Evidence map›Paper›PMID 37214984›Full record

ArticlebioRxiv : the preprint server for biology2023

Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods.

Alejandro Omar Blenkmann, Sabine Liliana Leske, Anaïs Llorens, Jack J Lin, Edward Chang, Peter Brunner, Gerwin Schalk, Jugoslav Ivanovic, Pål Gunnar Larsson, Robert Thomas Knight and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Alejandro Omar BlenkmannDepartment of Psychology, University of Oslo, Norway.
Sabine Liliana LeskeDepartment of Musicology, University of Oslo, Norway.
Anaïs LlorensDepartment of Psychology, University of Oslo, Norway.
Jack J LinDepartment of Neurology and Center for Mind and Brain, University of California, Davis, USA.
Edward ChangDepartment of Neurological Surgery, University of California, San Francisco, USA.
Peter BrunnerDepartment of Neurology, Albany Medical College, Albany, NY, USA.
Gerwin SchalkDepartment of Neurology, Albany Medical College, Albany, NY, USA.
Jugoslav IvanovicDepartment of Neurosurgery, Oslo University Hospital, Norway.
Pål Gunnar LarssonDepartment of Neurosurgery, Oslo University Hospital, Norway.
Robert Thomas KnightDepartment of Psychology and the Helen Wills Neuroscience Institute, University of California, Berkeley, USA.
Tor EndestadDepartment of Psychology, University of Oslo, Norway.
Anne-Kristin SolbakkDepartment of Psychology, University of Oslo, Norway.

Funding

Project 5: ComputationalP50MH109429 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI Robert Thomas Knight · 2017 to 2026
$25.3M
Neural circuit theory and trained recurrent network modeling of rapid learningU19NS107609 · NINDS · UNIVERSITY OF WASHINGTON · PI BUFFALO, ELIZABETH A · 2018 to 2022
$12.6M
ATTENTION, ORIENTATION, & THE HUMAN PREFRONTAL CORTEXR37NS021135 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI KNIGHT, ROBERT THOMAS · 2013 to 2019
$3.6M
Dynamics and Causal Functions of Large-Scale Cortical and Subcortical NetworksU01NS108916 · NINDS · WADSWORTH CENTER · PI WOLPAW, JONATHAN RICKEL · 2018 to 2019
$1.4M
NIMH NIH HHS P50 MH109429NINDS NIH HHS R37 NS021135NINDS NIH HHS U01 NS108916NINDS NIH HHS U19 NS107609
6 · The paper itself

Abstract

Precise electrode localization is important for maximizing the utility of intracranial EEG data. Electrodes are typically localized from post-implantation CT artifacts, but algorithms can fail due to low signal-to-noise ratio, unrelated artifacts, or high-density electrode arrays. Minimizing these errors usually requires time-consuming visual localization and can still result in inaccurate localizations. In addition, surgical implantation of grids and strips typically introduces non-linear brain deformations, which result in anatomical registration errors when post-implantation CT images are fused with the pre-implantation MRI images. Several projection methods are currently available, but they either fail to produce smooth solutions or do not account for brain deformations. To address these shortcomings, we propose two novel algorithms for the anatomical registration of intracranial electrodes that are almost fully automatic and provide highly accurate results. We first present

Indexed as

depth electrodeselectrocorticography (ECoG)intracranial EEG (iEEG)simulationsstereo electroencephalography (SEEG)subcortical gridssubdural grids

Identifiers

PMID37214984
PMCPMC10197594

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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.