Local Field Potential Frequency Research Articles

Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease: ADAPT-PD clinical trial methodology and early data (P1-11.002)

Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease: ADAPT-PD clinical trial methodology and early data (P1-11.002)

Extracting synchronized neuronal activity from local field potentials based on a marked point process framework

Objective. Brain-machine interfaces (BMIs) translate neural activity into motor commands to restore motor functions for people with paralysis. Local field potentials (LFPs) are promising for long-term BMIs, since the quality of the recording lasts longer than single neuronal spikes. Inferring neuronal spike activity from population activities such as LFPs is challenging, because LFPs stem from synaptic currents flowing in the neural tissue produced by various neuronal ensembles and reflect neural synchronization. Existing studies that combine LFPs with spikes leverage the spectrogram of the former, which can neither detect the transient characteristics of LFP features (here, neuromodulation in a specific frequency band) with high accuracy, nor correlate them with relevant neuronal activity with a sufficient time resolution. Approach. We propose a feature extraction and validation framework to directly extract LFP neuromodulations related to synchronized spike activity using recordings from the primary motor cortex of six Sprague Dawley rats during a lever-press task. We first select important LFP frequency bands relevant to behavior, and then implement a marked point process (MPP) methodology to extract transient LFP neuromodulations. We validate the LFP feature extraction by examining the correlation with the pairwise synchronized firing probability of important neurons, which are selected according to their contribution to behavioral decoding. The highly correlated synchronized firings identified by the LFP neuromodulations are fed into a decoder to check whether they can serve as a reliable neural data source for movement decoding. Main results. We find that the gamma band (30–80 Hz) LFP neuromodulations demonstrate significant correlation with synchronized firings. Compared with traditional spectrogram-based method, the higher-temporal resolution MPP method captures the synchronized firing patterns with fewer false alarms, and demonstrates significantly higher correlation than single neuron spikes. The decoding performance using the synchronized neuronal firings identified by the LFP neuromodulations can reach 90% compared to the full recorded neuronal ensembles. Significance. Our proposed framework successfully extracts the sparse LFP neuromodulations that can identify temporal synchronized neuronal spikes with high correlation. The identified neuronal spike pattern demonstrates high decoding performance, which suggest LFP can be used as an effective modality for long-term BMI decoding.

Prefrontal cortical plasticity during learning of cognitive tasks

Training in working memory tasks is associated with lasting changes in prefrontal cortical activity. To assess the neural activity changes induced by training, we recorded single units, multi-unit activity (MUA) and local field potentials (LFP) with chronic electrode arrays implanted in the prefrontal cortex of two monkeys, throughout the period they were trained to perform cognitive tasks. Mastering different task phases was associated with distinct changes in neural activity, which included recruitment of larger numbers of neurons, increases or decreases of their firing rate, changes in the correlation structure between neurons, and redistribution of power across LFP frequency bands. In every training phase, changes induced by the actively learned task were also observed in a control task, which remained the same across the training period. Our results reveal how learning to perform cognitive tasks induces plasticity of prefrontal cortical activity, and how activity changes may generalize between tasks.

Roles of Motor Cortex Neuron Classes in Reach-Related Modulation for Hemiparkinsonian Rats.

Disruption of the function of the primary motor cortex (M1) is thought to play a critical role in motor dysfunction in Parkinson’s disease (PD). Detailed information regarding the specific aspects of M1 circuits that become abnormal is lacking. We recorded single units and local field potentials (LFPs) of M1 neurons in unilateral 6-hydroxydopamine (6-OHDA) lesion rats and control rats to assess the impact of dopamine (DA) cell loss during rest and a forelimb reaching task. Our results indicated that M1 neurons can be classified into two groups (putative pyramidal neurons and putative interneurons) and that 6-OHDA could modify the activity of different M1 subpopulations to a large extent. Reduced activation of putative pyramidal neurons during inattentive rest and reaching was observed. In addition, 6-OHDA intoxication was associated with an increase in certain LFP frequencies, especially those in the beta range (broadly defined here as any frequency between 12 and 35 Hz), which become pathologically exaggerated throughout cortico-basal ganglia circuits after dopamine depletion. Furthermore, assessment of different spike-LFP coupling parameters revealed that the putative pyramidal neurons were particularly prone to being phase-locked to ongoing cortical oscillations at 12–35 Hz during reaching. Conversely, putative interneurons were neither hypoactive nor synchronized to ongoing cortical oscillations. These data collectively demonstrate a neuron type-selective alteration in the M1 in hemiparkinsonian rats. These alterations hamper the ability of the M1 to contribute to motor conduction and are likely some of the main contributors to motor impairments in PD.

Effect of Cross-Orientation Normalization on Different Neural Measures in Macaque Primary Visual Cortex.

Divisive normalization is a canonical mechanism that can explain a variety of sensory phenomena. While normalization models have been used to explain spiking activity in response to different stimulus/behavioral conditions in multiple brain areas, it is unclear whether similar models can also explain modulation in population-level neural measures such as power at various frequencies in local field potentials (LFPs) or steady-state visually evoked potential (SSVEP) that is produced by flickering stimuli and popular in electroencephalogram studies. To address this, we manipulated normalization strength by presenting static as well as flickering orthogonal superimposed gratings (plaids) at varying contrasts to 2 female monkeys while recording multiunit activity (MUA) and LFP from the primary visual cortex and quantified the modulation in MUA, gamma (32–80 Hz), high-gamma (104–248 Hz) power, as well as SSVEP. Even under similar stimulus conditions, normalization strength was different for the 4 measures and increased as: spikes, high-gamma, SSVEP, and gamma. However, these results could be explained using a normalization model that was modified for population responses, by varying the tuned normalization parameter and semisaturation constant. Our results show that different neural measures can reflect the effect of stimulus normalization in different ways, which can be modeled by a simple normalization model.

Effects of anterior thalamic nuclei stimulation on hippocampal activity: Chronic recording in a patient with drug-resistant focal epilepsy.

Implanted neurostimulation devices are gaining traction as palliative treatment options for certain forms of drug-resistant epilepsy, but clinical utility of these devices is hindered by incomplete mechanistic understanding of their therapeutic effects. Approved devices for anterior thalamic nuclei deep brain stimulation (ANT DBS) are thought to work at a network level, but limited sensing capability precludes characterization of neurophysiological effects outside the thalamus. Here, we describe a patient with drug-resistant temporal lobe epilepsy who was implanted with a responsive neurostimulation device (RNS System), involving hippocampal and ipsilateral temporal neocortical leads, and subsequently received ANT DBS. Over 1.5years, RNS System electrocorticography enabled multiscale characterization of neurophysiological effects of thalamic stimulation. In brain regions sampled by the RNS System, ANT DBS produced acute, phasic, frequency-dependent responses, including suppression of hippocampal low frequency local field potentials. ANT DBS modulated functional connectivity between hippocampus and neocortex. Finally, ANT DBS progressively suppressed hippocampal epileptiform activity in relation to the extent of hippocampal theta suppression, which informs stimulation parameter selection for ANT DBS. Taken together, this unique clinical scenario, involving hippocampal recordings of unprecedented chronicity alongside ANT DBS, sheds light on the therapeutic mechanism of thalamic stimulation and highlights capabilities needed in next-generation devices.

Dual mechanisms of ictal high frequency oscillations in human rhythmic onset seizures

High frequency oscillations (HFOs) are bursts of neural activity in the range of 80 Hz or higher, recorded from intracranial electrodes during epileptiform discharges. HFOs are a proposed biomarker of epileptic brain tissue and may also be useful for seizure forecasting. Despite such clinical utility of HFOs, the spatial context and neuronal activity underlying these local field potential (LFP) events remains unclear. We sought to further understand the neuronal correlates of ictal high frequency LFPs using multielectrode array recordings in the human neocortex and mesial temporal lobe during rhythmic onset seizures. These multiscale recordings capture single cell, multiunit, and LFP activity from the human brain. We compare features of multiunit firing and high frequency LFP from microelectrodes and macroelectrodes during ictal discharges in both the seizure core and penumbra (spatial seizure domains defined by multiunit activity patterns). We report differences in spectral features, unit-local field potential coupling, and information theoretic characteristics of high frequency LFP before and after local seizure invasion. Furthermore, we tie these time-domain differences to spatial domains of seizures, showing that penumbral discharges are more broadly distributed and less useful for seizure localization. These results describe the neuronal and synaptic correlates of two types of pathological HFOs in humans and have important implications for clinical interpretation of rhythmic onset seizures.

Predicting Single-Unit Activity from Local Field Potentials with LSTMs.

This paper investigates to what extent Long Short-Term Memory (LSTM) decoders can use Local Field Potentials (LFPs) to predict Single-Unit Activity (SUA) in Macaque Primary Motor cortex. The motivation is to determine to what degree the LFP signal can be used as a proxy for SUA, for both neuroscience and Brain-Computer Interface (BCI) applications. Firstly, the results suggest that the prediction quality varies significantly by implant location or animal. However, within each implant location / animal, the prediction quality seems to be correlated with the amount of power in certain LFP frequency bands (0-10, 10-20 and 40-50Hz, standardised LFPs). Secondly, the results suggest that bipolar LFPs are more informative as to SUA than unipolar LFPs. This suggests common mode rejection aids in the elimination of non-local neural information. Thirdly, the best individual bipolar LFPs generally perform better than when using all available unipolar LFPs. This suggests that LFP channel selection may be a simple but effective means of lossy data compression in Wireless Intracortical LFP-based BCIs. Overall, LFPs were moderately predictive of SUA, and improvements can likely be made.

Attention strengthens across-trial pre-stimulus phase coherence in visual cortex, enhancing stimulus processing

Attention selectively routes the most behaviorally relevant information from the stream of sensory inputs through the hierarchy of cortical areas. Previous studies have shown that visual attention depends on the phase of oscillatory brain activities. These studies mainly focused on the stimulus presentation period, rather than the pre-stimulus period. Here, we hypothesize that selective attention controls the phase of oscillatory neural activities to efficiently process relevant information. We document an attentional modulation of pre-stimulus inter-trial phase coherence (a measure of deviation between instantaneous phases of trials) of low frequency local field potentials (LFP) in visual area MT of macaque monkeys. Our data reveal that phase coherence increases following a spatial cue deploying attention towards the receptive field of the recorded neural population. We further show that the attentional enhancement of phase coherence is positively correlated with the modulation of the stimulus-induced firing rate, and importantly, a higher phase coherence is associated with a faster behavioral response. These results suggest a functional utilization of intrinsic neural oscillatory activities for an enhanced processing of upcoming stimuli.

Advantages and detection of phase coding in the absence of rhythmicity.

The encoding of information in spike phase relative to local field potential (LFP) oscillations offers several theoretical advantages over equivalent firing rate codes. One notable example is provided by place and grid cells in the rodent hippocampal formation, which exhibit phase precession—firing at progressively earlier phases of the 6–12 Hz movement‐related theta rhythm as their spatial firing fields are traversed. It is often assumed that such phase coding relies on a high amplitude baseline oscillation with relatively constant frequency. However, sustained oscillations with fixed frequency are generally absent in LFP and spike train recordings from the human brain. Hence, we examine phase coding relative to LFP signals with broadband low‐frequency (2–20 Hz) power but without regular rhythmicity. We simulate a population of grid cells that exhibit phase precession against a baseline oscillation recorded from depth electrodes in human hippocampus. We show that this allows grid cell firing patterns to multiplex information about location, running speed and movement direction, alongside an arbitrary fourth variable encoded in LFP frequency. This is of particular importance given recent demonstrations that movement direction, which is essential for path integration, cannot be recovered from head direction cell firing rates. In addition, we investigate how firing phase might reduce errors in decoded location, including those arising from differences in firing rate across grid fields. Finally, we describe analytical methods that can identify phase coding in the absence of high amplitude LFP oscillations with approximately constant frequency, as in single unit recordings from the human brain and consistent with recent data from the flying bat. We note that these methods could also be used to detect phase coding outside of the spatial domain, and that multi‐unit activity can substitute for the LFP signal. In summary, we demonstrate that the computational advantages offered by phase coding are not contingent on, and can be detected without, regular rhythmicity in neural activity.

Spatial attention enhances network, cellular and subthreshold responses in mouse visual cortex

Internal brain states strongly modulate sensory processing during behaviour. Studies of visual processing in primates show that attention to space selectively improves behavioural and neural responses to stimuli at the attended locations. Here we develop a visual spatial task for mice that elicits behavioural improvements consistent with the effects of spatial attention, and simultaneously measure network, cellular, and subthreshold activity in primary visual cortex. During trial-by-trial behavioural improvements, local field potential (LFP) responses to stimuli detected inside the receptive field (RF) strengthen. Moreover, detection inside the RF selectively enhances excitatory and inhibitory neuron responses to task-irrelevant stimuli and suppresses noise correlations and low frequency LFP fluctuations. Whole-cell patch-clamp recordings reveal that detection inside the RF increases synaptic activity that depolarizes membrane potential responses at the behaviorally relevant location. Our study establishes that mice display fundamental signatures of visual spatial attention spanning behavioral, network, cellular, and synaptic levels, providing new insight into rapid cognitive enhancement of sensory signals in visual cortex.

On the Relationship between MRI and Local Field Potential Measurements of Spatial and Temporal Variations in Functional Connectivity

Correlations between fluctuations in resting state BOLD fMRI signals are interpreted as measures of functional connectivity (FC), but the neural basis of their origins and their relationships to specific features of underlying electrophysiologic activity, have not been fully established. In particular, the dependence of FC metrics on different frequency bands of local field potentials (LFPs), and the relationship of dynamic changes in BOLD FC to underlying temporal variations of LFP correlations, are not known. We compared the spatial profiles of resting state coherences of different frequency bands of LFP signals, with high resolution resting state BOLD FC measurements. We also compared the probability distributions of temporal variations of connectivity in both modalities using a Markov chain model-based approach. We analyzed data obtained from the primary somatosensory (S1) cortex of monkeys. We found that in areas 3b and 1 of S1 cortex, low frequency LFP signal fluctuations were the main contributions to resting state LFP coherence. Additionally, the dynamic changes of BOLD FC behaved most similarly to the LFP low frequency signal coherence. These results indicate that, within the S1 cortex meso-scale circuit studied, resting state FC measures from BOLD fMRI mainly reflect contributions from low frequency LFP signals and their dynamic changes.

Correlated Neural Activity across the Brains of Socially Interacting Bats

Social interactions occur between multiple individuals, but what is the detailed relationship between the neural dynamics across their brains? To address this question across timescales and levels of neural activity, we used wireless electrophysiology to simultaneously record from pairs of bats engaged in a wide range of natural social interactions. We found that neural activity was remarkably correlated between their brains over timescales from seconds to hours. The correlation depended on a shared social environment and was most prominent in high frequency local field potentials (>30Hz), followed by local spiking activity. Furthermore, the degree of neural correlation covaried with the extent of social interactions, and an increase in correlation preceded their initiation. These results show that inter-brain correlation is an inherent feature of natural social interactions, reveal the domain of neural activity where it is most prominent, and provide a foundation for studying its functional role in social behaviors.

Visual cortex neurons phase-lock selectively to subsets of LFP oscillations.

It is generally thought that apart from receptive field differences, such as preferred orientation and spatial frequency selectivity, primary visual cortex neurons are functionally similar to each other. However, the genetic diversity of cortical neurons plus the existence of inputs additional to those required to explain known receptive field properties might suggest otherwise. Here we report the existence of desynchronized states in anesthetized cat area 17 lasting up to 45 min, characterized by variable narrow-band local field potential (LFP) oscillations in the range 2-100 Hz and the absence of a synchronized 1/f frequency spectrum. During these periods, spontaneously active neurons phase-locked to variable subsets of LFP oscillations. Individual neurons often ignored frequencies that others phase-locked to. We suggest that these desynchronized periods may correspond to REM sleep-like episodes occurring under anesthesia. Frequency-selective codes may be used for signaling during these periods. Hence frequency-selective combination and frequency-labeled pathways may represent a previously unsuspected dimension of cortical organization. NEW & NOTEWORTHY We investigated spontaneous neuronal firing during periods of desynchronized local field potential (LFP) activity, resembling REM sleep, in anesthetized cats. During these periods, neurons synchronized their spikes to specific phases of multiple LFP frequency components, with some neurons ignoring frequencies that others were synchronized to. Some neurons fired at phase alignments of frequency pairs, thereby acting as phase coincidence detectors. These results suggest that internal brain signaling may use frequency combination codes to generate temporally structured spike trains.

The effect of sevoflurane and isoflurane anesthesia on single unit and local field potentials.

Volatile general anesthetics are used commonly in adults and children, yet their mechanisms of action are complex and the changes in single unit firing and synaptic activity that underlie the broad decreases in neuronal activity induced by these drugs have not been well characterized. Capturing such changes throughout the anesthesia process is important for comparing the effects of different anesthetics and gaining a better understanding of their mechanisms of action and their impact on different brain regions. Using chronically implanted electrodes in the rabbit somatosensory cortex, we compared the effects of two common general anesthetics, isoflurane, and sevoflurane, on cortical neurons. Single unit activity and local field potentials (LFP) were recorded continuously before and during anesthetic delivery at 1 MAC, as well as during recovery. Our findings show that although isoflurane and sevoflurane belong to the same class of volatile general anesthetics, their effects upon cortical single units and LFP were quite different. Overall, the suppression of neuronal firing was greater and more uniform under sevoflurane. Moreover, the changes in LFP frequency bands suggest that effect of anesthesia upon beta oscillations does not necessarily depend on the level of single unit activity, but rather on the changes in GABA/glutamate neurotransmission induced by each drug.

Acute morphine administration alters the power of local field potentials in mesolimbic pathway of freely moving rats: Involvement of dopamine receptors

Increasing number of evidence support the role of ventral tegmental area (VTA) and nucleus accumbens (NAc) in mediating the opiate effects as the two critical components of brain reward pathway. It is believed that VTA to NAC dopaminergic projections mediate the reinforcing effects induced by opioid drugs. Although numerous studies have investigated mechanisms of reward processing in these brain regions, alterations of local field potentials (LFPs), as an index of total synaptic currents, has not been previously addressed.In the present study, thin metal electrodes were implanted in both VTA and shell sub-region of NAc to simultaneously record the spontaneous LFPs in freely moving rats. After one week recovery period, a single dose of morphine was systemically administered and the LFP recording was performed 15, 30, 45 and 60 post-injection. Also, in order to assess the role of dopamine system, two groups of animals were pre-treated by selective antagonists of dopamine type-1 and type-2 receptors 15 min prior to morphine injection.The obtained results indicated that in VTA, acute morphine administration potentiates the power of all LFP frequency bands (i.e. delta, theta, alpha, beta and gamma). However, in NAc shell, theta wave was significantly attenuated by morphine and other components were not affected. In addition, pre-treatment with both antagonists prevented the observed effect of morphine on LFP power suggesting the involvement of dopamine receptors in this process. Future studies should address mechanisms of dopamine-morphine interactions. It is also valuable to focus on acute and chronic effects of morphine on LFP power and assessment of the observed effects following naloxone challenge.

Hippocampal Neural Circuits Respond to Optogenetic Pacing of Theta Frequencies by Generating Accelerated Oscillation Frequencies

Biological oscillations can be controlled by a small population of rhythmic pacemaker cells, or in the brain, they also can emerge from complex cellular and circuit-level interactions. Whether and how these mechanisms are combined to give rise to oscillatory patterns that govern cognitive function are notwell understood. For example, the activity of hippocampal networks is temporally coordinated by a 7-to 9-Hz local field potential (LFP) theta rhythm, yet many individual cells decouple from the LFP frequency to oscillate at frequencies ∼1Hz higher. To better understand the network interactions that produce these complex oscillatory patterns, we asked whether the relative frequency difference between LFP and individual cells is retained when the LFP frequency is perturbed experimentally. We found that rhythmic optogenetic stimulation of medial septal GABAergic neurons controlled the hippocampal LFP frequency outside of the endogenous theta range, even during behavioral states when endogenous mechanisms would otherwise have generated 7- to 9-Hz theta oscillations. While the LFP frequency matched the optogenetically induced stimulation frequency, the oscillation frequency of individual hippocampal cells remained broadly distributed, and in a subset of cells including interneurons, it was accelerated beyond the new base LFP frequency. The inputs from septal GABAergic neurons to the hippocampus, therefore, do not appear to directly control the cellular oscillation frequency but rather engage cellular and circuit mechanisms that accelerate the rhythmicity of individual cells. Thus, theta oscillations are an example of cortical oscillations that combine inputs from a subcortical pacemaker with local computations to generate complex oscillatory patterns that support cognitive functions.

Spontaneous Infra-slow Brain Activity Has Unique Spatiotemporal Dynamics and Laminar Structure

Systems-level organization in spontaneous infra-slow (<0.1Hz) brain activity, measured using blood oxygen signals in fMRI and optical imaging, has become a major theme in the study of neural function in both humans and animal models. Yet the neurophysiological basis of infra-slow activity (ISA) remains unresolved. In particular, is ISA a distinct physiological process, or is it a low-frequency analog of faster neural activity? Here, using whole-cortex calcium/hemoglobin imaging in mice, we show that ISA in each of these modalities travels through the cortex along stereotypical spatiotemporal trajectories that are state dependent (wake versus anesthesia) and distinct from trajectories in delta (1-4Hz) activity. Moreover, mouse laminar electrophysiology reveals that ISA travels through specific cortical layers and is organized into unique cross-laminar temporal dynamics that are different from higher frequency local field potential activity. These findings suggest that ISA is a distinct neurophysiological process that is reflected in fMRI blood oxygen signals.

Adaptive quantization of local field potentials for wireless implants in freely moving animals: an open-source neural recording device

Objective. Modern neuroscience research requires electrophysiological recording of local field potentials (LFPs) in moving animals. Wireless transmission has the advantage of removing the wires between the animal and the recording equipment but is hampered by the large number of data to be sent at a relatively high rate. Approach. To reduce transmission bandwidth, we propose an encoder/decoder scheme based on adaptive non-uniform quantization. Our algorithm uses the current transmitted codeword to adapt the quantization intervals to changing statistics in LFP signals. It is thus backward adaptive and does not require the sending of side information. The computational complexity is low and similar at the encoder and decoder sides. These features allow for real-time signal recovery and facilitate hardware implementation with low-cost commercial microcontrollers. Main results. As proof-of-concept, we developed an open-source neural recording device called NeRD. The NeRD prototype digitally transmits eight channels encoded at 10 kHz with 2 bits per sample. It occupies a volume of 2 × 2 × 2 cm3 and weighs 8 g with a small battery allowing for 2 h 40 min of autonomy. The power dissipation is 59.4 mW for a communication range of 8 m and transmission losses below 0.1%. The small weight and low power consumption offer the possibility of mounting the entire device on the head of a rodent without resorting to a separate head-stage and battery backpack. The NeRD prototype is validated in recording LFPs in freely moving rats at 2 bits per sample while maintaining an acceptable signal-to-noise ratio (>30 dB) over a range of noisy channels. Significance. Adaptive quantization in neural implants allows for lower transmission bandwidths while retaining high signal fidelity and preserving fundamental frequencies in LFPs.

Spatiotemporal Neural Activity Changes in the Molluscan Olfactory Center Specifically Induced by Innately Aversive and &amp;lt;i&amp;gt;In Vitro&amp;lt;/i&amp;gt; Aversively Conditioned Odors

In the procerebrum (PC), the olfactory center, of the land slug Limax, an oscillation of local field potential (LFP) with 0.5 - 1 Hz is observed by electrophysiological extracellular recording. The oscillation has a phase delay along the distal-proximal axis, resulting in the propagation of waves from the distal to proximal region. One important advantage of nervous systems of mollusks such as Limax is that their nervous systems in vitro retain several types of computational properties found in vivo (e.g. learning and memory). A previous study showed that the LFP frequency in the PC of Limax increased specifically in response to innately aversive and in vitro aversively conditioned odors. In the present study, we examined spatiotemporal neural activity changes induced in the PC by those odors using the fluorescent voltage imaging technique. The results showed that innately aversive (onion and hexanol) and in vitro aversively conditioned (carrot, which is innately attractive) odors specifically induced an increase in propagation speed of the neural activity in the PC, while innately attractive odors did not induce it. The results also suggested that the avoidance behavior by those odors might be induced by the increase of propagation speed and the following increases in the discharges of the partial nerve that transmits the motor output.