Generalized sleep decoding with basal ganglia signals in multiple movement disorders.

Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson's disease, Essential Tremor, Dystonia, Essential Tremor, Huntington's disease, and Tourette's syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.

Rapid Compensation for Noisy Voluntary Movements in Adults with Primary Tic Disorders.

BACKGROUND: It has been proposed that tics and premonitory urges in primary tic disorders (PTD), like Tourette syndrome, are a manifestation of sensorimotor noise. However, patients with tics show no obvious movement imprecision in everyday life. One reason could be that patients have strategies to compensate for noise that disrupts performance (ie, noise that is task-relevant). OBJECTIVES: Our goal was to unmask effects of elevated sensorimotor noise on the variability of voluntary movements in patients with PTD. METHODS: We tested 30 adult patients with PTD (23 male) and 30 matched controls in a reaching task designed to unmask latent noise. Subjects reached to targets whose shape allowed for variability either in movement direction or extent. This enabled us to decompose variability into task-relevant versus less task-relevant components, where the latter should be less affected by compensatory strategies than the former. In alternating blocks, the task-relevant target dimension switched, allowing us to explore the temporal dynamics with which participants adjusted movement variability to changes in task demands. RESULTS: Both groups accurately reached to targets, and adjusted movement precision based on target shape. However, when task-relevant dimensions of the target changed, patients initially produced movements that were more variable than controls, before regaining precision after several reaches. This effect persisted across repeated changes in the task-relevant dimension across the experiment, and therefore did not reflect an effect of novelty, or differences in learning. CONCLUSIONS: Our results suggest that patients with PTD generate noisier voluntary movements compared with controls, but rapidly compensate according to current task demands. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Modulation of subthalamic beta oscillations by movement, dopamine, and deep brain stimulation in Parkinson's disease.

Subthalamic beta band activity (13-35 Hz) is known as a real-time correlate of motor symptom severity in Parkinson's disease (PD) and is currently explored as a feedback signal for closed-loop deep brain stimulation (DBS). Here, we investigate the interaction of movement, dopaminergic medication, and deep brain stimulation on subthalamic beta activity in PD patients implanted with sensing-enabled, implantable pulse generators. We recorded subthalamic activity from seven PD patients at rest and during repetitive movements in four conditions: after withdrawal of dopaminergic medication and DBS, with medication only, with DBS only, and with simultaneous medication and DBS. Medication and DBS showed additive effects in improving motor performance. Distinct effects of each therapy were seen in subthalamic recordings, with medication primarily suppressing low beta activity (13-20 Hz) and DBS being associated with a broad decrease in beta band activity (13-35 Hz). Movement suppressed beta band activity compared to rest. This suppression was most prominent when combining medication with DBS and correlated with motor improvement within patients. We conclude that DBS and medication have distinct effects on subthalamic beta activity during both rest and movement, which might explain their additive clinical effects as well as their difference in side-effect profiles. Importantly, subthalamic beta activity significantly correlated with motor symptoms across all conditions, highlighting its validity as a feedback signal for closed-loop DBS.

Contribution of basal ganglia activity to REM sleep disorder in Parkinson's disease.

BACKGROUND: Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common sleep problems and represents a key prodromal marker in Parkinson's disease (PD). It remains unclear whether and how basal ganglia nuclei, structures that are directly involved in the pathology of PD, are implicated in the occurrence of RBD. METHOD: Here, in parallel with whole-night video polysomnography, we recorded local field potentials from two major basal ganglia structures, the globus pallidus internus and subthalamic nucleus, in two cohorts of patients with PD who had varied severity of RBD. Basal ganglia oscillatory patterns during RBD and REM sleep without atonia were analysed and compared with another age-matched cohort of patients with dystonia that served as controls. RESULTS: We found that beta power in both basal ganglia nuclei was specifically elevated during REM sleep without atonia in patients with PD, but not in dystonia. Basal ganglia beta power during REM sleep positively correlated with the extent of atonia loss, with beta elevation preceding the activation of chin electromyogram activities by ~200 ms. The connectivity between basal ganglia beta power and chin muscular activities during REM sleep was significantly correlated with the clinical severity of RBD in PD. CONCLUSIONS: These findings support that basal ganglia activities are associated with if not directly contribute to the occurrence of RBD in PD. Our study expands the understanding of the role basal ganglia played in RBD and may foster improved therapies for RBD by interrupting the basal ganglia-muscular communication during REM sleep in PD.

Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements.

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.

Single threshold adaptive deep brain stimulation in Parkinson's disease depends on parameter selection, movement state and controllability of subthalamic beta activity.

BACKGROUND: Deep brain stimulation (DBS) is an invasive treatment option for patients with Parkinson's disease. Recently, adaptive DBS (aDBS) systems have been developed, which adjust stimulation timing and amplitude in real-time. However, it is unknown how changes in parameters, movement states and the controllability of subthalamic beta activity affect aDBS performance. OBJECTIVE: To characterize how parameter choice, movement state and controllability interactively affect the electrophysiological and behavioral response to single threshold aDBS. METHODS: We recorded subthalamic local field potentials in 12 patients with Parkinson's disease receiving single threshold aDBS in the acute post-operative state. We investigated changes in two aDBS parameters: the onset time and the smoothing of real-time beta power. Electrophysiological patterns and motor performance were assessed while patients were at rest and during a simple motor task. We further studied the impact of controllability on aDBS performance by comparing patients with and without beta power modulation during continuous stimulation. RESULTS: Our findings reveal that changes in the onset time control the extent of beta power suppression achievable with single threshold adaptive stimulation during rest. Behavioral data indicate that only specific parameter combinations yield a beneficial effect of single threshold aDBS. During movement, action induced beta power suppression reduces the responsivity of the closed loop algorithm. We further demonstrate that controllability of beta power is a prerequisite for effective parameter dependent modulation of subthalamic beta activity. CONCLUSION: Our results highlight the interaction between single threshold aDBS parameter selection, movement state and controllability in driving subthalamic beta activity and motor performance. By this means, we identify directions for the further development of closed-loop DBS algorithms.

Motor network gamma oscillations in chronic home recordings predict dyskinesia in Parkinson's disease.

In Parkinson's disease, imbalances between "antikinetic" and "prokinetic" patterns of neuronal oscillatory activity are related to motor dysfunction. Invasive brain recordings from the motor network have suggested that medical or surgical therapy can promote a prokinetic state by inducing narrowband gamma rhythms (65-90 Hz). Excessive narrowband gamma in the motor cortex promotes dyskinesia in rodent models, but the relationship between narrowband gamma and dyskinesia in humans has not been well established. To assess this relationship, we used a sensing-enabled deep brain stimulator system, attached to both motor cortex and basal ganglia (subthalamic or pallidal) leads, paired with wearable devices that continuously tracked motor signs in the contralateral upper limbs. We recorded 984 hours of multisite field potentials in 30 hemispheres of 16 subjects with Parkinson's disease (2/16 female, mean age 57 ± 12 years) while at home on usual antiparkinsonian medications. Recordings were done two to four weeks after implantation, prior to starting therapeutic stimulation. Narrowband gamma was detected in the precentral gyrus, subthalamic nucleus, or both structures on at least one side of 92% of subjects with a clinical history of dyskinesia. Narrowband gamma was not detected in the globus pallidus. Narrowband gamma spectral power in both structures co-fluctuated similarly with contralateral wearable dyskinesia scores (mean correlation coefficient of ρ=0.48 with a range of 0.12-0.82 for cortex, ρ=0.53 with a range of 0.5-0.77 for subthalamic nucleus). Stratification analysis showed the correlations were not driven by outlier values, and narrowband gamma could distinguish "on" periods with dyskinesia from "on" periods without dyskinesia. Time lag comparisons confirmed that gamma oscillations herald dyskinesia onset without a time lag in either structure when using 2-minute epochs. A linear model incorporating the three oscillatory bands (beta, theta/alpha, and narrowband gamma) increased the predictive power of dyskinesia for several subject hemispheres. We further identified spectrally distinct oscillations in the low gamma range (40-60 Hz) in three subjects, but the relationship of low gamma oscillations to dyskinesia was variable. Our findings support the hypothesis that excessive oscillatory activity at 65-90 Hz in the motor network tracks with dyskinesia similarly across both structures, without a detectable time lag. This rhythm may serve as a promising control signal for closed-loop deep brain stimulation using either cortical or subthalamic detection.

2D and 3D in vitro angiogenesis assays highlight different aspects of angiogenesis.

In angiogenesis research, scientists need to carefully select appropriate in vitro models to test their hypotheses to minimize the risk for false negative or false positive study results. In this study, we investigate molecular differences between simple two-dimensional and more complex three-dimensional angiogenesis assays and compare them to in vivo data from cancer-associated angiogenesis using an unbiased transcriptomic analysis. Human umbilical vein endothelial cells were treated with VEGF in 2D wound healing and proliferation assays and the 3D spheroid sprouting assay. VEGF-induced transcriptomic shifts were assessed in both settings by bulk RNA sequencing. Immunocytochemistry was used for protein detection. The data was linked to the transcriptomic profile of vascular endothelial cells from a single cell RNA sequencing dataset of various cancer tissue compared to adjacent healthy tissue control. VEGF induced a more diverse transcriptomic shift in vascular endothelial cells in a 3D experimental setting (767 differentially expressed genes) compared to the 2D settings (167 differentially expressed genes). Particularly, VEGF-induced changes in cell-matrix interaction, tip cell formation, and glycolysis were pronounced in the 3D spheroid sprouting experiments. Immunocytochemistry for VCAM1 and CD34 confirmed enhanced expression in response to VEGF-treatment in 3D settings. In vivo, vascular endothelial cells within various cancer tissue were characterized by strong transcriptomic changes in cell-matrix interaction and glycolysis similar to the 3D setting. Consequently, 3D assays may better address certain key aspects of angiogenesis in comparison to fast and scalable 2D assays. This should be taken into consideration within the context of each research question.

Dopaminergic reinforcement in the motor system: Implications for Parkinson's disease and deep brain stimulation.

Millions of people suffer from dopamine-related disorders spanning disturbances in movement, cognition and emotion. These changes are often attributed to changes in striatal dopamine function. Thus, understanding how dopamine signalling in the striatum and basal ganglia shapes human behaviour is fundamental to advancing the treatment of affected patients. Dopaminergic neurons innervate large-scale brain networks, and accordingly, many different roles for dopamine signals have been proposed, such as invigoration of movement and tracking of reward contingencies. The canonical circuit architecture of cortico-striatal loops sparks the question, of whether dopamine signals in the basal ganglia serve an overarching computational principle. Such a holistic understanding of dopamine functioning could provide new insights into symptom generation in psychiatry to neurology. Here, we review the perspective that dopamine could bidirectionally control neural population dynamics, increasing or decreasing their strength and likelihood to reoccur in the future, a process previously termed neural reinforcement. We outline how the basal ganglia pathways could drive strengthening and weakening of circuit dynamics and discuss the implication of this hypothesis on the understanding of motor signs of Parkinson's disease (PD), the most frequent dopaminergic disorder. We propose that loss of dopamine in PD may lead to a pathological brain state where repetition of neural activity leads to weakening and instability, possibly explanatory for the fact that movement in PD deteriorates with repetition. Finally, we speculate on how therapeutic interventions such as deep brain stimulation may be able to reinstate reinforcement signals and thereby improve treatment strategies for PD in the future.

Liquid Biopsy Proteomics in Ophthalmology.

Minimally invasive liquid biopsies from the eye capture locally enriched fluids that contain thousands of proteins from highly specialized ocular cell types, presenting a promising alternative to solid tissue biopsies. The advantages of liquid biopsies include sampling the eye without causing irreversible functional damage, potentially better reflecting tissue heterogeneity, collecting samples in an outpatient setting, monitoring therapeutic response with sequential sampling, and even allowing examination of disease mechanisms at the cell level in living humans, an approach that we refer to as TEMPO (Tracing Expression of Multiple Protein Origins). Liquid biopsy proteomics has the potential to transform molecular diagnostics and prognostics and to assess disease mechanisms and personalized therapeutic strategies in individual patients. This review addresses opportunities, challenges, and future directions of high-resolution liquid biopsy proteomics in ophthalmology, with particular emphasis on the large-scale collection of high-quality samples, cutting edge proteomics technology, and artificial intelligence-supported data analysis.

Automatic registration with continuous pose updates for marker-less surgical navigation in spine surgery.

Established surgical navigation systems for pedicle screw placement have been proven to be accurate, but still reveal limitations in registration or surgical guidance. Registration of preoperative data to the intraoperative anatomy remains a time-consuming, error-prone task that includes exposure to harmful radiation. Surgical guidance through conventional displays has well-known drawbacks, as information cannot be presented in-situ and from the surgeon's perspective. Consequently, radiation-free and more automatic registration methods with subsequent surgeon-centric navigation feedback are desirable. In this work, we present a marker-less approach that automatically solves the registration problem for lumbar spinal fusion surgery in a radiation-free manner. A deep neural network was trained to segment the lumbar spine and simultaneously predict its orientation, yielding an initial pose for preoperative models, which then is refined for each vertebra individually and updated in real-time with GPU acceleration while handling surgeon occlusions. An intuitive surgical guidance is provided thanks to the integration into an augmented reality based navigation system. The registration method was verified on a public dataset with a median of 100% successful registrations, a median target registration error of 2.7 mm, a median screw trajectory error of 1.6°and a median screw entry point error of 2.3 mm. Additionally, the whole pipeline was validated in an ex-vivo surgery, yielding a 100% screw accuracy and a median target registration error of 1.0 mm. Our results meet clinical demands and emphasize the potential of RGB-D data for fully automatic registration approaches in combination with augmented reality guidance.

WarpDrive: Improving spatial normalization using manual refinements.

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Transcriptional Comparison of Human and Murine Retinal Neovascularization.

Purpose: Retinal neovascularization (RNV) is the leading cause of vision loss in diseases like proliferative diabetic retinopathy (PDR). A significant failure rate of current treatments indicates the need for novel treatment targets. Animal models are crucial in this process, but current diabetic retinopathy models do not develop RNV. Although the nondiabetic oxygen-induced retinopathy (OIR) mouse model is used to study RNV development, it is largely unknown how closely it resembles human PDR. Methods: We therefore performed RNA sequencing on murine (C57BL/6J) OIR retinas (n = 14) and human PDR RNV membranes (n = 7) extracted during vitrectomy, each with reference to control tissue (n=13/10). Differentially expressed genes (DEG) and associated biological processes were analyzed and compared between human and murine RNV to assess molecular overlap and identify phylogenetically conserved factors. Results: In total, 213 murine- and 1223 human-specific factors were upregulated with a small overlap of 94 DEG (7% of human DEG), although similar biological processes such as angiogenesis, regulation of immune response, and extracellular matrix organization were activated in both species. Phylogenetically conserved mediators included ANGPT2, S100A8, MCAM, EDNRA, and CCR7. Conclusions: Even though few individual genes were upregulated simultaneously in both species, similar biological processes appeared to be activated. These findings demonstrate the potential and limitations of the OIR model to study human PDR and identify phylogenetically conserved potential treatment targets for PDR.

Cross-Platform Identification and Validation of Uveal Melanoma Vitreous Protein Biomarkers.

Purpose: The purpose of this study was to profile protein expression liquid vitreous biopsies from patients with uveal melanoma (UM) using mass spectrometry to identify prognostic biomarkers, signaling pathways, and therapeutic targets. Methods: Vitreous biopsies were collected from two cohorts in a pilot study: comparative control eyes with epiretinal membranes (ERM; n = 3) and test eyes with UM (n = 8). Samples were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Identified proteins were compared to data from a targeted multiplex ELISA proteomics platform. Results: A total of 69 significantly elevated proteins were detected in the UM vitreous, including LYVE-1. LC-MS/MS identified 62 significantly upregulated proteins in UM vitreous that were not previously identified by ELISA. Analysis of differential protein expression by tumor molecular classification (gene expression profiling [GEP] and preferentially expressed antigen in melanoma [PRAME]) further identified proteins that correlated with these classifications. Patients with high-risk GEP tumors displayed elevated vitreous expression of HGFR (fold-change [FC] = 2.66E + 03, P value = 0.003) and PYGL (FC = 1.02E + 04, P = 1.72E-08). Patients with PRAME positive tumors displayed elevated vitreous expression of ENPP-2 (FC = 3.21, P = 0.04), NEO1 (FC = 2.65E + 03, P = 0.002), and LRP1 (FC = 5.59E + 02, P value = 0.01). IGF regulatory effectors were highly represented (P value = 1.74E-16). Cross-platform analysis validated seven proteins identified by ELISA and LC-MS/MS. Conclusions: Proteomic analysis of liquid biopsies may provide prognostic information supporting gene expression of tumor biopsies. The use of multiple protein detection platforms in the same patient samples increases the sensitivity of candidate biomarker detection and allows for precise characterization of the vitreous proteome.

Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants.

Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for identifying and advancing novel clinical BCI approaches does not exist. Here, we developed a platform that integrates brain signal decoding with connectomics and demonstrate its utility across 123 hours of invasively recorded brain data from 73 neurosurgical patients treated for movement disorders, depression and epilepsy. First, we introduce connectomics-informed movement decoders that generalize across cohorts with Parkinson's disease and epilepsy from the US, Europe and China. Next, we reveal network targets for emotion decoding in left prefrontal and cingulate circuits in DBS patients with major depression. Finally, we showcase opportunities to improve seizure detection in responsive neurostimulation for epilepsy. Our platform provides rapid, high-accuracy decoding for precision medicine approaches that can dynamically adapt neuromodulation therapies in response to the individual needs of patients.

Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.

Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is impractical in non-regenerative organs, such as the eye and brain, because tissue biopsies would cause serious damage. We resolve this problem by integrating proteomics of liquid biopsies with single-cell transcriptomics from all known ocular cell types to trace the cellular origin of 5,953 proteins detected in the aqueous humor. We identified hundreds of cell-specific protein markers, including for individual retinal cell types. Surprisingly, our results reveal that retinal degeneration occurs in Parkinson's disease, and the cells driving diabetic retinopathy switch with disease stage. Finally, we developed artificial intelligence (AI) models to assess individual cellular aging and found that many eye diseases not associated with chronological age undergo accelerated molecular aging of disease-specific cell types. Our approach, which can be applied to other organ systems, has the potential to transform molecular diagnostics and prognostics while uncovering new cellular disease and aging mechanisms.

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses.

A critical challenge in translational research is establishing a viable and efficient interface between patient care in the operating room (OR) and the research laboratory. Here, we developed a protocol for acquiring high-quality liquid biopsies for molecular analyses from the aqueous humor and the vitreous from patients undergoing eye surgery. In this workflow, a Mobile Operating Room Lab Interface (MORLI) cart equipped with a computer, a barcode scanner, and lab instruments, including onboard cold storage, is used to obtain and archive human biological samples. A web-based data privacy-compliant database enables annotating each sample over its lifetime, and a cartesian coordinate system allows tracking each barcoded specimen in storage, enabling quick and accurate retrieval of samples for downstream analyses. Molecular characterization of human tissue samples not only serves as a diagnostic tool (e.g., to distinguish between infectious endophthalmitis and other non-infectious intraocular inflammation) but also represents an important component of translational research, allowing the identification of new drug targets, development of new diagnostic tools, and personalized therapeutics.

Pathological pallidal beta activity in Parkinson's disease is sustained during sleep and associated with sleep disturbance.

Parkinson's disease (PD) is associated with excessive beta activity in the basal ganglia. Brain sensing implants aim to leverage this biomarker for demand-dependent adaptive stimulation. Sleep disturbance is among the most common non-motor symptoms in PD, but its relationship with beta activity is unknown. To investigate the clinical potential of beta activity as a biomarker for sleep quality in PD, we recorded pallidal local field potentials during polysomnography in PD patients off dopaminergic medication and compared the results to dystonia patients. PD patients exhibited sustained and elevated beta activity across wakefulness, rapid eye movement (REM), and non-REM sleep, which was correlated with sleep disturbance. Simulation of adaptive stimulation revealed that sleep-related beta activity changes remain unaccounted for by current algorithms, with potential negative outcomes in sleep quality and overall quality of life for patients.

Neurophysiological mechanisms of deep brain stimulation across spatiotemporal resolutions.

Deep brain stimulation is a neuromodulatory treatment for managing the symptoms of Parkinson's disease and other neurological and psychiatric disorders. Electrodes are chronically implanted in disease-relevant brain regions and pulsatile electrical stimulation delivery is intended to restore neurocircuit function. However, the widespread interest in the application and expansion of this clinical therapy has preceded an overarching understanding of the neurocircuit alterations invoked by deep brain stimulation. Over the years, various forms of neurophysiological evidence have emerged which demonstrate changes to brain activity across spatiotemporal resolutions; from single neuron, to local field potential, to brain-wide cortical network effects. Though fruitful, such studies have often led to debate about a singular putative mechanism. In this Update we aim to produce an integrative account of complementary instead of mutually exclusive neurophysiological effects to derive a generalizable concept of the mechanisms of deep brain stimulation. In particular, we offer a critical review of the most common historical competing theories, an updated discussion on recent literature from animal and human neurophysiological studies, and a synthesis of synaptic and network effects of deep brain stimulation across scales of observation, including micro-, meso- and macroscale circuit alterations.