- Publication Date:
- NSF-PAR ID:
- Journal Name:
- IEEE transactions on biomedical circuits and systems
- Page Range or eLocation-ID:
- Sponsoring Org:
- National Science Foundation
More Like this
1024-Electrode Hybrid Voltage/Current-Clamp Neural Interface System-on-Chip with Dynamic Incremental-SAR AcquisitionWe present a neural interface system-on-chip (NISoC) with 1,024 channels of simultaneous electrical recording and stimulation for high-resolution high-throughput electrophysiology. The 2mm 2mm NISoC in 65nm CMOS integrates a 32 32 array of electrodes vertically coupled to analog front-ends supporting both voltage and current clamping through a programmable interface, ranging over 100dB in voltage and 120dB in current, with 0.82mW power per channel at 5.96mVrms input-referred voltage noise from DC to 12.5kHz signal bandwidth. This includes onchip acquisition with a back-end array of 32 dynamic incremental SAR ADCs for 25Msps 11-ENOB acquisition at 2fJ/level FOM.
Introduction:Current brain-computer interfaces (BCIs) primarily rely on visual feedback. However, visual feedback may not be sufficient for applications such as movement restoration, where somatosensory feedback plays a crucial role. For electrocorticography (ECoG)-based BCIs, somatosensory feedback can be elicited by cortical surface electro-stimulation . However, simultaneous cortical stimulation and recording is challenging due to stimulation artifacts. Depending on the orientation of stimulating electrodes, their distance to the recording site, and the stimulation intensity, these artifacts may overwhelm the neural signals of interest and saturate the recording bioamplifiers, making it impossible to recover the underlying information . To understand how these factors affect artifact propagation, we performed a preliminary characterization of ECoG signals during cortical stimulation.Materials/Methods/ResultsECoG electrodes were implanted in a 39-year old epilepsy patient as shown in Fig. 1. Pairs of adjacent electrodes were stimulated as a part of language cortical mapping. For each stimulating pair, a charge-balanced biphasic square pulse train of current at 50 Hz was delivered for five seconds at 2, 4, 6, 8 and 10 mA. ECoG signals were recorded at 512 Hz. The signals were then high-pass filtered (≥1.5 Hz, zero phase), and the 5-second stimulation epochs were segmented. Within each epoch, artifact-induced peaks were detectedmore »
Characterization of Stimulation Artifact Behavior in Simultaneous Electrocorticography Grid Stimulation and RecordingBi-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. This approach, however, is suboptimal in many BCI applications. Alternative artifact mitigation methods can be devised by investigating the mechanics of artifact propagation. To characterize stimulation artifact behaviors, we collected and analyzed electrocorticography (ECoG) data from eloquent cortex mapping. Ratcheting and phase-locking of stimulation artifacts were observed, as well as dipole-like properties. Artifacts as large as ±1,100 μV appeared as far as 15-37 mm away from the stimulating channel when stimulating at 10 mA. Analysis also showed that the majority of the artifact power was concentrated at the stimulation pulse train frequency (50 Hz) and its super-harmonics (100, 150, 200 Hz). Lower frequencies (0-32 Hz) experienced minimal artifact contamination. These findings could inform the design of future bi-directional ECoG-based BCIs.
Developing electrophysiological platforms to capture electrical activities of neurons and exert modulatory stimuli lays the foundation for many neuroscience-related disciplines, including the neuron–machine interface, neuroprosthesis, and mapping of brain circuitry. Intrinsically more advantageous than genetic and chemical neuronal probes, electrical interfaces directly target the fundamental driving force—transmembrane currents—behind the complicated and diverse neuronal signals, allowing for the discovery of neural computational mechanisms of the most accurate extent. Furthermore, establishing electrical access to neurons is so far the most promising solution to integrate large-scale, high-speed modern electronics with neurons that are highly dynamic and adaptive. Over the evolution of electrode-based electrophysiologies, there has long been a trade-off in terms of precision, invasiveness, and parallel access due to limitations in fabrication techniques and insufficient understanding of membrane–electrode interactions. On the one hand, intracellular platforms based on patch clamps and sharp electrodes suffer from acute cellular damage, fluid diffusion, and labor-intensive micromanipulation, with little room for parallel recordings. On the other hand, conventional extracellular microelectrode arrays cannot detect from subcellular compartments or capture subthreshold membrane potentials because of the large electrode size and poor seal resistance, making it impossible to depict a comprehensive picture of a neuron's electrical activities. Recently, the application ofmore »
Artifact-free and high-temporal-resolution in vivo opto-electrophysiology with microLED optoelectrodes
The combination of in vivo extracellular recording and genetic-engineering-assisted optical stimulation is a powerful tool for the study of neuronal circuits. Precise analysis of complex neural circuits requires high-density integration of multiple cellular-size light sources and recording electrodes. However, high-density integration inevitably introduces stimulation artifact. We present minimal-stimulation-artifact (miniSTAR) μLED optoelectrodes that enable effective elimination of stimulation artifact. A multi-metal-layer structure with a shielding layer effectively suppresses capacitive coupling of stimulation signals. A heavily boron-doped silicon substrate silences the photovoltaic effect induced from LED illumination. With transient stimulation pulse shaping, we reduced stimulation artifact on miniSTAR μLED optoelectrodes to below 50 μVpp, much smaller than a typical spike detection threshold, at optical stimulation of >50 mW mm–2irradiance. We demonstrated high-temporal resolution (<1 ms) opto-electrophysiology without any artifact-induced signal quality degradation during in vivo experiments. MiniSTAR μLED optoelectrodes will facilitate functional mapping of local circuits and discoveries in the brain.