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1.
STAR Protoc ; 4(4): 102570, 2023 Dec 15.
Article in English | MEDLINE | ID: mdl-37729059

ABSTRACT

Micro-light-emitting-diode (µLED) silicon probes feature independently controllable miniature light-emitting-diodes (LEDs) embedded at several positions in each shank of a multi-shank probe, enabling temporally and spatially precise optogenetic neural circuit interrogation. Here, we present a protocol for performing causal and reproducible neural circuit manipulations in chronically implanted, freely moving animals. We describe steps for introducing optogenetic constructs, preparing and implanting a µLED probe, performing simultaneous in vivo electrophysiology with focal optogenetic perturbation, and recovering a probe following termination of an experiment. For complete details on the use and execution of this protocol, please refer to Watkins de Jong et al. (2023).1.


Subject(s)
Optogenetics , Silicon , Animals , Optogenetics/methods , Neurons/physiology , Electrophysiological Phenomena , Electrophysiology/methods
2.
IEEE Trans Biomed Circuits Syst ; 17(4): 741-753, 2023 08.
Article in English | MEDLINE | ID: mdl-37490369

ABSTRACT

We report a power-efficient analog front-end integrated circuit (IC) for multi-channel, dual-band subcortical recordings. In order to achieve high-resolution multi-channel recordings with low power consumption, we implemented an incremental ΔΣ ADC (IADC) with a dynamic zoom-and-track scheme. This scheme continuously tracks local field potential (LFP) and adaptively adjusts the input dynamic range (DR) into a zoomed sub-LFP range to resolve tiny action potentials. Thanks to the reduced DR, the oversampling rate of the IADC can be reduced by 64.3% compared to the conventional approach, leading to significant power reduction. In addition, dual-band recording can be easily attained because the scheme continuously tracks LFPs without additional on-chip hardware. A prototype four-channel front-end IC has been fabricated in 180 nm standard CMOS processes. The IADC achieved 11.3-bit ENOB at 6.8 µW, resulting in the best Walden and SNDR FoMs, 107.9 fJ/c-s and 162.1 dB, respectively, among two different comparison groups: the IADCs reported up to date in the state-of-the-art neural recording front-ends; and the recent brain recording ADCs using similar zooming or tracking techniques to this work. The intrinsic dual-band recording feature reduces the post-processing FPGA resources for subcortical signal band separation by >45.8%. The front-end IC with the zoom-and-track IADC showed an NEF of 5.9 with input-referred noise of 8.2 µVrms, sufficient for subcortical recording. The performance of the whole front-end IC was successfully validated through in vivo animal experiments.


Subject(s)
Brain , Neurons , Animals , Neurons/physiology , Brain/physiology , Action Potentials/physiology , Amplifiers, Electronic , Equipment Design , Signal Processing, Computer-Assisted
3.
bioRxiv ; 2023 Feb 06.
Article in English | MEDLINE | ID: mdl-36798252

ABSTRACT

Optogenetics are a powerful tool for testing how a neural circuit influences neural activity, cognition, and behavior. Accordingly, the number of studies employing optogenetic perturbation has grown exponentially over the last decade. However, recent studies have highlighted that the impact of optogenetic stimulation/silencing can vary depending on the construct used, the local microcircuit connectivity, extent/power of illumination, and neuron types perturbed. Despite these caveats, the majority of studies employ optogenetics without simultaneously recording neural activity in the circuit that is being perturbed. This dearth of simultaneously recorded neural data is due in part to technical difficulties in combining optogenetics and extracellular electrophysiology. The recent introduction of µLED silicon probes, which feature independently controllable miniature LEDs embedded at several levels of each of multiple shanks of silicon probes, provides a tractable method for temporally and spatially precise interrogation of neural circuits. Here, we provide a protocol addressing how to perform chronic recordings using µLED probes. This protocol provides a schematic for performing causal and reproducible interrogations of neural circuits and addresses all phases of the recording process: introduction of optogenetic construct, implantation of the µLED probe, performing simultaneous optogenetics and electrophysiology in vivo , and post-processing of recorded data. SUMMARY: This method allows a researcher to simultaneously perturb neural activity and record electrophysiological signal from the same neurons with high spatial specificity using silicon probes with integrated µLEDs. We outline a procedure detailing all stages of the process for performing reliable µLED experiments in chronically implanted rodents.

4.
Adv Sci (Weinh) ; 9(18): e2105414, 2022 06.
Article in English | MEDLINE | ID: mdl-35451232

ABSTRACT

Dynamic interactions within and across brain areas underlie behavioral and cognitive functions. To understand the basis of these processes, the activities of distributed local circuits inside the brain of a behaving animal must be synchronously recorded while the inputs to these circuits are precisely manipulated. Even though recent technological advances have enabled such large-scale recording capabilities, the development of the high-spatiotemporal-resolution and large-scale modulation techniques to accompany those recordings has lagged. A novel neural probe is presented in this work that enables simultaneous electrical monitoring and optogenetic manipulation of deep neuronal circuits at large scales with a high spatiotemporal resolution. The "hectoSTAR" micro-light-emitting-diode (µLED) optoelectrode features 256 recording electrodes and 128 stimulation µLEDs monolithically integrated on the surface of its four 30-µm thick silicon micro-needle shanks, covering a large volume with 1.3-mm × 0.9-mm cross-sectional area located as deep as 6 mm inside the brain. The use of this device in behaving mice for dissecting long-distance network interactions across cortical layers and hippocampal regions is demonstrated. The recording-and-stimulation capabilities hectoSTAR µLED optoelectrodes enables will open up new possibilities for the cellular and circuit-based investigation of brain functions in behaving animals.


Subject(s)
Electrophysiological Phenomena , Optogenetics , Animals , Cardiac Electrophysiology , Cerebral Cortex , Mice , Neurons/physiology , Optogenetics/methods
5.
IEEE Trans Biomed Eng ; 69(1): 334-346, 2022 01.
Article in English | MEDLINE | ID: mdl-34191721

ABSTRACT

We report a miniaturized, minimally invasive high-density neural recording interface that occupies only a 1.53 mm2 footprint for hybrid integration of a flexible probe and a 256-channel integrated circuit chip. To achieve such a compact form factor, we developed a custom flip-chip bonding technique using anisotropic conductive film and analog circuit-under-pad in a tiny pitch of 75 µm. To enhance signal-to-noise ratios, we applied a reference-replica topology that can provide the matched input impedance for signal and reference paths in low-noise aimpliers (LNAs). The analog front-end (AFE) consists of LNAs, buffers, programmable gain amplifiers, 10b ADCs, a reference generator, a digital controller, and serial-peripheral interfaces (SPIs). The AFE consumes 51.92 µW from 1.2 V and 1.8 V supplies in an area of 0.0161 mm2 per channel, implemented in a 180 nm CMOS process. The AFE shows > 60 dB mid-band CMRR, 6.32 µVrms input-referred noise from 0.5 Hz to 10 kHz, and 48 MΩ input impedance at 1 kHz. The fabricated AFE chip was directly flip-chip bonded with a 256-channel flexible polyimide neural probe and assembled in a tiny head-stage PCB. Full functionalities of the fabricated 256-channel interface were validated in both in vitro and in vivo experiments, demonstrating the presented hybrid neural recording interface is suitable for various neuroscience studies in the quest of large scale, miniaturized recording systems.


Subject(s)
Amplifiers, Electronic , Neurosciences , Equipment Design , Signal Processing, Computer-Assisted
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