Correlates of a single cortical action potential in the epidural EEG

Single neuron contributions to the auditory brainstem EEG

The auditory brainstem response (ABR) is an acoustically evoked EEG potential that is an important diagnostic tool for hearing loss, especially in newborns. The ABR originates from the response sequence of auditory brainstem nuclei, and a click-evoked ABR typically shows three positive peaks ('waves') within the first six milliseconds. However, an assignment of the waves of the ABR to specific sources is difficult, and a quantification of contributions to the ABR waves is not available. Here, we exploit the large size and physical separation of the barn owl first-order cochlear nucleus magnocellularis (NM) to estimate single-cell contributions to the ABR. We simultaneously recorded NM neurons' spikes and the EEG, and found that ≳ 5, 000 spontaneous single-cell spikes are necessary to isolate a significant spike-triggered average response at the EEG electrode. An average single-neuron contribution to the ABR was predicted by convolving the spike-triggered average with the cell's peri-stimulus time histogram. Amplitudes of predicted contributions of single NM cells typically reached 32.9 ± 1.1 nV (mean ± SE, range: 2.5 - 162.7 nV), or 0.07 ± 0.02% (median ± SE range: 0.01 - 4.0%) of the ABR amplitude. The time of the predicted peak coincided best with the peak of the ABR wave II, and this coincidence was independent of the click sound level. Our results suggest that wave II of the ABR is shaped by a small fraction of NM units.

The effects of low intensity focused ultrasound on neuronal activity in pain processing regions in a rodent model of common peroneal nerve injury

BACKGROUND

Non-invasive, external low intensity focused ultrasound (liFUS) offers promise for treating neuropathic pain when applied to the dorsal root ganglion (DRG).

OBJECTIVE

We examine how external liFUS treatment applied to the L5 DRG affects neuronal changes in single-unit activity from the primary somatosensory cortex (SI) and anterior cingulate cortex (ACC) in a common peroneal nerve injury (CPNI) rodent model.

METHODS

Male Sprague Dawley rats were divided into two cohorts: CPNI liFUS and CPNI sham liFUS. Baseline single-unit activity (SUA) recordings were taken 20 min prior to treatment and for 4 h post treatment in 20 min intervals, then analyzed for frequency and compared to baseline. Recordings from the SI and ACC were separated into pyramidal and interneurons based on waveform and principal component analysis.

RESULTS

Following CPNI surgery, all rats (n = 30) displayed a significant increase in mechanical sensitivity. In CPNI liFUS rats, there was a significant increase in pyramidal neuron spike frequency in the SI region compared to the CPNI sham liFUS animals beginning at 120 min following liFUS treatment (p < 0.05). In the ACC, liFUS significantly attenuated interneuron firing beginning at 80 min after liFUS treatment (p < 0.05).

CONCLUSION

We demonstrate that liFUS changed neuronal spiking in the SI and ACC regions 80 and 120 min after treatment, respectively, which may in part correlate with improved sensory thresholds. This may represent a mechanism of action how liFUS attenuates neuropathic pain. Understanding the impact of liFUS on pain circuits will help advance the use of liFUS as a non-invasive neuromodulation option.

Electrophysiological characterization of the hyperdirect pathway and its functional relevance for subthalamic deep brain stimulation

The subthalamic nucleus (STN) receives input from various cortical areas via hyperdirect pathway (HDP) which bypasses the basal-ganglia loop. Recently, the HDP has gained increasing interest, because of its relevance for STN deep brain stimulation (DBS). To understand the HDP's role cortical responses evoked by STN-DBS have been investigated. These responses have short (<2 ms), medium (2-15 ms), and long (20-70 ms) latencies. Medium-latency responses are supposed to represent antidromic cortical activations via HDP. Together with long-latency responses the medium responses can potentially be used as biomarker of DBS efficacy as well as side effects. We here propose that the activation sequence of the cortical evoked responses can be conceptualized as high frequency oscillations (HFO) for signal analysis. HFO might therefore serve as marker for antidromic activation. Using existing knowledge on HFO recordings, this approach allows data analyses and physiological modeling to advance the pathophysiological understanding of cortical DBS-evoked high-frequency activity.

Noninvasive neuromagnetic single-trial analysis of human neocortical population spikes

Neuronal spiking is commonly recorded by invasive sharp microelectrodes, whereas standard noninvasive macroapproaches (e.g., electroencephalography [EEG] and magnetoencephalography [MEG]) predominantly represent mass postsynaptic potentials. A notable exception are low-amplitude high-frequency (∼600 Hz) somatosensory EEG/MEG responses that can represent population spikes when averaged over hundreds of trials to raise the signal-to-noise ratio. Here, a recent leap in MEG technology-featuring a factor 10 reduction in white noise level compared with standard systems-is leveraged to establish an effective single-trial portrayal of evoked cortical population spike bursts in healthy human subjects. This time-resolved approach proved instrumental in revealing a significant trial-to-trial variability of burst amplitudes as well as time-correlated (∼10 s) fluctuations of burst response latencies. Thus, ultralow-noise MEG enables noninvasive single-trial analyses of human cortical population spikes concurrent with low-frequency mass postsynaptic activity and thereby could comprehensively characterize cortical processing, potentially also in diseases not amenable to invasive microelectrode recordings.

Biophysically detailed forward modeling of the neural origin of EEG and MEG signals

Electroencephalography (EEG) and magnetoencephalography (MEG) are among the most important techniques for non-invasively studying cognition and disease in the human brain. These signals are known to originate from cortical neural activity, typically described in terms of current dipoles. While the link between cortical current dipoles and EEG/MEG signals is relatively well understood, surprisingly little is known about the link between different kinds of neural activity and the current dipoles themselves. Detailed biophysical modeling has played an important role in exploring the neural origin of intracranial electric signals, like extracellular spikes and local field potentials. However, this approach has not yet been taken full advantage of in the context of exploring the neural origin of the cortical current dipoles that are causing EEG/MEG signals. Here, we present a method for reducing arbitrary simulated neural activity to single current dipoles. We find that the method is applicable for calculating extracranial signals, but less suited for calculating intracranial electrocorticography (ECoG) signals. We demonstrate that this approach can serve as a powerful tool for investigating the neural origin of EEG/MEG signals. This is done through example studies of the single-neuron EEG contribution, the putative EEG contribution from calcium spikes, and from calculating EEG signals from large-scale neural network simulations. We also demonstrate how the simulated current dipoles can be used directly in combination with detailed head models, allowing for simulated EEG signals with an unprecedented level of biophysical details. In conclusion, this paper presents a framework for biophysically detailed modeling of EEG and MEG signals, which can be used to better our understanding of non-inasively measured neural activity in humans.

Measuring network disruption in neurodegenerative diseases: New approaches using signal analysis

Advanced neuroimaging has increased understanding of the pathogenesis and spread of disease, and offered new therapeutic targets. MRI and positron emission tomography have shown that neurodegenerative diseases including Alzheimer's disease (AD), Lewy body dementia (LBD), Parkinson's disease (PD), frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) are associated with changes in brain networks. However, the underlying neurophysiological pathways driving pathological processes are poorly defined. The gap between what imaging can discern and underlying pathophysiology can now be addressed by advanced techniques that explore the cortical neural synchronisation, excitability and functional connectivity that underpin cognitive, motor, sensory and other functions. Transcranial magnetic stimulation can show changes in focal excitability in cortical and transcortical motor circuits, while electroencephalography and magnetoencephalography can now record cortical neural synchronisation and connectivity with good temporal and spatial resolution.Here we reflect on the most promising new approaches to measuring network disruption in AD, LBD, PD, FTD, MS, and ALS. We consider the most groundbreaking and clinically promising studies in this field. We outline the limitations of these techniques and how they can be tackled and discuss how these novel approaches can assist in clinical trials by predicting and monitoring progression of neurophysiological changes underpinning clinical symptomatology.

Morphological and Biophysical Determinants of the Intracellular and Extracellular Waveforms in Nigral Dopaminergic Neurons: A Computational Study

Action potentials (APs) in nigral dopaminergic neurons often exhibit two separate components: the first reflecting spike initiation in the dendritically located axon initial segment (AIS) and the second the subsequent dendro-somatic spike. These components are separated by a notch in the ascending phase of the somatic extracellular waveform and in the temporal derivative of the somatic intracellular waveform. Still, considerable variability exists in the presence and magnitude of the notch across neurons. To systematically address the contribution of AIS, dendritic and somatic compartments to shaping the two-component APs, we modeled APs of previously in vivo electrophysiologically characterized and 3D-reconstructed male mouse and rat dopaminergic neurons. A parsimonious two-domain model, with high (AIS) and lower (dendro-somatic) Na⁺ conductance, reproduced the notch in the temporal derivatives, but not in the extracellular APs, regardless of morphology. The notch was only revealed when somatic active currents were reduced, constraining the model to three domains. Thus, an initial AIS spike is followed by an actively generated spike by the axon-bearing dendrite (ABD), in turn followed mostly passively by the soma. The transition from being a source compartment for the AIS spike to a source compartment for the ABD spike satisfactorily explains the extracellular somatic notch. Larger AISs and thinner ABD (but not soma-to-AIS distance) accentuate the AIS component. We conclude that variability in AIS size and ABD caliber explains variability in AP extracellular waveform and separation of AIS and dendro-somatic components, given the presence of at least three functional domains with distinct excitability characteristics.SIGNIFICANCE STATEMENT Midbrain dopamine neurons make an important contribution to circuits mediating motivation and movement. Understanding the basic rules that govern the electrical activity of single dopaminergic neurons is therefore essential to reveal how they ultimately contribute to movement and motivation as well as what goes wrong in associated disorders. Our computational study focuses on the generation and propagation of action potentials and shows that different morphologies and excitability characteristics of the cell body, dendrites and proximal axon can explain the diversity of action potentials shapes in this population. These compartments likely make differential contributions both to normal dopaminergic signaling and could potentially underlie pathological dopaminergic signaling implicated in addiction, schizophrenia, Parkinson's disease, and other disorders.

Contribution of the Axon Initial Segment to Action Potentials Recorded Extracellularly

Action potentials (APs) are electric phenomena that are recorded both intracellularly and extracellularly. APs are usually initiated in the short segment of the axon called the axon initial segment (AIS). It was recently proposed that at the onset of an AP the soma and the AIS form a dipole. We study the extracellular signature [the extracellular AP (EAP)] generated by such a dipole. First, we demonstrate the formation of the dipole and its extracellular signature in detailed morphological models of a reconstructed pyramidal neuron. Then, we study the EAP waveform and its spatial dependence in models with axonal AP initiation and contrast it with the EAP obtained in models with somatic AP initiation. We show that in the models with axonal AP initiation the dipole forms between somatodendritic compartments and the AIS, and not between soma and dendrites as in the classical models. The soma-dendrites dipole is present only in models with somatic AP initiation. Our study has consequences for interpreting extracellular recordings of single-neuron activity and determining electrophysiological neuron types, but also for better understanding the origins of the high-frequency macroscopic extracellular potentials recorded in the brain.

Refractoriness Accounts for Variable Spike Burst Responses in Somatosensory Cortex

Neurons in the primary somatosensory cortex (S1) respond to peripheral stimulation with synchronized bursts of spikes, which lock to the macroscopic 600-Hz EEG waves. The mechanism of burst generation and synchronization in S1 is not yet understood. Using models of single-neuron responses fitted to unit recordings from macaque monkeys, we show that these synchronized bursts are the consequence of correlated synaptic inputs combined with a refractory mechanism. In the presence of noise these models reproduce also the observed trial-to-trial response variability, where individual bursts represent one of many stereotypical temporal spike patterns. When additional slower and global excitability fluctuations are introduced the single-neuron spike patterns are correlated with the population activity, as demonstrated in experimental data. The underlying biophysical mechanism of S1 responses involves thalamic inputs arriving through depressing synapses to cortical neurons in a high-conductance state. Our findings show that a simple feedforward processing of peripheral inputs could give rise to neuronal responses with nontrivial temporal and population statistics. We conclude that neural systems could use refractoriness to encode variable cortical states into stereotypical short-term spike patterns amenable to processing at neuronal time scales (tens of milliseconds).

Magnitude and behavior of cross-talk effects in multichannel electrophysiology experiments

Modern neurophysiological experiments frequently involve multiple channels separated by very small distances. A unique methodological concern for multiple-electrode experiments is that of capacitive coupling (cross-talk) between channels. Yet the nature of the cross-talk recording circuit is not well known in the field, and the extent to which it practically affects neurophysiology experiments has never been fully investigated. Here we describe a simple electrical circuit model of simultaneous recording and stimulation with two or more channels and experimentally verify the model using ex vivo brain slice and in vivo whole-brain preparations. In agreement with the model, we find that cross-talk amplitudes increase nearly linearly with the impedance of a recording electrode and are larger for higher frequencies. We demonstrate cross-talk contamination of action potential waveforms from intracellular to extracellular channels, which is observable in part because of the different orders of magnitude between the channels. This contamination is electrode impedance-dependent and matches predictions from the model. We use recently published parameters to simulate cross-talk in high-density multichannel extracellular recordings. Cross-talk effectively spatially smooths current source density (CSD) estimates in these recordings and induces artefactual phase shifts where underlying voltage gradients occur; however, these effects are modest. We show that the effects of cross-talk are unlikely to affect most conclusions inferred from neurophysiology experiments when both originating and receiving electrode record signals of similar magnitudes. We discuss other types of experiments and analyses that may be susceptible to cross-talk, techniques for detecting and experimentally reducing cross-talk, and implications for high-density probe design.NEW & NOTEWORTHY We develop and experimentally verify an electrical circuit model describing cross-talk that necessarily occurs between two channels. Recorded cross-talk increased with electrode impedance and signal frequency. We recorded cross-talk contamination of spike waveforms from intracellular to extracellular channels. We simulated high-density multichannel extracellular recordings and demonstrate spatial smoothing and phase shifts that cross-talk enacts on CSD measurements. However, when channels record similar-magnitude signals, effects are modest and unlikely to affect most conclusions.

Local field potentials primarily reflect inhibitory neuron activity in human and monkey cortex

The local field potential (LFP) is generated by large populations of neurons, but unitary contribution of spiking neurons to LFP is not well characterised. We investigated this contribution in multi-electrode array recordings from human and monkey neocortex by examining the spike-triggered LFP average (st-LFP). The resulting st-LFPs were dominated by broad spatio-temporal components due to ongoing activity, synaptic inputs and recurrent connectivity. To reduce the spatial reach of the st-LFP and observe the local field related to a single spike we applied a spatial filter, whose weights were adapted to the covariance of ongoing LFP. The filtered st-LFPs were limited to the perimeter of 800 μm around the neuron, and propagated at axonal speed, which is consistent with their unitary nature. In addition, we discriminated between putative inhibitory and excitatory neurons and found that the inhibitory st-LFP peaked at shorter latencies, consistently with previous findings in hippocampal slices. Thus, in human and monkey neocortex, the LFP reflects primarily inhibitory neuron activity.

Dipolar extracellular potentials generated by axonal projections

Extracellular field potentials (EFPs) are an important source of information in neuroscience, but their physiological basis is in many cases still a matter of debate. Axonal sources are typically discounted in modeling and data analysis because their contributions are assumed to be negligible. Here, we established experimentally and theoretically that contributions of axons to EFPs can be significant. Modeling action potentials propagating along axons, we showed that EFPs were prominent in the presence of terminal zones where axons branch and terminate in close succession, as found in many brain regions. Our models predicted a dipolar far field and a polarity reversal at the center of the terminal zone. We confirmed these predictions using EFPs from the barn owl auditory brainstem where we recorded in nucleus laminaris using a multielectrode array. These results demonstrate that axonal terminal zones can produce EFPs with considerable amplitude and spatial reach.

Acute Exposure to Pacific Ciguatoxin Reduces Electroencephalogram Activity and Disrupts Neurotransmitter Metabolic Pathways in Motor Cortex

Ciguatera fish poisoning (CFP) is a common human food poisoning caused by consumption of ciguatoxin (CTX)-contaminated fish affecting over 50,000 people worldwide each year. CTXs are classified depending on their origin from the Pacific (P-CTXs), Indian Ocean (I-CTXs), and Caribbean (C-CTXs). P-CTX-1 is the most toxic CTX known and the major source of CFP causing an array of neurological symptoms. Neurological symptoms in some CFP patients last for several months or years; however, the underlying electrophysiological properties of acute exposure to CTXs remain unknown. Here, we used CTX purified from ciguatera fish sourced in the Pacific Ocean (P-CTX-1). Delta and theta electroencephalography (EEG) activity was reduced remarkably in 2 h and returned to normal in 6 h after a single exposure. However, second exposure to P-CTX-1 induced not only a further reduction in EEG activities but also a 2-week delay in returning to baseline EEG values. Ciguatoxicity was detected in the brain hours after the first and second exposure by mouse neuroblastoma assay. The spontaneous firing rate of single motor cortex neuron was reduced significantly measured by single-unit recording with high spatial resolution. Expression profile study of neurotransmitters using targeted profiling approach based on liquid chromatography-tandem mass spectrometry revealed an imbalance between excitatory and inhibitory neurotransmitters in the motor cortex. Our study provides a possible link between the brain oscillations and neurotransmitter release after acute exposure to P-CTX-1. Identification of EEG signatures and major metabolic pathways affected by P-CTX-1 provides new insight into potential biomarker development and therapeutic interventions.

Homeostatic dynamics, hysteresis and synchronization in a low-dimensional model of burst suppression

Burst suppression, a pattern of the electroencephalogram characterized by quasi-periodic alternation of high-voltage activity (burst) and isoelectric silence (suppression), is typically associated with states of unconsciousness, such as in deep general anesthesia and certain etiologies of coma. Recent computational models for burst suppression have attributed the slow (up to tens of seconds) time-scale of burst termination and re-initiation to cycling in supportive physiological process, such as cerebral metabolism. That is, activity-dependent substrate ('energy') depletion during bursts, followed by substrate recovery during suppression. Such a model falls into the category of a fast-slow dynamical system, commonly used to describe neuronal bursting more generally. Here, following this basic paradigm, we develop a low dimensional mean field model for burst suppression that adds several new features and capabilities to previous models. Most notably, this new model includes explicit homeostatic interactions wherein the rates of substrate recovery are tied to neuronal activity in a supply demand loop, creating a physiologically consistent, reciprocal interaction between the neural and substrate processes. We develop formal analysis of the model dynamics, showing, in particular, the capability of the model to produce burst-like activity as a consequence of neuronal downregulation only, without any direct perturbation to the substrate dynamics. Further, we use a synchronization analysis to contrast different mechanisms for spatially local versus global bursting. The analysis performed generates characterizations that are consistent with experimental observations of spatiotemporal features such as burst onset, duration, and spatial organization and, moreover, generates predictions regarding the presence of bistability and hysteresis in the underlying system. Thus, the model provides new dynamical insight into the mechanisms of burst suppression and, moreover, a tractable platform for more detailed future characterizations.

Toward Deep Brain Monitoring with Superficial EEG Sensors Plus Neuromodulatory Focused Ultrasound

Noninvasive recordings of electrophysiological activity have limited anatomic specificity and depth. We hypothesized that spatially tagging a small volume of brain with a unique electroencephalography (EEG) signal induced by pulsed focused ultrasound could overcome those limitations. As a first step toward testing this hypothesis, we applied transcranial ultrasound (2 MHz, 200-ms pulses applied at 1050 Hz for 1 s at a spatial peak temporal average intensity of 1.4 W/cm(2)) to the brains of anesthetized rats while simultaneously recording EEG signals. We observed a significant 1050-Hz electrophysiological signal only when ultrasound was applied to a living brain. Moreover, amplitude demodulation of the EEG signal at 1050 Hz yielded measurement of gamma band (>30 Hz) brain activity consistent with direct measurements of that activity. These results represent preliminary support for use of pulsed focused ultrasound as a spatial tagging mechanism for non-invasive EEG-based mapping of deep brain activity with high spatial resolution.

Millisecond Coupling of Local Field Potentials to Synaptic Currents in the Awake Visual Cortex

The cortical local field potential (LFP) is a common measure of population activity, but its relationship to synaptic activity in individual neurons is not fully established. This relationship has been typically studied during anesthesia and is obscured by shared slow fluctuations. Here, we used patch-clamp recordings in visual cortex of anesthetized and awake mice to measure intracellular activity; we then applied a simple method to reveal its coupling to the simultaneously recorded LFP. LFP predicted membrane potential as accurately as synaptic currents, indicating a major role for synaptic currents in the relationship between cortical LFP and intracellular activity. During anesthesia, cortical LFP predicted excitation far better than inhibition; during wakefulness, it predicted them equally well, and visual stimulation further enhanced predictions of inhibition. These findings reveal a central role for synaptic currents, and especially inhibition, in the relationship between the subthreshold activity of individual neurons and the cortical LFP during wakefulness.

Detectability of the somatosensory evoked high frequency oscillation (HFO) co-recorded by scalp EEG and ECoG under propofol

Objective

The somatosensory evoked potential (SEP) elicited by median nerve stimulation consists of the N20 peak together with the concurrent high frequency oscillation (HFO, > 500 Hz). We describe the conditions for HFO detection in ECoG and scalp EEG in intraoperative recordings.

Methods

During neurosurgical interventions in six patients under propofol anesthesia, the SEP was recorded from subdural electrode strips (15 recordings) and from scalp electrodes (10/15 recordings). We quantified the spatial attenuation of the Signal-to-Noise Ratio (SNR) of N20 and HFO along the contacts of the electrode strip. We then compared the SNR of ECoG and simultaneous scalp EEG in a biophysical framework.

Results

HFO detection under propofol anesthesia was demonstrated. Visual inspection of strip cortical recordings revealed phase reversal for N20 in 14/15 recordings and for HFO in 10/15 recordings. N20 had higher maximal SNR (median 33.5 dB) than HFO (median 23 dB). The SNR of N20 attenuated with a larger spatial extent (median 7.2 dB/cm) than the SNR of HFO (median 12.3 dB/cm). We found significant correlations between the maximum SNR (rho = 0.58, p = 0.025) and the spatial attenuation (rho = 0.86, p < 0.001) of N20 and HFO. In 3/10 recordings we found HFO in scalp EEG. Based on the spatial attenuation and SNR in the ECoG, we estimated the scalp EEG amplitude ratio N20/HFO and found significant correlation with recorded values (rho = 0.65, p = 0.049).

Conclusions

We proved possible the intraoperative SEP HFO detection under propofol anesthesia. The spatial attenuation along ECoG contacts represents a good estimator of the area contributing to scalp EEG. The SNR and the spatial attenuation in ECoG recordings provide further insights for the prediction of HFO detectability in scalp EEG. The results obtained in this context may not be limited to SEP HFO, but could be generalized to biological signatures lying in the same SNR and frequency range.

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Somatosensory evoked HFOs can be recorded in ECoG and scalp EEG intraoperatively under propofol anesthesia.

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The HFO amplitude in ECoG attenuated to noise level over a smaller spatial scale than the N20 amplitude.

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The spatial attenuation of the cortical SNR directly relates to the noise level and to the scalp EEG amplitude.

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Parameters extracted from ECoG allowed estimating the ratio of N20/HFO amplitude in scalp EEG.