bioRxiv Subject Collection: Neuroscience's Journal

"Fire! Do Not Fire!": A new paradigm testing how autonomous systems affect agency and moral decision-making.
Autonomous systems have pervaded many aspects of human activities. However, research suggest that the interaction with those machines may influence human decision-making processes. These effects raise ethical concerns in moral situations. We created an ad hoc setup to investigate the effects of system autonomy on moral decision-making and human agency in a trolley-like dilemma. In a battlefield simulation, participants had to decide whether to initiate an attack depending on conflicting moral values. Our results suggest that our paradigm is suitable for future research aimed at understanding the effects of system autonomy on moral decision-making and human agency.

Sensitization of Human and Rat Nociceptors by Low Dose Morphine is TLR4-dependent
While opioids remain amongst the most effective treatments for moderate-to-severe pain, their substantial side effect profile remains a major limitation to broader clinical use. One such side effect is opioid-induced hyperalgesia (OIH), which includes a transition from opioid-induced analgesia to pain enhancement. Evidence in rodents supports the suggestion that OIH may be produced by the action of opioids at Toll-like Receptor 4 (TLR4) either on immune cells that, in turn, produce pronociceptive mediators to act on nociceptors, or by a direct action at nociceptor TLR4. And, sub-analgesic doses of several opioids have been shown to induce hyperalgesia in rodents by their action as TLR4 agonists. In the present in vitro patch-clamp electrophysiology experiments, we demonstrate that low dose morphine directly sensitizes human as well as rodent dorsal root ganglion (DRG) neurons, an effect of this opioid analgesic that is antagonized by LPS-RS Ultrapure, a selective TLR4 antagonist. We found that morphine (100 nM) reduced rheobase in human (by 36%) and rat (by 26%) putative C-type nociceptors, an effect of morphine that was markedly attenuated by preincubation with LPS-RS Ultrapure. Our findings support the suggestion that in humans, as well as in rodents, OIH is mediated by the direct action of opioids at TLR4 on nociceptors.

Concurrent action observation but not motor imagery modulates interhemispheric inhibition during physical execution
Motor control relies on an inhibitory connection between the motor cortices of the brain, known as interhemispheric inhibition (IHI). This phenomenon is well established during the execution of unilateral motor tasks. It is unknown if the neurophysiological effects associated with IHI during physical execution (PE) also occur during action observation (AO) and motor imagery (MI) and/or if the addition of these covert processes to PE moderates IHI; speaking to differences in neurophysiology and functional equivalence. Participants (N=23) performed unilateral concentric wrist contractions (50% maximum voluntary contraction) under three conditions: PE alone, concurrent PE+AO, and concurrent PE+MI. To index IHI, we induced an ipsilateral silent period (iSP) and assessed iSP duration during each condition via neuro-navigated single-pulse transcranial magnetic stimulation (TMS) over the ipsilateral motor cortex. Relative to PE alone, iSP decreased during PE+AO, yet only when this condition preceded PE+MI. iSP duration was not modulated during PE+MI. Together, these data suggest that PE+AO promotes bilateral recruitment and interhemispheric cooperation rather than inhibition. AO and MI differentially impact interhemispheric coordination, serving to suppress inhibition only when AO is primed by MI.

High-speed AFM reveals fluctuations and dimer splitting of the N-terminal domain of GluA2-γ2
AMPA glutamate receptors (AMPARs) enable rapid excitatory synaptic transmission by localizing to the postsynaptic density of glutamatergic spines. AMPARs possess large extracellular N-terminal domains (NTDs), which participate in AMPAR clustering at synapses. Nevertheless, the dynamics of NTDs and the molecular mechanism governing their synaptic clustering remain elusive. Here, we employed high-speed atomic force microscopy (HS-AFM) to directly visualize the conformational dynamics of NTDs in the GluA2 subunit with TARP {gamma}2 in lipid environments. HS-AFM videos of GluA2-{gamma}2 in the resting and open states revealed fluctuations in NTD dimers. Conversely, in the desensitized state, the two NTD dimers adopted a separated conformation with less fluctuation. Notably, we visualized individual NTD dimers transitioning into monomers. Furthermore, this NTD-dimer splitting resulted in intersubunit exchange between NTD dimers and an increased number of binding sites with the synaptic protein neuronal pentraxin 1. Therefore, our findings illuminate the significance of NTD dynamics in the synaptic clustering of AMPARs.

Human disease-specific cell signatures in non-lesional tissue in Multiple Sclerosis detected by single-cell and spatial transcriptomics
Recent investigations of cell type changes in Multiple Sclerosis (MS) using single-cell profiling methods have focused on active lesional and peri-lesional brain tissue, and have implicated a number of peripheral and central nervous system cell types. However, an important question is the extent to which so-called "normal-appearing" non-lesional tissue in individuals with MS accumulate changes over the lifespan. Here, we compared post-mortem non-lesional brain tissue from donors with a pathological or clinical diagnosis of MS from the Religious Orders Study or Rush Memory and Aging Project (ROSMAP) cohorts to age- and sex-matched brains from persons without MS (controls). We profiled three brain regions using single-nucleus RNA-seq: dorsolateral prefrontal cortex (DLPFC), normal appearing white matter (NAWM) and the pulvinar in thalamus (PULV), from 15 control individuals, 8 individuals with MS, and 5 individuals with other detrimental pathologies accompanied by demyelination, resulting in a total of 78 samples. We identified region- and cell type-specific differences in non-lesional samples from individuals diagnosed with MS and/or exhibiting secondary demyelination with other neurological conditions, as compared to control donors. These differences included lower proportions of oligodendrocytes with expression of myelination related genes MOBP, MBP, PLP1, as well as higher proportions of CRYAB+ oligodendrocytes in all three brain regions. Among microglial signatures, we identified subgroups that were higher in both demyelination (TMEM163+/ERC2+), as well as those that were specifically higher in MS donors (HIF1A+/SPP1+) and specifically in donors with secondary demyelination (SOCS6+/MYO1E+), in both white and grey matter. To validate our findings, we generated Visium spatial transcriptomics data on matched tissue from 13 donors, and recapitulated our observations of gene expression differences in oligodendrocytes and microglia. Finally, we show that some of the differences observed between control and MS donors in NAWM mirror those previously reported between control WM and active lesions in MS donors. Overall, our investigation sheds additional light on cell type- and disease-specific differences present even in non-lesional white and grey matter tissue, highlighting widespread cellular signatures that may be associated with downstream pathological changes.

ElectroPhysiomeGAN: Generation of Biophysical Neuron Model Parameters from Recorded Electrophysiological Responses
Recent advances in connectomics, biophysics, and neuronal electrophysiology warrant modeling of neurons with further details in both network interaction and cellular dynamics. Such models may be referred to as ElectroPhysiome, as they incorporate the connectome and individual neuron electrophysiology to simulate neuronal activities. The nervous system of C. elegans is considered a viable framework for such ElectroPhysiome studies due to advances in connectomics of its somatic nervous system and electrophysiological recordings of neuron responses. In order to achieve a simulated ElectroPhysiome, the set of parameters involved in modeling individual neurons need to be estimated from electrophysiological recordings. Here, we address this challenge by developing a novel deep generative method called ElectroPhysiomeGAN (EP-GAN), which once trained, can instantly generate parameters associated with the Hodgkin-Huxley neuron model (HH-model) for neurons with graded potential response. The method combines Generative Adversarial Network (GAN) architecture with Recurrent Neural Network (RNN) Encoder and can generate an extensive number of parameters (>170) given the neuron's membrane potential responses and steady-state current profiles. We validate our method by estimating HH-model parameters for 200 synthetic neurons with graded membrane potential followed by 9 experimentally recorded neurons (where 6 of them newly recorded) in the nervous system of C. elegans. Compared to other methods, EP-GAN is advantageous in both accuracy of generated parameters and inference speed. In addition, EP-GAN preserves performance when provided with incomplete membrane potential responses up to 25% and steady-state current profiles up to 75%. EP-GAN is designed to leverage the generative capability of GAN to align with the dynamical structure of HH-model, and thus able to achieve such performance.

A functional perspective on the conditional covariance comparison problem in dementia analysis
Although there are many methods to compare the covariance structures of two populations available in the literature, few are suitable for clinical application due to the inability to account for covariate(s) that affect the dependence structure of the variables being investigated. A common method is to adjust the effect of the covariates via a linear model and work with the resulting residuals. However, removing the effects of the covariates could potentially eliminate valuable information from the analysis. We propose a functional nonparametric covariance matrix estimator to account for any given value in the covariate(s), which allows a comparison of the functional covariance structures of the multivariate data. This comparison is facilitated via a test statistic involving the first eigenvalue of the combined form of covariance matrices of the two groups. Three different approaches, namely, the parametric Tracy-Widom, the semi-parametric Forkman's test, and the nonparametric Permutation method, are used to compute the approximate p-values of the test statistic. We have conducted extensive simulation studies to determine the type I error and power of the proposed hypothesis testing methods and developed practical recommendations for implementing this novel approach. Finally, we apply our methods to the Alzheimer's Disease Neuroimaging Initiative (ADNI) study to compare cerebrospinal fluid (CSF) biomarkers between dementia and non-dementia cohorts, which offers a fascinating insight into the differences between covariance structures of biomarkers amyloid {beta}(1-42) (A{beta}42), total tau (tau), and phosphorylated tau (ptau) for given values of age, sex, and years of education.

Pancreatic Schwann cell reprogramming supports cancer-associated neuronal remodeling
The peripheral nervous system is a key regulator of cancer progression. In pancreatic ductal adenocarcinoma (PDAC), the sympathetic branch of the autonomic nervous system inhibits cancer development. This inhibition is associated with extensive sympathetic nerve sprouting in early pancreatic cancer precursor lesions. However, the underlying mechanisms behind this process remain unclear. This study aimed to investigate the roles of pancreatic Schwann cells in the structural plasticity of sympathetic neurons. We examined the changes in the number and distribution of Schwann cells in a transgenic mouse model of PDAC and in a model of metaplastic pancreatic lesions induced by chronic inflammation. Schwann cells proliferated and expanded simultaneously with new sympathetic nerve sprouts in metaplastic/neoplastic pancreatic lesions. Sparse genetic labeling showed that individual Schwann cells in these lesions had a more elongated and branched structure than those under physiological conditions. Schwann cells overexpressed proinflammatory and neurotrophic factors, including glial cell-derived neurotrophic factor (GDNF). Sympathetic neurons upregulated the GDNF receptor and promoted cell growth in response to GDNF in vitro. Selective genetic deletion of Gdnf in Schwann cells completely blocked sympathetic nerve sprouting in metaplastic pancreatic lesions in vivo. This study demonstrated that pancreatic Schwann cells underwent adaptive reprogramming during early cancer development, supporting a protective antitumor neuronal response. These finding could help to develop new strategies to modulate cancer associated neural plasticity.

Comparative roles of caudate and putamen in the serial order of behavior: Effects of striatal glutamate receptor blockade on variable versus fixed spatial self-ordered sequencing in marmosets
Self-ordered sequencing is an important executive function involving planning and executing a series of steps to achieve goal-directed outcomes. Lateral frontal cortex is implicated in this behavior, but downstream striatal outputs remain relatively unexplored. We trained marmosets on a three-stimulus self-ordered spatial sequencing task using a touch-sensitive screen to explore the role of caudate nucleus and putamen in random and fixed response arrays. By transiently blocking glutamatergic inputs to these regions, using intra-striatal CNQX microinfusions, we demonstrate that caudate and putamen are both required for, but contribute differently to, flexible and fixed sequencing. CNQX into either caudate or putamen impaired variable array accuracy, and infusions into both simultaneously elicited a greater impairment. We demonstrate that continuous perseverative errors in the variable array were caused by putamen infusions, likely due to interference with the putamen's established role in monitoring motor feedback. Caudate infusions, on the other hand caused recurrent perseveration, with deficits possibly reflecting interference with the caudate's established role in spatial working memory and goal-directed planning. In contrast to the variable array, whilst both caudate and putamen are needed for fixed array responding, combined effects were not additive, suggesting possible competing roles. Infusions in either region led to continuous perseveration when infused individually, but not when infused simultaneously. Caudate infusions did not cause recurrent perseveration in the fixed array; instead, this was caused by putamen infusions. The results overall are consistent with a role of caudate in planning and flexible responding, but putamen in more rigid habitual or automatic responding.

Age-Related Differences in Human Cortical Microstructure Depend on the Distance to the Nearest Vein
Age-related differences in cortical microstructure are used to understand the neuronal mechanisms that underlie human brain ageing. The cerebral vasculature contributes to cortical ageing, but its precise influence on age-related differences in cortical microstructure is poorly understood. In a cross-sectional study, we combine venous imaging with vessel distance mapping (VDM) to investigate the influence of venous distances on age-related differences in the microstructural architecture of the cortex. We focus on primary somatosensory cortex (S1) and primary motor cortex (M1) as both show age-related alterations linked to neurodegeneration and behavioural decline. We scanned 18 younger adults and 17 older adults at a 7T MRI scanner to measure age-related changes in quantitative T1 (qT1) values and positive QSM (pQSM) values at 0.5 mm isotropic resolution as proxies for cortical myelin and cortical iron content, respectively. We modelled different cortical depths using an equi-volume approach and assessed the distance of each voxel in each layer to its nearest vein using VDM. Our data reveal a dependence both of cortical qT1 and cortical pQSM values on venous distance. In addition, there is an interaction between venous distance and age on qT1 values, driven by lower myelination in older compared to younger adults in voxels that are farther away from a vein and higher myelination in older adults in voxels that are closer to a vein. This effect is particularly pronounced in M1 and indicates that the venous distance may act as a protective mechanism in healthy ageing. Together, our data show that the local venous architecture explains a significant amount of variance in standard measures of cortical microstructure, and should be considered in neurobiological models of human brain organisation and cortical ageing.

Systematic cross-species comparison of prefrontal cortex functional networks targeted via Transcranial Magnetic Stimulation
Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation method that safely modulates neural activity in vivo. Its precision in targeting specific brain networks makes TMS invaluable in diverse clinical applications. For example, TMS is used to treat depression by targeting prefrontal brain networks and their connection to other brain regions. However, despite its widespread use, the underlying neural mechanisms of TMS are not completely understood. Non-human primates (NHPs) offer an ideal model to study TMS mechanisms through invasive electrophysiological recordings. As such, bridging the gap between NHP experiments and human applications is imperative to ensure translational relevance. Here, we systematically compare the TMS-targeted functional networks in the prefrontal cortex in humans and NHPs. To conduct this comparison, we combine TMS electric field modeling in humans and macaques with resting-state functional magnetic resonance imaging (fMRI) data to compare the functional networks targeted via TMS across species. We identified distinct stimulation zones in macaque and human models, each exhibiting variations in the impacted networks (macaque: Frontoparietal Network, Somatomotor Network; human: Frontoparietal Network, Default Network). We identified differences in brain gyrification and functional organization across species as the underlying cause of found network differences. The TMS-network profiles we identified will allow researchers to establish consistency in network activation across species, aiding in the translational efforts to develop improved TMS functional network targeting approaches.

Visuo-motor updating in autism symptomatology
Autism Spectrum Disorder (ASD) presents a range of challenges, including heightened sensory sensitivities. Here, we examine the idea that sensory overload in ASD may be linked to issues with efference copy mechanisms, which predict the sensory outcomes of self-generated actions, such as eye movements. Efference copies play a vital role in maintaining visual and motor stability. Disrupted efference copies hinder precise predictions, leading to increased reliance on actual feedback and potential distortions in perceptions across eye movements. In our first experiment, we tested how well individuals with varying levels of autistic traits updated their mental map after making eye movements. We found that those with more autistic traits had difficulty using information from their eye movements to update the spatial representation of their mental map, resulting in significant errors in object localization. In the second experiment, we looked at how participants perceived an object displacement after making eye movements. Using a trans-saccadic spatial updating task, we found that those with higher autism scores exhibited a greater bias, indicating under-compensation of eye movements and a failure to maintain spatial stability during saccades. Overall, our study underscores efference copy's vital role in visuo-motor stability, aligning with Bayesian theories of autism, potentially informing interventions for improved action-perception integration in autism.

Modulation of the spatiotemporal dynamics of striatal direct pathway neurons and motor output by mGluR5
Striatal spiny projection neurons (SPNs) integrate glutamatergic input from motor cortex and thalamus with various neuromodulatory signals to regulate motor output. In vivo Ca2+ imaging has demonstrated that spatially compact clusters of direct and indirect pathway SPNs (dSPNs and iSPNs) co-activate during spontaneous movement. This co-activity is statistically greater between neurons in close proximity, correlates with the animal's behavioral state, and could, in part, reflect shared excitatory inputs. However, whether and how synaptic mechanism have a role in generating this distinctive spatiotemporal activity is unknown. Here, we show that the Group I metabotropic glutamate receptor 5 (mGluR5) plays a key role in the formation and regulation of spatially clustered SPN co-activity. Pharmacological modulation of mGluR5 signaling bidirectionally altered movement and spatially clustered dynamics, but not mean activity levels of dSPNs. Targeted deletion of mGluR5 in dSPNs recapitulated the effects on spatiotemporal neural dynamics and movement demonstrating a striatal specific effect of mGluR5. These changes in locomotion and neural ensemble dynamics were also correlated with changes in dSPNs synaptic properties in the cKO mice. Together results suggest excitatory synaptic function influences motor function by shaping the characteristic spatially clustered patterns of co-activity that typify dSPN activation in vivo.

A subcortical switchboard for exploratory, exploitatory, and disengaged states
To survive in evolving environments with uncertain resources, animals need to dynamically adapt their behavior and exhibit flexibility in choosing appropriate behavioral strategies, for example, to exploit familiar choices, to explore and acquire novel information, or to disengage altogether. Previous studies have mainly investigated how forebrain regions represent choice costs and values as well as optimal decision strategies during explore/exploit trade-offs. However, the neural mechanisms by which the brain implements alternative behavioral strategies such as exploiting, exploring or disengaging from the environment, remains poorly understood. Here we identify a neural hub critical for flexible switching between behavioral strategies, the median raphe nucleus (MRN). Using cell-type specific optogenetic manipulations, calcium fiber photometry and circuit tracing in mice performing diverse instinctive and learnt behavioral tasks, we found that the MRN's main cell types, GABAergic, glutamatergic (VGluT2-positive), and serotonergic neurons, have complementary functions and drive exploitation, exploration and disengagement, respectively. Suppression of MRN GABAergic neurons, for instance through inhibitory input from lateral hypothalamus which conveys strong positive valence to the MRN, leads to perseverance in current actions and goals, and thus promotes exploitatory behavior. In contrast, activation of MRN VGluT2+ neurons drives exploratory behavior. Activity of serotonergic MRN neurons is necessary for general task engagement. Input from the lateral habenula conveying negative valence suppresses serotonergic MRN neurons, leading to disengagement. These findings establish the MRN as a central behavioral switchboard, uniquely positioned to flexibly control behavioral strategies. These circuits thus may also play an important role in the etiology and possible treatment of major mental pathologies such as depressive or obsessive-compulsive disorders.

Using Machine Learning to Identify Neural Mechanisms Underlying the Development of Cognition in Children and Adolescents with ADHD
Background: Attention Deficit Hyperactivity Disorder (ADHD) is the most common neurodevelopmental disorder in children and adolescents that has been linked to poorer higher-order cognitive functioning abilities. However, little is known about the neural mechanisms underlying the development of executive functioning in children and adolescents with ADHD. Methods: The neural mechanisms associated with higher order cognitive functioning (e.g., executive functioning) was studied in a large cohort of 479 participants. The cohort was split between neurotypical children and adolescents (n=106), and children and adolescents with ADHD (n=373) between the ages of 6 and 16. fMRI data was collected while participants watched a short movie-clip. We applied machine learning models to functional connectivity profiles generated from the fMRI data to identify patterns of network connectivity that differentially predict cognitive abilities in our cohort. Result: We found models using functional connectivity profiles in response to movie-watching successfully predicted IQ, visual spatial, verbal comprehension, and fluid reasoning in children ages 6 to 11, but not in adolescents with ADHD. The models identified connections with the default mode, memory retrieval, and dorsal attention networks as driving prediction during early and middle childhood, but connections with the somatomotor, cingulo-opercular, and frontoparietal networks were more important in middle childhood. Conclusion: Computational models applied to neuroimaging data in response to naturalistic stimuli can identify distinct neural mechanisms associated with predicting cognitive abilities at different developmental stages in children and adolescents with ADHD

Egr1 is a sex-specific regulator of neuronal chromatin, synaptic plasticity, and behaviour
Sex differences are found in brain structure and function across species, and across brain disorders in humans. The major source of brain sex differences is differential secretion of steroid hormones from the gonads across the lifespan. Specifically, ovarian hormones oestrogens and progesterone are known to dynamically change structure and function of the adult female brain, having a major impact on psychiatric risk. However, due to limited molecular studies in female rodents, very little is still known about molecular drivers of female-specific brain and behavioural plasticity. Here we show that overexpressing Egr1, a candidate oestrous cycle-dependent transcription factor, induces sex-specific changes in ventral hippocampal neuronal chromatin, gene expression, and synaptic plasticity, along with hippocampus-dependent behaviours. Importantly, Egr1 overexpression mimics the high-oestrogenic phase of the oestrous cycle, and affects behaviours in ovarian hormone-depleted females but not in males. We demonstrate that Egr1 opens neuronal chromatin directly across the sexes, although with limited genomic overlap. Our study not only reveals the first sex-specific chromatin regulator in the brain, but also provides functional evidence that this sex-specific gene regulation drives neuronal gene expression, synaptic plasticity, and anxiety- and depression-related behaviour. Our study exemplifies an innovative sex-based approach to studying neuronal gene regulation in order to understand sex-specific synaptic and behavioural plasticity and inform novel brain disease treatments.

Identification of new ciliary signaling pathways in the brain and insights into neurological disorders
Primary cilia are conserved sensory hubs essential for signaling transduction and embryonic development. Ciliary dysfunction causes a variety of developmental syndromes with neurological features and cognitive impairment, whose basis mostly remains unknown. Despite connections to neural function, the primary cilium remains an overlooked organelle in the brain. Most neurons have a primary cilium; however, it is still unclear how this organelle modulates brain architecture and function, given the lack of any systemic dissection of neuronal ciliary signaling. Here, we present the first in vivo glance at the molecular composition of cilia in the mouse brain. We have adapted in vivo BioID (iBioID), targeting the biotin ligase BioID2 to primary cilia in neurons. We identified tissue-specific signaling networks enriched in neuronal cilia, including Eph/Ephrin and GABA receptor signaling pathways. Our iBioID ciliary network presents a wealth of neural ciliary hits that provides new insights into neurological disorders. Our findings are a promising first step in defining the fundamentals of ciliary signaling and their roles in shaping neural circuits and behavior. This work can be extended to pathological conditions of the brain, aiming to identify the molecular pathways disrupted in the brain cilium. Hence, finding novel therapeutic strategies will help uncover and leverage the therapeutic potential of the neuronal cilium.

Seasonal variation in D2/3 dopamine receptor availability in the human brain
Brain functional and physiological plasticity is essential to combat dynamic environmental challenges. The rhythmic in vivo dopamine signaling pathway, which regulates emotion, reward and learning, shows seasonal patterns with higher capacity of dopamine synthesis and lower number of dopamine transporters during dark seasons. However, seasonal variation of the dopamine receptor signaling remains to be characterized. Here, based on historical database of healthy human brain [11C]raclopride PET scans (n = 291, 224 males and 67 females), we investigated the seasonal patterns of D2/3 dopamine receptor signaling. We found that daylength at the time of scanning was negatively correlated with availability of this type of receptors in the striatum. Likely, seasonally varying D2/3 receptor signaling also underlies the seasonality of mood, feeding, and motivational processes.

Model-Based Closed-Loop Control of Thalamic Deep Brain Stimulation
Closed-loop control of deep brain stimulation (DBS) is crucial for effective and automatic treatments of various neurological disorders like Parkinson disease (PD) and essential tremor (ET). Manual (open-loop) DBS programming solely based on clinical observations relies on neurologist expertise and patient experience. The continuous stimulation in open-loop DBS may decrease battery life and cause side effects. On the contrary, a closed-loop DBS system utilizes a feedback biomarker/signal to track worsening (or improving) patient symptoms and offers several advantages compared to open-loop DBS. Existing closed-loop DBS control systems do not incorporate physiological mechanisms underlying the DBS or symptoms, for example how DBS modulates dynamics of synaptic plasticity. In this work, we proposed a computational framework for development of a model-based DBS controller where a biophysically-reasonable model can describe the relationship between DBS and neural activity, and a polynomial-based approximation can estimate the relationship between the neural and behavioral activity. A controller is utilized in our model in a quasi-real-time manner to find DBS patterns that significantly reduce the worsening of symptoms. These DBS patterns can be tested clinically by predicting the effect of DBS before delivering it to the patient. We applied this framework to the problem of finding optimal DBS frequencies for essential tremor given EMG recordings solely. Building on our recent network model of ventral intermediate nuclei (Vim), the main surgical target of the tremor, in response to DBS, we developed a biophysically-reasonable simulation in which physiological mechanisms underlying Vim-DBS are linked to symptomatic changes in EMG signals. By utilizing a PID controller, we showed that a closed-loop system can track EMG signals and adjusts the stimulation frequency of Vim-DBS so that the power of EMG in [2, 200] Hz reaches a desired target. We demonstrated that our model-based closed-loop control system of Vim-DBS finds an appropriate DBS frequency that aligns well with clinical studies. Our model-based closed-loop system is adaptable to different control targets, highlighting its potential usability for different diseases and personalized systems.

The Art of Brainwaves: A Survey on Event-Related Potential Visualization Practices
Electroencephalography (EEG) and event-related potentials (ERPs) have been analyzed for more than 70 years. Yet, we know little about how practitioners visualize the results of their analyses. Here, we designed an online survey (n=213) targeting EEG practitioners from novice to expert level. Our primary goal is to better understand the visualization tools currently in use, the challenges researchers face, and their experiences and opinions on how best to display their brain data. Finally, we explored whether researchers are aware of more general visualization issues. In this paper we provide an overview of the most popular ERP visualization tools. Then, we found that the community does not have a unique nomenclature to refer to some plot types, and we propose a set of recommendations to name the most popular ERP plot types. Finally, we provide an analysis of practitioner feature preferences for software developers and conclude with further recommendations for ERP practitioners.