Literature DB >> 25995352

Cell type- and activity-dependent extracellular correlates of intracellular spiking.

Costas A Anastassiou1, Rodrigo Perin2, György Buzsáki3, Henry Markram2, Christof Koch4.   

Abstract

Despite decades of extracellular action potential (EAP) recordings monitoring brain activity, the biophysical origin and inherent variability of these signals remain enigmatic. We performed whole cell patch recordings of excitatory and inhibitory neurons in rat somatosensory cortex slice while positioning a silicon probe in their vicinity to concurrently record intra- and extracellular voltages for spike frequencies under 20 Hz. We characterize biophysical events and properties (intracellular spiking, extracellular resistivity, temporal jitter, etc.) related to EAP recordings at the single-neuron level in a layer-specific manner. Notably, EAP amplitude was found to decay as the inverse of distance between the soma and the recording electrode with similar (but not identical) resistivity across layers. Furthermore, we assessed a number of EAP features and their variability with spike activity: amplitude (but not temporal) features varied substantially (∼ 30-50% compared with mean) and nonmonotonically as a function of spike frequency and spike order. Such EAP variation only partly reflects intracellular somatic spike variability and points to the plethora of processes contributing to the EAP. Also, we show that the shape of the EAP waveform is qualitatively similar to the negative of the temporal derivative to the intracellular somatic voltage, as expected from theory. Finally, we tested to what extent EAPs can impact the lowpass-filtered part of extracellular recordings, the local field potential (LFP), typically associated with synaptic activity. We found that spiking of excitatory neurons can significantly impact the LFP at frequencies as low as 20 Hz. Our results question the common assertion that the LFP acts as proxy for synaptic activity.
Copyright © 2015 the American Physiological Society.

Entities:  

Keywords:  LFP; clustering; extracellular recordings; intracellular spikes; spike waveform

Mesh:

Year:  2015        PMID: 25995352      PMCID: PMC4509390          DOI: 10.1152/jn.00628.2014

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  63 in total

1.  Temporal interaction between single spikes and complex spike bursts in hippocampal pyramidal cells.

Authors:  K D Harris; H Hirase; X Leinekugel; D A Henze; G Buzsáki
Journal:  Neuron       Date:  2001-10-11       Impact factor: 17.173

2.  Electrical interactions via the extracellular potential near cell bodies.

Authors:  G R Holt; C Koch
Journal:  J Comput Neurosci       Date:  1999 Mar-Apr       Impact factor: 1.621

3.  Relationships between spike-free local field potentials and spike timing in human temporal cortex.

Authors:  Stavros Zanos; Theodoros P Zanos; Vasilis Z Marmarelis; George A Ojemann; Eberhard E Fetz
Journal:  J Neurophysiol       Date:  2011-12-07       Impact factor: 2.714

4.  Macroscopic models of local field potentials and the apparent 1/f noise in brain activity.

Authors:  Claude Bédard; Alain Destexhe
Journal:  Biophys J       Date:  2009-04-08       Impact factor: 4.033

5.  Ephaptic coupling of cortical neurons.

Authors:  Costas A Anastassiou; Rodrigo Perin; Henry Markram; Christof Koch
Journal:  Nat Neurosci       Date:  2011-01-16       Impact factor: 24.884

6.  Theoretical analysis of field potentials in anisotropic ensembles of neuronal elements.

Authors:  C Nicholson
Journal:  IEEE Trans Biomed Eng       Date:  1973-07       Impact factor: 4.538

7.  An evaluation of the conductivity profile in the somatosensory barrel cortex of Wistar rats.

Authors:  Takakuni Goto; Rieko Hatanaka; Takeshi Ogawa; Akira Sumiyoshi; Jorge Riera; Ryuta Kawashima
Journal:  J Neurophysiol       Date:  2010-09-01       Impact factor: 2.714

8.  Large identified pyramidal cells in macaque motor and premotor cortex exhibit "thin spikes": implications for cell type classification.

Authors:  Ganesh Vigneswaran; Alexander Kraskov; Roger N Lemon
Journal:  J Neurosci       Date:  2011-10-05       Impact factor: 6.167

9.  The spiking component of oscillatory extracellular potentials in the rat hippocampus.

Authors:  Erik W Schomburg; Costas A Anastassiou; György Buzsáki; Christof Koch
Journal:  J Neurosci       Date:  2012-08-22       Impact factor: 6.167

10.  Massively parallel recording of unit and local field potentials with silicon-based electrodes.

Authors:  Jozsef Csicsvari; Darrell A Henze; Brian Jamieson; Kenneth D Harris; Anton Sirota; Péter Barthó; Kensall D Wise; György Buzsáki
Journal:  J Neurophysiol       Date:  2003-08       Impact factor: 2.714

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  24 in total

1.  Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform.

Authors:  Clayton P Mosher; Yina Wei; Jan Kamiński; Anirban Nandi; Adam N Mamelak; Costas A Anastassiou; Ueli Rutishauser
Journal:  Cell Rep       Date:  2020-03-10       Impact factor: 9.423

2.  Neural network model of an amphibian ventilatory central pattern generator.

Authors:  Ginette Horcholle-Bossavit; Brigitte Quenet
Journal:  J Comput Neurosci       Date:  2019-05-22       Impact factor: 1.621

3.  Magnitude and behavior of cross-talk effects in multichannel electrophysiology experiments.

Authors:  Matthew J Nelson; Silvana Valtcheva; Laurent Venance
Journal:  J Neurophysiol       Date:  2017-04-19       Impact factor: 2.714

4.  Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability.

Authors:  Brian D Allen; Caroline Moore-Kochlacs; Jacob G Bernstein; Justin P Kinney; Jorg Scholvin; Luís F Seoane; Chris Chronopoulos; Charlie Lamantia; Suhasa B Kodandaramaiah; Max Tegmark; Edward S Boyden
Journal:  J Neurophysiol       Date:  2018-07-11       Impact factor: 2.714

5.  A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'.

Authors:  Nicholas V Swindale; Catalin Mitelut; Timothy H Murphy; Martin A Spacek
Journal:  J Vis Exp       Date:  2017-02-10       Impact factor: 1.355

6.  A neural network for online spike classification that improves decoding accuracy.

Authors:  Deepa Issar; Ryan C Williamson; Sanjeev B Khanna; Matthew A Smith
Journal:  J Neurophysiol       Date:  2020-02-26       Impact factor: 2.714

7.  A low-cost, scalable, current-sensing digital headstage for high channel count μECoG.

Authors:  Michael Trumpis; Michele Insanally; Jialin Zou; Ashraf Elsharif; Ali Ghomashchi; N Sertac Artan; Robert C Froemke; Jonathan Viventi
Journal:  J Neural Eng       Date:  2017-01-19       Impact factor: 5.379

8.  In vitro multichannel single-unit recordings of action potentials from mouse sciatic nerve.

Authors:  L Chen; S J Ilham; T Guo; S Emadi; B Feng
Journal:  Biomed Phys Eng Express       Date:  2017-07-26

Review 9.  Improving data quality in neuronal population recordings.

Authors:  Kenneth D Harris; Rodrigo Quian Quiroga; Jeremy Freeman; Spencer L Smith
Journal:  Nat Neurosci       Date:  2016-08-26       Impact factor: 24.884

10.  Spike Afterpotentials Shape the In Vivo Burst Activity of Principal Cells in Medial Entorhinal Cortex.

Authors:  Dóra É Csordás; Caroline Fischer; Johannes Nagele; Martin Stemmler; Andreas V M Herz
Journal:  J Neurosci       Date:  2020-04-24       Impact factor: 6.167

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