Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 197

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Nanowire transistor arrays for mapping neural circuits in acute brain slices

Open access
Qing, Quan, Pal, Sumon K., Tian, Bozhi, Duan, Xiaojie, Timko, Brian P., Cohen-Karni, Tzahi, Murthy, Venkatesh N., Lieber, Charles M.·2010·Proceedings of the National Academy of Sciences

Abstract

Revealing the functional connectivity in natural neuronal networks is central to understanding circuits in the brain. Here, we show that silicon nanowire field-effect transistor (Si NWFET) arrays fabricated on transparent substrates can be reliably interfaced to acute brain slices. NWFET arrays were readily designed to record across a wide range of length scales, while the transparent device chips enabled imaging of individual cell bodies and identification of areas of healthy neurons at both upper and lower tissue surfaces. Simultaneous NWFET and patch clamp studies enabled unambiguous identification of action potential signals, with additional features detected at earlier times by the nanodevices. NWFET recording at different positions in the absence and presence of synaptic and ion-channel blockers enabled assignment of these features to presynaptic firing and postsynaptic depolarization from regions either close to somata or abundant in dendritic projections. In all cases, the NWFET signal amplitudes were from 0.3–3 mV. In contrast to conventional multielectrode array measurements, the small active surface of the NWFET devices, ∼0.06 μm 2 , provides highly localized multiplexed measurements of neuronal activities with demonstrated sub-millisecond temporal resolution and, significantly, better than 30 μm spatial resolution. In addition, multiplexed mapping with 2D NWFET arrays revealed spatially heterogeneous functional connectivity in the olfactory cortex with a resolution surpassing substantially previous electrical recording techniques. Our demonstration of simultaneous high temporal and spatial resolution recording, as well as mapping of functional connectivity, suggest that NWFETs can become a powerful platform for studying neural circuits in the brain.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.0914737107

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 197

Metadata

Authors
Qing, Q., Pal, S. K., Tian, B., Duan, X., Timko, B. P., Cohen-Karni, T., Murthy, V. N., & Lieber, C. M.
Venue
Proceedings of the National Academy of Sciences
Published
2010-01-19
Volume
107
Issue
5
Pages
1882-1887
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2108603877
Cited by
197
References
2
FWCI
8.43
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Nanowire transistor arrays for mapping neural circuits in acute brain slices. https://app.cochat.ai/papers/10.1073/pnas.0914737107
The paper
Qing, Q., Pal, S. K., Tian, B., Duan, X., Timko, B. P., Cohen-Karni, T., Murthy, V. N., & Lieber, C. M. (2010). Nanowire transistor arrays for mapping neural circuits in acute brain slices. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0914737107

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.