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Orlova, N.

Publications and source records attributed to Orlova, N..

6 recordsLinked to original sources
bioRxiv2024

Standardised Measurements for Monitoring and Comparing Multiphoton Microscope Systems

The goal of this protocol is to enable better characterisation of multiphoton microscopy hardware across a large user base. The scope of this protocol is purposefully limited to focus on hardware, touching on software and data analysis routines only where relevant. The intended audiences are scientists using and building multiphoton microscopes in their laboratories. The goal is that any scientist, not only those with optical expertise, can test whether their multiphoton microscope is performing well and producing consistent data over the lifetime of their system.

neuroscience↗
bioRxiv2023

Stimulus novelty uncovers coding diversity in visual cortical circuits

Detecting novel stimuli in the environment is critical for learning and survival, yet the neural basis of novelty processing is not understood. To characterize cell type-specific novelty processing, we surveyed the activity of [~]15,000 excitatory and inhibitory neurons in mice performing a visual task with novel and familiar stimuli. Clustering revealed a dozen functional neuron types defined by experience-dependent encoding. Vasoactive-intestinal-peptide (Vip) expressing inhibitory neurons were diverse, encoding novel stimuli, omissions of familiar stimuli, or behavioral features. Distinct Somatostatin (Sst) expressing inhibitory neurons encoded either familiar or novel stimuli. Subsets of excitatory neurons co-clustered with specific Vip or Sst subpopulations, while Sst and Vip inhibitory clusters were non-overlapping. This study establishes that novelty processing is mediated by diverse functional neuron types in the visual cortex.

neuroscience↗
bioRxiv2020

Removing independent noise in systems neuroscience data using DeepInterpolation

Progress in nearly every scientific discipline is hindered by the presence of independent noise in spatiotemporally structured datasets. Three widespread technologies for measuring neural activity--calcium imaging, extracellular electrophysiology, and fMRI--all operate in domains in which shot noise and/or thermal noise deteriorate the quality of measured physiological signals. Current denoising approaches sacrifice spatial and/or temporal resolution to increase the Signal-to-Noise Ratio of weak neuronal events, leading to missed opportunities for scientific discovery. Here, we introduce DeepInterpolation, a general-purpose denoising algorithm that trains a spatio-temporal nonlinear interpolation model using only noisy samples from the original raw data. Applying DeepInterpolation to in vivo two-photon Ca2+ imaging yields up to 6 times more segmented neuronal segments with a 15 fold increase in single pixel SNR, uncovering network dynamics at the single-trial level. In extracellular electrophysiology recordings, DeepInterpolation recovered 25% more high-quality spiking units compared to a standard data analysis pipeline. On fMRI datasets, DeepInterpolation increased the SNR of individual voxels 1.6-fold. All these improvements were attained without sacrificing spatial or temporal resolution. DeepInterpolation could well have a similar impact in other domains for which independent noise is present in experimental data.

neuroscience↗
bioRxiv2018

Remote focusing system for simultaneous dual-plane mesoscopic multiphoton imaging

We present a dual-plane mesoscopic imaging system capable of simultaneous image acquisition from two independent focal planes. The system was designed as an add-on to a recently introduced large field-of-view two-photon microscopy system, developed by Sofroniew, et al., eLife, 5, e14472, 2016. In this work, we merge two advanced multiphoton imaging technologies, i.e., temporal-division multiplexing and remote focusing, to maintain diffraction-limited resolution at both imaging planes, and achieve a more than 2-fold increase in the systems overall imaging throughput. We introduce a novel solution to decode temporally interleaved analog signals at nanosecond timescales to achieve high-speed time-multiplexed imaging. Detailed characterization and comparison of the modified and the original two-photon microscopy system was performed.\n\nOCIS Codes(190.4180) Multiphoton processes; (180.5810) Scanning microscopy; (170.2520) Fluorescence microscopy.

neuroscience↗
bioRxiv2018

Two-photon frequency division multiplexing for functional in vivo imaging: a feasibility study.

Recently, we presented a new approach to create high-speed amplitude modulation of femtosecond laser pulses and tag multiple excitation beams with specific modulation frequencies. In this work, we discuss the utility of this method to record calcium signals in brain tissue with two-photon frequency-division multiplexing (2P-FDM) microscopy. While frequency-multiplexed imaging appears slightly inferior in terms of image quality as compared to conventional two-photon laser scanning microscopy due to shot noise-induced cross-talk between frequency channels, applying this technique to record average signals from regions of interest (ROI) such as neuronal cell bodies was found to be promising. We use phase information associated with each pixel or waveform within a selected ROI to phase-align and recombine the signals into one extended amplitude-modulated waveform. This procedure narrows the frequency detection window, effectively decreasing noise contributions from other frequency channels. Using theoretical analysis, numerical simulations, and in vitro imaging we demonstrate a reduction of cross-talk by more than an order of magnitude and predict the usefulness of 2P-FDM for functional studies of brain activity.

neuroscience↗