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Peene, R. C.

Publications and source records attributed to Peene, R. C..

3 recordsLinked to original sources

Measuring neuronal input-output operations in vivo with random access projection microscopy

Neurons transform thousands of synaptic inputs into spiking output, and understanding this transformation requires measuring many submicron synapses at millisecond timescales in vivo. Here we present SLAP2, a two-photon random access projection microscope with no per-target access time cost, yielding over 5-fold faster imaging than existing methods, and performant real-time hardware motion correction. Flexible scanning modes enable measurement of hundreds of synapses at ~200 Hz, >800 synapses volumetrically at 50-100 Hz, and compartment-resolved dendritic voltage at 2-10 kHz in behaving mice. Simultaneous dendritic glutamate and somatic calcium imaging in visual cortex pyramidal neurons revealed nonlinear input-output amplification of stimulus onset and preferred stimulus orientation responses. Amplified features are associated with spatially organized inputs and stronger trial-to-trial coupling between synaptic activity and somatic output. These measurements establish SLAP2 as a powerful tool for recording intricate patterns of subcellular fluorescence dynamics in behaving animals.

neuroscience↗

Psilocybin collapses visual change detection and drives cortical dynamics toward a state of surprise

Psilocybin profoundly alters visual perception, yet the neuronal mechanisms underlying these effects remain unclear. Here we combined large-scale Neuropixels recordings with cell-type specific optogenetics in head-fixed mice performing a visual change-detection task. Psilocybin severely impaired task performance without overt motor deficits. In cortex, the drug modestly suppressed activity of layer 5 neurons while preserving representations of image identity. By contrast, psilocybin imposed a 4-Hz oscillation on visually evoked activity that preferentially affected neurons encoding image change rather than image identity. Under psilocybin, expected image repetitions aberrantly recruited change-encoding ensembles and shifted cortical population dynamics towards trajectories normally evoked by genuine stimulus changes. These effects were strongest in somatostatin-expressing (SST) interneurons in visual cortex. The strength of this modulation depended on image structure and was greatest for images with clear, continuous contours, which preferentially recruited change-encoding ensembles. These findings demonstrate that psilocybin drives internally generated cortical surprise signals, providing a circuit mechanism for altered perception in the acute psychedelic state.

neuroscience↗

ARAX: a graph-based modular reasoning tool for translational biomedicine

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSWith the rapidly growing volume of knowledge and data in biomedical databases, improved methods for knowledge-graph-based computational reasoning are needed in order to answer translational questions. Previous efforts to solve such challenging computational reasoning problems have contributed tools and approaches, but progress has been hindered by the lack of an expressive analysis workflow language for translational reasoning and by the lack of a reasoning engine--supporting that language--that federates semantically integrated knowledge-bases. ResultsWe introduce ARAX, a new reasoning system for translational biomedicine that provides a web browser user interface and an application programming interface. ARAX enables users to encode translational biomedical questions and to integrate knowledge across sources to answer the users query and facilitate exploration of results. For ARAX, we developed new approaches to query planning, knowledge-gathering, reasoning, and result ranking and dynamically integrate knowledge providers for answering biomedical questions. To illustrate ARAXs application and utility in specific disease contexts, we present several use-case examples. Availability and ImplementationThe source code and technical documentation for building the ARAX server-side software and its built-in knowledge database are freely available online (https://github.com/RTXteam/RTX). We provide a hosted ARAX service with a web browser interface at arax.rtx.ai and a web application programming interface (API) endpoint at arax.rtx.ai/api/arax/v1.3/ui/. Contactdmk333@psu.edu

bioinformatics↗