Literature DB >> 10899213

Intracellular features predicted by extracellular recordings in the hippocampus in vivo.

D A Henze1, Z Borhegyi, J Csicsvari, A Mamiya, K D Harris, G Buzsáki.   

Abstract

Multichannel tetrode array recording in awake behaving animals provides a powerful method to record the activity of large numbers of neurons. The power of this method could be extended if further information concerning the intracellular state of the neurons could be extracted from the extracellularly recorded signals. Toward this end, we have simultaneously recorded intracellular and extracellular signals from hippocampal CA1 pyramidal cells and interneurons in the anesthetized rat. We found that several intracellular parameters can be deduced from extracellular spike waveforms. The width of the intracellular action potential is defined precisely by distinct points on the extracellular spike. Amplitude changes of the intracellular action potential are reflected by changes in the amplitude of the initial negative phase of the extracellular spike, and these amplitude changes are dependent on the state of the network. In addition, intracellular recordings from dendrites with simultaneous extracellular recordings from the soma indicate that, on average, action potentials are initiated in the perisomatic region and propagate to the dendrites at 1.68 m/s. Finally we determined that a tetrode in hippocampal area CA1 theoretically should be able to record electrical signals from approximately 1, 000 neurons. Of these, 60-100 neurons should generate spikes of sufficient amplitude to be detectable from the noise and to allow for their separation using current spatial clustering methods. This theoretical maximum is in contrast to the approximately six units that are usually detected per tetrode. From this, we conclude that a large percentage of hippocampal CA1 pyramidal cells are silent in any given behavioral condition.

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Year:  2000        PMID: 10899213     DOI: 10.1152/jn.2000.84.1.390

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


  259 in total

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Authors:  M C Quirk; K I Blum; M A Wilson
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3.  An evaluation of synapse independence.

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4.  Epileptic seizures from abnormal networks: why some seizures defy predictability.

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5.  Measuring the quality of neuronal identification in ensemble recordings.

Authors:  Samuel A Neymotin; William W Lytton; Andrey V Olypher; André A Fenton
Journal:  J Neurosci       Date:  2011-11-09       Impact factor: 6.167

Review 6.  The neural basis of the blood-oxygen-level-dependent functional magnetic resonance imaging signal.

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Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2002-08-29       Impact factor: 6.237

7.  Inhibition of the cluster of differentiation 14 innate immunity pathway with IAXO-101 improves chronic microelectrode performance.

Authors:  John K Hermann; Madhumitha Ravikumar; Andrew J Shoffstall; Evon S Ereifej; Kyle M Kovach; Jeremy Chang; Arielle Soffer; Chun Wong; Vishnupriya Srivastava; Patrick Smith; Grace Protasiewicz; Jingle Jiang; Stephen M Selkirk; Robert H Miller; Steven Sidik; Nicholas P Ziats; Dawn M Taylor; Jeffrey R Capadona
Journal:  J Neural Eng       Date:  2018-04       Impact factor: 5.379

8.  Time Cells in the Hippocampus Are Neither Dependent on Medial Entorhinal Cortex Inputs nor Necessary for Spatial Working Memory.

Authors:  Marta Sabariego; Antonia Schönwald; Brittney L Boublil; David T Zimmerman; Siavash Ahmadi; Nailea Gonzalez; Christian Leibold; Robert E Clark; Jill K Leutgeb; Stefan Leutgeb
Journal:  Neuron       Date:  2019-05-02       Impact factor: 17.173

Review 9.  Technologies for imaging neural activity in large volumes.

Authors:  Na Ji; Jeremy Freeman; Spencer L Smith
Journal:  Nat Neurosci       Date:  2016-08-26       Impact factor: 24.884

Review 10.  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

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