Studying the Effects of Brain Stimulation on Cognitive Control and Associated EEG in Human Subjects.

Cognitive control is a central element of human cognition that is impaired in several psychiatric diseases. It is closely associated with brain regions that are prominently dysregulated in disease such as the dorsal anterior cingulate cortex (dACC), the dorso-lateral prefrontal cortex (dlPFC), the orbitofrontal cortex (OFC), and the amygdala. Linking cognitive control to specific neural substrates and circuit-level interactions is critical for understanding how control disruptions lead to neurological and psychiatric diseases. This is work that is best done in humans, and so we will study cognitive control using intracranial local field potential recordings in human epilepsy patients. We will study cognitive control in patients who are having electrodes implanted for pre-surgical localization of epileptic seizures. These patients have electrodes in many of the brain regions involved in cognitive control, which is a unique opportunity to record from the human brain at a network level. Participants will perform laboratory tasks that measure cognitive control while we record the brain's electrical activity. The goal of this research proposal is to characterize and model cortical oscillations underlying the conflict resolution aspect of cognitive control in the healthy and anxious/depressed mental states to inform design of neuromodulation interventions for restoration towards healthy mental states. We will take three complimentary approaches to achieve this goal. 1) Using intracranial EEG recorded in epilepsy patients undergoing invasive monitoring for surgical evaluation, we will determine cortical neural oscillations underlying cognitive control in the framework of a conflict task. We will also use this to differentiate between normal and depressed or anxious subjects. 2) We will use a neural population cortical model to simulate and characterize feasible neural mechanisms underlying dlPFC and temporal cortical oscillations observed during conflict processing. We will use a data driven approach for estimating relevant model parameters. 3) We will use the model calibrated to individual subjects to design a cortical electrical stimulation paradigm to modulate the simulated oscillations towards a desired healthy state. We will then validate our model by testing model predictions in 4 human subjects and determine if we can successfully change both neural signals as well as associated behavior. This is not a randomized controlled trial. All participants will receive brain recording, and all will receive stimulation once stimulation methods are set up. The randomization will be within subject: some blocks of the task will be performed under different conditions that emphasize different aspects of the control calculation. Some blocks will have brain stimulation, and some will not.

Invasive Decoding and Stimulation of Altered Reward Computations in Depression

Participants (n=24) will complete a decision-making task in which participants will make decisions under uncertainty and seek to maximize rewards. The researchers will assess behavioral (risk attitudes) and neural (LFP) responses using a combination of intracranial recordings and computational modeling. A subset of patients will complete the game a second time under electrical stimulation of pre-identified anatomical targets in orbitofrontal cortex, hippocampus or amygdala. In addition, patients' depression status will be assessed through questionnaires (BDI-II and HDSA). Finally, the researchers will examine whether electrical stimulation results in behavioral or mood modulation.

In-depth Investigation of Brain Network Interactions

Research Statement SIGNIFICANCE Memory impairments are common to several neurological and psychiatric disorders, including Alzheimer's disease and depression, and these impose a heavy burden on patients, families and society (Dickerson and Eichenbaum, 2007). Novel treatment and diagnostic strategies are needed, and these may arise from a deeper understanding of the brain basis of episodic memory (Tulving, 1983). Group-averaged neuroimaging studies have revealed that a distributed network, known as the 'default network' (DN), increases activity during the recollection of past events (Buckner et al. 2008). This network occupies regions including posteromedial cortex (PMC), posterior parietal cortex (PPC), and the medial temporal lobe (MTL), as well as lateral temporal and lateral and medial prefrontal cortices. Building on recent advances in functional magnetic resonance imaging (fMRI; Poldrack et al., 2015; Laumann et al., 2015), recent evidence has shown that when functional anatomy is defined in individuals, the DN comprises at least two juxtaposed networks, named DN-A and DN-B for convenience (Figure 1). This finding forces us to reconsider the role of the DN in episodic processes (see also: Dastjerdi et al., 2011; Andrews-Hanna et al., 2010). Here we propose experiments to deepen our understanding of these networks using a multimodal approach that provides high spatiotemporal resolution and whole-brain network definition. We will combine within-individual fMRI mapping with intracranial electroencephalography (iEEG) and electrical brain stimulation (EBS). We will directly record local field potentials from precisely mapped network regions, and apply electrical stimulation with millimeter precision. This will provide novel information regarding episodic memory in two domains that cannot be gathered by fMRI alone: i) characterizing fast temporal dynamics of network recruitment during episodic recollection, and ii) establishing causal interactions between brain regions during recollection. INNOVATION Methodologically, this project will provide proof of principle that precision fMRI mapping can be performed in a clinical population and successfully combined with invasive recordings and stimulation. Theoretical innovation will be obtained through a deeper understanding of the task-response dynamics, coupling, and causal relationships between regions of distributed networks, including how neural engagement changes during memory recollection. Finally, this proposal provides translational innovation by directly testing whether precision-fMRI guided intracranial stimulation can be used modulate memory performance. APPROACH General methods: Participants in the proposed experiments will be neurosurgical patients with presumed focal epilepsy that are to undergo implantation with intracranial electrodes for localizing seizure foci. The proposal will be carried out at the Northwestern University Feinberg School of Medicine. Patients scheduled for intracranial seizure monitoring will be invited to enroll in the study and will undergo 1 to 4 sessions of fMRI prior to surgical implantation of electrodes. After surgery, patients are typically monitored for ~7 days in the Northwestern Memorial Hospital Comprehensive Epilepsy Centre (CEC), during which they will be invited to participate in the proposed experiments. All subjects must provide informed consent before participating. Enrollment: A minimum of 40-50 patients are expected to be monitored at the CEC over the next 3 years. Electrode locations are determined by the clinical needs of the patient. 60-70% of patients are typically implanted with dense coverage of the medial temporal lobes achieved through depth electrodes with trajectories that allow sampling of lateral temporal cortices. A small number of electrodes are also typically implanted in posterior cingulate, lateral inferior parietal and ventromedial prefrontal cortex. Due to the distributed nature of the networks under investigation, which contain regions in multiple cortical zones, it is likely that we will have coverage over relevant brain regions in many cases. Some patients are also likely to be implanted with broader cortical coverage using subdural grids. Preliminary results have shown that even when a patient is implanted only with depth electrodes, which are not placed on the cortical surface but penetrate into the brain, coverage of different candidate network regions was often achieved along the electrode trajectory. With conservative estimates, 20-30 subjects will be good candidates for the project aims outlined below. Given the high signal-to-noise ratio of iEEG (usually a 200-300% task-evoked increase in signal from baseline; Parvizi and Kastner, 2017), reliable effects can typically be found within individuals. All proposed analyses will be carried out within individuals, hence multiple subjects are required to generalize the findings, not increase statistical power. Therefore, a small number of subjects (as low as n = 12) would be sufficient (e.g. Braga and Buckner, 2017; Foster et al., 2013). Neuroimaging acquisition: MR scans will be collected in 1-4 sessions from each patient. Preliminary data has shown that in this clinical population 2-3 MRI sessions are desirable to allow exclusion of non-compliant runs (e.g. those containing excess head motion). We will collect 6-8 runs of fMRI data per session, resulting in between 42 - 224 mins of fMRI data per patient. This will allow robust and reliable estimates of network topography. Subject sleepiness will be monitored through an in-scanner eye-tracking camera. Compliance may be improved by allowing patients to watch movies inside the scanner when needed, with pilot analyses showing comparable maps are obtained using movie and visual fixation task data. Hence both tasks will be administered to improve compliance. Network definition within individuals: Networks will be defined within individuals using two methods to ensure robustness. MRI preprocessing will be performed using a custom pipeline 'iProc' that optimizes within-subject alignment and minimizes blurring. Individual seed regions will be hand-selected and correlation maps will be thresholded at r > 0.2 to remove regions of low certainty. The networks of interest, DN-A and DN-B, will be targeted and identified using the expected anatomical distribution of each network (described in detail in Braga and Buckner, 2017). Once candidate seed regions are selected, definition of networks will be performed again in each individual using data-driven clustering, which reduces potential experimenter bias. Networks from the clustering analysis that most closely match up with the networks defined by hand will be selected and labelled as DN-A and DN-B. Network maps will be used to label electrode contacts (each 'electrode' can have multiple 'contacts' along its shaft or grid) by their approximate location within or near each network. Electrode localization: Electrode locations will be determined using a computerized tomography (CT) scan. Estimates of the center of each contact in CT space will be obtained using BioImage Suite. The CT image will be registered to the anatomical T1 image (containing brain tissue locations) using a linear transform, allowing coordinates of each contact to be projected to the T1 space. Preliminary data has shown that the inter-rater error in this localization process is typically ~1mm. A 2-mm radius sphere will be generated centered on each contact coordinate to approximate the sampling volume of each contact, which is extended due to tissue conductance. Contacts that are predominantly sampling white matter will be removed by excluding contacts whose sphere does not overlap with the gray matter ribbon (estimated using FreeSurfer). The overlap between spheres and gray matter will be used for surface-based and volume-based functional connectivity (FC) analyses. FC maps will be created for each contact, and the resulting maps will be visualized. If a contact fails to produce a FC map with distant regions of high correlation (indicating that the contact is sampling a distributed network), the contact will be excluded. If the contact's FC map resembles DN-A and DN-B, as defined using the clustering and manually defined seed-based analyses, this contact will be labelled as sampling DN-A and DN-B and included for further analysis. Two nearby electrodes, one situated in DN-A and one in DN-B, will be selected a priori in two different cortical zones (e.g. PMC vs. PPC, based on coverage). iEEG processing: All contacts within the epileptic zone or corrupted by external noise will be removed from further analysis. Raw signals will be notch filtered at 60, 120 and 180 Hz to remove electrical noise and harmonics. Notch-filtered signals will be re-referenced by subtracting the common average, after removal of pathogenic or spiky signals, as well as those presenting as clear outliers in power spectra plots. Data will be bandpass filtered to extract amplitude and phase information at different frequency bands. The high-frequency broadband (HFB; 70-140 Hz) signal is an important surrogate for local neuronal population activity and corresponds to low-frequency correlations of the blood oxygenation-level dependent signal (Logothetis et al., 2001). HFB band-limited power will be calculated and low-pass filtered at <0.1 Hz. Pair-wise correlations in HFB power will be used to estimate functional connectivity. Direct cortical stimulation: Risks associated with the research stimulation protocol are considered incremental and are further reduced by carrying out the stimulation under supervision of a clinical researcher, when patients are on antiepileptic medication, and keeping stimulation to within safety limits. Low frequency (1 Hz) single pulse stimulation will be applied to regions of DN-A and DN-B to map cortico-cortical evoked potentials (CCEPs). This will be used to estimate the strength, as well as provide data on the directionality of connections between regions. In a departure from original plans, based on recent findings (Hermiller et al. 2019), theta-burst stimulation (gamma-band stimulation applied intermittently at theta frequencies) will be applied to regions of DN-A regions in lateral temporal, posteromedial and prefrontal cortices during a recollection task to test if stimulation of distant DN-A regions can lead to improvements in hippocampus-mediated episodic memory recollection. Currents will be administered at a threshold below that which causes after-discharges (usually around 6-8 mA).

Understanding the Neural Mechanisms Behind tDCS

Effects of STN DBS on Cognition and Brain Networks in PD Patients Analyzed Based on EEG and fNIRS

In recent years, deep brain electrical stimulation (DBS) has become a primary treatment for improving clinical symptoms in Parkinson's disease (PD) patients with predominantly motor slowing after poor drug effects from conventional drug therapy medications or after the progression of the disease. However, previous studies have been controversial in examining whether DBS-STN promotes or impairs cognitive function in patients with PD. Previous studies have found that DBS may affect executive function in patients with PD and that specific brain regions are closely related to executive function. In this study, the investigators used electroencephalograph-functional near-infrared spectroscopy (EEG-fNIRS) to obtain brain network connectivity in subjects and to explore the possible relationship between executive function and brain network connectivity in patients with Parkinson's disease. To explore the possible brain network connectivity affecting execution in DBS-STN and to predict postoperative executive function in PD patients in DBS. Among the single cognitive domains impaired, executive function impairment is the most common, accounting for more than 70% of the cases, and impairment of attention, working memory, and visuospatial ability are also more common. Impaired executive function is the most characteristic cognitive impairment in PD patients, which is related to the disruption of the integrity of the frontal-striatal loops, designing a wide range of functional brain regions, such as the frontal lobe, parietal lobe, cingulate gyrus, thalamus, substantia nigra, and so on, and clinically manifested as impaired cognitive flexibility, planning, concept formation, working memory, and learning ability. Executive dysfunction can seriously affect patients' social behavior, especially when performing more complex tasks that require the integration of multiple steps in a particular order. Previous studies have found that brain network connectivity in specific brain regions is closely related to cognitive function, for example, there have been many clinical studies based on functional MRI blood oxygenation signals, but because of the poor immunity to electromagnetic interference, patients with implanted electrodes have to be DBS-off in order to do the MRI. Because of poor anti-motor interference, only some motor imagery and simple finger movements can be acquired under the DBS-off condition for functional MRI, and functional MRI has been an important issue limiting cognitive neuroscience research due to its low temporal resolution and its inability to monitor in real-time the changes of cortical brain blood oxygenation signals in the task paradigm. Therefore, this study plans to design a multicenter, prospective, randomized, parallel-controlled equipotent clinical trial, which innovatively combines electroencephalography (EEG) with high temporal resolution and functional near-infrared spectroscopy (fNIRS) with a high spatial resolution to monitor cortical oxygenation signals in real-time, so that the brain electrophysiological and blood oxygenation signals can be acquired in real-time during a test of executive function (Stroop/TMT). The real-time measurement and evaluation of cognitive function by synchronously acquiring electrophysiological and oxygenation signaling changes in the brain while the patient is performing the executive function test (Stroop/TMT) and obtaining real-time EEG-fNIRS brain network data during the executive function test has always been a higher-order field of cognitive function research. The present study investigated the mechanisms of executive function impairment in PD patients and whether DBS-STN affects the brain network mechanisms of executive function. It is hoped to (1) quantify cognitive function and possible trends in cognitive functioning in PD patients by EEG-fNIRS technique, (2) Explain whether there are differences in executive function at the level of brain functional network connectivity between surgical and conservative treatments and whether there are interaction effects of the differences with the duration of treatment and the treatment modality as well as to analyze their simple effects, (3) To minimize artificial confounders of short-term learning effects and testers familiar with previous neurocognitive psychobehavioral tests, (4) To explore the mechanism of DBS on the changes of cortical brain networks in PD patients, to avoid or reduce the interference of surgery on cognitive functions, and to provide a theoretical basis for treating personalized surgical plans. In this study, the investigators planned to design a multicenter, prospective, randomized, parallel-controlled clinical trial. A total of 80 patients were randomly assigned to the DBS-STN group. The DBS treatment group, with the non-DBS treatment group, routinely DBS-on at 1 month postoperatively. The conservative treatment routinely on oral medication and the data on patients' brain function was collected by the simultaneous EEG-fNIRS bimodal technique in combination with cognitive testing (Stroop/TMT) at baseline, 1 month after DBS (DBS-on), and at 6 months/12 months after DBS, respectively.

DBS for Cognitive Deficits After Traumatic Brain Injury

Traumatic brain injury (TBI) remains a significant public health issue with an incidence of 55-70 million individuals worldwide. In Canada, TBI leads to 23,000 hospitalizations per year with 8% of individuals succumbing to their injuries. In addition to neurologic deficits, TBI may lead to a spectrum of long-term impairments, including cognitive difficulties (e.g., attention, memory), neurologic symptoms (e.g., headaches, dizziness) and neuropsychiatric sequalae (e.g. anxiety, post-traumatic stress disorder). TBI has also been associated with neurodegenerative disorders, such as chronic traumatic encephalopathy and the development of Alzheimer's-type pathology. Cognitive rehabilitation programs are important tools for clinical recovery of TBI patients, improving functional outcomes and the quality of life. Some of these strategies are based on the development of compensatory strategies and neuroplasticity. Due to the short liver nature of some of the associated improvements and neuroplastic phenomena, stimulating specific neuronal circuits has been proposed. To date, class I evidence suggests that cognitive improvement following rehabilitation is more effective than sham treatment. In general, however, cognitive rehabilitation therapy is effective in 80-90% of patients. This means that 10-20% of patients remain severely disabled despite treatment. Deep Brain Stimulation is a neurosurgical tool that has been widely used for over twenty years. Most of the experience with DBS comes from the movement disorder literature where significant success has been had with the management of disabling Parkinson's Disease (PD) and dystonia. Owing to similar underlying circuitry, and the frequent co-occurrence of psychiatric and neurologic conditions, DBS has been suggested for the management of treatment resistant neuropsychiatric conditions, with some promising results. To date, clinical studies using DBS following TBI are largely comprised of case reports and small case series. The most common application of invasive neurostimulation has been for the treatment of post-TBI dystonic symptoms and tremor. In addition to motor improvement, Miller et al reported a series of 4 patients who presented an improvement in visuospatial memory following fornix burst stimulation. Zhou et al reported that DBS delivered to the anterior limb of internal capsule and the region of the nucleus accumbens improved post-TBI auditory hallucinations, mood changes, and insomnia in a single female patient. Kuhn et al. reported a patient who had a substantial reduction in post- TBI self-mutilating behavior following posterior hypothalamus stimulation. An improvement in emotional adjustment and functional independence was reported in 4 TBI patients treated with nucleus accumbens DBS.Aside from the cognitive, psychiatric and mood improvements described above, DBS has also been investigated for the recovery of consciousness in patients in minimally conscious states. Out of 10 patients reported in the literature, an improvement was observed in 8 individuals using coma scales and related metrics. Patients with memory and cognitive deficits following TBI that do not respond to conventional treatments experience a decrease in quality of life. Despite advances in neuroimaging, genetics, pharmacology and psychosocial interventions in the last half century, little progress has been made in altering the natural history of the condition or its outcome. This study would explore whether a surgical therapy is safe and potentially effective in patients who develop refractory memory and cognitive deficits following TBI. Preclinical studies suggest that DBS may improve memory deficits in TBI models. Moreover, DBS delivered to the fornix has shown promising clinical results in patients with Alzheimer's disease. The main mechanism for the improvements induced by DBS in memory tests is the development of multiple forms of plasticity.

PSA Versus STN DBS for DT

This is a randomized, double-blinded, crossover trial aiming at comparing the efficacy of PSA and STN DBS in treating dystonic tremor. Enrolled patients will undergo bilateral DBS surgery, targeting both PSA and STN with single trajectory. Three months post-implantation, patients enter a 4-month double-blinded crossover phase with PSA and STN DBS in randomized order. After 7 months post-implantation (at the end of the crossover phase), patients enter an open-label phase during which programming parameters are not restricted until the termination of the study at 12-month follow-up.

Bilateral Single-Electrode VO Combined With STN-DBS for Treating Meige Syndrome

While deep brain stimulation (DBS) targeting the subthalamic nucleus (STN) or the globus pallidus interna (GPi) has shown moderate efficacy, incomplete symptom relief and high stimulation thresholds with associated side effects remain significant limitations. Emerging evidence suggests that dual-target neuromodulation combining STN with ventralis oralis (VO) nucleus stimulation may synergistically modulate hyperactive basal ganglia-thalamocortical circuits, potentially enhancing therapeutic outcomes.The study will involve patients diagnosed with Meige syndrome who are eligible for DBS therapy. Participants will be randomly assigned to one of two groups.The primary outcome measure is the improvement in motor symptoms, assessed using the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS) before and after treatment. Secondary outcomes will include changes in quality of life, anxiety and depression scores, and any adverse effects related to the DBS procedure.The results of this study will be used to guide future clinical trials and inform the treatment options for patients with Meige syndrome.

Neural Mechanisms and Clinical Applications of DBS for Modulating Sleep Dysregulation in PD

This single-center longitudinal observational study will enroll 20 idiopathic Parkinson's disease (PD) patients with bilateral subthalamic nucleus (STN) deep brain stimulation (DBS) systems (Medtronic Percept™ PC) to evaluate the neurophysiological mechanisms of DBS in sleep regulation. Participants will undergo preoperative clinical assessments (MDS-UPDRS III for motor symptoms, NMSS for non-motor symptoms, PDSS for sleep-specific dysfunction) and two nights of wearable PSG recordings. Postoperatively, DBS parameters will be optimized at 1 month for motor symptom control. Follow-up evaluations at 3, 6, and 12 months post-operation include in-hospital PSG and local field potential (LFP) recordings: Night 1 captures data under DBS-OFF conditions, followed by Night 2 with DBS-ON under optimized programming, alongside repeated clinical assessments. Sleep architecture (NREM/REM stages, arousal indices,atonia) and STN-LFPs will be analyzed and correlated with clinical outcomes. Machine learning models will identify LFP biomarkers predictive of sleep improvement to inform closed-loop stimulation strategies. Based on the machine learning results, we will investigate the adaptive algorithm and validate its effectiveness in the second phase. Adaptive stimulation will be administered for one month, followed by two consecutive nights of polysomnography (PSG) monitoring and Parkinson's Disease Sleep Scale (PDSS) assessments at the study interval endpoint. Subsequently, patients will undergo routine open-loop stimulation for one month, with two additional consecutive nights of PSG monitoring and PDSS evaluations conducted upon completion of this phase. Sleep improvement outcomes will be systematically compared between the two stimulation modalities.

Identifying Local Field Potential Biomarkers for Obsessive-compulsive Disorder Treatment With Deep Brain Stimulation