Evidence map›Paper›PMID 42221554›Full record

ArticleData science in science2026

Neurodatascience: Past, Present, and Future.

Keiland W Cooper, Babak Shahbaba, Norbert J Fortin

Abstract read
In one paragraph

Article in Data science in science, 2026. 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

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

3 authors.

Keiland W CooperDepartment of Neurobiology and Behavior, University of California, Irvine, Irvine, California, USA.ORCID 0000-0002-0358-9645
Babak ShahbabaDepartment of Statistics, University of California, Irvine, California, USA.ORCID 0000-0002-8102-1609
Norbert J FortinDepartment of Neurobiology and Behavior, University of California, Irvine, Irvine, California, USA.ORCID 0000-0002-6793-6984

Funding

Nicotinic enhancement of auditory-cognitive processingR01DC017687 · NIDCD · UNIVERSITY OF CALIFORNIA-IRVINE · PI METHERATE, RAJU · 2019 to 2023
$3.1M
Scalable Bayesian Stochastic Process Models for Neural Data AnalysisR01MH115697 · NIMH · UNIVERSITY OF CALIFORNIA-IRVINE · PI SHAHBABA, BABAK · 2018 to 2022
$1.7M
SCH: Individualized learning and prediction for heterogeneous multimodal data from wearable devicesR01CA297869 · NCI · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI Yuqing Guo, Annie Qu · 2024 to 2026
$900k
NCI NIH HHS R01 CA297869NIDCD NIH HHS R01 DC017687NIMH NIH HHS R01 MH115697
6 · The paper itself

Abstract

The study of the brain is a compelling example of the power of convergent science. Over the last few decades, advances in neuroscience techniques and experimentation, as well as in data science tools to analyze the resulting data, have dramatically furthered our understanding of fundamental brain functions. Historically, it has been common for analytical approaches to have a considerable lag in development following the availability of new neuroscience techniques. However, this relationship has not simply been unidirectional, as there have been examples in which analytical developments have directly led to new scientific questions and experiments. Here we review how this interplay between neuroscience and data science advances has unfolded in the past and into the present, with a focus on electrophysiology and calcium imaging. Applying lessons learned from the past and present, we then discuss expected developments, challenges, and opportunities in the future. We end by providing recommendations on how to foster the necessary team science approach to continue the advancement of research at the intersection of neuroscience and data science, which we call neurodatascience, toward a sustainable future.

Indexed as

big DataBrain activitycomputational neurosciencedeep learningdimensionality reductionmachine learningneural decodingsignal processing

Identifiers

PMID42221554
PMCPMC13218777

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.