Columnar Localization and Laminar Origin of Cortical Surface Electrical Potentials

Baratham, Vyassa L; Dougherty, Max; Hermiz, John; Ledochowitsch, Peter; Maharbiz, Michel M.; Bouchard, Kristofer E.

doi:10.1523/jneurosci.1787-21.2022

Cited by 10 publications

(32 citation statements)

References 61 publications

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“…The high-gamma range of high frequency CSEPs is of particular interest because it is a highly informative signal for clinical applications of brain-computer interfaces, and it is related to multi-unit spiking activity (Baratham et al 2022; Livezey and Glaser 2021; Ray and Maunsell 2011). In CSEPs recorded from rat auditory cortex, we observed multiple peaks in the evoked high frequency neural spectra.…”

Section: Discussionmentioning

confidence: 99%

“…These results support the hypothesis that time-varying high-gamma amplitude arises from at least two distinct components: a power-law component and a bandlimited component. More broadly, we conjecture that the generating sources of the distinct frequency components observed in rat CSEPs may be spiking activity in different layers of cortex (Baratham et al 2022). Because neurons in different cortical layers perform different computations, if true, this conjecture would imply that different frequency components are biomarkers of layer-resolved cortical computations.…”

Section: Discussionmentioning

confidence: 99%

“…In order to gain access to the high frequency range (70-1,000 Hz) of cortical surface electrical potentials (CSEPs), we recorded CSEPs from rat auditory cortex using µ ECoG arrays. Data collection and preprocessing methodology for the rat data has been previously described (Baratham et al 2022; Dougherty et al 2019). All animal procedures were performed in accordance with established animal care protocols approved by the Lawrence Berkeley National Laboratory Institutional Animal Care and Use Committee.…”

Section: Methodsmentioning

confidence: 99%

“…Importantly, it is the fast time-scale (10's of milliseconds) modulations of high-frequency amplitudes that contains task relevant information. Distinguishing whether high frequencies in CSEPS are band-limited or broad-band impacts their biophysical interpretation, for example whether the recorded signals are differentially generated (and potentially resolvable) across layers of cortex (Baratham et al 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Based on observations from our recently published study (Baratham et al 2022), we hypothesized that high frequency CSEPs are composed of one-or-more bandlimited components in addition to a broadband component. To test this hypothesis, we used high-quality neural amplifiers to record with µ ECoG from rat auditory cortex in response to sounds and high-density ECoG from human sensorimotor cortex during speech production.…”

Section: Introductionmentioning

confidence: 99%

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Cortical surface electrical potentials are composed of multiple bandlimited frequency components, including high-gamma

Livezey

Hwang

Usovich

et al. 2022

Preprint

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A common challenge in neuroscience is how to decompose noisy, multi-source signals measured in experiments into biophysically interpretable components. Analysis of cortical surface electrical potentials (CSEPs) measured using electrocorticography arrays (ECoG) typifies this problem. We hypothesized that high frequency (70-1,000 Hz) CSEPs are composed of broadband (i.e., power-law) and bandlimited components with potentially differing biophysical origins. In particular, the high-gamma band (70-150 Hz) has been shown to be highly predictive for encoding and decoding behaviors and stimuli. Despite its demonstrated importance, whether high-gamma is composed of a bandlimited signal is poorly understood. To address this gap, we recorded CSEPs from rat auditory cortex and demonstrate that the evoked CSEPs are composed of multiple distinct frequency components, including high-gamma. We then show, using a novel robust regression method, that at fast timescales and on single trials during speech production, human high-gamma amplitude cannot be explained by a modulating power-law component; thus, high-gamma is band-limited. Furthermore, we show that the power-law component is less predictive of produced speech compared to the raw high-gamma amplitude. Finally, we show that the largest variance component of human ECoG signals is low-frequency and band-limited, not broadband. Together these results demonstrate that there are multiple, band-limited components of high frequency power in cortical surface electrical potentials, including the high-gamma band, which may have different biophysical origins.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Cortical surface electrical potentials are composed of multiple bandlimited frequency components, including high-gamma

Livezey

Hwang

Usovich

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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Large-scale single-neuron speech sound encoding across the depth of human cortex

Leonard,

Gwilliams,

Sellers

et al. 2023

Nature

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Understanding the neural basis of speech perception requires that we study the human brain both at the scale of the fundamental computational unit of neurons and in their organization across the depth of cortex. Here we used high-density Neuropixels arrays1–3 to record from 685 neurons across cortical layers at nine sites in a high-level auditory region that is critical for speech, the superior temporal gyrus4,5, while participants listened to spoken sentences. Single neurons encoded a wide range of speech sound cues, including features of consonants and vowels, relative vocal pitch, onsets, amplitude envelope and sequence statistics. Neurons at each cross-laminar recording exhibited dominant tuning to a primary speech feature while also containing a substantial proportion of neurons that encoded other features contributing to heterogeneous selectivity. Spatially, neurons at similar cortical depths tended to encode similar speech features. Activity across all cortical layers was predictive of high-frequency field potentials (electrocorticography), providing a neuronal origin for macroelectrode recordings from the cortical surface. Together, these results establish single-neuron tuning across the cortical laminae as an important dimension of speech encoding in human superior temporal gyrus.

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Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation

Lo,

Jiang,

Woodington

et al. 2024

J. Neural Eng.

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Objective: Micro-electrocorticographic (μECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to use μECoG array to decode, in rats, body position during open field navigation, through isolated single-unit activities.Approach: μECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300 to 3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns.Main results: Single-unit spikes could be extracted during chronic recording from μECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson’s r of 0.607 and 0.571, respectively.Significance: μECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface.

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Columnar Localization and Laminar Origin of Cortical Surface Electrical Potentials

Cited by 10 publications

References 61 publications

Cortical surface electrical potentials are composed of multiple bandlimited frequency components, including high-gamma

Cortical surface electrical potentials are composed of multiple bandlimited frequency components, including high-gamma

Large-scale single-neuron speech sound encoding across the depth of human cortex

Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation

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