Characterization of neocortical principal cells and interneurons by network interactions and extracellular features.

By P. Barthó, H. Hirase, L. Monconduit, Michaël Zugaro, Kenneth D. Harris, György Buzsáki. Journal of Neurophysiology, 2004

895 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/eb69d66e10c548a54c5a21bcaafacdb689744803

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Citations in the corpus

Firing Rate Homeostasis in Visual Cortex of Freely Behaving Rodents (2013, methodology): “Regular spiking pyramidal neurons comprise 80% of neocortical neurons; to enrich for putative pyramidal neurons, we separated RSUs from pFS cells ( 50% of the nonpyramidal population) using established criteria (Barthó et al., 2004; Cardin et al., 2007; Liu et al., 2009; Niell and Stryker, 2008): un”
Challenges and opportunities for large-scale electrophysiology with Neuropixels probes (2018, background): “The size of the recorded populations may enable the study of neural computation at a single-trial level during behavioral tasks, and may allow effective study of connected pairs of neurons, which typically represent only a small fraction of recorded pairs (<1%; [36,37]).”
Gamma-band synchronization in the neocortex: novel analysis methods and their application to sensory and motivational systems (2013, methodology): “The approach of identifying cell types using extracellular recordings is quite well accepted, e.g. see (Bartho et al., 2004; Csicsvari et al., 1999, 2003; Mitchell et al., 2007).”
Nanotools for Neuroscience and Brain Activity Mapping (2013, background): “This may be valuable for identifying cells along broadly de ﬁ ned categories, such as pyramidal neurons versus interneuron 84 or dopaminergic versus nondopaminergic.”
Modulation of visual responses by behavioral state in mouse visual cortex. (2010, positive): “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”
Sparse Representation of Sounds in the Unanesthetized Auditory Cortex (2008, methodology): “Multiple features of spike waveforms seem to be required to classify a given cell as a pyramidal cell or an interneuron [35,48], with narrow-spiking cells usually considered to be interneurons.”
Large-scale recording of neuronal ensembles (2004, background): “Importantly, the geometrically precise distribution of the recording sites also allows for the determination of the spatial relationship of the isolated single neuron”
Coherent theta oscillations and reorganization of spike timing in the hippocampal- prefrontal network upon learning. (2010, positive): “These neurons were then subdivided according to their putative cell type on the basis of action potential duration (Barthó et al., 2004; Figure S6A).”
Differential attention-dependent response modulation across cell classes in macaque visual area V4. (2007, methodology): “Several different metrics of waveform duration have been used, including the timing of the peak (Wilson et al., 1994; Frank et al., 2001; GonzalezBurgos et al., 2004; Bartho et al., 2004), the return to baseline after the peak (Rao et al.”
Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex (2007, background): “, 2003) and additional studies based on cross-correlation analysis of spike trains (Bartho et al., 2004; Tamura et al., 2004) have shown the reliability of such an approach in identifying neuronal typing.”
Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits (2005, background): “Such statistical description may be based on random sampling of connections with multineuron recordings [3,4,5].”
Cortical firing and sleep homeostasis. (2009, methodology): “Consistent with previous studies (Bartho et al., 2004; McCormick et al., 1985; Steriade et al., 1993c), these three types were subdivided into two groups based on the width of the action potential at 1/2 amplitude (Figures 7B and 7D).”
Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop (2009, methodology): “We took advantage of the simultaneously recorded EC cells to physiologically identify units as excitatory or inhibitory neurons by their short-latency temporal interactions with other neurons (Barthó et al., 2004; Sirota et al., 2008).”
Automated long-term recording and analysis of neural activity in behaving animals (2016, methodology): “…We clustered motor cortical and striatal units into putative principal neurons and interneurons based on their spike shapes and firing rates (Barthó et al., 2004; Berke et al., 2004; Connors and Gutnick, 1990), thus identifying 264 fast spiking and 455 medium spiny neurons in striatum, and…”
Physiological properties and behavioral correlates of hippocampal granule cells and mossy cells (2017, neutral): “Putative monosynaptic connections are associated with precisely timed spiking relationships at short (<5 ms) latency offsets between two recorded neurons, as detected by narrow significant peaks (excitatory) or troughs (inhibitory) in the cross-correlogram (Figure S2B; Barthó et al., 2004).”