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418 results for “prefrontal cortex”
Activity in developing prefrontal cortex is shaped by sleep and sensory experience
<p>In developing rats, behavioral state exerts a profound modulatory influence on neural activity throughout the sensorimotor system, including primary motor cortex (M1). We hypothesized that similar state-dependent modulation occurs in prefrontal cortical areas with which M1 forms functional connections. Here, using 8- and 12-day-old rats cycling freely between sleep and wake, we record neural activity in M1, secondary motor cortex (M2), and medial prefrontal cortex (mPFC). At both ages in all three areas, neural activity increased during active sleep (AS) compared with wake. Also, regardless of behavioral state, neural activity in all three areas increased during periods when limbs were moving. The movement-related activity in M2 and mPFC, like that in M1, is driven by sensory feedback. Our results, which diverge from those of previous studies using anesthetized pups, demonstrate that AS-dependent modulation and sensory responsivity extend to prefrontal cortex. These findings expand the range of possible factors shaping the activity-dependent development of higher-order cortical areas.</p>
The neuronal implementation of representational geometry in primate prefrontal cortex
<p><span>Modern neuroscience has seen the rise of a population-doctrine that represents cognitive variables using geometrical structures in activity space. Representational geometry does not, however, account for how individual neurons implement these representations. Here, leveraging the principle of sparse coding, we present a framework to dissect representational geometry into biologically interpretable components that retain links to single neurons. Applied to extracellular recordings from the primate prefrontal cortex in a working memory task with interference, the identified components revealed disentangled and sequential memory representations including the recovery of memory content after distraction, signals hidden to conventional analyses. Remarkably, each component was contributed by small subpopulations of neurons with distinct electrophysiological properties and response dynamics. Modelling showed that such sparse implementations are supported by recurrently connected circuits as in prefrontal cortex. The perspective of neuronal implementation links representational geometries to their cellular constituents, providing mechanistic insights into how neural systems encode and process information.</span></p>
raw and preprocessed data included to the paper "Striatum-projecting prefrontal cortex neurons support working memory maintenance"
<p>This Dataset includes matlab variables containing all raw and preprocessed data</p><p>1) fiber photometry experiments (GCaMP and GFP)</p><p>2) miniscope experiments</p><p>3) optogenetics experiments</p><p>4) DLC video analysis for photometry recording, optogenetic inhibition ArchT, optogenetic activation ChR2, optogenetic activation ChR2 + MK801, control experiments for optogenetic inhibition and activation</p><p>5) Source Data Files for all main and supplementary Figures</p><p> </p><p> collected for the paper</p><p> </p><p><strong>"Striatum-projecting prefrontal cortex neurons support working memory maintenance"</strong></p><p>Maria Wilhelm1,2,6, Yaroslav Sych1,7, Aleksejs Fomins1,2, José Luis Alatorre Warren1,8, Christopher Lewis1, Laia Serratosa Capdevila1, Roman Boehringer3, Elizabeth A. Amadei3, Benjamin Grewe2,3,4, Eoin C. O'Connor5, Benjamin J. Hall5,9, Fritjof Helmchen1,2,4*</p><p>1Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland.</p><p>2Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland. </p><p>3Institute of Neuroinformatics, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland. </p><p>4University Research Priority Program (URPP) Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zurich, Zurich, Switzerland</p><p>5Neuroscience & Rare Diseases, Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland.</p><p>6Present address: Institute for Neuroscience, ETH Zurich, 8057 Zurich, Switzerland. </p><p>7Present address: Institute of Cellular and Integrative Neuroscience, CNRS, University of Strasbourg, Strasbourg, France.</p><p>8Present address: Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway.</p><p>9Present address: Circuit Biology Department, H. Lundbeck A/S, Valby, Denmark.</p><p>These authors contributed equally: Maria Wilhelm, Yaroslav Sych</p><p>*email: <a href="mailto:helmchen@hifo.uzh.ch">helmchen@hifo.uzh.ch</a></p>
Modulation of Cognitive Control Signals in Prefrontal Cortex by Rhythmic Transcranial Magnetic Stimulation
ClinicalTrials.gov study NCT03828734. IPD Sharing: Not stated. Countries: 1. Publications: 13.
Prefrontal Cortex Stimulation as Treatment for Crack-cocaine Addiction
ClinicalTrials.gov study NCT01337297. IPD Sharing: Not stated. Countries: 1. Publications: 11.
The Effect of Prefrontal Cortex Stimulation on Antisocial and Aggressive Behavior
ClinicalTrials.gov study NCT02427672. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Transcranial Direct Current Stimulation Over Dorsolateral Prefrontal Cortex in Alcoholism
ClinicalTrials.gov study NCT01330394. IPD Sharing: Not stated. Countries: 1. Publications: 13.
Activity in developing prefrontal cortex is shaped by sleep and sensory experience
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Stable and dynamic representations of value in the prefrontal cortex
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The neuronal implementation of representational geometry in primate prefrontal cortex
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Theta oscillations coordinate grid-like representations between ventromedial prefrontal and entorhinal cortex
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Data from: The involvement of the human prefrontal cortex in the emergence of visual awareness
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Comparative anatomy of primate prefrontal cortex: Volumes of the areas of interest
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Data from: Three-photon in vivo imaging of neurons and glia in the medial prefrontal cortex with sub-cellular resolution
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Cell-specific protein expression in Alzheimer's disease prefrontal cortex
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Intracranial and behavioral data from "Asymmetric coding of reward prediction errors in human insula and dorsomedial prefrontal cortex"
<p>Preprocessed intracranial EEG and behavioral data from Hoy, Quiroga-Martinez, et al. manuscript titled "Asymmetric coding of reward prediction errors in human insula and dorsomedial prefrontal cortex" published in Nature Communications (2023). Source data files for figures are included as well.</p>
RNA sequencing data from the prefrontal cortex and hippocampus of male (12 weeks old) hemizyguous CAG-HERV-W-env mice and wild-type controls
<p>RNA sequencing data from the prefrontal cortex (PFC) and hippocampus (HIPP) of male (12 weeks old) hemizyguous CAG<sup>HERV-Wenv </sup>mice ( C57BL6/J;129P2/Ola-Hprt mice; <em>n</em> = 3) relative to wild-type ( <em>n</em> = 3) littermates. Total RNA was extracted from prefrontal and hippocampal samples using the SPLIT RNA extraction kit (Lexogen, Austria) following the manufacturer’s recommendations and was sent to the Functional Genomics Center in Zurich (FGCZ) for quality control and RNA sequencing. The quality of the isolated RNA was determined with a Fragment Analyzer (Agilent, Santa Clara, California, USA). Only those samples with a 260 nm/280 nm ratio between 1.8–2.1, a 28S/18S ratio within 1.5–2, and RIN (>8) values qualified for a Poly-A enrichment strategy in order to generate the sequencing libraries applying the TruSeq mRNA Stranded Library Prep Kit (Illumina, Inc, California, USA). After Poly-A selection using Oligo-dT beads the mRNA was reverse-transcribed into cDNA. The cDNA was fragmented, end-repaired and poly-adenylated before ligation of TruSeq UD Indices (IDT, Coralville, Iowa, USA). The quality and quantity of the amplified sequencing libraries were validated using a Fragment Analyzer SS NGS Fragment Kit (1–6000 bp) (Agilent, Waldbronn, Germany). The equimolar pool of the samples was spiked into a NovaSeq6000 run targeting ~15M reads per sample on a S1 FlowCell (Novaseq S1 Reagent Kit, 100 cycles, Illumina, Inc, California, USA). Reads were quality-checked with FastQC. Sequencing adapters were removed with Trimmomatic and aligned to the reference genome and transcriptome of Mus Musculus (GENCODE, GRCm38,p5) with STAR v2.7.3. Distribution of the reads across genomic isoform expression was quantified using the R package GenomicRanges from Bioconductor Version 3.10. Minimum mapping quality, as well as minimum feature overlaps, was set to 10. Multi-overlaps were allowed. Differentially expressed genes (DEGs) were identified using the R package edgeR from Bioconductor Version 3.10, using a generalized linear model (glm) regression, a quasi-likelihood (QL) differential expression test and the trimmed means of M-values (TMM) normalization.</p>
Medial prefrontal cortex and anteromedial thalamus interaction regulates motivation related behavior and dopaminergic neuron activity: fMRI: Rats
<p>Rat fMRI activation images supplementing for Fig. 3d and Suppl. Fig. 5.</p>
Medial prefrontal cortex and anteromedial thalamus interaction regulates motivation related behavior and dopaminergic neuron activity: fMRI: Human
<p>Human fMRI activation images supplementing for Fig. 8 and Suppl. Fig. 11.</p>
Data associated with the publication 'Population-level coding of avoidance learning in medial prefrontal cortex' by Benjamin Ehret et al.
<p>This repository contains data for the following publication:</p> <p>Population-level coding of avoidance learning in medial prefrontal cortex</p> <p>Ehret B., Boehringer R., Amadei E. A., Cervera M. R., Henning C., Galgali A., Mante V., Grewe, B. F.</p> <p>Nature Neuroscience 2024</p> <p> </p> <p>The associated analysis code is published here:</p> <p>https://github.com/behret/paper_code_active_avoidance</p> <p> </p> <p>This repository contains 1) source data to reproduce all figures and 2) processed data to reproduce most analyses. </p> <p>A small subset requires access to the raw data, which is too extensive to be published online. However, raw data can be made available upon request.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.