The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Characterization of Neocortical Principal Cells and Interneurons by Network Interactions and Extracellular Features
Abstract
Most neuronal interactions in the cortex occur within local circuits. Because principal cells and GABAergic interneurons contribute differently to cortical operations, their experimental identification and separation is of utmost important. We used 64-site two-dimensional silicon probes for high-density recording of local neurons in layer 5 of the somatosensory and prefrontal cortices of the rat. Multiple-site monitoring of units allowed for the determination of their two-dimensional spatial position in the brain. Of the ∼60,000 cell pairs recorded, 0.2% showed robust short-term interactions. Units with significant, short-latency (<3 ms) peaks following their action potentials in their cross-correlograms were characterized as putative excitatory (pyramidal) cells. Units with significant suppression of spiking of their partners were regarded as putative GABAergic interneurons. A portion of the putative interneurons was reciprocally connected with pyramidal cells. Neurons physiologically identified as inhibitory and excitatory cells were used as templates for classification of all recorded neurons. Of the several parameters tested, the duration of the unfiltered (1 Hz to 5 kHz) spike provided the most reliable clustering of the population. High-density parallel recordings of neuronal activity, determination of their physical location and their classification into pyramidal and interneuron classes provide the necessary tools for local circuit analysis.
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Cites
Dynamics of the Hippocampal Ensemble Code for Space
Wilson, M. A., & McNaughton, B. L. (1993) · Science · doi:10.1126/science.8351520 · Cited by 2,350
Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo
Klausberger, T., Magill, P. J., Márton, L. F., Roberts, J. D. B., Cobden, P. M., Buzsáki, G., & Somogyi, P. (2003) · Nature · doi:10.1038/nature01374 · Cited by 1,345
Self-citationInfluence of dendritic structure on firing pattern in model neocortical neurons
Mainen, Z. F., & Sejnowski, T. J. (1996) · Nature · doi:10.1038/382363a0 · Cited by 1,231
Oscillatory coupling of hippocampal pyramidal cells and interneurons in the behaving rat
Csicsvari, J., Hirase, H., Czurkó, A., Mamiya, A., & Buzsáki, G. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-01-00274.1999 · Cited by 966
Self-citationMarkram, H., Lübke, J., Frotscher, M., Roth, A., & Sakmann, B. (1997) · The Journal of Physiology · doi:10.1113/jphysiol.1997.sp022031 · Cited by 960
Hippocampal CA1 interneurons: an in vivo intracellular labeling study
Sik, A., Penttonen, M., Ylinen, A., & Buzsaki, G. (1995) · The Journal of Neuroscience · doi:10.1523/jneurosci.15-10-06651.1995 · Cited by 669
Pyramidal cell communication within local networks in layer 2/3 of rat neocortex.
Holmgren, C., Harkany, T., Svennenfors, B., & Zilberter, Y. (2003) · The Journal of Physiology · doi:10.1113/jphysiol.2003.044784 · Cited by 573
Maccaferri, G., David, J., Roberts, B., Szucs, P., Cottingham, C. A., & Somogyi, P. (2000) · The Journal of Physiology · doi:10.1111/j.1469-7793.2000.t01-3-00091.x · Cited by 357
Tamás, G., Buhl, E. H., & Somogyi, P. (1997) · The Journal of Physiology · doi:10.1113/jphysiol.1997.sp022054 · Cited by 278 · cited 5×
“…also evoked by single interneuron spikes in both pyramidal and interneuron targets (Buhl et al. 1997; Maccaferri et al. 2000; J Neurophysiol • VOL 92 • JULY 2004 • www.jn.org by 10.220.33.4 on M ay 27, 2017 http://jn.physiology.org/ D ow nloaded from Tamas et al. 1997; Thomson and Bannister 2003).”
BackgroundResultInfluentialPhysiological properties of inhibitory interneurons in cat striate cortex
Azouz, R. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.6.534 · Cited by 173
Cited by
Large-scale recording of neuronal ensembles
Buzsáki, G. (2004) · Nature Neuroscience · doi:10.1038/nn1233 · Cited by 1,875
Self-citationPerineuronal nets stabilize the grid cell network
Christensen, A. C., Lensjø, K. K., Lepperød, M. E., Dragly, S.-A., Sutterud, H., Blackstad, J. S., Fyhn, M., & Hafting, T. (2021) · Nature Communications · doi:10.1038/s41467-020-20241-w · Cited by 1,865
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
“We classified units as broad- or narrow-spiking according to their average spike waveform (Figure S2), which has been shown to correspond roughly to excitatory versus inhibitory cell type (Barthó et al., 2004; McCormick et al., 1985) and has also been shown to correspond to different visual response properties in”
Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex
The Petilla Interneuron Nomenclature Group (PING) (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2402 · Cited by 1,491
Highly nonrandom features of synaptic connectivity in local cortical circuits
Song, S., Sjöström, P. J., Reigl, M., Nelson, S., & Chklovskii, D. B. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030068 · Cited by 1,512
Metadata
- Authors
- Barthó, P., Hirase, H., Monconduit, L., Zugaro, M., Harris, K. D., & Buzsáki, G.
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2004-07
- Volume
- 92
- Issue
- 1
- Pages
- 600-608
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- OpenAlex
- W2032773159
- Cited by
- 887
- References
- 10
- FWCI
- 5.44
- Type
- journal article
- Language
- en
- Open access
- closed
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