Analysis Of Local Field Potentials Research Articles

Systems-level analysis of local field potentials reveals differential effects of lysergic acid diethylamide and ketamine on neuronal activity and functional connectivity.

Psychedelic substances have in recent years attracted considerable interest as potential treatments for several psychiatric conditions, including depression, anxiety, and addiction. Imaging studies in humans point to a number of possible mechanisms underlying the acute effects of psychedelics, including changes in neuronal firing rates and excitability as well as alterations in functional connectivity between various brain nodes. In addition, animal studies using invasive recordings, have suggested synchronous high-frequency oscillations involving several brain regions as another key feature of the psychedelic brain state. To better understand how the imaging data might be related to high-resolution electrophysiological measurements, we have here analyzed the aperiodic part of the local field potential (LFP) in rodents treated with a classic psychedelic (LSD) or a dissociative anesthetic (ketamine). In addition, functional connectivity, as quantified by mutual information measures in the LFP time series, has been assessed with in and between different structures. Our data suggest that the altered brain states of LSD and ketamine are caused by different underlying mechanisms, where LFP power shifts indicate increased neuronal activity but reduced connectivity following ketamine, while LSD also leads to reduced connectivity but without an accompanying change in LFP broadband power.

Top-down control of human motor thalamic neuronal activity during the auditory oddball task

The neurophysiology of selective attention in visual and auditory systems has been studied in animal models but not with single unit recordings in human. Here, we recorded neuronal activity in the ventral intermediate nucleus as well as the ventral oral anterior, and posterior nuclei of the motor thalamus in 25 patients with parkinsonian (n = 6) and non-parkinsonian tremors (n = 19) prior to insertion of deep brain stimulation electrodes while they performed an auditory oddball task. In this task, patients were requested to attend and count the randomly occurring odd or “deviant” tones, ignore the frequent standard tones and report the number of deviant tones at trial completion. The neuronal firing rate decreased compared to baseline during the oddball task. Inhibition was specific to auditory attention as incorrect counting or wrist flicking to the deviant tones did not produce such inhibition. Local field potential analysis showed beta (13–35 Hz) desynchronization in response to deviant tones. Parkinson’s disease patients off medications had more beta power than the essential tremor group but less neuronal modulation of beta power to the attended tones, suggesting that dopamine modulates thalamic beta oscillations for selective attention. The current study demonstrated that ascending information to the motor thalamus can be suppressed during auditory attending tasks, providing indirect evidence for the searchlight hypothesis in humans. These results taken together implicate the ventral intermediate nucleus in non-motor cognitive functions, which has implications for the brain circuitry for attention and the pathophysiology of Parkinson’s disease.

Evaluation of the Antiseizure Activity of Endemic Plant Halfordia kendack Guillaumin and Its Main Constituent, Halfordin, on a Zebrafish Pentylenetetrazole (PTZ)-Induced Seizure Model.

Epilepsy is a neurological disease that burdens over 50 million people worldwide. Despite the considerable number of available antiseizure medications, it is estimated that around 30% of patients still do not respond to available treatment. Herbal medicines represent a promising source of new antiseizure drugs. This study aimed to identify new drug lead candidates with antiseizure activity from endemic plants of New Caledonia. The crude methanolic leaf extract of Halfordia kendack Guillaumin (Rutaceae) significantly decreased (75 μg/mL and 100 μg/mL) seizure-like behaviour compared to sodium valproate in a zebrafish pentylenetetrazole (PTZ)-induced acute seizure model. The main coumarin compound, halfordin, was subsequently isolated by liquid-liquid chromatography and subjected to locomotor, local field potential (LFP), and gene expression assays. Halfordin (20 μM) significantly decreased convulsive-like behaviour in the locomotor and LFP analysis (by 41.4% and 60%, respectively) and significantly modulated galn, and penka gene expression.

Potential therapeutic mechanism of deep brain stimulation of the nucleus accumbens in obsessive-compulsive disorder.

Deep brain stimulation (DBS) of the nucleus accumbens (NAc) (NAc-DBS) is an effective solution to refractory obsessive-compulsive disorder (OCD). However, evidence for the neurobiological mechanisms of OCD and the effect of NAc-DBS is still lacking. One hypothesis is that the electrophysiological activities in the NAc are modulated by DBS, and another hypothesis is that the activities of neurotransmitters in the NAc are influenced by DBS. To investigate these potential alterations, rats with quinpirole (QNP)- induced OCD were treated with DBS of the core part of NAc. Then, extracellular spikes (SPK) and local field potentials (LFP) in the NAc were recorded, and the levels of relevant neurotransmitters and related proteins were measured. Analysis of SPK revealed that the firing rate was decreased and the firing pattern was changed after NAc-DBS, and analysis of LFP showed that overall power spectral density (PSD) levels were reduced after NAc-DBS. Additionally, we found that the relative powers of the theta band, alpha band and beta band were increased in OCD status, while the relative powers of the delta band and gamma band were decreased. This pathological pattern of power distribution was reformed by NAc-DBS. Furthermore, we found that the local levels of monoamines [dopamine (DA) and serotonin (5-HT)] and amino acids [glutamate (Glu) and gamma-aminobutyric acid (GABA)] in the NAc were increased in OCD status, and that the expression of the two types of DA receptors in the NAc exhibited an opposite change. These abnormalities could be reversed by NAc-DBS. These findings provide a more comprehensive understanding about the function of the NAc in the pathophysiology of OCD and provide more detailed evidence for the potential effect of NAc-DBS.

Altered Odor-Evoked Electrophysiological Responses in the Anterior Piriform Cortex of Conscious APP/PS1 Mice.

Olfactory decline is an indicator of early-stage Alzheimer's disease (AD). Although the anterior piriform cortex (aPC) is an important brain area involved in processing olfactory input, little is known about how its neuronal activity is affected in early-stage AD. To elucidate whether odor-induced electrophysiological responses are altered in the aPC of 3-5-month-old APP/PS1 mice. Using head-fixed multi-channel recording techniques in APP/PS1 AD mouse model to uncover potential aberrance of the aPC neuronal firing and local field potential (LFP) in response to vanillin. We show that the firing rate of aPC neurons evoked by vanillin is significantly reduced in conscious APP/PS1 mice. LFP analysis demonstrates reduced low- and high-gamma (γlow,γhigh) oscillations during both the baseline and odor stimulation periods in APP/PS1 mice. Moreover, according to spike-field coherence (SFC) analysis, APP/PS1 mice show decreased coherence between odor-evoked spikes and γlow rhythms, while the coherence with γhigh rhythms and the ΔSFC of the oscillations is unaffected. Furthermore, APP/PS1 mice show reduced phase-locking strength in the baseline period, such that there is no difference between baseline and odor-stimulation conditions. This contrasts markedly with wild type mice, where phase-locking strength decreases on stimulation. The abnormalities in both the neuronal and oscillatory activities of the aPC may serve as electrophysiological indicators of underlying olfactory decline in early AD.

Febrile Seizures Cause Depression and Anxiogenic Behaviors in Rats.

Febrile seizure (FS) is a common type of seizure occurring in human during infancy and childhood. Although an epileptic seizure is associated with psychiatric disorders and comorbid diseases such as depression, anxiety, autism spectrum disorders, sleep disorders, attention deficits, cognitive impairment, and migraine, the causal relationship between FS and psychiatric disorders is poorly understood. The objective of the current study was to investigate the relationship of FS occurrence in childhood with the pathogenesis of anxiety disorder and depression using an FS rat model. We induced febrile seizures in infantile rats (11 days postnatal) using a mercury vapor lamp. At 3 weeks and 12 weeks after FS induction, we examined behaviors and recorded local field potentials (LFPs) to assess anxiety and depression disorder. Interestingly, after FS induction in infantile rats, anxiogenic behaviors and depression-like phenotypes were found in both adult and juvenile FS rats. The analysis of LFPs revealed that 4–7 Hz hippocampal theta rhythm, a neural oscillatory marker for anxiety disorder, was significantly increased in FS rats compared with their wild-type littermates. Taken together, our findings suggest that FS occurrence in infants is causally related to increased levels of anxiety-related behaviors and depression-like symptoms in juvenile and adult rodents.

Attenuation of neural responses in subthalamic nucleus during internally guided voluntary movements in Parkinson's disease.

The proposed models of segregated functional loops describe the organization of motor control over externally triggered (ET) and internally guided (IG) movements. The dopamine deficiency in Parkinson’s disease (PD) is considered to cause a disturbance in the functional loop regulating IG movements. At the same time, the neural mechanisms of movement performance and the role of basal ganglia in motor control remain unclear.The aim of this study was to compare neuronal responses in the subthalamic nucleus (STN) during ET and IG movements in PD. We found and analyzed 26 sensitive neurons in 12 PD patients who underwent surgery for implantation of electrodes for deep brain stimulation. We also analyzed the local field potentials (LFP) of the STN of six patients during the postoperative period. Patients were asked to perform voluntary movements (clenching and unclenching the fist) evoked by verbal command (ET) or self-initiated (IG). We showed heterogeneity of neuronal responses and did not find sensitive neurons associated with only one type of movement. Most cells were characterized by leading responses, indicating that the STN has an important role in movement initiation. At the same time, we found attenuation of motor responses during IG movement vs. stable responses during ET movements. LFP analysis also showed attenuation of beta desynchronization during multiple IG movements.We propose that stable neuronal response to ET movements is associated with the reboot of the motor program for each movement, while attenuation of responses to IG movement is associated with single motor program launching for multiple movements.

Xenon LFP Analysis Platform Is a Novel Graphical User Interface for Analysis of Local Field Potential From Large-Scale MEA Recordings.

High-density multi-electrode array (HD-MEA) has enabled neuronal measurements at high spatial resolution to record local field potentials (LFP), extracellular action potentials, and network-wide extracellular recording on an extended spatial scale. While we have advanced recording systems with over 4,000 electrodes capable of recording data at over 20 kHz, it still presents computational challenges to handle, process, extract, and view information from these large recordings. We have created a computational method, and an open-source toolkit built in Python, rendered on a web browser using Plotly’s Dash for extracting and viewing the data and creating interactive visualization. In addition to extracting and viewing entire or small chunks of data sampled at lower or higher frequencies, respectively, it provides a framework to collect user inputs, analyze channel groups, generate raster plots, view quick summary measures for LFP activity, detect and isolate noise channels, and generate plots and visualization in both time and frequency domain. Incorporated into our Graphical User Interface (GUI), we also created a novel seizure detection method, which can be used to detect the onset of seizures in all or a selected group of channels and provide the following measures of seizures: distance, duration, and propagation across the region of interest. We demonstrate the utility of this toolkit, using datasets collected from an HD-MEA device comprising of 4,096 recording electrodes. For the current analysis, we demonstrate the toolkit and methods with a low sampling frequency dataset (300 Hz) and a group of approximately 400 channels. Using this toolkit, we present novel data demonstrating increased seizure propagation speed from brain slices of Scn1aHet mice compared to littermate controls. While there have been advances in HD-MEA recording systems with high spatial and temporal resolution, limited tools are available for researchers to view and process these big datasets. We now provide a user-friendly toolkit to analyze LFP activity obtained from large-scale MEA recordings with translatable applications to EEG recordings and demonstrate the utility of this new graphic user interface with novel biological findings.

Phase amplitude coupling analysis of local field potentials in working memory of rats affected by transcranial magneto-acoustic-electrical stimulation

Transcranial magneto-acoustic-electrical stimulation is a new non-invasive neuromodulation technology, in which the induced electric field generated by the coupling effect of ultrasound and static magnetic field are used to regulate the neural rhythm oscillation activity in the corresponding brain region. The purpose of this paper is to investigate the effects of transcranial magneto-acoustic-electrical stimulation on the information transfer and communication in neuronal clusters during memory. In the experiment, twenty healthy adult Wistar rats were randomly divided into a control group (five rats) and stimulation groups (fifteen rats). Transcranial magneto-acoustic-electrical stimulation of 0.05~0.15 T and 2.66~13.33 W/cm 2 was applied to the rats in stimulation groups, and no stimulation was applied to the rats in the control group. The local field potentials signals in the prefrontal cortex of rats during the T-maze working memory tasks were acquired. Then the coupling differences between delta rhythm phase, theta rhythm phase and gamma rhythm amplitude of rats in different parameter stimulation groups and control group were compared. The experimental results showed that the coupling intensity of delta and gamma rhythm in stimulation groups was significantly lower than that in the control group ( P<0.05), while the coupling intensity of theta and gamma rhythm was significantly higher than that in the control group ( P<0.05). With the increase of stimulation parameters, the degree of coupling between delta and gamma rhythm showed a decreasing trend, while the degree of coupling between theta and gamma rhythm tended to increase. The preliminary results of this paper indicated that transcranial magneto-acoustic-electrical stimulation inhibited delta rhythmic neuronal activity and enhanced the oscillation of theta and gamma rhythm in the prefrontal cortex, thus promoted the exchange and transmission of information between neuronal clusters in different spatial scales. This lays the foundation for further exploring the mechanism of transcranial magneto-acoustic-electrical stimulation in regulating brain memory function.

LFP Analysis of Brain Injured Anesthetized Animals Undergoing Closed-Loop Intracortical Stimulation.

Activity dependent stimulation (ADS) is a closed loop stimulation technique whose neurophysiological effects have not been deeply investigated. Here we explored how Local field Potentials (LFP) are impacted by a focal ischemic lesion and, subsequently, by ADS treatment. Intracortical microelectrode arrays were implanted in the rostral forelimb area (RFA) and in the primary somatosensory area (S1) of anaesthetized rats. An ischemic injury was induced in the caudal forelimb area through microinjections of Endothelin-1. The lesion induced an acute depressive trend in LFP power in RFA (evaluated in 6 bands of interest: Delta (1–4Hz), Theta (4–8Hz), Alpha (8–11Hz), Beta (11–30Hz), LowGamma (30–55Hz) and HighGamma (55–80)) followed by a noticeable significant rebound in both areas. Applying ADS induced an overall decrease of power. The lesion impacted the connectivity in a frequency specific manner, resulting in widespread increase in connectivity in Delta both between and within areas. Two hours after the lesion, without stimulation, correlated activity between areas increased in Beta and Gamma. After stimulation, inter-area connectivity increased in Delta, Theta and Alpha, while considerably dropping within RFA in highGamma. By computing phase-amplitude coupling, we found that the lesion produced an incremental increase in the coupling between (Theta) Alpha phase and (lowGamma) highGamma amplitude within RFA, while S1 had a more generalized increase. Likewise, coupling between Theta phase and lowGamma/highGamma amplitudes increased between areas after lesion. ADS induced a similar increase, but greater in magnitude both within and between RFA and S1. These results have important implications on the emerging field of closed-loop adaptive stimulation promoting ADS as an innovative tool for the treatment of neurological disorders.

A novel deep recurrent convolutional neural network for subthalamic nucleus localization using local field potential signals

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a well-established interventional treatment for improving motor symptoms of patients suffering from Parkinson’s disease (PD). While STN is originally localized using imaging modalities, additional intraoperative guidance such as microelectrode recording (MER) is crucial to refine the final electrode trajectory. Analysis of MER by an experienced neurophysiologist maintains good clinical outcomes, although the procedure requires long duration and jeopardizes the safety of the surgery. Lately, local field potentials (LFP) investigation has inspired the emergence of adaptive DBS and revealed beneficial perception of PD mechanisms. Several studies confronting LFP analysis to detect the anatomical borders of STN, have focused on handcrafted feature engineering, which does not certainly capture delicate differences in LFP. This study gauges the ability of deep learning to exhibit valuable insight into the electrophysiological neural rhythms of STN using LFP. A recurrent convolutional neural network (CNN) strategy is presented, where local features are extracted from LFP signals via CNN, followed by recurrent layers to aggregate the best features for classification. The proposed model outperformed the state-of-the-art techniques, yielding highest average accuracy of 96.79%. This is the first study on the analysis of LFP signals to localize STN using deep recurrent CNN. The developed model has the potential to extract high level biomarkers regarding STN region, which would boost the neurosurgeon’s confidence in adjusting the trajectory intraoperatively for optimal lead implantation. LFP is a robust guidance tool and could be an alternative solution to the current scenario using MER.

Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson's disease.

Parkinson’s disease motor symptoms are associated with an increase in subthalamic nucleus beta band oscillatory power. However, these oscillations are phasic, and there is a growing body of evidence suggesting that beta burst duration may be of critical importance to motor symptoms. This makes insights into the dynamics of beta bursting generation valuable, in particular to refine closed-loop deep brain stimulation in Parkinson’s disease. In this study, we ask the question “Can average burst duration reveal how dynamics change between the ON and OFF medication states?”. Our analysis of local field potentials from the subthalamic nucleus demonstrates using linear surrogates that the system generating beta oscillations is more likely to act in a non-linear regime OFF medication and that the change in a non-linearity measure is correlated with motor impairment. In addition, we pinpoint the simplest dynamical changes that could be responsible for changes in the temporal patterning of beta oscillations between medication states by fitting to data biologically inspired models, and simpler beta envelope models. Finally, we show that the non-linearity can be directly extracted from average burst duration profiles under the assumption of constant noise in envelope models. This reveals that average burst duration profiles provide a window into burst dynamics, which may underlie the success of burst duration as a biomarker. In summary, we demonstrate a relationship between average burst duration profiles, dynamics of the system generating beta oscillations, and motor impairment, which puts us in a better position to understand the pathology and improve therapies such as deep brain stimulation.

Characterization of exploratory patterns and hippocampal–prefrontal network oscillations during the emergence of free exploration

During free exploration, the emergence of patterned and sequential behavioral responses to an unknown environment reflects exploration traits and adaptation. However, the behavioral dynamics and neural substrates underlying the exploratory behavior remain poorly understood. We developed computational tools to quantify the exploratory behavior and performed in vivo electrophysiological recordings in a large arena in which mice made sequential excursions into unknown territory. Occupancy entropy was calculated to characterize the cumulative and moment-to-moment behavioral dynamics in explored and unexplored territories. Local field potential analysis revealed that the theta activity in the dorsal hippocampus (dHPC) was highly correlated with the occupancy entropy. Individual dHPC and prefrontal cortex (PFC) oscillatory activities could classify various aspects of free exploration. Initiation of exploration was accompanied by a coordinated decrease and increase in theta activity in PFC and dHPC, respectively. Our results indicate that dHPC and PFC work synergistically in shaping free exploration by modulating exploratory traits during emergence and visits to an unknown environment.

Longitudinal analysis of local field potentials recorded from directional deep brain stimulation lead implants in the subthalamic nucleus

Objective. The electrode–tissue interface surrounding a deep brain stimulation (DBS) lead is known to be highly dynamic following implantation, which may have implications on the interpretation of intraoperatively recorded local field potentials (LFPs). We characterized beta-band LFP dynamics following implantation of a directional DBS lead in the sensorimotor subthalamic nucleus (STN), which is a primary target for treating Parkinson’s disease. Approach. Directional STN-DBS leads were implanted in four healthy, non-human primates. LFPs were recorded over two weeks and again 1–4 months after implantation. Impedance was measured for two weeks post-implant without stimulation to compare the reactive tissue response to changes in LFP oscillations. Beta-band (12–30 Hz) peak power was calculated from the LFP power spectra using both common average referencing (CAR) and intra-row bipolar referencing (IRBR). Results. Resting-state LFPs in two of four subjects revealed a steady increase of beta power over the initial two weeks post-implant whereas the other two subjects showed variable changes over time. Beta power variance across days was significantly larger in the first two weeks compared to 1–4 months post-implant in all three long-term subjects. Further, spatial maps of beta power several hours after implantation did not correlate with those measured two weeks or 1–4 months post-implant. CAR and IRBR beta power correlated across short- and long-term time points. However, depending on the time period, subjects showed a significant bias towards larger beta power using one referencing scheme over the other. Lastly, electrode–tissue impedance increased over the two weeks post-implant but showed no significant correlation to beta power. Significance. These results suggest that beta power in the STN may undergo significant changes following DBS lead implantation. DBS lead diameter and electrode recording configurations can affect the post-implant interpretation of oscillatory features. Such insights will be important for extrapolating results from intraoperative and externalized LFP recordings.

Adaptive changes in local field potential oscillation associated with morphine conditioned place preference in mice

Neural adaptation associated with formation of morphine conditioned place preference remained largely unexplored. This study monitored longitudinal changes in neural signaling during pre-conditioning, conditioning and post-conditioning periods of morphine conditioned place preference (CPP) paradigm for investigation of adaptive mechanisms of opiate addiction. Male Swiss albino mice implanted with intracranial electrodes into the nucleus accumbens (NAc), striatum (STr) and hippocampus (HC) were used for recording of local field potentials (LFPs). Animals received a 10-day schedule for associative learning to pair the specific compartment of the chamber with morphine effects. Exploratory behavior and LFP signals were recorded during pre-conditioning (baseline level), conditioning (day 1, 5 and 10) and post-conditioning (day 1, 4 and 7) periods. Repeated measures one-way ANOVA followed by Tukey test revealed significant increases in number of visit and time spent in morphine compartment during post-conditioning days. Frequency analysis of LFP highlighted the increases in alpha activity (12 – 18 Hz) in the NAc from post-conditioning day 1 until day 7. Moreover, significantly increased coherent activities between the pair of NAc-HC were developed within gamma frequency range (35 – 42 Hz) on morphine conditioning day 10 and disappeared during post-conditioning days. Taken together, these findings emphasized NAc LFP signaling and neural connectivities between the NAc and HC associated with morphine CPP. These adaptive changes might underlie the formation of morphine conditioned place preference and behavioral consequences such as craving and relapse.

Steady state evoked potential (SSEP) responses in the primary and secondary somatosensory cortices of anesthetized cats: Nonlinearity characterized by harmonic and intermodulation frequencies

When presented with an oscillatory sensory input at a particular frequency, F [Hz], neural systems respond with the corresponding frequency, f [Hz], and its multiples. When the input includes two frequencies (F1 and F2) and they are nonlinearly integrated in the system, responses at intermodulation frequencies (i.e., n1*f1+n2*f2 [Hz], where n1 and n2 are non-zero integers) emerge. Utilizing these properties, the steady state evoked potential (SSEP) paradigm allows us to characterize linear and nonlinear neural computation performed in cortical neurocircuitry. Here, we analyzed the steady state evoked local field potentials (LFPs) recorded from the primary (S1) and secondary (S2) somatosensory cortex of anesthetized cats (maintained with alfaxalone) while we presented slow (F1 = 23Hz) and fast (F2 = 200Hz) somatosensory vibration to the contralateral paw pads and digits. Over 9 experimental sessions, we recorded LFPs from N = 1620 and N = 1008 bipolar-referenced sites in S1 and S2 using electrode arrays. Power spectral analyses revealed strong responses at 1) the fundamental (f1, f2), 2) its harmonic, 3) the intermodulation frequencies, and 4) broadband frequencies (50-150Hz). To compare the computational architecture in S1 and S2, we employed simple computational modeling. Our modeling results necessitate nonlinear computation to explain SSEP in S2 more than S1. Combined with our current analysis of LFPs, our paradigm offers a rare opportunity to constrain the computational architecture of hierarchical organization of S1 and S2 and to reveal how a large-scale SSEP can emerge from local neural population activities.

MER based analysis of local field potentials with deep brain stimulation subthalamic nucleus in Parkinson\'s disease using coherence and entropy techniques

Deep brain stimulation (DBS) is a device-based well-developed and well-established innovative frontier surgical-therapeutic method which reduces the symptoms of Parkinson‘s disease (PD) and restores and increases the motor-functioning. DBS gives a unique-opportunity to study the electricaloscillatory( harmonic-ripples) neural-activity of various sub-cortical-structures in PD-subjects. However, the electrically-stimulating local field potentials (LFPs) are fundamentally concerned during subthalamicnuclei (STN) recording. The fluctuations, measured to signify collective neuronal-discharge from neurons surrounding the electrode. The acquisition of extracellular activity of irregular-patterns of STN-activity typically acquired from a population-of-neurons detected as” local field potentials” has discard luminosity on the pathophysiology and seizes the latent to pilot to elegance in modern DBS management. The recordings are often gathered with either intraoperative microelectrode for neuronal-activity and/or DBSleads for chronic-macro-stimulation and reflect oscillatory-activity within nuclei of the basal-ganglia (BG) and thalamic-targets for diagnosing PD. LFP-recordings have numerous clinical implications and presently used to optimize DBS outcomes in closed-loop adaptive-devices/systems. However, the origins of the LFPs are implied softly and implicitly. Thus, the goal of this present study is to analyze LFP recordings within the milieu of clinical-applications for clinical-significancy and this goal is attained with frequency analysis ranging the band from 1Hz-250Hz and coherence band between 0 and 1 level. The results of the study suggest that the spatial-reach of the LFP can extend several millimeters. This study presents a comprehensive investigation into the existing research which gives insights into the origin of LFP-signals and identify the variables that need to be considered when analyzing LFP-signals in clinical settings principally

Complete sleep and local field potential analysis regarding estrus cycle, pregnancy, postpartum and post-weaning periods and homeostatic sleep regulation in female rats

Sleep and local field potential (LFP) characteristics were addressed during the reproductive cycle in female rats using long-term (60–70 days) recordings. Changes in homeostatic sleep regulation was tested by sleep deprivation (SDep). The effect of mother-pup separation on sleep was also investigated during the postpartum (PP) period. First half of the pregnancy and early PP period showed increased wakefulness (W) and higher arousal indicated by elevated beta and gamma activity. Slow wave sleep (SWS) recovery was suppressed while REM sleep replacement was complete after SDep in the PP period. Pup separation decreased maternal W during early-, but increased during middle PP while did not affect during late PP. More W, less SWS, higher light phase beta activity but lower gamma activity was seen during the post-weaning estrus cycle compared to the virgin one. Maternal sleep can be governed by the fetuses/pups needs and their presence, which elevate W of mothers. Complete REM sleep- and incomplete SWS replacement after SDep in the PP period may reflect the necessity of maternal REM sleep for the offspring while SWS increase may compete with W essential for maternal care. Maternal experience may cause sleep and LFP changes in the post-weaning estrus cycle.

Modeling dependence via copula of functionals of Fourier coefficients

The goal of this paper is to develop a measure for characterizing complex dependence between time series that cannot be captured by traditional measures such as correlation and coherence. Our approach is to use copula models of functionals of the Fourier coefficients which is a generalization of coherence. Here, we use standard parametric copula models with a single parameter from both elliptical and Archimedean families. Our approach is to analyze changes in activity in local field potentials in the rat cortex prior to and immediately following the onset of stroke. We present the necessary theoretical background, the multivariate models and an illustration of our methodology on these local field potential data. Simulations with nonlinear dependent data reveal that there is information that is missed by not taking into account dependence on specific frequencies. Moreover, these simulations demonstrate how our proposed method captures more complex nonlinear dependence between time series. Finally, we illustrate our copula-based approach in the analysis of local field potentials of rats.

Online analysis of local field potentials for seizure detection in freely moving rats.

Seizure detection during online recording of electrophysiological parameters is very important in epileptic patients. In the present study, online analysis of field potential recordings was used for detecting spontaneous seizures in epileptic animals. Epilepsy was induced in rats by pilocarpine injection. During the chronic period of the pilocarpine model, local field potential (LFP) recording was run for at least 24 hr. At the same time, video monitoring of the animals was done to determine the real time of seizure occurrence. Both power and sample entropy of LFP were used for online analysis. Obtained results showed that changes in LFP power are a better index for seizure detection. In addition, when we used one hundred consecutive epochs (each epoch equals 10 ms) of LFP for data analysis, the best detection was achieved. It may be suggested that power is a suitable parameter for online analysis of LFP in order to detect the spontaneous seizures correctly.