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Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX): comparing multi-electrode recordings from simulated and biological mammalian cortical tissue.

Tomsett RJ, Ainsworth M, Thiele A, Sanayei M, Chen X, Gieselmann MA, Whittington MA, Cunningham MO, Kaiser M - Brain Struct Funct (2014)

Bottom Line: We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons.A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue.We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.

View Article: PubMed Central - PubMed

Affiliation: School of Computing Science, Newcastle University, Claremont Tower, Newcastle upon Tyne, NE1 7RU, UK, indigentmartian@gmail.com.

ABSTRACT
Local field potentials (LFPs) sampled with extracellular electrodes are frequently used as a measure of population neuronal activity. However, relating such measurements to underlying neuronal behaviour and connectivity is non-trivial. To help study this link, we developed the Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX). We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons. We then developed VERTEX as an easy-to-use Matlab tool for simulating LFPs from large populations (>100,000 neurons). A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue. Our model, with virtual electrodes placed anywhere in 3D, allows direct comparisons with the in vitro recording setup. We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.

No MeSH data available.


Related in: MedlinePlus

Comparison of experimental (a–c) and simulated (d–f) MEA recordings. a Map of gamma frequency power across the electrode array in vitro. Electrode positions shown as grey dots, corner numbers indicate electrode IDs. Shadedareas show where electrodes were discounted because they fell either outside the slice boundaries or within the white matter. Gamma power is strongest at the top of the slice, corresponding to L2/3. b Example experimental LFP traces from electrodes 41–44 (indicated by grey rectangle in a). Traces have been normalised to unit standard deviation for ease of comparison. c Cross correlation of signals from electrodes 41–44 with signal from electrode 42, illustrating phase inversion in the signal from electrode 41. This electrode was identified as being in layer 1 by post hoc histology (not shown). Gamma map and cross-correlations estimated from 18 s of data. d–f as a–c, but for the neocortical slice model (gamma map and cross-correlations estimated from 1.5 s of simulation data)
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Fig9: Comparison of experimental (a–c) and simulated (d–f) MEA recordings. a Map of gamma frequency power across the electrode array in vitro. Electrode positions shown as grey dots, corner numbers indicate electrode IDs. Shadedareas show where electrodes were discounted because they fell either outside the slice boundaries or within the white matter. Gamma power is strongest at the top of the slice, corresponding to L2/3. b Example experimental LFP traces from electrodes 41–44 (indicated by grey rectangle in a). Traces have been normalised to unit standard deviation for ease of comparison. c Cross correlation of signals from electrodes 41–44 with signal from electrode 42, illustrating phase inversion in the signal from electrode 41. This electrode was identified as being in layer 1 by post hoc histology (not shown). Gamma map and cross-correlations estimated from 18 s of data. d–f as a–c, but for the neocortical slice model (gamma map and cross-correlations estimated from 1.5 s of simulation data)

Mentions: As described in previous experiments (Ainsworth et al. 2011; Cunningham et al. 2003, 2004b; Traub et al. 2005a, b), P2/3 neurons spike infrequently, while B2/3 neurons spike on most oscillation periods. Excitatory neurons in L4 do not take part in the oscillation (though still spike infrequently), while L4 interneurons are weakly entrained to the oscillation. In addition to the L2/3 gamma, the comparison slice exhibited increased gamma power in part of the infra-granular layers (see Fig. 9a, electrodes 6, 7, 16, 17, 26, 27), presumably caused by L5 as described by Ainsworth et al. (2011). We therefore used a relatively high coupling strength of P5 to B5 and NB5 neurons and a larger noisy drive current to L5 neurons to enable the L2/3 gamma to generate gamma in L5. The L5 gamma oscillation also weakly entrained L6 neurons to the oscillation.


Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX): comparing multi-electrode recordings from simulated and biological mammalian cortical tissue.

Tomsett RJ, Ainsworth M, Thiele A, Sanayei M, Chen X, Gieselmann MA, Whittington MA, Cunningham MO, Kaiser M - Brain Struct Funct (2014)

Comparison of experimental (a–c) and simulated (d–f) MEA recordings. a Map of gamma frequency power across the electrode array in vitro. Electrode positions shown as grey dots, corner numbers indicate electrode IDs. Shadedareas show where electrodes were discounted because they fell either outside the slice boundaries or within the white matter. Gamma power is strongest at the top of the slice, corresponding to L2/3. b Example experimental LFP traces from electrodes 41–44 (indicated by grey rectangle in a). Traces have been normalised to unit standard deviation for ease of comparison. c Cross correlation of signals from electrodes 41–44 with signal from electrode 42, illustrating phase inversion in the signal from electrode 41. This electrode was identified as being in layer 1 by post hoc histology (not shown). Gamma map and cross-correlations estimated from 18 s of data. d–f as a–c, but for the neocortical slice model (gamma map and cross-correlations estimated from 1.5 s of simulation data)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4481302&req=5

Fig9: Comparison of experimental (a–c) and simulated (d–f) MEA recordings. a Map of gamma frequency power across the electrode array in vitro. Electrode positions shown as grey dots, corner numbers indicate electrode IDs. Shadedareas show where electrodes were discounted because they fell either outside the slice boundaries or within the white matter. Gamma power is strongest at the top of the slice, corresponding to L2/3. b Example experimental LFP traces from electrodes 41–44 (indicated by grey rectangle in a). Traces have been normalised to unit standard deviation for ease of comparison. c Cross correlation of signals from electrodes 41–44 with signal from electrode 42, illustrating phase inversion in the signal from electrode 41. This electrode was identified as being in layer 1 by post hoc histology (not shown). Gamma map and cross-correlations estimated from 18 s of data. d–f as a–c, but for the neocortical slice model (gamma map and cross-correlations estimated from 1.5 s of simulation data)
Mentions: As described in previous experiments (Ainsworth et al. 2011; Cunningham et al. 2003, 2004b; Traub et al. 2005a, b), P2/3 neurons spike infrequently, while B2/3 neurons spike on most oscillation periods. Excitatory neurons in L4 do not take part in the oscillation (though still spike infrequently), while L4 interneurons are weakly entrained to the oscillation. In addition to the L2/3 gamma, the comparison slice exhibited increased gamma power in part of the infra-granular layers (see Fig. 9a, electrodes 6, 7, 16, 17, 26, 27), presumably caused by L5 as described by Ainsworth et al. (2011). We therefore used a relatively high coupling strength of P5 to B5 and NB5 neurons and a larger noisy drive current to L5 neurons to enable the L2/3 gamma to generate gamma in L5. The L5 gamma oscillation also weakly entrained L6 neurons to the oscillation.

Bottom Line: We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons.A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue.We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.

View Article: PubMed Central - PubMed

Affiliation: School of Computing Science, Newcastle University, Claremont Tower, Newcastle upon Tyne, NE1 7RU, UK, indigentmartian@gmail.com.

ABSTRACT
Local field potentials (LFPs) sampled with extracellular electrodes are frequently used as a measure of population neuronal activity. However, relating such measurements to underlying neuronal behaviour and connectivity is non-trivial. To help study this link, we developed the Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX). We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons. We then developed VERTEX as an easy-to-use Matlab tool for simulating LFPs from large populations (>100,000 neurons). A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue. Our model, with virtual electrodes placed anywhere in 3D, allows direct comparisons with the in vitro recording setup. We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.

No MeSH data available.


Related in: MedlinePlus