LFP publications

Purpose: High‐frequency oscillations (HFOs) are an emerging biomarker for epileptic tissue. Yet the mechanism by which HFOs are produced is unknown, and their rarity makes them difficult to study. Our objective was to examine the occurrence of HFOs in relation to action potentials (APs) and the effect of microstimulation in the tetanus toxin (TT) model of epilepsy, a nonlesional model with a short latency to spontaneous seizures. Methods: Rats were injected with TT into dorsal hippocampus and implanted with a 16‐channel (8 × 2) multielectrode array, one row each in CA3 and CA1. After onset of spontaneous seizures (3–9 days), recordings were begun of APs and local field potentials, analyzed for the occurrence of interictal spikes and HFOs. Recordings were made during microstimulation of each electrode using customized, open‐source software. Results: Population bursts of APs during interictal spikes were phase‐locked with HFOs, which were observable almost exclusively with high‐amplitude interictal spikes. Furthermore, HFOs could reliably be produced by microstimulation of the hippocampus, providing evidence that these oscillations can be controlled temporally by external means. Discussion: We show for the first time the occurrence of HFOs in the TT epilepsy model, an attractive preparation for their experimental investigation and, importantly, one with a different etiology than that of status models, providing further evidence of the generality of HFOs. The ability to provoke HFOs with microstimulation may prove useful for better understanding of HFOs by directly evoking them in the lab, and designing high‐throughput techniques for presurgical localization of the epileptic focus.

The local field potential (LFP) and multiunit activity (MUA) are extracellularly recorded signals that describe local neuronal network dynamics. In our experiments, the LFP and MUA, recorded from the same electrode in macaque primary visual cortex V1 in response to drifting grating visual stimuli, were evaluated on coarse timescales (∼1–5 s) and fine timescales (<0.1 s). On coarse timescales, MUA and the LFP both produced sustained visual responses to optimal and non-optimal oriented visual stimuli. The sustainedness of the two signals across the population of recording sites was correlated (correlation coefficient, ∼0.4). At most recording sites, the MUA was at least as sustained as the LFP and significantly more sustained for optimal orientations. In previous literature, the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging studies was found to be more strongly correlated with the LFP than with the MUA as a result of the lack of sustained response in the MUA signal. Because we found that MUA was as sustained as the LFP, MUA may also be correlated with BOLD. On fine timescales, we computed the coherence between the LFP and MUA over the frequency range 10–150 Hz. The LFP and MUA were weakly but significantly coherent (∼0.14) in the gamma band (20–90 Hz). The amount of gamma-band coherence was correlated with the power in the gamma band of the LFP. The data were consistent with the proposal that the LFP and MUA are generated in a noisy, resonant cortical network.

Consistent with human perceptual data, we found many more black-dominant than white-dominant responses in layer 2/3 neurons of the macaque primary visual cortex (V1). Seeking the mechanism of this black dominance of layer 2/3 neurons, we measured the laminar pattern of population responses (multiunit activity and local field potential) and found that a small preference for black is observable in early responses in layer 4Cβ, the parvocellular-input layer, but not in the magnocellular-input layer 4Cα. Surprisingly, further analysis of the dynamics of black-white responses in layers 4Cβ and 2/3 suggested that black-dominant responses in layer 2/3 were not generated simply because of the weak black-dominant inputs from 4Cβ. Instead, our results indicated the neural circuitry in V1 is wired with a preference to strengthen black responses. We hypothesize that this selective wiring could be due to (1) feedforward connectivity from black-dominant neurons in layer 4C to cells in layer 2/3 or (2) recurrent interactions between black-dominant neurons in layer 2/3, or a combination of both.

A popular model of binaural processing, proposed by Jeffress (1948), states that external interaural time delays (ITDs) are compensated by internal axonal delays allowing ITD to be spatially represented by a population of coincidence detectors in the medial superior olive (MSO). Isolating single-neuron responses in MSO is difficult because of the presence of a strong extracellular field potential known as the neurophonic, so that few studies have tested Jeffress's key prediction. Phase delays in the nucleus laminaris neurophonic in owls have been observed and are consistent with a Jeffress-like model. Here, we recorded neurophonic responses in cat MSO to monaural tones at locations along its dendritic axis. Fourier analysis of the neurophonic was used to extract amplitude and phase at the stimulus frequency. Amplitude, as a function of depth, showed two peaks separated by a dip. A half-cycle phase shift was observed at depths close to the dip, over a wide frequency range. Current source density analysis for contralateral (ipsilateral) stimulation shows a current source close to the neurophonic amplitude peak and a sink a few hundred micrometers ventromedially (dorsolaterally). These results are consistent with a dipole configuration: contralateral (ipsilateral) excitation causes a current sink at the ventromedial (dorsolateral) dendrites and a source at the soma and dorsolateral (ventromedial) dendrites. Incorporating these results in a dipole model explains the phase and amplitude patterns observed. We conclude that the half-cycle phase shift is consistent with a current dipole, making it difficult to derive measurements of axonal delays from the neurophonic.

The neurophonic is a sound-evoked, frequency-following potential that can be recorded extracellularly in nucleus laminaris of the barn owl. The origin of the neurophonic, and thus the mechanisms that give rise to its exceptional temporal precision, has not yet been identified. Putative generators of the neurophonic are the activity of afferent axons, synaptic activation of laminaris neurons, or action potentials in laminaris neurons. To identify the generators, we analyzed the neurophonic in the high-frequency (>2.5 kHz) region of nucleus laminaris in response to monaural pure-tone stimulation. The amplitude of the neurophonic is typically in the millivolt range. The signal-to-noise ratio reaches values beyond 30 dB. To assess which generators could give rise to these large, synchronous extracellular potentials, we developed a computational model. Spike trains were produced by an inhomogeneous Poisson process and convolved with a spike waveform. The model explained the dependence of the simulated neurophonic on parameters such as the mean rate, the vector strength of phase locking, the number of statistically independent sources, and why the signal-to-noise ratio is independent of the spike waveform and subsequent filtering of the signal. We found that several hundred sources are needed to reach the observed signal-to-noise ratio. The summed coherent signal from the densely packed afferent axons and activation of their synapses on laminaris neurons are alone sufficient to explain the measured properties of the neurophonic.

Multiple extracellular microelectrodes (multi-electrode arrays, or MEAs) effectively record rapidly varying neural signals, and can also be used for electrical stimulation. Multi-electrode recording can serve as artificial output (efferents) from a neural system, while complex spatially and temporally targeted stimulation can serve as artificial input (afferents) to the neuronal network. Multi-unit or local field potential (LFP) recordings can not only be used to control real world artifacts, such as prostheses, computers or robots, but can also trigger or alter subsequent stimulation. Real-time feedback stimulation may serve to modulate or normalize aberrant neural activity, to induce plasticity, or to serve as artificial sensory input. Despite promising closed-loop applications, commercial electrophysiology systems do not yet take advantage of the bidirectional capabilities of multi-electrodes, especially for use in freely moving animals. We addressed this lack of tools for closing the loop with NeuroRighter, an open-source system including recording hardware, stimulation hardware, and control software with a graphical user interface. The integrated system is capable of multi-electrode recording and simultaneous patterned microstimulation (triggered by recordings) with minimal stimulation artifact. The potential applications of closed-loop systems as research tools and clinical treatments are broad; we provide one example where epileptic activity recorded by a multi-electrode probe is used to trigger targeted stimulation, via that probe, to freely moving rodents.

Primary sensory cortex integrates sensory information from afferent feedforward thalamocortical projection systems and convergent intracortical microcircuits. Both input systems have been demonstrated to provide different aspects of sensory information. Here we have used high-density recordings of laminar current source density (CSD) distributions in primary auditory cortex of Mongolian gerbils in combination with pharmacological silencing of cortical activity and analysis of the residual CSD, to dissociate the feedforward thalamocortical contribution and the intracortical contribution to spectral integration. We found a temporally highly precise integration of both types of inputs when the stimulation frequency was in close spectral neighborhood of the best frequency of the measurement site, in which the overlap between both inputs is maximal. Local intracortical connections provide both directly feedforward excitatory and modulatory input from adjacent cortical sites, which determine how concurrent afferent inputs are integrated. Through separate excitatory horizontal projections, terminating in cortical layers II/III, information about stimulus energy in greater spectral distance is provided even over long cortical distances. These projections effectively broaden spectral tuning width. Based on these data, we suggest a mechanism of spectral integration in primary auditory cortex that is based on temporally precise interactions of afferent thalamocortical inputs and different short- and long-range intracortical networks. The proposed conceptual framework allows integration of different and partly controversial anatomical and physiological models of spectral integration in the literature.

Cave fish have rarely been investigated with regard to their inner ear morphology, hearing abilities, and acoustic communication. Based on a previous study that revealed morphological differences in the saccular otolith between a cave and two surface populations of Poecilia mexicana, we checked for additional differences in utricular and lagenar otoliths and tested whether different populations have similar hearing sensitivities. We found pronounced differences in the shape of all three otoliths. Otoliths of the saccule and lagena from cave fish differed from those of surface fish in the features of the face oriented towards the sensory epithelium. In addition, otoliths of the utricle and lagena were significantly heavier in cave fish. Auditory sensitivities were measured between 100 and 1500Hz, utilizing the auditory evoked potential recording technique. We found similar hearing abilities in cave and surface fish, with greatest sensitivity between 200 and 300Hz. An acoustic survey revealed that neither ecotype produced species-specific sounds. Our data indicate that cave dwelling altered the otolith morphology in Atlantic mollies, probably due to metabolic differences. Different otolith morphology, however, did not affect general auditory sensitivity or acoustic behavior.

An understanding of the in vivo spatial emergence of abnormal brain activity during spontaneous seizure onset is critical to future early seizure detection and closed-loop seizure prevention therapies. In this study, we use Granger causality (GC) to determine the strength and direction of relationships between local field potentials (LFPs) recorded from bilateral microelectrode arrays in an intermittent spontaneous seizure model of chronic temporal lobe epilepsy before, during, and after Racine grade partial onset generalized seizures. Our results indicate distinct patterns of directional GC relationships within the hippocampus, specifically from the CA1 subfield to the dentate gyrus, prior to and during seizure onset. Our results suggest sequential and hierarchical temporal relationships between the CA1 and dentate gyrus within and across hippocampal hemispheres during seizure. Additionally, our analysis suggests a reversal in the direction of GC relationships during seizure, from an abnormal pattern to more anatomically expected pattern. This reversal correlates well with the observed behavioral transition from tonic to clonic seizure in time-locked video. These findings highlight the utility of GC to reveal dynamic directional temporal relationships between multichannel LFP recordings from multiple brain regions during unprovoked spontaneous seizures.

Recent studies demonstrate that mosquitoes listen to each other's wing beats just prior to mating in flight. Field potentials from sound-transducing neurons in the antennae contain both sustained and oscillatory components to pure and paired tone stimuli. Described here is a direct comparison of these two types of response in the dengue vector mosquito, Aedes aegypti. Across a wide range of frequencies and intensities, sustained responses to one- and two-tone stimuli are about equal in magnitude to oscillatory responses to the beats produced by two-tone stimuli. All of these responses are much larger than the oscillatory responses to one-tone stimuli. Similarly, the frequency range extends up to at least the fifth harmonic of the male flight tone for sustained responses to one- and two-tone stimuli and oscillatory responses at the beat frequency of two-tone stimuli, whereas the range of oscillatory response to a one-tone stimulus is limited to, at most, the third harmonic. Thresholds near the fundamental of the flight tone are lower for oscillatory responses than for sustained deflections, lower for males than for females, and within the behaviorally relevant range. A simple model of the transduction process can qualitatively account for both oscillatory and sustained responses to pure and paired tones. These data leave open the question as to which of several alternative strategies underlie flight tone matching behavior in mosquitoes.

During anesthesia, slow-wave sleep and quiet wakefulness, neuronal membrane potentials collectively switch between de- and hyperpolarized levels, the cortical UP and DOWN states. Previous studies have shown that these cortical UP/DOWN states affect the excitability of individual neurons in response to sensory stimuli, indicating that a significant amount of the trial-to-trial variability in neuronal responses can be attributed to ongoing fluctuations in network activity. However, as intracellular recordings are frequently not available, it is important to be able to estimate their occurrence purely from extracellular data. Here, we combine in vivo whole cell recordings from single neurons with multi-site extracellular microelectrode recordings, to quantify the performance of various approaches to predicting UP/DOWN states from the deep-layer local field potential (LFP). We find that UP/DOWN states in deep cortical layers of rat primary auditory cortex (A1) are predictable from the phase of LFP at low frequencies (< 4 Hz), and that the likelihood of a given state varies sinusoidally with the phase of LFP at these frequencies. We introduce a novel method of detecting cortical state by combining information concerning the phase of the LFP and ongoing multi-unit activity.

Brain-machine interfaces (BMIs) use signals recorded directly from the brain to control an external device, such as a computer cursor or a prosthetic limb. These control signals have been recorded from different levels of the brain, from field potentials at the scalp or cortical surface to single neuron action potentials. At present, the more invasive recordings have better signal quality, but also lower stability over time. Recently, subdural field potentials have been proposed as a stable, good quality source of control signals, with the potential for higher spatial and temporal bandwidth than EEG. Here we used finite element modeling in rats and humans and spatial spectral analysis in rats to compare the spatial resolution of signals recorded epidurally (outside the dura), with those recorded from subdural and scalp locations. Resolution of epidural and subdural signals was very similar in rats and somewhat less so in human models. Both were substantially better than signals recorded at the scalp. Resolution of epidural and subdural signals in humans was much more similar when the cerebrospinal fluid layer thickness was reduced. This suggests that the less invasive epidural recordings may yield signals of similar quality to subdural recordings, and hence may be more attractive as a source of control signals for BMIs.

The rapidly increasing use of the local field potential (LFP) has motivated research to better understand its relation to the gold standard of neural activity, single unit (SU) spiking. We addressed this in an in vivo, awake, restrained mouse auditory cortical electrophysiology preparation by asking whether the LFP could actually be used to predict stimulus-evoked SU spiking. Implementing a Bayesian algorithm to predict the likelihood of spiking on a trial by trial basis from different representations of the despiked LFP signal, we were able to predict, with high quality and fine temporal resolution (2 ms), the time course of a SU's excitatory or inhibitory firing rate response to natural species-specific vocalizations. Our best predictions were achieved by representing the LFP by its wide-band Hilbert phase signal, and approximating the statistical structure of this signal at different time points as independent. Our results show that each SU's action potential has a unique relationship with the LFP that can be reliably used to predict the occurrence of spikes. This "signature" interaction can reflect both pre- and post-spike neural activity that is intrinsic to the local circuit rather than just dictated by the stimulus. Finally, the time course of this "signature" may be most faithful when the full bandwidth of the LFP, rather than specific narrow-band components, is used for representation.

In analyzing neurophysiologic data, individual experimental trials are usually assumed to be statistically independent. However, many studies employing functional imaging and electrophysiology have shown that brain activity during behavioral tasks includes temporally correlated trial-to-trial fluctuations. This could lead to spurious results in statistical significance tests used to compare data from different interleaved behavioral conditions presented throughout an experiment. We characterize trial-to-trial fluctuations in local field potentials recorded from the frontal cortex of a macaque monkey performing an oculomotor delayed response task. Our analysis identifies slow fluctuations (<0.1 Hz) of spectral power in 22/27 recording sessions. These trial-to-trial fluctuations are non-Gaussian, and call into question the statistical utility of standard trial shuffling. We compare our results with evidence for slow fluctuations in human functional imaging studies and other electrophysiologic studies in nonhuman primates.

Changes in the sensory environment are good indicators for behaviorally relevant events and strong triggers for the reallocation of attention. In the auditory domain, violations of a pattern of repetitive stimuli precipitate in the event-related potentials as mismatch negativity (MMN). Stimulus-specific adaptation (SSA) of single neurons in the auditory cortex has been proposed to be the cellular substrate of MMN (Nelken and Ulanovsky, 2007). However, until now, the existence of SSA in the awake auditory cortex has not been shown. In the present study, we recorded single and multiunits in parallel with evoked local field potentials ( e LFPs) in the primary auditory cortex of the awake rat. Both neurons and e LFPs in the awake animal adapted in a stimulus-specific manner, and SSA was controlled by stimulus probability and frequency separation. SSA of isolated units was significant during the first stimulus-evoked “on” response but not in the following inhibition and rebound of activity. The e LFPs exhibited SSA in the first negative deflection and, to a lesser degree, in a slower positive deflection but no MMN. Spike adaptation correlated closely with adaptation of the fast negative deflection but not the positive deflection. Therefore, we conclude that single neurons in the auditory cortex of the awake rat adapt in a stimulus-specific manner and contribute to corresponding changes in e LFP but do not generate a late deviant response component directly equivalent to the human MMN. Nevertheless, the described effect may reflect a certain part of the process needed for sound discrimination.

A fundamental organizational principle of the primate motor system is cortical control of contralateral limb movements. Motor areas also appear to play a role in the control of ipsilateral limb movements. Several studies in monkeys have shown that individual neurons in primary motor cortex (M1) may represent, on average, the direction of movements of the ipsilateral arm. Given the increasing body of evidence demonstrating that neural ensembles can reliably represent information with a high temporal resolution, here we characterize the distributed neural representation of ipsilateral upper limb kinematics in both monkey and man. In two macaque monkeys trained to perform center-out reaching movements, we found that the ensemble spiking activity in M1 could continuously represent ipsilateral limb position. Interestingly, this representation was more correlated with joint angles than hand position. Using bilateral electromyography recordings, we excluded the possibility that postural or mirror movements could exclusively account for these findings. In addition, linear methods could decode limb position from cortical field potentials in both monkeys. We also found that M1 spiking activity could control a biomimetic brain–machine interface reflecting ipsilateral kinematics. Finally, we recorded cortical field potentials from three human subjects and also consistently found evidence of a neural representation for ipsilateral movement parameters. Together, our results demonstrate the presence of a high-fidelity neural representation for ipsilateral movement and illustrates that it can be successfully incorporated into a brain–machine interface.

Background: The giant synapses of Held play an important role in high-fidelity auditory processing and provide a model system for synaptic transmission at central synapses. Whether transmission of action potentials can fail at these synapses has been investigated in recent studies. At the endbulbs of Held in the anteroventral cochlear nucleus (AVCN) a consistent picture emerged, whereas at the calyx of Held in the medial nucleus of the trapezoid body (MNTB) results on the reliability of transmission remain inconsistent. In vivo this discrepancy could be due to the difficulty in identifying failures of transmission. Methods/findings: We introduce a novel method for detecting unreliable transmission in vivo. Based on the temporal relationship between a cells' waveform and other potentials in the recordings, a statistical test is developed that provides a balanced decision between the presence and the absence of failures. Its performance is quantified using simulated voltage recordings and found to exhibit a high level of accuracy. The method was applied to extracellular recordings from the synapses of Held in vivo. At the calyces of Held failures of transmission were found only rarely. By contrast, at the endbulbs of Held in the AVCN failures were found under spontaneous, excited, and suppressed conditions. In accordance with previous studies, failures occurred most abundantly in the suppressed condition, suggesting a role for inhibition. Conclusions/significance: Under the investigated activity conditions/anesthesia, transmission seems to remain largely unimpeded in the MNTB, whereas in the AVCN the occurrence of failures is related to inhibition and could be the basis/result of computational mechanisms for temporal processing. More generally, our approach provides a formal tool for studying the reliability of transmission with high statistical accuracy under typical in vivo recording conditions.

We developed a new method to estimate the spatial extent of summation, the cortical spread, of the local field potential (LFP) throughout all layers of macaque primary visual cortex V1 by taking advantage of the V1 retinotopic map. We mapped multi-unit activity and LFP visual responses with sparse-noise at several cortical sites simultaneously. The cortical magnification factor near the recording sites was precisely estimated by track reconstruction. The new method combined experimental measurements together with a model of signal summation to obtain the cortical spread of the LFP. This new method could be extended to cortical areas that have topographic maps such as S1 or A1, and to cortical areas without functional columnar maps, such as rodent visual cortex. In macaque V1, the LFP was the sum of signals from a very local region, the radius of which was on average 250 μm. The LFP's cortical spread varied across cortical layers, reaching a minimum value of 120 μm in layer 4B. An important functional consequence of the small cortical spread of the LFP is that the visual field maps of LFP and MUA recorded at a single electrode site were very similar. The similar spatial scale of the visual responses, the restricted cortical spread, and their laminar variation led to new insights about the sources and possible applications of the LFP.

Recent findings have revealed the importance of orthonasal and retronasal olfaction in food memory, especially in conditioned odor aversion (COA); however, little is known about the dynamics of the cerebral circuit involved in the recognition of an odor as a toxic food signal and whether the activated network depends on the way (orthonasal vs retronasal) the odor was first experienced. In this study, we mapped the modulations of odor-induced oscillatory activities through COA learning using multisite recordings of local field potentials in behaving rats. During conditioning, orthonasal odor alone or associated with ingested odor was paired with immediate illness. For all animals, COA retrieval was assessed by orthonasal smelling only. Both types of conditioning induced similarly strong COA. Results pointed out (1) a predictive correlation between the emergence of powerful beta (15–40 Hz) activity and the behavioral expression of COA and (2) a differential network distribution of this beta activity according to the way the animals were exposed to the odor during conditioning. Indeed, for both types of conditioning, the aversive behavior was predicted by the emergence of a strong beta oscillatory activity in response to the odor in the olfactory bulb, piriform cortex, orbitofrontal cortex, and basolateral amygdala. This network was selectively extended to the infralimbic and insular cortices when the odor was ingested during acquisition. These differential networks could participate in different food odor memory; these results are discussed in line with recent behavioral results that indicate that COA can be formed over long odor-illness delays only if the odor is ingested.

Object Control signals for brain-machine interfaces may be obtained from a variety of sources, each with their own relative merits. Electrocorticography (ECoG) provides better spatial and spectral resolution than scalp electroencephalography and does not include the risks attendant upon penetration of the brain parenchyma associated with single and multiunit recordings. For these reasons, subdural electrode recordings have been proposed as useful primary or adjunctive control signals for brain-machine interfaces. The goal of the present study was to determine if 2D control signals could be decoded from ECoG. Methods Six patients undergoing invasive monitoring for medically intractable epilepsy using subdural grid electrodes were asked to perform a motor task involving moving a joystick in 1 of 4 cardinal directions (up, down, left, or right) and a fifth condition (“trigger”). Evoked activity was synchronized to joystick movement and analyzed in the theta, alpha, beta, gamma, and high-gamma frequency bands. Results Movement-related cortical potentials could be accurately differentiated from rest with very high accuracy (83–96%). Further distinguishing the movement direction (up, down, left, or right) could also be resolved with high accuracy (58–86%) using information only from the high-gamma range, whereas distinguishing the trigger condition from the remaining directions provided better accuracy. Conclusions Two-dimensional control signals can be derived from ECoG. Local field potentials as measured by ECoG from subdural grids will be useful as control signals for a brain-machine interface.