A single-center, assessor-blinded, randomized controlled clinical trial to test the safety and efficacy of a novel brain-computer interface controlled functional electrical stimulation (BCI-FES) intervention for gait rehabilitation in the chronic stroke population.

Background: In the United States, there are over seven million stroke survivors, with many facing gait impairments due to foot drop. This restricts their community ambulation and hinders functional independence, leading to several long-term health complications. Despite the best available physical therapy, gait function is incompletely recovered, and this occurs mainly during the acute phase post-stroke.

Simulation-Informed Power Budget Estimate of a Fully-Implantable Brain-Computer Interface.

This study aims to estimate the maximum power consumption that guarantees a thermally safe operation for a titanium-enclosed chest wall unit (CWU) subcutaneously implanted in the pre-pectoral area. This unit is a central piece of an envisioned fully-implantable bi-directional brain-computer interface (BD-BCI). To this end, we created a thermal simulation model using the finite element method implemented in COMSOL.

A CMOS BD-BCI: Neural Recorder with Two-Step Time-Domain Quantizer and Multi-Polar Stimulator with Dual-Mode Charge Balancing.

This work presents a bi-directional brain-computer interface (BD-BCI) including a high-dynamic-range (HDR) two-step time-domain neural acquisition (TTNA) system and a high-voltage (HV) multipolar neural stimulation system incorporating dual-mode time-based charge balancing (DTCB) technique. The proposed TTNA includes four independent recording modules that can sense microvolt neural signals while tolerating large stimulation artifacts. In addition, it exhibits an integrated input-referred noise of 2.

Power Budget of a Skull Unit in a Fully-Implantable Brain-Computer Interface: Bio-Heat Model.

The aim of this study is to estimate the maximum power consumption that guarantees the thermal safety of a skull unit (SU). The SU is part of a fully-implantable bi-directional brain computer-interface (BD-BCI) system that aims to restore walking and leg sensation to those with spinal cord injury (SCI). To estimate the SU power budget, we created a bio-heat model using the finite element method (FEM) implemented in COMSOL.

Suppression of cortical electrostimulation artifacts using pre-whitening and null projection.

Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers.

Anatomical organization of temporally correlated neural calcium activity in the hippocampal CA1 region.

Hippocampal CA1 neuronal ensembles generate sequential patterns of firing activity that contribute to episodic memory formation and spatial cognition. Here we used calcium imaging to record neural ensemble activities in mouse hippocampal CA1 and identified CA1 excitatory neuron sub-populations whose members are active across the same second-long period of time. We identified groups of hippocampal neurons sharing temporally correlated neural calcium activity during behavioral exploration and found that they also organized as clusters in anatomical space.

Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research.

Introduction: Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback.

Methods: A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator.

Development of highly sensitive, flexible dual L-glutamate and GABA microsensors for in vivo brain sensing.

Real-time tracking of neurotransmitter levels in vivo has been technically challenging due to the low spatiotemporal resolution of current methods. Since the imbalance of cortical excitation/inhibition (E:I) ratios are associated with a variety of neurological disorders, accurate monitoring of excitatory and inhibitory neurotransmitter levels is crucial for investigating the underlying neural mechanisms of these conditions. Specifically, levels of the excitatory neurotransmitter L-glutamate, and the inhibitory neurotransmitter GABA, are assumed to play critical roles in the E:I balance.

Artifact propagation in subdural cortical electrostimulation: Characterization and modeling.

Cortical stimulation electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies.

A Fully-Integrated 1µW/Channel Dual-Mode Neural Data Acquisition System for Implantable Brain-Machine Interfaces.

This paper presents an ultra-low power mixed-signal neural data acquisition (MSN-DAQ) system that enables a novel low-power hybrid-domain neural decoding architecture for implantable brain-machine interfaces with high channel count. Implemented in 180nm CMOS technology, the 32-channel custom chip operates at 1V supply voltage and achieves excellent performance including 1.07µW/channel, 2.

Pre-whitening and Null Projection as an Artifact Suppression Method for Electrocorticography Stimulation in Bi-Directional Brain Computer Interfaces.

Electrocorticography (ECoG)-based bi-directional (BD) brain-computer interfaces (BCIs) are a forthcoming technology promising to help restore function to those with motor and sensory deficits. A major problem with this paradigm is that the cortical stimulation necessary to elicit artificial sensation creates strong electrical artifacts that can disrupt BCI operation by saturating recording amplifiers or obscuring useful neural signal. Even with state-of-the-art hardware artifact suppression methods, robust signal processing techniques are still required to suppress residual artifacts that are present at the digital back-end.

A Prototype of a Fully-Implantable Charge-Balanced Artificial Sensory Stimulator for Bi-directional Brain-Computer-Interface (BD-BCI).

Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Previously we developed and validated a benchtop prototype of a fully implantable BCI system for motor decoding. Here, a prototype artificial sensory stimulator was integrated into the benchtop system to develop a prototype of a fully-implantable BD-BCI.

Thermal Analysis of a Skull Implant in Brain-Computer Interfaces.

The goal of this study is to estimate the thermal impact of a titanium skull unit (SU) implanted on the exterior aspect of the human skull. We envision this unit to house the front-end of a fully implantable electrocorticogram (ECoG)-based bi-directional (BD) brain-computer interface (BCI). Starting from the bio-heat transfer equation with physiologically and anatomically constrained tissue parameters, we used the finite element method (FEM) implemented in COMSOL to build a computational model of the SU's thermal impact.

Optimal artifact suppression in simultaneous electrocorticography stimulation and recording for bi-directional brain-computer interface applications.

Objective: Electrocorticogram (ECoG)-based brain-computer interfaces (BCIs) are a promising platform for the restoration of motor and sensory functions to those with neurological deficits. Such bi-directional BCI operation necessitates simultaneous ECoG recording and stimulation, which is challenging given the presence of strong stimulation artifacts. This problem is exacerbated if the BCI's analog front-end operates in an ultra-low power regime, which is a basic requirement for fully implantable medical devices.

An Energy-Efficient CMOS Dual-Mode Array Architecture for High-Density ECoG-Based Brain-Machine Interfaces.

This article presents an energy-efficient electrocorticography (ECoG) array architecture for fully-implantable brain machine interface systems. A novel dual-mode analog signal processing method is introduced that extracts neural features from high- γ band (80-160 Hz) at the early stages of signal acquisition. Initially, brain activity across the full-spectrum is momentarily observed to compute the feature weights in the digital back-end during full-band mode operation.

A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface.

Objective: State-of-the-art invasive brain-machine interfaces (BMIs) have shown significant promise, but rely on external electronics and wired connections between the brain and these external components. This configuration presents health risks and limits practical use. These limitations can be addressed by designing a fully implantable BMI similar to existing FDA-approved implantable devices.

Electroencephalography-based endogenous brain-computer interface for online communication with a completely locked-in patient.

Background: Brain-computer interfaces (BCIs) have demonstrated the potential to provide paralyzed individuals with new means of communication, but an electroencephalography (EEG)-based endogenous BCI has never been successfully used for communication with a patient in a completely locked-in state (CLIS).

Methods: In this study, we investigated the possibility of using an EEG-based endogenous BCI paradigm for online binary communication by a patient in CLIS. A female patient in CLIS participated in this study.

Characterization of Stimulation Artifact Behavior in Simultaneous Electrocorticography Grid Stimulation and Recording.

Bi-directional brain-computer interfaces (BCIs) require simultaneous stimulation and recording to achieve closed-loop operation. It is therefore important that the interface be able to distinguish between neural signals of interest and stimulation artifacts. Current bi-directional BCIs address this problem by temporally multiplexing stimulation and recording.

Electrocorticographic Activity of the Brain During Micturition.

Current therapies for neurogenic bladder do not allow spinal cord injury patients to regain conscious control of urine storage or voiding. Novel neural technologies may provide means to improve or restore the connection between the brain and the bladder; however, the specific brain areas and their underlying neural activities responsible for micturition must be better understood in order to design such technologies. In this retrospective study, we analyzed electrocorticographic (ECoG) data obtained from epilepsy patients who underwent ECoG grid implantation for epilepsy surgery evaluation, in the hopes of determining specific electrophysiological activity associated with micturition.

Subspace-Based Suppression of Cortical Stimulation Artifacts.

Bi-directional brain-computer interfaces for the restoration of movement and sensation must simultaneously record neural signals and deliver cortical stimulation. This poses a challenge since stimulation artifacts can be orders of magnitude stronger than neural signals. In this article, we propose a novel subspace-based method for the removal of cortical electrical stimulation artifacts.

Electrocorticographic Encoding of Human Gait in the Leg Primary Motor Cortex.

While prior noninvasive (e.g., electroencephalographic) studies suggest that the human primary motor cortex (M1) is active during gait processes, the limitations of noninvasive recordings make it impossible to determine whether M1 is involved in high-level motor control (e.

CMOS Ultralow Power Brain Signal Acquisition Front-Ends: Design and Human Testing.

Two brain signal acquisition (BSA) front-ends incorporating two CMOS ultralow power, low-noise amplifier arrays and serializers operating in mosfet weak inversion region are presented. To boost the amplifier's gain for a given current budget, cross-coupled-pair active load topology is used in the first stages of these two amplifiers. These two BSA front-ends are fabricated in 130 and 180 nm CMOS processes, occupying 5.

Characterization of electrocorticogram high-gamma signal in response to varying upper extremity movement velocity.

The mechanism by which the human primary motor cortex (M1) encodes upper extremity movement kinematics is not fully understood. For example, human electrocorticogram (ECoG) signals have been shown to modulate with upper extremity movements; however, this relationship has not been explicitly characterized. To address this issue, we recorded high-density ECoG signals from patients undergoing epilepsy surgery evaluation as they performed elementary upper extremity movements while systematically varying movement speed and duration.

Performance Assessment of a Custom, Portable, and Low-Cost Brain-Computer Interface Platform.

Objective: Conventional brain-computer interfaces (BCIs) are often expensive, complex to operate, and lack portability, which confines their use to laboratory settings. Portable, inexpensive BCIs can mitigate these problems, but it remains unclear whether their low-cost design compromises their performance. Therefore, we developed a portable, low-cost BCI and compared its performance to that of a conventional BCI.

Automated detection and analysis of depolarization events in human cardiomyocytes using MaDEC.

Optical imaging-based methods for assessing the membrane electrophysiology of in vitro human cardiac cells allow for non-invasive temporal assessment of the effect of drugs and other stimuli. Automated methods for detecting and analyzing the depolarization events (DEs) in image-based data allow quantitative assessment of these different treatments. In this study, we use 2-photon microscopy of fluorescent voltage-sensitive dyes (VSDs) to capture the membrane voltage of actively beating human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs).