Components Of Local Field Potentials Research Articles

Aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.

The aperiodic component of local field potentials can be modeled to produce useful and reproducible indices of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters (namely the exponent, offset and knee), with which we fit cortical, basal ganglia, and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinson's disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the aperiodic parameters of basal ganglia and thalamic signals compared to those from neocortex.

Cortical Responses to Vagus Nerve Stimulation Are Modulated by Brain State in Nonhuman Primates.

Vagus nerve stimulation (VNS) has been tested as therapy for several brain disorders and as a means to modulate cortical excitability and brain plasticity. Cortical effects of VNS, manifesting as vagal-evoked potentials (VEPs), are thought to arise from activation of ascending cholinergic and noradrenergic systems. However, it is unknown whether those effects are modulated by brain state at the time of stimulation. In 2 freely behaving macaque monkeys, we delivered short trains of 5 pulses to the left cervical vagus nerve at different frequencies (5-300 Hz) while recording local field potentials (LFPs) from sites in contralateral prefrontal, sensorimotor and parietal cortical areas. Brain states were inferred from spectral components of LFPs and the presence of overt movement: active awake, resting awake, REM sleep and NREM sleep. VNS elicited VEPs in all sampled cortical areas. VEPs comprised early (<70 ms), intermediate (70-250 ms) and late (>250 ms) components. The magnitude of the intermediate and late components was largest during NREM sleep and smallest during wakefulness, whereas that of the early component was not modulated by brain state. VEPs during NREM were larger for stimuli delivered at the depolarized phase of ongoing delta oscillations. Higher pulsing frequencies generated larger VEPs. These short VNS trains did not affect brain state transitions during wakefulness or sleep. Our findings suggest that ongoing brain state modulates the evoked effects of VNS on cortical activity. This has implications for the role of ongoing cortical activity and brain state in shaping cortical responses to peripheral stimuli, for the modulation of vagal interoceptive signaling by cortical activity, and for the dose calibration of VNS therapies.

Cell-type-specific resonances shape the responses of striatal neurons to synaptic input.

Neurons respond to synaptic inputs in cell-type-specific ways. Each neuron type may thus respond uniquely to shared patterns of synaptic input. We applied statistically identical barrages of artificial synaptic inputs to four striatal cell types to assess differences in their responses to a realistic input pattern. Each interneuron type fired in phase with a specific input-frequency component. The fast-spiking interneuron fired in relation to the gamma-band (and higher) frequencies, the low-threshold spike interneuron to the beta-band frequencies, and the cholinergic neurons to the delta-band frequencies. Low-threshold spiking and cholinergic interneurons showed input impedance resonances at frequencies matching their spiking resonances. Fast-spiking interneurons showed resonance of input impedance but at lower than gamma frequencies. The spiny projection neuron's frequency preference did not have a fixed frequency but instead tracked its own firing rate. Spiny cells showed no input impedance resonance. Striatal interneurons are each tuned to a specific frequency band corresponding to the major frequency components of local field potentials. Their influence in the circuit may fluctuate along with the contribution of that frequency band to the input. In contrast, spiny neurons may tune to any of the frequency bands by a change in firing rate.

Can pathway-specific LFPs be obtained in cytoarchitectonically complex structures?

Deciphering how the brain encodes the continuous flow of information contained in natural stimuli requires understanding the spontaneous activity of functional assemblies in multiple neuronal populations. A promising integrative approach that combines multisite recordings of local field potentials (LFP) with an independent component analysis (ICA) enables continuous readouts of population specific activities of functionally different neuron groups to be obtained. We previously used this technique successfully in the hippocampus, a single-layer neuronal structure. Here we provide numerical evidence that the cytoarchitectonic complexity of other brain structures does not compromise the value of the ICA-separated LFP components, given that spatial sampling of LFP is representative. The spatial distribution of an LFP component may be quite complex due to folded and multilayered structure of the neuronal aggregate. Nevertheless, the time course of each LFP component is still a reliable postsynaptic convolution of spikes fired by a homogeneous afferent population. This claim is supported by preliminary experimental data obtained in the lateral geniculate nucleus of the awake monkey.

Increase of spike–LFP coordination in rat prefrontal cortex during working memory

Working memory (WM) refers to the short-term maintenance of information with higher cognitive functions. Recent researches show that local field potentials (LFPs) and spikes, as different modes of neural signals, encode WM, respectively. There is a growing interest in how these two signals encode WM in coordination. The aim of this study is to investigate spike–LFP coupling coding of WM via the joint entropy analysis. The experimental data were multi-channel spikes and LFPs obtained from SD rat prefrontal cortex through the implanted microelectrode array during the WM tasks in Y-maze. The short-time Fourier transform (STFT) was applied to analyze the power changes of WM related frequency bands in the LFPs. The joint entropy indexes (JEIs) between spikes and the principle components of LFPs were calculated for each pair of the spike and the LFP series during WM. The results showed that the power of theta (4–12Hz), low gamma (LG, 30–60Hz) and high gamma band (HG, 60–100Hz) in LFPs increased during the WM tasks. In addition, the JEIs between spikes and LFPs components (theta, LG and HG) significantly increased in the correct trials. Besides, the coupling levels were low when the rats waiting in the starting area. These results suggest that the JEIs between spikes and LFPs components (theta, LG and HG) encode WM effectively. These findings could lead to improved understanding of the WM mechanism from the view of spike–LFP joint encoding.

Frequency dependence of signal power and spatial reach of the local field potential.

Despite its century-old use, the interpretation of local field potentials (LFPs), the low-frequency part of electrical signals recorded in the brain, is still debated. In cortex the LFP appears to mainly stem from transmembrane neuronal currents following synaptic input, and obvious questions regarding the ‘locality’ of the LFP are: What is the size of the signal-generating region, i.e., the spatial reach, around a recording contact? How far does the LFP signal extend outside a synaptically activated neuronal population? And how do the answers depend on the temporal frequency of the LFP signal? Experimental inquiries have given conflicting results, and we here pursue a modeling approach based on a well-established biophysical forward-modeling scheme incorporating detailed reconstructed neuronal morphologies in precise calculations of population LFPs including thousands of neurons. The two key factors determining the frequency dependence of LFP are the spatial decay of the single-neuron LFP contribution and the conversion of synaptic input correlations into correlations between single-neuron LFP contributions. Both factors are seen to give low-pass filtering of the LFP signal power. For uncorrelated input only the first factor is relevant, and here a modest reduction (<50%) in the spatial reach is observed for higher frequencies (>100 Hz) compared to the near-DC () value of about . Much larger frequency-dependent effects are seen when populations of pyramidal neurons receive correlated and spatially asymmetric inputs: the low-frequency () LFP power can here be an order of magnitude or more larger than at 60 Hz. Moreover, the low-frequency LFP components have larger spatial reach and extend further outside the active population than high-frequency components. Further, the spatial LFP profiles for such populations typically span the full vertical extent of the dendrites of neurons in the population. Our numerical findings are backed up by an intuitive simplified model for the generation of population LFP.

Excitatory and inhibitory contributions to local field potentials in human and monkey

Local field potentials (LFPs) are a common measure of the neuronal population activity. However, their origins are not yet fully understood. A recent in vitro study has shown that even single spikes emitted by an interneuron can trigger detectable unitary field potentials in extracellular medium [1]. Their contributions can be additionally amplified due to strong spatial correlations in interneuronal firing [2]. Nevertheless, inhibitory activity in vivo is strongly correlated with the excitatory potentials leading to effective cancellations of generated field potentials. As a result, the unitary field potentials induced by interneuronal spikes can not be separated from background activity. Here, we describe a technique that allows to disambiguate the excitatory and inhibitory contributions. We study the contribution of excitatory and inhibitory neurons in awake and sleeping brain of human and monkey. The experimental data were recorded intracortically in patients accepted for the surgical treatment of epileptic foci. We discriminated 82 single units over a electrode grid of 92 electrodes (covering an area of 4 mm × 4 mm) together with accompanying local field potentials. We compared the results with LPFs and spikes recorded from electrode arrays of the same geometry implanted in motor cortex of macaque monkeys [3]. For both datasets, we determined the field potential components related to spikes of inhibitory neurons by means of spike-triggered average (STA) and covariance (STC) methods [4]. First, we determined the spatial reach of the spike-induced field by means of spike-triggered average analysis. We found that the potentials triggered by putative interneurons propagate across the electrode grid at velocity higher than the field of putative pyramidal neurons (propagation velocity: 0.5 m/s and 0.3 m/s, respectively). In addition, the spike-triggered covariance analysis revealed gamma-band components in the local field potentials of interneurons but not pyramidal neurons. These high-frequency components are most likely related to the oscillations generated within a local network. To test this hypothesis, we simulate a network of simplified neurons that manifest gamma-band synchronization. Next, we apply the spike-triggered analysis to the field potentials calculated as a local average of the membrane potentials. The results of the simulations are compared to the experimental data. We demonstrate that spike triggered covariance allows to separate components that are not accessible to standard techniques due to cancellations of the field produced by inhibitory and excitatory potentials. The application of this technique to the activities recorded in interneurons revealed previously unidentified components of local field potentials. Computer simulations suggest that these components are related to nonlinear interactions within the networks of inhibitory and excitatory neurons. Interestingly, we have not found such gamma-band components in the LFPs associated with excitatory neurons. Overall, our results point to essentially different relations between LFPs and spikes of excitatory and inhibitory neurons. We propose that this difference may provide a new electrophysiological criterion for the identification of interneurons.

Encoding of rat working memory by power of multi-channel local field potentials via sparse non-negative matrix factorization

Working memory plays an important role in human cognition. This study investigated how working memory was encoded by the power of multi-channel local field potentials (LFPs) based on sparse nonnegative matrix factorization (SNMF). SNMF was used to extract features from LFPs recorded from the prefrontal cortex of four Sprague-Dawley rats during a memory task in a Y maze, with 10 trials for each rat. Then the power-increased LFP components were selected as working memory-related features and the other components were removed. After that, the inverse operation of SNMF was used to study the encoding of working memory in the time-frequency domain. We demonstrated that theta and gamma power increased significantly during the working memory task. The results suggested that postsynaptic activity was simulated well by the sparse activity model. The theta and gamma bands were meaningful for encoding working memory.

Deactivation of the inferior colliculus by cooling demonstrates intercollicular modulation of neuronal activity.

The auditory pathways coursing through the brainstem are organized bilaterally in mirror image about the midline and at several levels the two sides are interconnected. One of the most prominent points of interconnection is the commissure of the inferior colliculus (CoIC). Anatomical studies have revealed that these fibers make reciprocal connections which follow the tonotopic organization of the inferior colliculus (IC), and that the commissure contains both excitatory and, albeit fewer, inhibitory fibers. The role of these connections in sound processing is largely unknown. Here we describe a method to address this question in the anaesthetized guinea pig. We used a cryoloop placed on one IC to produce reversible deactivation while recording electrophysiological responses to sounds in both ICs. We recorded single units, multi-unit clusters and local field potentials (LFPs) before, during and after cooling. The degree and spread of cooling was measured with a thermocouple placed in the IC and other auditory structures. Cooling sufficient to eliminate firing was restricted to the IC contacted by the cryoloop. The temperature of other auditory brainstem structures, including the contralateral IC and the cochlea were minimally affected. Cooling below 20°C reduced or eliminated the firing of action potentials in frequency laminae at depths corresponding to characteristic frequencies up to ~8 kHz. Modulation of neural activity also occurred in the un-cooled IC with changes in single unit firing and LFPs. Components of LFPs signaling lemniscal afferent input to the IC showed little change in amplitude or latency with cooling, whereas the later components, which likely reflect inter- and intra-collicular processing, showed marked changes in form and amplitude. We conclude that the cryoloop is an effective method of selectively deactivating one IC in guinea pig, and demonstrate that auditory processing in the IC is strongly influenced by the other.

Encoding of brain state changes in local field potentials modulated by motor behaviors

Local field potentials (LFPs) measure aggregate neural activity resulting from the coordinated firing of neurons within a local network. We hypothesized that state parameters associated with the underlying brain dynamics may be encoded in LFPs but may not be directly measurable in the signal temporal and spectral contents. Using the Kalman filter we estimated latent state changes in LFPs recorded in monkey motor cortical areas during the execution of a visually instructed reaching task, under different applied force conditions. Prior to the estimation, matched filtering was performed to decouple behavior-relevant signals (Stamoulis and Richardson, J Comput Neurosci, 2009) from unrelated background oscillations. State changes associated with baseline oscillations appeared insignificant. In contrast, state changes estimated from LFP components associated with the execution of movement were significant. Approximately direction-invariant state vectors were consistently observed. Their patterns appeared invariant also to force field conditions, with a peak in the first 200 ms of the movement interval, but exponentially decreasing to the zero state approximately 200 ms from movement onset, also the time at which movement velocity reached its peak. Thus, state appeared to be modulated by the dynamics of movement but neither by movement direction nor by the mechanical environment. Finally, we compared state vectors estimated using the Kalman filter to the basis functions obtained through Principal Component Analysis. The pattern of the estimated state vector was very similar to that of the first PCA component, further suggesting that LFPs may directly encode brain state fluctuations associated with the dynamics of behavior.

Reduction of prelimbic inhibitory gating of auditory evoked potentials after fear conditioning.

Inhibitory gating (IG) is a basic central nervous system process for filtering repetitive sensory information. Although IG deficits coincide with cognitive and emotional dysfunction in a variety of neuropsychiatric disorders, limited research has been completed on the basic, functional nature of IG. Persistent IG occurs in rat prelimbic medial prefrontal cortex (mPFC), a crucial site for modulating emotional learning. To investigate the interaction of affect and IG, we recorded local field potentials (LFP) directly from prelimbic mPFC and examined the influence of tone-shock fear conditioning (FC) on IG. Behavioral reactions during IG were observed before and after FC, and increase of orienting response after FC indicated induction of tone-shock association. After FC, some components of LFP response exhibited short-term weakening of IG. On a subsequent day of recording, IG strengthened for all LFP components, but individual components differed in their particular changes. Affective regulation of IG represents an important factor influencing within-subject IG variability, and these results have implications for understanding the role of rapid, implicit neural coding involved in emotional learning and affective disruption in psychiatric disease.