Design Choices for Next-Generation Neurotechnology Can Impact Motion Artifact in Electrophysiological and Fast-Scan Cyclic Voltammetry Measurements

Nicolai, Evan N.; Michelson, Nicholas J.; Settell, Megan L.; Hara, Seth A.; Trevathan, James K.; Anders, Jennifer; Stocking, Kaylene C.; Luján, J. Luis; Kozai, Takashi D. Y.; Ludwig, Kip A.

doi:10.3390/mi9100494

Cited by 16 publications

(15 citation statements)

References 65 publications

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“…In particular, mechanical vibrations may create variations of biopotential measurements (Luna-Lozano and Pallas-Areny, 2010). Such undesired signals may have different origins, including the bending of the electrode wires and the electrochemical changes at the electrode-electrolyte interface induced by small displacements of the electrodes (Salatino et al, 2017;Nicolai et al, 2018). Here we observed sound contamination of neural signals in different setups.…”

Section: Discussionmentioning

confidence: 49%

Acoustic contamination of electrophysiological brain signals during speech production and sound perception

Roussel

Bocquelet

Palma

et al. 2019

Preprint

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A current challenge of neurotechnologies is the development of speech brain-computer interfaces to restore communication in people unable to speak. To achieve a proof of concept of such system, neural activity of patients implanted for clinical reasons can be recorded while they speak. Using such simultaneously recorded audio and neural data, decoders can be built to predict speech features using features extracted from brain signals. A typical neural feature is the spectral power of field potentials in the high-gamma frequency band (between 70 and 200 Hz), a range that happens to overlap the fundamental frequency of speech. Here, we analyzed human electrocorticographic (ECoG) and intracortical recordings during speech production and perception as well as rat microelectrocorticographic (µ-ECoG) recordings during sound perception. We observed that electrophysiological signals, recorded with different recording setups, often contain spectrotemporal features highly correlated with those of the sound, especially within the high-gamma band. The characteristics of these correlated spectrotemporal features support a contamination of electrophysiological recordings by sound. In a recording showing high contamination, using neural features within the high-gamma frequency band dramatically increased the performance of linear decoding of acoustic speech features, while such improvement was very limited for another recording showing weak contamination. Further analysis and in vitro replication suggest that the contamination is caused by a mechanical action of the sound waves onto the cables and connectors along the recording chain, transforming sound vibrations into an undesired electrical noise that contaminates the biopotential measurements. This study does not question the existence of relevant physiological neural information underlying speech production or sound perception in the high-gamma frequency band, but alerts on the fact that care should be taken to evaluate and eliminate any possible acoustic contamination of neural signals in order to investigate the cortical dynamics of these processes.

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Section: Discussionmentioning

confidence: 49%

Acoustic contamination of electrophysiological brain signals during speech production and sound perception

Roussel

Bocquelet

Palma

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…Anesthetized animals were placed on a microwaveable heating pad (Deltaphase isothermal pad; Braintree Scientific, Braintree, MA) (1.6-mm mesh), with the head mechanically fixed using a custombuilt stereotaxic frame to minimize motion artifacts (Nicolai 2018). The animal was placed 20 cm from the monitor on the side contralateral to the site of implantation, spanning a total visual field of 120°w ide by 60°high.…”

Section: Methodsmentioning

confidence: 99%

Isoflurane and ketamine differentially influence spontaneous and evoked laminar electrophysiology in mouse V1

Michelson

Kozai

2018

Journal of Neurophysiology

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General anesthesia is ubiquitous in research and medicine, yet although the molecular mechanisms of anesthetics are well characterized, their ultimate influence on cortical electrophysiology remains unclear. Moreover, the influence that different anesthetics have on sensory cortices at neuronal and ensemble scales is mostly unknown, and represents an important gap in knowledge that has widespread relevance for neural sciences. To address this knowledge gap, this work explored the effects of isoflurane and ketamine/xylazine, two widely used anesthetic paradigms, on electrophysiological behavior in mouse primary visual cortex. First, multiunit activity and local field potentials were examined to understand how each anesthetic influences spontaneous activity. Then, the inter-laminar relationships between populations of neurons at different cortical depths were studied to assess whether anesthetics influenced resting-state functional connectivity. Lastly, the spatiotemporal dynamics of visually evoked multiunit and local field potentials were examined to determine how each anesthetic alters communication of visual information. We found that isoflurane enhanced the rhythmicity of spontaneous ensemble activity at 10-40 Hz, which coincided with large increases in coherence between layer IV with superficial and deep layers. Ketamine preferentially increased local field potential power from 2-4 Hz, and the largest increases in coherence were observed between superficial and deep layers. Visually evoked responses across layers were diminished under isoflurane, and enhanced under ketamine anesthesia. These findings demonstrate that isoflurane and ketamine anesthesia differentially impact sensory processing in V1.

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“…Motion artifacts typically manifest as rapid, variable deflections and as such they are extremely difficult to remove at the analysis stage. At the acquisition stage, motion artifacts originate from multiple sources ( Nicolai et al., 2018 ) some of which are inherent to the selected methodology (e.g., the interface between the electrodes and brain parenchyma). Using this protocol, motion artifacts are typically negligible relative to the evoked response and thus should not be a major concern.…”

Section: Troubleshootingmentioning

confidence: 99%

Measuring synaptic transmission and plasticity with fEPSP recordings in behaving mice

et al. 2022

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Summary Spontaneous spiking activity depends on intrinsic excitability and synaptic input. Historically, synaptic activity has been mostly studied ex vivo . Here, we describe a versatile and robust protocol to record field excitatory postsynaptic potentials (fEPSPs) in behaving rodents. The protocol allows estimating the input–output relationship of a specific pathway, short-term and long-term plasticity, and their modulation by pharmacological or pharmacogenetic interventions and behavioral states. However, experimenters must be aware of the protocol’s specificity and interpret results with care. For complete details on the use and execution of this profile, please refer to Styr et al. (2019) .

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Design Choices for Next-Generation Neurotechnology Can Impact Motion Artifact in Electrophysiological and Fast-Scan Cyclic Voltammetry Measurements

Cited by 16 publications

References 65 publications

Acoustic contamination of electrophysiological brain signals during speech production and sound perception

Acoustic contamination of electrophysiological brain signals during speech production and sound perception

Isoflurane and ketamine differentially influence spontaneous and evoked laminar electrophysiology in mouse V1

Measuring synaptic transmission and plasticity with fEPSP recordings in behaving mice

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