000003 is a subproject for the "Investigation of the Cortical Communication (CORTICOM) System" dataset.

Non-linear embedding methods for identifying similar iEEG records from over 200 RNS System patients (Paper at https://doi.org/10.3389/fdata.2022.840508)

This study seeks to considerably improve dexterous control of prosthetic limbs by implementing decoding strategies that enable the user to not only control the movements of the arm and hand, but also the forces transmitted through the hand. Tactile sensations will be conveyed to the user through intracortical microstimulation (ICMS) of somatosensory cortex.

Overall, this proposal will investigate the functional utility of stereotyped HFOs by capturing them with a new implantable system (Brain Interchange - BIC of CorTec), which can sample neural data at higher rates >=1kHz and deliver targeted electrical stimulation to achieve seizure control. In contrast to current closed-loop systems (RNS), which wait for the seizure to start before delivering stimulation, the BIC system will monitor the spatial topography and rate of stereotyped HFOs and deliver targeted stimulation to these HFO generating areas to prevent seizures from occurring. If the outcomes of our research in acute setting become successful, we will execute a clinical trial and run our methods with the implantable BIC system in a chronic ambulatory setting.

New generation Adaptive deep brain stimulation (aDBS) systems can record, stimulate and use signals from the brain to make responsive adjustments to a patient's behavioral state, offering the possibility to reduce side effects and improve responsiveness in the treatment of intractable obsessive-compulsive disorder. Data collected includes LFPs from the ventral striatum, scape EEG, and Automated Facial Affect Recognition (AFAR), a measure of emotional valence.

This dataset accompanies the study, "Adaptive deep brain stimulation for dynamic gait control in Parkinson’s disease: a randomized feasibility trial," by Louie et al., published in Nature Medicine (2026). The provided data can be used to reproduce the figures in the article using the code available in this repository: https://github.com/UCSF-wang-lab/gp-FaDBS/. The full article is available at: https://www.nature.com/articles/s41591-026-04434-2. Requests for additional neurophysiology data may be directed to doris.wang@ucsf.edu.

Placeholder Description

To advance the development of next-generation personalized therapies for long-term seizure freedom, we urgently need technologies that improve seizure diagnostics while reducing risks associated with invasive neurosurgical procedures. Among the more than 1,000,000 Americans with uncontrolled focal epilepsy, many have poorly localized seizure foci. These individuals face the highest rates of ‘failure’ (i.e., ongoing seizures) after epilepsy surgery. To meet this need for safer, more effective invasive electrode studies and simultaneously enable discovery to advance next-generation therapies, this project leverages a successful, long-term collaboration between clinicians, engineers, material scientists, neuroscientists and industrial partners at New York University School of Medicine, University of Pennsylvania, Duke University, the University of Utah, Blackrock Neurotech, and Dyconex, AG to translate modern thin-film technology into next generation FDA-approved implantable neurological devices. We have developed and extensively tested a novel electrode array based on liquid crystal polymer thin-film (LCP-TF) technology. When combined with large-scale data acquisition systems, LCP-TF electrodes will provide higher quality neural recordings than existing FDA-approved electrode arrays, with improved safely and at an affordable cost.

In home collection

Electrophysiological data from implanted electrodes in the human brain are rare, and therefore scientific access to such data has remained somewhat exclusive. Here we present a freely available curated library of implanted electrocorticographic data and analyses for 16 behavioural experiments, with 204 individual datasets from 34 patients recorded with the same amplifiers and at the same settings. For each dataset, electrode positions were carefully registered to brain anatomy. A large set of fully annotated analysis scripts with which to interpret these data is embedded in the library alongside them.

At the same time, it is becoming increasingly clear that the technologies that support these demonstrations remain painfully inadequate and inaccessible for both research and clinical application: current non-invasive technologies are typically imprecise; and current invasive technologies, which are more precise, are currently only available with serious restrictions for human use. Moreover, all of the few existing neuromodulation platforms for human use require substantial expertise in diverse areas of engineering, physiology, and regulatory domains that is not available to most groups. This lack of availability of sufficiently capable and readily useable neuromodulation technologies greatly impedes the development, application, and optimization of new adaptive protocols for improving symptoms of devastating neurological and psychiatric disorders. The purpose of the project proposed here is to address this critical issue by developing, validating, and widely sharing with the community an easy-to-use adaptive neuromodulation ecosystem (comprised of technology and protocols) that is optimized for the needs of invasive basic and clinical research.

This proposal aims to undertake a comprehensive single-cellular, population-, local circuit- and stimulation-based evaluation of the role that the dorsal prefrontal cortex plays in human social cognition. Despite ongoing progress in our understanding of basic elements of social behavior through animal models, astonishingly little is known about the single-neuronal and causal mechanisms that underlie human social cognition. A core network of areas comprising the dorsomedial prefrontal, dorsolateral prefrontal and anterior cingulate cortex of the frontal lobe has been suggested to play a critical role in human social behavior; sub-serving processes that include emotional judgment, social reasoning and theory of mind. Unlike more basic sensorimotor processes, these social processes require individuals not only to represent the observed behavior or actions of others but to also infer their hidden internal states and beliefs which are inherently unobservable and unknown. These higher-order social processes play a central role in human ontogeny and are broadly affected in psychosocial conditions such as schizophrenia, depression and autism spectrum disorder. Yet, despite their importance, extraordinarily little is known about how the activities of neurons in the human brain give rise to these diverse social cognitive functions or what precise role specific prefrontal areas play. Building on our groups unique combined experience in acute single-neuronal recordings from the these dorsal prefrontal areas, social neuroscience and theory, population analyses, computational modeling and real-time stimulation techniques and by using a novel structured multi-set social task, this proposal aims to address, for the first time, vital questions about how social information is processed in humans at the cellular level, what specific cognitive processes are engaged across cortical areas, whether these processes are dissociable from more generalized cognitive mechanisms, how these key computations interrelate and, crucially, what causal contribution do neural activities in these prefrontal areas play in human social cognition at the behavioral level. Together, this systematic cross-modal, inter-disciplinary, multi-institutional collaborative effort promises to provide unprecedented new insights into human social cognition at the cellular level and offer an innovative new framework by which to investigate the prospective contribution of the dorsal prefrontal cortex to psychosocial conditions such as autism spectrum disorder.

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.

The objective of this project is to improve the outcome of people with medication resistant mesial temporal lobe epilepsy by bringing novel, cutting edge technology in neurostimulation to bear in a strong academic/industry/national laboratory collaboration. The team is using a novel bi-directional neuromodulation system combined with novel neurostimulation algorithms in a practical, step-wise optimization design from a non-human primate model to humans to set the stage for future clinical testing.

This project seeks to design, test, and optimize a novel wireless recording array for a neural speech prosthetic. Patients with various types of motor disorders such as Amyotrophic lateral sclerosis (ALS) and Locked-in-Syndrome (LOS) can have difficulty or an inability to communicate. We aim to restore this ability by reading signals directly from the brain and translating them into speech. We will design and test novel high density, high channel-count electrodes to read from the brain at an unprecedented spatial scale. We will also develop wireless technology to enable this speech translation during everyday usage. With our advanced technology for reading the brain, we aim to literally give a voice to the voiceless.

O1UE9Q1CVPCO is a subproject for the "Spinal Root Stimulation for Restoration of Function in Lower-Limb Amputees" dataset.