Vernier time-to-digital converter with ring oscillators for in-pixel time-of-arrival and time-over-threshold measurement in 28 nm CMOS

The paper describes a design of a prototype chip in 28 nm CMOS technology, consisting of 8 × 4 pixels with 50 μm pitch, dedicated for the precise measurement of Time-of-Arrival (ToA) and Time-over-Threshold (ToT) with a resolution within the picosecond range. To address this requirement, in-pixel Vernier time-to-digital converter (TDC) has been implemented, which utilizes two ring oscillators per pixel. Overall chip architecture is introduced as well as pixel architecture and selected simulation results. The pixel consists of a recording channel and TDC part. The recording channel is composed of an inverter-based front-end amplifier with Zimmerman feedback, a discriminator, a calibration block and a threshold setting block. TDC part includes two ring oscillators together with their calibration blocks and additional logic with counters/shift registers that allow for precise ToA measurement (using Vernier method) as well as ToT measurement (using one of the oscillators). Alternatively, single photon counting (SPC) mode can be used. Frequency of oscillators is set in three steps. First, two global 8-bit digital-to-analog converters (DACs) are used for initial setting of all ring oscillators. Then, per-oscillator capacitance bank and 6-bit DAC are used for fine setting. Simulation results of core blocks suggest that the ToA resolution on the order of tens of picoseconds may be achieved. The chips are already fabricated and are currently being prepared for measurements.

A semi-centralized blockchain system with multi-chain for auditing communications of Wide Area Protection System

Wide Area Protection System (WAPS) undertakes the important task of maintaining system reliability and stability when the power system is subject to abnormal or predetermined unstable conditions. The existing WAPS adopts a centralized mechanism to record and audit communication messages, which faces the risk of excessive authority and tampering with communication records and audit logs, thus making it impossible to achieve true transparency and fairness. Due to the involvement of multiple parties and equipment maintained by different manufacturers in the communication of WAPS, there are difficulties in tracing the cause of the accident and determining the at-fault party following misoperations and miss trips. To address this issue, we propose a semi-centralized blockchain system with multi-chain for auditing communications of WAPS. We first propose a semi-centralized system architecture according to the system architecture and management requirements of WAPS. Then, we utilize the blockchain network as a self-recording channel to achieve tamper-proof and non-repudiation verification interaction. We also design a multi-chain structure and classification node mechanism to meet the communication auditing requirements of multiple WAPS. We have designed a new block structure that conforms to the communication protocol of WAPS. To reduce the storage burden caused by the ever-expanding blockchain ledger, we propose a deletable blockchain scheme while maintaining the integrity and security of blockchain. Analysis and experiments show that the proposed blockchain system can support the secure, transparent, tamper-proof and traceable communication recording and auditing of WAPS along with high performance.

Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield

Neural-Matrix style, high-density electrode arrays for brain-machine interfaces (BMIs) and neuroscientific research require the use of multiplexing: Each recording channel can be routed to one of several electrode sites on the array. This capability allows the user to flexibly distribute recording channels to the locations where the most desirable neural signals can be resolved. For example, in the Neuropixel probe, 960 electrodes can be addressed by 384 recording channels. However, currently no adaptive methods exist to use recorded neural data to optimize/customize the electrode selections per recording context. Here, we present an algorithm called classification-based selection (CBS) that optimizes the joint electrode selections for all recording channels so as to maximize isolation quality of detected neurons. We show, in experiments using Neuropixels in non-human primates, that this algorithm yields a similar number of isolated neurons as would be obtained if all electrodes were recorded simultaneously. Neuron counts were 41-85% improved over previously published electrode selection strategies. The neurons isolated from electrodes selected by CBS were a 73% match, by spike timing, to the complete set of recordable neurons around the probe. The electrodes selected by CBS exhibited higher average per-recording-channel signal-to-noise ratio. CBS, and selection optimization in general, could play an important role in development of neurotechnologies for BMI, as signal bandwidth becomes an increasingly limiting factor. Code and experimental data have been made available1.

Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification (PSID)

Neural activity exhibits dynamics that in addition to a behavior of interest also relate to other brain functions or internal states. Understanding how neural dynamics explain behavior requires dissociating behaviorally relevant and irrelevant dynamics, which is not achieved with current neural dynamic models as they are learned without considering behavior. We develop a novel preferential subspace identification (PSID) algorithm that models neural activity while dissociating and prioritizing its behaviorally relevant dynamics. Applying PSID to large-scale neural activity in two monkeys performing naturalistic 3D reach-and-grasps uncovered new features for neural dynamics. First, PSID revealed the behaviorally relevant dynamics to be markedly lower-dimensional than otherwise implied. Second, PSID discovered distinct rotational dynamics that were more predictive of behavior. Finally, PSID more accurately learned the behaviorally relevant dynamics for each joint and recording channel. PSID provides a general new tool to reveal behaviorally relevant neural dynamics that can otherwise go unnoticed.

ASSESSING THE IMPACT OF CONGRUENT AND INCONGRUENT STIMULUS IN STROOP TASK, USING EVENT-RELATED POTENTIALS (ERP) IN PATIENTS WITH DEPRESSION

The main goal of this event-related potentials (ERPs) study was to assess the effects of stimulations in Stroop task in brain activities of patients with different degrees of depression. Eighteen patients (10 males, with the mean age [Formula: see text]) were asked to fill out Beck’s depression questionnaire. Electroencephalographic (EEG) signals of subjects were recorded in three channels (Pz, Cz, and Fz) during Stroop test. This test entailed 360 stimulations, which included 120 congruent, 120 incongruent, and 120 neutral stimulations. To analyze the data, 18 time features in each type of stimulus were extracted from the ERP components and the optimal features were selected. The correlation between the subjects’ scores in Beck’s depression questionnaires and the extracted time features in each recording channel was calculated in order to select the best features. Total area, and peak-to-peak time window in the Cz channel in both the congruent and incongruent stimulus showed significant correlation with Beck scores, with [Formula: see text], [Formula: see text] and [Formula: see text], [Formula: see text], respectively. Consequently, given the correlation between time features and the subjects’ Beck scores with different degrees of depression, it can be interpreted that in case of growth in degrees of depression, stimulations involving congruent images would produce more challenging interferences for the patients compared to incongruent stimulations which can be more effective in diagnosing the level of disorder.

Low-power low-area techniques for multichannel recording circuits dedicated to biomedical experiments

This paper presents techniques introduced to minimize both power and silicon area of the multichannel integrated recording circuits dedicated to biomedical experiments. The proposed methods were employed in multichannel integrated circuit fabricated in CMOS 180nm process and were validated with the use of a wide range of measurements. The results show that both a single recording channel and correction blocks occupy about 0.061 mm2 of the area and consume only 8.5 μW of power. The input referred noise is equal to 4.6 μVRMS. With the use of additional digital circuitry, each of the recording channels may be independently configured. The lower cut-off frequency may be set within the range of 0.1 Hz–700 Hz, while the upper cut-off frequency, depending on the recording mode chosen, can be set either to 3 kHz/13 kHz or may be tuned in the 2 Hz–400 Hz range. The described methods were introduced in the 64-channel integrated circuit. The key aspect of the proposed design is the fact that proposed techniques do not limit functionality of the system and do not deteriorate its overall parameters.