Variability of extracellular spike waveforms of cortical neurons

Fee, M. S., Mitra, P. P., Kleinfeld, D. (1996) Variability of extracellular spike waveforms of cortical neurons. Journal of Neurophysiology, 76 (6). pp. 3823-3833. ISSN 00223077 (ISSN)

URL: https://www.ncbi.nlm.nih.gov/pubmed/8985880

Abstract

1. Here we study the variability in extracellular records of action potentials. Our work is motivated in part, by the need to construct effective algorithms to classify single-unit waveforms from multiunit recordings. 2. We used microwire electrode pairs (stereotrodes) to record from primary somatosensory cortex of awake, behaving rat. Our data consist of continuous records of extracellular activity and segmented records of extracellular spikes. Spectral and principal component techniques are used to analyze mean single-unit waveforms, the variability between different instances of a single-unit waveform, and the underlying background activity. 3. The spectrum of the variability between different instances of a single unit waveforms is not white, and falls off above 1 kHz with a frequency dependence of roughly f-2. This spectrum is different from that of the mean spike waveforms, which falls off roughly as f-4, but is essentially identical with the spectrum of background activity. The spatial coherence of the variability on the 10-μm scale also falls off at high frequencies. 4. The variability between different instances of a single-unit waveform is dominated by a relatively small number of principal components. As a consequence, there is a large anisotropy in the cluster of the spike waveforms. 5. The background noise cannot be represented as a stationary Gaussian random process. In particular, we observed that the spectrum changes significantly between successive 20-ms intervals. Furthermore, the total power in the background activity exhibits larger fluctuations than is consistent with a stationary Gaussian random process. 6. Roughly half of the single-unit spike waveforms exhibit systematic changes as a function of the interspike interval. Although this results in a non-Gaussian distribution in the space of wave forms, the distribution can be modeled by a scalar function of the interspike interval. 7. We use a set of 44 mean single-unit waveforms to define the space of differences between spike waveforms. This characterization, together with that of the background activity, is used to construct a filter that optimizes the detection of differences between single-unit waveforms. Further, an information theoretic measure is defined that characterizes the detectability.

Item Type: Paper
Uncontrolled Keywords: animal experiment anisotropy article brain cell neurotransmission nonhuman priority journal rat somatosensory cortex somatosensory stimulation vibrissa Action Potentials Algorithms Animals Electrophysiology Neurons Normal Distribution Rats
Subjects: physics > neurophysics
organism description > animal > mammal > rodent > rat
organism description > animal > mammal > rodent > rat
CSHL Authors:
Communities: CSHL labs > Mitra lab
Depositing User: CSHL Librarian
Date Deposited: 04 Apr 2012 18:24
Last Modified: 10 Feb 2017 19:55
Related URLs:
URI: http://repository.cshl.edu/id/eprint/25830

Actions (login required)

Administrator's edit/view item Administrator's edit/view item
CSHL HomeAbout CSHLResearchEducationNews & FeaturesCampus & Public EventsCareersGiving