The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Nanotools for Neuroscience and Brain Activity Mapping
Open accessAbstract
Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function.
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.
Integrity signals
Registry
Cites
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.
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
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Kim, D.-H., Lu, N., Ma, R., Kim, Y.-S., Kim, R.-H., Wang, S., Wu, J., Won, S. M., Tao, H., Islam, A., et al. (2011) · Science · doi:10.1126/science.1206157 · Cited by 4,836
The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes
Buzsáki, G., Anastassiou, C. A., & Koch, C. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3241 · Cited by 4,225
What we can do and what we cannot do with fMRI
Logothetis, N. K. (2008) · Nature · doi:10.1038/nature06976 · Cited by 3,612
Positioning single atoms with a scanning tunnelling microscope
Eigler, D. M., & Schweizer, E. K. (1990) · Nature · doi:10.1038/344524a0 · Cited by 3,161
Azevedo, F. A. C., Carvalho, L. R. B., Grinberg, L. T., Farfel, J. M., Ferretti, R. E. L., Leite, R. E. P., Filho, W. J., Lent, R., & Herculano‐Houzel, S. (2009) · Journal of Comparative Neurology · doi:10.1002/cne.21974 · Cited by 2,337
Large-scale recording of neuronal ensembles
Buzsáki, G. (2004) · Nature Neuroscience · doi:10.1038/nn1233 · Cited by 1,875
Modulation of visual responses by behavioral state in mouse visual cortex
Niell, C. M., & Stryker, M. P. (2010) · Neuron · doi:10.1016/j.neuron.2010.01.033 · Cited by 1,483
Long-term dynamics of CA1 hippocampal place codes
Ziv, Y., Burns, L. D., Cocker, E. D., Hamel, E. O., Ghosh, K. K., Kitch, L. J., Gamal, A. E., & Schnitzer, M. J. (2013) · Nature Neuroscience · doi:10.1038/nn.3329 · Cited by 1,155
Self-citation
Cited by
Syringe-injectable electronics
Liu, J., Fu, T.-M., Cheng, Z., Hong, G., Zhou, T., Jin, L., Duvvuri, M., Jiang, Z., Kruskal, P., Xie, C., et al. (2015) · Nature Nanotechnology · doi:10.1038/nnano.2015.115 · Cited by 687
Glial responses to implanted electrodes in the brain
Salatino, J. W., Ludwig, K. A., Kozai, T. D. Y., & Purcell, E. K. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-017-0154-1 · Cited by 642
A jump-start for electroceuticals
Famm, K., Litt, B., Tracey, K. J., Boyden, E. S., & Slaoui, M. (2013) · Nature · doi:10.1038/496159a · Cited by 554
Self-citationPast, present and future of spike sorting techniques
Rey, H. G., Pedreira, C., & Quian Quiroga, R. (2015) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2015.04.007 · Cited by 462
Progress towards biocompatible intracortical microelectrodes for neural interfacing applications
Jorfi, M., Skousen, J. L., Weder, C., & Capadona, J. R. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/1/011001 · Cited by 384
Metadata
- Authors
- Alivisatos, A. P., Andrews, A. M., Boyden, E. S., Chun, M., Church, G. M., Deisseroth, K., Donoghue, J. P., Fraser, S. E., Lippincott-Schwartz, J., Looger, L. L., Masmanidis, S., McEuen, P. L., Nurmikko, A. V., Park, H., Peterka, D. S., Reid, C., Roukes, M. L., Scherer, A., Schnitzer, M., Sejnowski, T. J., Shepard, K. L., Tsao, D., Turrigiano, G., Weiss, P. S., Xu, C., Yuste, R., & Zhuang, X.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-03-20
- Volume
- 7
- Issue
- 3
- Pages
- 1850-1866
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2119480884
- Cited by
- 356
- References
- 22
- FWCI
- 23.45
- 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: Nanotools for Neuroscience and Brain Activity Mapping. https://app.cochat.ai/papers/10.1021/nn4012847
- The paper
- Alivisatos, A. P., Andrews, A. M., Boyden, E. S., Chun, M., Church, G. M., Deisseroth, K., Donoghue, J. P., Fraser, S. E., Lippincott-Schwartz, J., Looger, L. L., Masmanidis, S., McEuen, P. L., Nurmikko, A. V., Park, H., Peterka, D. S., Reid, C., Roukes, M. L., Scherer, A., Schnitzer, M., . . . Zhuang, X. (2013). Nanotools for Neuroscience and Brain Activity Mapping. ACS Nano. https://doi.org/10.1021/nn4012847
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.
