Evidence map›Paper›PMID 32410946›Full record

ArticleFrontiers in neuroscience2020

Intraoperative Microelectrode Recordings in Substantia Nigra Pars Reticulata in Anesthetized Rats.

Hanyan Li, George C McConnell

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hanyan LiDepartment of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
George C McConnellDepartment of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Substantia Nigra pars reticulata (SNr) is a promising target for deep brain stimulation (DBS) to treat the gait and postural disturbances in Parkinson's disease (PD). Positioning the DBS electrode within the SNr is critical for the development of preclinical models of SNr DBS to investigate underlying mechanisms. However, a complete characterization of intraoperative microelectrode recordings in the SNr to guide DBS electrode placement is lacking. In this study, we recorded extracellular single-unit activity in anesthetized rats at multiple locations in the medial SNr (mSNr), lateral SNr (lSNr), and the Ventral Tegmental Area (VTA). Immunohistochemistry and fluorescently dyed electrodes were used to map neural recordings to neuroanatomy. Neural recordings were analyzed in the time domain (i.e., firing rate, interspike interval (ISI) correlation, ISI variance, regularity, spike amplitude, signal-to-noise ratio, half-width, asymmetry, and latency) and the frequency domain (i.e., spectral power in frequency bands of interest). Spike amplitude decreased and ISI correlation increased in the mSNr versus the lSNr. Spike amplitude, signal-to-noise ratio, and ISI correlation increased in the VTA versus the mSNr. ISI correlation increased in the VTA versus the lSNr. Spectral power in the VTA increased versus: (1) the mSNr in the 20-30 Hz band and (2) the lSNr in the 20-40 Hz band. No significant differences were observed between structures for any other feature analyzed. Our results shed light on the heterogeneity of the SNr and suggest electrophysiological features to promote precise targeting of SNr subregions during stereotaxic surgery.

Indexed as

action potentialsdeep brain stimulationintraoperative microelectrode recordingsParkinson’s diseaseSubstantia Nigra pars reticulata

Identifiers

PMID32410946
PMCPMC7201294

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.