was asked to move his/her hand in a circle and estimate its position. The experiments were performed on eight subjects with proprioception training and eight subjects with visual training. Results of the experiments show three important points: (1) visual learning rate is significantly more than that of proprioception; (2) means of visual and proprioceptive errors are decreased by training but statistical analysis shows that this decrement is significant for proprioceptive error and non-significant for visual error, and (3) visual errors in training phase even in the beginning of it, is much less than errors of the main test stage because in the main test, the subject has to focus on two senses. The results of the experiments in this paper is in agreement with the results of the neural model simulation.

Cortical Morphology in Cannabis Use Disorder: Implications for Transcranial Direct Current Stimulation Treatment.

Introduction: Transcranial direct current stimulation (tDCS) has been studied as an adjunctive treatment option for substance use disorders (SUDs). Alterations in brain structure following SUD may change tDCS-induced electric field (EF) and subsequent responses; however, group-level differences between healthy controls (HC) and participants with SUDs in terms of EF and its association with cortical architecture have not yet been modeled quantitatively. This study provides a methodology for group-level analysis of computational head models to investigate the influence of cortical morphology metrics on EFs. Methods: Whole-brain surface-based morphology was conducted, and cortical thickness, volume, and surface area were compared between participants with cannabis use disorders (CUD) (n=20) and age-matched HC (n=22). Meanwhile, EFs were simulated for bilateral tDCS over the dorsolateral prefrontal cortex. The effects of structural alterations on EF distribution were investigated based on individualized computational head models. Results: Regarding EF, no significant difference was found within the prefrontal cortex; however, EFs were significantly different in left-postcentral and right-superior temporal gyrus (P<0.05) with higher levels of variance in CUD compared to HC [F(39, 43)=5.31, P<0.0001, C=0.95]. Significant differences were observed in cortical area (caudal anterior cingulate and rostral middle frontal), thickness (lateral orbitofrontal), and volume (paracentral and fusiform) between the two groups. Conclusion: Brain morphology and tDCS-induced EFs may be changed following CUD; however, differences between CUD and HCs in EFs do not always overlap with brain areas that show structural alterations. To sufficiently modulate stimulation targets, whether individuals with CUD need different stimulation doses based on tDCS target location should be checked.

Lack of visual information alters lower limb motor coordination to control center of mass trajectory during walking.

Vision, as queen of the senses, plays a critical role in guiding locomotion. Little is known about the effects of vision on gait coordination in terms of variability. The uncontrolled manifold (UCM) approach offers a window to the structure of motor variability that has been difficult to obtain from the traditional correlation analysis. In this study, we used the UCM analysis to quantify how the lower limb motion is coordinated to control the center of mass (COM) while walking under different visual conditions. We also probed how synergy strength evolved along the stance phase. Ten healthy participants walked on the treadmill with and without visual information. Leg joint angle variance with respect to the whole-body COM was partitioned into good (i.e., the one that kept the COM) and bad (i.e., the one that changed the COM) variances. We observed that after vision was eliminated, both variances increased throughout the stance phase while the strength of the synergy (the normalized difference between the two variances) decreased significantly and even reduced to zero at heel contact. Thus, walking with restricted vision alters the strength of the kinematic synergy to control COM in the plane of progression. We also found that the strength of this synergy varied across different walking phases and gait events in both visual conditions. We concluded that the UCM analysis can quantify altered coordination of COM when vision is blocked and sheds insights on the role of vision in the synergistic control of locomotion.

Modeling of cerebellar transcranial electrical stimulation effects on hand tremor in Parkinson's disease.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder with different motor and neurocognitive symptoms. Tremor is a well-known symptom of this disease. Increasing evidence suggested that the cerebellum may substantially contribute to tremors as a clinical symptom of PD. However, the theoretical foundations behind these observations are not yet fully understood. Methods: In this study, a computational model is proposed to consider the role of the cerebellum and to show the effectiveness of cerebellar transcranial alternating current stimulation (tACS) on the rest tremor in participants with PD. The proposed model consists of the cortex, cerebellum, spinal circuit-muscular system (SC-MS), and basal ganglia blocks as the most critical parts of the brain, which are involved in generating rest tremors. The cortex, cerebellum, and SC-MS blocks were modeled using Van der Pol oscillators that interacted through synchronization procedures. Basal ganglia are considered as a regulator of the coupling weights defined between oscillators. In order to evaluate the global behavior of the model, we applied tACS on the cerebellum of fifteen PD patients for 15 min at each patient's peak frequency of their rest tremors. A tri-axial accelerometer recorded rest tremors before, during, and after the tACS. Results and Discussion: The simulation of the model provides a suggestion for the possible role of the cerebellum on rest tremors and how cerebellar tACS can affect these tremors. Results of human experiments also showed that the online and offline effects of cerebellar tACS could lead to the reduction of rest tremors significantly by about %76 and %68, respectively. Our findings suggest that the cerebellar tACS could serve as a reliable, therapeutic technique to suppress the PD tremor.

Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments.

One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.

Do the chaotic features of gait change in Parkinson's disease?

Some previous studies have focused on chaotic properties of Parkinson's disease (PD). It seems that considering PD from dynamical systems perspective is a relevant method that may lead to better understanding of the disease. There is some ambiguity about chaotic nature in PD symptoms and normal behaviour. Some studies claim that normal gait has somehow a chaotic behaviour and disturbed gait in PD has decreased chaotic nature. However, it is worth noting that the basis of this idea is the difference of fractal behaviour in gait of normal and PD patients, which is concluded from Long Range Correlation (LRC) indices. Our primary calculations show that a large number of normal persons and patients have similar LRC. It seems that chaotic studies on PD need a different view. Because of short time recording of symptoms, accurate calculation of chaotic features is tough. On the other hand, long time recording of symptoms is experimentally difficult. In this research, we have first designed a physiologically plausible model for normal and PD gait. Then, after validating the model with neural network classifier, we used the model for extracting long time simulation of stride in normal and PD persons. These long time simulations were then used for calculating the chaotic features of gait. According to change of phase space behaviour and alteration of three largest lyapunov exponents, it was observed that simulated normal persons act as chaotic systems in stride production, but simulated PD does not have chaotic dynamics and is stochastic. Based on our results, it may be claimed that normal gait has chaotic nature which is disturbed in PD state. Surely, long time real recordings from gait signal in normal persons and PD patients are necessary to warranty this hypothesis.

The effect of proprioceptive training on multisensory perception under visual uncertainty.

Most previous studies on multisensory integration concern mandatory integration. Moreover, no study has evaluated the effect of modality training on the result of integration. The purpose of this study is to evaluate the effect of training on visual-proprioceptive integration; i.e., we investigate the effect of proprioceptive modality training on the hand location estimation, when visual feedback exists. To achieve this goal, the effect of visual uncertainty on the estimation of hand position in visual-proprioceptive integration is studied in two groups: trained proprioception and untrained proprioception. The visual uncertainty is provided by an unpredictable spatial shift between visual and proprioceptive sensory feedbacks. The experiment was performed on nine subjects with trained proprioception and 11 subjects without proprioception training. The experiment had three phases: "familiarization", to draw participant's attention to a modality, "proprioception test", to estimate the hand position using only proprioception, and "vision-proprioception test", to investigate the effect of the visual uncertainty (bias) on hand position estimation. Our results indicate that: (i) modality training increases the subject reliance on the proprioceptive sensory information (i.e., bias decrement in sensory integration); and (ii) increasing the discrepancy between the modalities leads to more uncertainty (i.e., variance) in the estimation of hand position, but the variance of the final estimate is less than the variance of the proprioceptive estimate. This result confirms the theory that both senses contribute to the multisensory perception and in contrast to some studies, the dominant sense does not fully override the non-dominant one in the range of applied shift between the sensory sources.

A Neuro-Computational Model for Discrete-Continuous Dual-Task Process.

Studies on dual-task (DT) procedures in human behavior are important, as they can offer great insight into the cognitive control system. Accordingly, a discrete-continuous auditory-tracking DT experiment was conducted in this study with different difficulty conditions, including a continuous mouse-tracking task concurrent with a discrete auditory task (AT). Behavioral results of 25 participants were investigated via different factors, such as response time (RT), errors, and hesitations (pauses in tracking tasks). In DT, synchronization of different target neuron units was observed in corresponding brain regions; consequently, a computational model of the stimulus process was proposed to investigate the DT interference procedure during the stimulus process. This generally relates to the bottom-up attention system that a neural resource allocates for various ongoing stimuli. We proposed a black-box model based on interactions and mesoscopic behaviors of neural units. Model structure was implemented based on neurological studies and oscillator units to represent neural activities. Each unit represents one stimulus feature of task concept. Comparing the model's output behavior with the experiment results (RT) validates the model. Evaluation of the proposed model and data on RT implies that the stimulus of the AT affects the DT procedure in the model output (84% correlation). However, the continuous task is not significantly changed (26% correlation). The continuous task simulation results were inconsistent with the experiment, suggesting that continuous interference occurs in higher cognitive processing regions and is controlled by the top-down attentional system. However, this is consistent with the psychological research finding of DT interference occurring in response preparation rather than the stimulus process stage. Furthermore, we developed the proposed model by adding qualitative interpretation and saving the model's generality to address various types of discrete continuous DT procedures. The model predicts a justification method for brain rhythm interactions by synchronization, and manipulating parameters would produce different behaviors. The decrement of coupling parameter and strength factor would predict a similar pattern as in Parkinson's disease and ADHD disorder, respectively. Also, by increasing the similarity factor among the features, the model's result shows automatic task performance in each task.

A fuzzy-oscillatory model of medial prefrontal cortex control function in spatial memory retrieval in human navigation function.

Navigation can be broadly defined as the process of moving from an origin to a destination through path-planning. Previous research has shown that navigation is mainly related to the function of the medial temporal lobe (MTL), including the hippocampus (HPC), and medial prefrontal cortex (mPFC), which controls retrieval of the spatial memories from this region. In this study, we suggested a cognitive and computational model of human navigation with a focus on mutual interactions between the hippocampus (HPC) and the mPFC using the concept of synchrony. The Van-der-pol oscillator was used to model the synchronous process of receiving and processing "what stream" information. A fuzzy lookup table system was applied for modeling the controlling function of the mPFC in retrieving spatial information from the HPC. The effect of attention level was also included and simulated. The performance of the model was evaluated using information reported in previous experimental research. Due to the inherent stability of the proposed fuzzy-oscillatory model, it is less sensitive to the exact values of the initial conditions, and therefore, it is shown that it is consistent with the actual human performance in real environments. Analyzing the proposed cognitive and fuzzy-oscillatory computational model demonstrates that the model is able to reproduce certain cognitive and functional disturbances in navigation in related diseases such as Alzheimer's disease (AD). We have shown that an increase in the bifurcation parameter of the Van-der-pol equation represents an increase in the low-frequency spectral power density and a decrease in the high-frequency spectral power as occurs in AD due to an increase in the amyloid plaques in the brain. These changes in the frequency characteristics of neuronal activity, in turn, lead to impaired recall and retrieval of landmarks information and learned routes upon encountering them. As a result, and because of the wrong frequency code being transmitted, the relevant set of rules in the mPFC is not activated, or another unrelated set will be activated, which leads to forgetfulness and erroneous decisions in routing and eventually losing the route in Alzheimer's patients.

DLPFC stimulation alters large-scale brain networks connectivity during a drug cue reactivity task: A tDCS-fMRI study.

Transcranial direct current stimulation (tDCS) is a promising intervention for reducing craving/consumption in individuals with substance use disorders. However, its exact mechanism of action has not yet been well explored. We aimed to examine the network-based effects of tDCS while people with methamphetamine use disorders (MUDs) were exposed to drug cues. In a randomized, double-blind sham-controlled trial with a crossover design, 15 participants with MUDs were recruited to receive 20 min of active/sham tDCS with an anode/cathode over F4/F3. MRI data, including structural and task-based functional MRI during a standard drug cue-reactivity task, were collected immediately before and after stimulation sessions. Craving scores were also recorded before and after MRI scans. Individualized head models were generated to determine brain regions with strong electric fields (EFs). Using atlas-based parcellation of head models, averaged EFs were extracted from the main nodes of three large-scale networks that showed abnormalities in MUDs; executive control (ECN), default mode (DMN), and ventral attention (VAN) networks. Main nodes with high EF intensity were used as seed regions for task-based functional connectivity (FC) [using generalized psychophysiological interaction (gPPI)] and activity [using a general linear model (GLM)] calculations. Subjective craving showed a significant reduction in immediate craving after active (-15.42 ± 5.42) compared to sham (-1 ± 2.63). In seed-to-whole brain results, the PFC node in ECN showed an enhanced PPI connectivity with precuneus and visual cortex; the cluster center in MNI (6, -84, -12); the PFC node in DMN showed a decreased PPI connectivity with contralateral parietal cortex;(-48, -60, 46). ROI-to-ROI results showed increased PPI connectivity within/between ECN-VAN while connectivity between ECN-DMN decreased. In line with connectivity, functional activity in the right PFC node in DMN decreased after tDCS while activity in PFC nodes of ECN/VAN increased. EF calculations in PFC nodes revealed that EF in DMN was outward, while the direction of EFs was inward in ECN/VAN. This study provides new insight into neural circuitry underlying MUDs that can be modulated by tDCS at the network level and specifically suggests that bilateral tDCS increases cortical excitability in ECN and VAN, while it has opposite effects on DMN that may be related to the direction of EFs.

Group and individual level variations between symmetric and asymmetric DLPFC montages for tDCS over large scale brain network nodes.

Two challenges to optimizing transcranial direct current stimulation (tDCS) are selecting between, often similar, electrode montages and accounting for inter-individual differences in response. These two factors are related by how tDCS montage determines current flow through the brain considered across or within individuals. MRI-based computational head models (CHMs) predict how brain anatomy determines electric field (EF) patterns for a given tDCS montage. Because conventional tDCS produces diffuse brain current flow, stimulation outcomes may be understood as modulation of global networks. Therefore, we developed a network-led, rather than region-led, approach. We specifically considered two common "frontal" tDCS montages that nominally target the dorsolateral prefrontal cortex; asymmetric "unilateral" (anode/cathode: F4/Fp1) and symmetric "bilateral" (F4/F3) electrode montages. CHMs of 66 participants were constructed. We showed that cathode location significantly affects EFs in the limbic network. Furthermore, using a finer parcellation of large-scale networks, we found significant differences in some of the main nodes within a network, even if there is no difference at the network level. This study generally demonstrates a methodology for considering the components of large-scale networks in CHMs instead of targeting a single region and specifically provides insight into how symmetric vs asymmetric frontal tDCS may differentially modulate networks across a population.