Evidence map›Paper›PMID 37693443›Full record

ArticlebioRxiv : the preprint server for biology2023

A unified open-source platform for multimodal neural recording and perturbation during naturalistic behavior.

Jonathan P Newman, Jie Zhang, Aarón Cuevas-López, Nicholas J Miller, Takato Honda, Marie-Sophie H van der Goes, Alexandra H Leighton, Filipe Carvalho, Gonçalo Lopes, Anna Lakunina and 4 more

Abstract readPreprint
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

14 authors.

Jonathan P NewmanDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
Jie ZhangDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
Aarón Cuevas-LópezOpen Ephys Inc. Atlanta, GA, USA.
Nicholas J MillerDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
Takato HondaDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
Marie-Sophie H van der GoesDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
Alexandra H LeightonOpen Ephys Production Site, Lisbon, Portugal.
Filipe CarvalhoOpen Ephys Production Site, Lisbon, Portugal.
Gonçalo LopesNeuroGEARS Ltd, London, UK.
Anna LakuninaAllen Institute for Neural Dynamics, Seattle, Washington, USA.
Joshua H SiegleAllen Institute for Neural Dynamics, Seattle, Washington, USA.
Mark T HarnettDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
Matthew A WilsonDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
Jakob VoigtsDepartment of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.

Funding

Medical Scientist Training ProgramT32GM007753 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI WALENSKY, LOREN DAVID · 1985 to 2021
$50.0M
A dendritic mechanism for cholinergic neuromodulation of cortical functionR01NS106031 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI HARNETT, MARK THOMAS · 2018 to 2022
$1.7M
ONIX: A Neural Acquisition System for Unencumbered, Closed-Loop Recordings in Small, Freely Moving AnimalsR44NS127725 · NINDS · OPEN EPHYS, INC · PI NEWMAN, JONATHAN · 2022 to 2023
$1.4M
Integrated compressive sensing microscope for high-speed functional biological imagingR21EY028381 · NEI · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI CHIN, SANG PETER · 2017 to 2018
$490k
Supplement: Robotic Platform for High-Densisty in Vivo Intracellular recordingR21NS103098 · NINDS · UNIVERSITY OF MINNESOTA · PI HARNETT, MARK THOMAS, KODANDARAMAIAH, SUHASA B · 2017 to 2018
$483k
Network and dendritic mechanisms of context-dependent cortical computationK99NS118112 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI VOIGTS, JAKOB · 2020 to 2021
$207k
NEI NIH HHS R21 EY028381NIGMS NIH HHS T32 GM007753NINDS NIH HHS K99 NS118112NINDS NIH HHS R01 NS106031NINDS NIH HHS R21 NS103098NINDS NIH HHS R44 NS127725
6 · The paper itself

Abstract

Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge, we developed ONIX, an open-source data acquisition system with high data throughput (2GB/sec) and low closed-loop latencies (<1ms) that uses a novel 0.3 mm thin tether to minimize behavioral impact. Head position and rotation are tracked in 3D and used to drive active commutation without torque measurements. ONIX can acquire from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, 3D-trackers, and other data sources. We used ONIX to perform uninterrupted, long (~7 hours) neural recordings in mice as they traversed complex 3-dimensional terrain. ONIX allowed exploration with similar mobility as non-implanted animals, in contrast to conventional tethered systems which restricted movement. By combining long recordings with full mobility, our technology will enable new progress on questions that require high-quality neural recordings during ethologically grounded behaviors.

Identifiers

PMID37693443
PMCPMC10491150

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.