Cross-Correlation Analysis of Electroencephalographic Potentials and Slow Membrane Transients

Klee, Manfred R.; Offenloch, Kurt; Tigges, Johannes

doi:10.1126/science.147.3657.519

Cited by 81 publications

(20 citation statements)

References 18 publications

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“…This information is complementary to that provided by action potentials, since it relates to processes that are causal to generation of action potentials (Rasch et al, 2009), but may not clearly manifest in action potential patterns, in cases where excitatory inputs are subthreshold or offset by concurrent inhibition (Creutzfeldt et al, 1966; Klee et al, 1965; Schroeder et al, 1998). The problem with LFPs recorded using a distant reference electrode is that generator location and sampling area are each unknown.…”

Section: Discussionmentioning

confidence: 99%

How Local Is the Local Field Potential?

Kajikawa

Schroeder

2011

Neuron

539

466

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Summary Local field potentials (LFPs) are of growing importance in neurophysiological investigations. LFPs supplement action potential recordings by indexing activity relevant to EEG, MEG and hemodynamic (fMRI) signals. Recent reports suggest that LFPs reflect activity within very small domains of several hundred microns. We examined this conclusion by comparing LFP, current source density (CSD), and multiunit activity (MUA) signals in macaque auditory cortex. Estimated by frequency tuning bandwidths, these signals' “listening areas” differ systematically with an order of: MUA < CSD < LFP. Computational analyses confirm that observed LFPs receive non-local contributions. Direct measurements indicate passive spread of LFPs to sites more than a centimeter from their origins. These findings appear to be independent of the frequency content of the LFP. Our results challenge the idea that LFP recordings typically integrate over extremely circumscribed local domains. Rather, LFPs appear as a mixture of local potentials with “volume conducted” potentials from distant sites.

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Section: Discussionmentioning

confidence: 99%

How Local Is the Local Field Potential?

Kajikawa

Schroeder

2011

Neuron

539

466

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“…The LFP, icEEG, and scalp EEG signals represent extracellular field potentials primarily originated by postsynaptic activity, integrated over different volumes (Creutzfeldt et al, 1966a, Creutzfeldt et al, 1966b, Klee et al, 1965, Niedermeyer and Lopes da Silva, 1999). The amplitude of these signals depends on the geometric arrangement of the active cells, within each element volume, as well as on the degree of synchrony among the multiple element volumes, over larger distances (Einevoll et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

A study of the electro-haemodynamic coupling using simultaneously acquired intracranial EEG and fMRI data in humans

Murta

Tierney³

et al. 2016

NeuroImage

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In current fMRI studies designed to map BOLD changes related to interictal epileptiform discharges (IED), which are recorded on simultaneous EEG, the information contained in the morphology and field extent of the EEG events is exclusively used for their classification. Usually, a BOLD predictor based on IED onset times alone is constructed, effectively treating all events as identical. We used intracranial EEG (icEEG)-fMRI data simultaneously recorded in humans to investigate the effect of including any of the features: amplitude, width (duration), slope of the rising phase, energy (area under the curve), or spatial field extent (number of contacts over which the sharp wave was observed) of the fast wave of the IED (the sharp wave), into the BOLD model, to better understand the neurophysiological origin of sharp wave-related BOLD changes, in the immediate vicinity of the recording contacts. Among the features considered, the width was the only one found to explain a significant amount of additional variance, suggesting that the amplitude of the BOLD signal depends more on the duration of the underlying field potential (reflected in the sharp wave width) than on the degree of neuronal activity synchrony (reflected in the sharp wave amplitude), and, consequently, that including inter-event variations of the sharp wave width in the BOLD signal model may increase the sensitivity of forthcoming EEG-fMRI studies of epileptic activity.

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“…There is considerable debate on the precise contributions of neural activity to extracellular potentials in the 100 – 500 Hz frequency range. Lower frequency LFP signals, below ∼100-200 Hz, are generally believed to reflect post-synaptic transmembrane potentials (Klee et al, 1965; Mitzdorf, 1985; Buzsaki, 2006; Okun et al, 2010). The tuning of gamma-band activity in cat V1 measured by intracellular membrane potential is closely correlated with that of spiking activity (Azouz and Gray, 2003), which itself is associated with rapid fluctuations in subthreshold membrane potential (Azouz and Gray, 2008).…”

Section: Discussionmentioning

confidence: 99%

Optimizing the Decoding of Movement Goals from Local Field Potentials in Macaque Cortex

Markowitz¹,

Wong²,

Gray³

et al. 2011

J. Neurosci.

106

134

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The successful development of motor neuroprosthetic devices hinges on the ability to accurately and reliably decode signals from the brain. Motor neuroprostheses are widely investigated in behaving non-human primates, but technical constraints have limited progress in optimizing performance. In particular, the organization of movement-related neuronal activity across cortical layers remains poorly understood due, in part, to the widespread use of fixed-geometry multielectrode arrays. In this study, we use chronically-implanted multielectrode arrays with individually movable electrodes to examine how the encoding of movement goals depends on cortical depth. In a series of recordings spanning several months, we varied the depth of each electrode in the pre-arcuate gyrus of frontal cortex in two monkeys as they performed memory-guided eye movements. We decode eye movement goals from local field potentials (LFPs) and multiunit spiking activity recorded across a range of depths up to 3 mm from the cortical surface. We show that both LFP and multiunit signals yield the highest decoding performance at superficial sites, within 0.5 mm of the cortical surface, while performance degrades substantially at sites deeper than 1 mm. We also analyze performance by varying bandpass filtering characteristics and simulating changes in microelectrode array channel count and density. The results indicate that the performance of LFP-based neuroprostheses strongly depends on recording configuration and that recording depth is a critical parameter limiting system performance.

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Cross-Correlation Analysis of Electroencephalographic Potentials and Slow Membrane Transients

Cited by 81 publications

References 18 publications

How Local Is the Local Field Potential?

How Local Is the Local Field Potential?

A study of the electro-haemodynamic coupling using simultaneously acquired intracranial EEG and fMRI data in humans

Optimizing the Decoding of Movement Goals from Local Field Potentials in Macaque Cortex

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