Evidence map›Paper›PMID 40552318›Full record

ArticleNature reviews electrical engineering2025

Innovating beyond electrophysiology through multimodal neural interfaces.

Mehrdad Ramezani, Yundong Ren, Ertugrul Cubukcu, Duygu Kuzum

Abstract read
In one paragraph

Article in Nature reviews electrical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

4 authors.

Mehrdad RamezaniDepartment of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-3144-3192
Yundong RenDepartment of NanoEngineering, University of California San Diego, La Jolla, CA, USA.
Ertugrul CubukcuDepartment of NanoEngineering, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0003-2496-0156
Duygu KuzumDepartment of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-2125-1285

Funding

Traveling Waves in Neocortical Circuits: Mechanisms, Computational Roles in Sensory Processing, and Impact on Sensory PerceptionU01NS131914 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI COLEMAN, TODD P, KUZUM, DUYGU · 2023 to 2025
$6.0M
E-Organoids: Functional Brain Organoids Co-grafted with Transparent MicrothreadsDP2EB030992 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KUZUM, DUYGU · 2020 to 2020
$2.4M
Optimization of Transparent Microelectrode Arrays for Large-scale Multimodal Monitoring of Neural ActivityU01NS139877 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Gert Cauwenberghs, Ertugrul Cubukcu · 2025 to 2026
$2.0M
Neuro-flakes: Direct Voltage Imaging of Neural Activity with Atomically-thin Optoelectronic MaterialsR21EY033676 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CUBUKCU, ERTUGRUL · 2022 to 2024
$576k
NEI NIH HHS R21 EY033676NIBIB NIH HHS DP2 EB030992NINDS NIH HHS U01 NS131914NINDS NIH HHS U01 NS139877
6 · The paper itself

Abstract

Neural circuits distributed across different brain regions mediate how neural information is processed and integrated, resulting in complex cognitive capabilities and behaviour. To understand dynamics and interactions of neural circuits, it is crucial to capture the complete spectrum of neural activity, ranging from the fast action potentials of individual neurons to the population dynamics driven by slow brain-wide oscillations. In this Review, we discuss how advances in electrical and optical recording technologies, coupled with the emergence of machine learning methodologies, present a unique opportunity to unravel the complex dynamics of the brain. Although great progress has been made in both electrical and optical neural recording technologies, these alone fail to provide a comprehensive picture of the neuronal activity with high spatiotemporal resolution. To address this challenge, multimodal experiments integrating the complementary advantages of different techniques hold great promise. However, they are still hindered by the absence of multimodal data analysis methods capable of providing unified and interpretable explanations of the complex neural dynamics distinctly encoded in these modalities. Combining multimodal studies with advanced data analysis methods will offer novel perspectives to address unresolved questions in basic neuroscience and to develop treatments for various neurological disorders.

Identifiers

PMID40552318
PMCPMC12183007

What OpenQuestion holds

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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.