Correlation-based spike sorting of multivariate data

Automated classification of waveforms is an important method of data processing used in various fields of science, such as neuroscience, biomedical engineering, etc. This work shows the possibility of sorting special waveforms i.e. spikes recorded with multichannel electrode arrays by using principles of correlation and data-driven reference. A new method to estimate the number of k-means clusters by using a Monte Carlo method is introduced. To demonstrate the performance of the algorithm, generated signals were used, which are created to mimic multichannel recording of the extra-cellular neuronal signals.

Сравнительный анализ методов решения некорректных обратных задач для многоканальной гиперспектрометрии

A comparative analysis of various implementations of multichannel recording using optical filters is performed to improve the spectral resolution of multichannel hyperspectrometers at maintaining the high spatial resolution. The computing power of different means of multichannel data processing is considered as well. The recovery of spectral brightness density using multichannel recording data is shown to be an incorrect task. The methods proposed to solve it are wavelet transformation, Tikhonov’s regularization approach, and Godunov method. The spectral brightness density is simulated using the multichannel recording results taking into account the measurement error. The applicability limits are established for each method. It is supposed that the Tikhonov method is more resistant to measurement errors. Various approaches for selecting optical filters that participate in the multichannel recording are compared with respect to the final accuracy of spectral brightness density reconstruction using the recording data, which evidences the benefits of the classical method. The optimal combination of the amount of optical filters and the number of recording channels is found as well. The wide application necessitates three channels with four optical filters and eight channels with two optical filters.

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.

Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation

Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel “whole brain” readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior.