Dipole source localization of mouse electroencephalogram using the Fieldtrip toolbox

Reliability of Upper Limb Pin-Prick Stimulation With Electroencephalography: Evoked Potentials, Spectra and Source Localization

In order for electroencephalography (EEG) with sensory stimuli measures to be used in research and neurological clinical practice, demonstration of reliability is needed. However, this is rarely examined. Here we studied the test-retest reliability of the EEG latency and amplitude of evoked potentials and spectra as well as identifying the sources during pin-prick stimulation. We recorded EEG in 23 healthy older adults who underwent a protocol of pin-prick stimulation on the dominant and non-dominant hand. EEG was recorded in a second session with rest intervals of 1 week. For EEG electrodes Fz, Cz, and Pz peak amplitude, latency and frequency spectra for pin-prick evoked potentials was determined and test-retest reliability was assessed. Substantial reliability ICC scores (0.76-0.79) were identified for evoked potential negative-positive amplitude from the left hand at C4 channel and positive peak latency when stimulating the right hand at Cz channel. Frequency spectra showed consistent increase of low-frequency band activity (< 5 Hz) and also in theta and alpha bands in first 0.25 s. Almost perfect reliability scores were found for activity at both low-frequency and theta bands (ICC scores: 0.81-0.98). Sources were identified in the primary somatosensory and motor cortices in relation to the positive peak using s-LORETA analysis. Measuring the frequency response from the pin-prick evoked potentials may allow the reliable assessment of central somatosensory impairment in the clinical setting.

Nine-day continuous recording of EEG and 2-hour of high-density EEG under chronic sleep restriction in mice

This work provides an EEG dataset collected from nine mice during the sleep deprivation (SD) paradigm for the sleep science community. It includes 9-day of continuous recording of the frontal and parietal EEG, accelerometer, and 2-hour of high-density EEG (HD-EEG) under SD and SD-free conditions. Eighteen hours of SD were conducted on 5 consecutive days. The HD-EEG data were saved in the EEGLAB format and stored as the brain imaging data structure (BIDS). These datasets can be used to (i) compare mouse HD-EEG to human HD-EEG, (ii) track oscillatory activities of the sleep EEG (e.g., slow waves, spindles) across the cortical regions under different conditions of sleep pressure, and (iii) investigate the cortical traveling waves in the mouse brain. We also provided Python code for basic analyses of this dataset, including the detection of slow waves and sleep spindles. We hope that our dataset will reveal hidden activities during sleep and lead to a better understanding of the functions and mechanisms of sleep.

Electrical Source Imaging in Freely Moving Rats: Evaluation of a 12-Electrode Cortical Electroencephalography System

This work presents and evaluates a 12-electrode intracranial electroencephalography system developed at the National Institute of Mental Health (Klecany, Czech Republic) in terms of an electrical source imaging (ESI) technique in rats. The electrode system was originally designed for translational research purposes. This study demonstrates that it is also possible to use this well-established system for ESI, and estimates its precision, accuracy, and limitations. Furthermore, this paper sets a methodological basis for future implants. Source localization quality is evaluated using three approaches based on surrogate data, physical phantom measurements, and in vivo experiments. The forward model for source localization is obtained from the FieldTrip-SimBio pipeline using the finite-element method. Rat brain tissue extracted from a magnetic resonance imaging template is approximated by a single-compartment homogeneous tetrahedral head model. Four inverse solvers were tested: standardized low-resolution brain electromagnetic tomography, exact low-resolution brain electromagnetic tomography (eLORETA), linear constrained minimum variance (LCMV), and dynamic imaging of coherent sources. Based on surrogate data, this paper evaluates the accuracy and precision of all solvers within the brain volume using error distance and reliability maps. The mean error distance over the whole brain was found to be the lowest in the eLORETA solution through signal to noise ratios (SNRs) (0.2 mm for 25 dB SNR). The LCMV outperformed eLORETA under higher SNR conditions, and exhibiting higher spatial precision. Both of these inverse solvers provided accurate results in a phantom experiment (1.6 mm mean error distance across shallow and 2.6 mm across subcortical testing dipoles). Utilizing the developed technique in freely moving rats, an auditory steady-state response experiment provided results in line with previously reported findings. The obtained results support the idea of utilizing a 12-electrode system for ESI and using it as a solid basis for the development of future ESI dedicated implants.

High-density EEG of auditory steady-state responses during stimulation of basal forebrain parvalbumin neurons

We present high-density EEG datasets of auditory steady-state responses (ASSRs) recorded from the cortex of freely moving mice with or without optogenetic stimulation of basal forebrain parvalbumin (BF-PV) neurons, known as a subcortical hub circuit for the global workspace. The dataset of ASSRs without BF-PV stimulation (dataset 1) contains raw 36-channel EEG epochs of ASSRs elicited by 10, 20, 30, 40, and 50 Hz click trains and time stamps of stimulations. The dataset of ASSRs with BF-PV stimulation (dataset 2) contains raw 36-channel EEG epochs of 40-Hz ASSRs during BF-PV stimulation with latencies of 0, 6.25, 12.5, and 18.75 ms and time stamps of stimulations. We provide the datasets and step-by-step tutorial analysis scripts written in Python, allowing for descriptions of the event-related potentials, spectrograms, and the topography of power. We complement this experimental dataset with simulation results using a time-dependent perturbation on coupled oscillators. This publicly available dataset will be beneficial to the experimental and computational neuroscientists.

Measurement(s)	functional brain measurement • response to auditory stimulus
Technology Type(s)	electroencephalography (EEG)
Factor Type(s)	stimulation frequency • optogenetic stimulation of basal forebrain parvalbumin neurons
Sample Characteristic - Organism	Mus musculus

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12758720

Optogenetic stimulation of basal forebrain parvalbumin neurons modulates the cortical topography of auditory steady-state responses

High-density electroencephalographic (hdEEG) recordings are widely used in human studies to determine spatio-temporal patterns of cortical electrical activity. How these patterns of activity are modulated by subcortical arousal systems is poorly understood. Here, we couple selective optogenetic stimulation of a defined subcortical cell-type, basal forebrain (BF) parvalbumin (PV) neurons, with hdEEG recordings in mice (Opto-hdEEG). Stimulation of BF PV projection neurons preferentially generated time-locked gamma oscillations in frontal cortices. BF PV gamma-frequency stimulation potently modulated an auditory sensory paradigm used to probe cortical function in neuropsychiatric disorders, the auditory steady-state response (ASSR). Phase-locked excitation of BF PV neurons in advance of 40 Hz auditory stimuli enhanced the power, precision and reliability of cortical responses, and the relationship between responses in frontal and auditory cortices. Furthermore, synchronization within a frontal hub and long-range cortical interactions were enhanced. Thus, phasic discharge of BF PV neurons changes cortical processing in a manner reminiscent of global workspace models of attention and consciousness.

A Novel Visualization Method for Sleep Spindles Based on Source Localization of High Density EEG

Equivalent dipole source localization is a well-established approach to localizing the electrical activity in electroencephalogram (EEG). So far, source localization has been used primarily in localizing the epileptic source in human epileptic patients. Currently, source localization techniques have been applied to account for localizing epileptic source among the epileptic patients. Here, we present the first application of source localization in the field of sleep spindle in mouse brain. The spatial distribution of cortical potential was obtained by high density EEG and then the anterior and posterior sleep spindles were classified based on the K-mean clustering algorithm. To solve the forward problem, a realistic geometry brain model was produced based on boundary element method (BEM) using mouse MRI. Then, we applied four different source estimation algorithms (minimum norm, eLORETA, sLORETA, and LORETA) to estimate the spatial location of equivalent dipole source of sleep spindles. The estimated sources of anterior and posterior spindles were plotted in a cine-mode that revealed different topographic patterns of spindle propagation. The characterization of sleep spindles may be better be distinguished by our novel visualization method.

Pharmaco-EEG Studies in Animals: A History-Based Introduction to Contemporary Translational Applications

Current research on the effects of pharmacological agents on human neurophysiology finds its roots in animal research, which is also reflected in contemporary animal pharmaco-electroencephalography (p-EEG) applications. The contributions, present value and translational appreciation of animal p-EEG-based applications are strongly interlinked with progress in recording and neuroscience analysis methodology. After the pioneering years in the late 19th and early 20th century, animal p-EEG research flourished in the pharmaceutical industry in the early 1980s. However, around the turn of the millennium the emergence of structurally and functionally revealing imaging techniques and the increasing application of molecular biology caused a temporary reduction in the use of EEG as a window into the brain for the prediction of drug efficacy. Today, animal p-EEG is applied again for its biomarker potential - extensive databases of p-EEG and polysomnography studies in rats and mice hold EEG signatures of a broad collection of psychoactive reference and test compounds. A multitude of functional EEG measures has been investigated, ranging from simple spectral power and sleep-wake parameters to advanced neuronal connectivity and plasticity parameters. Compared to clinical p-EEG studies, where the level of vigilance can be well controlled, changes in sleep-waking behaviour are generally a prominent confounding variable in animal p-EEG studies and need to be dealt with. Contributions of rodent pharmaco-sleep EEG research are outlined to illustrate the value and limitations of such preclinical p-EEG data for pharmacodynamic and chronopharmacological drug profiling. Contemporary applications of p-EEG and pharmaco-sleep EEG recordings in animals provide a common and relatively inexpensive window into the functional brain early in the preclinical and clinical development of psychoactive drugs in comparison to other brain imaging techniques. They provide information on the impact of drugs on arousal and sleep architecture, assessing their neuropharmacological characteristics in vivo, including central exposure and information on kinetics. In view of the clear disadvantages as well as advantages of animal p-EEG as compared to clinical p-EEG, general statements about the usefulness of EEG as a biomarker to demonstrate the translatability of p-EEG effects should be made with caution, however, because they depend on the particular EEG or sleep parameter that is being studied. The contribution of animal p-EEG studies to the translational characterisation of centrally active drugs can be furthered by adherence to guidelines for methodological standardisation, which are presently under construction by the International Pharmaco-EEG Society (IPEG).

Precaution for volume conduction in rodent cortical electroencephalography using high-density polyimide-based microelectrode arrays on the skull

In humans, significant progress has been made to link spatial changes in electroencephalographic (EEG) spectral density, connectivity strength, and phase-amplitude modulation to neurological, physiological, and psychological correlates. In contrast, standard rodent EEG techniques employ only few electrodes, which results in poor spatial resolution. Recently, a technique was developed to overcome this limitation in mice. This technique was based on a polyimide-based microelectrode (PBM) array applied on the mouse skull, maintaining a significant number of electrodes with consistent contact, electrode impedance, and mechanical stability. The present study built on this technique by extending it to rats. Therefore, a similar PBM array, but adapted to rats, was designed and fabricated. In addition, this array was connected to a wireless EEG headstage, allowing recording in untethered, freely moving rats. The advantage of a high-density array relies on the assumption that the signal recorded from the different electrodes is generated from distinct sources, i.e., not volume-conducted. Therefore, the utility and validity of the array were evaluated by determining the level of synchrony between channels due to true synchrony or volume conduction during basal vigilance states and following a subanesthetic dose of ketamine. Although the PBM array allowed recording with high signal quality, under both drug and drug-free conditions, high synchronization existed due to volume conduction between the electrodes even in the higher spectral frequency range. Discrimination existed only between frontally and centrally/distally grouped electrode pairs. Therefore, caution should be used in interpreting spatial data obtained from high-density PBM arrays in rodents.

Hydrodynamic assembly of conductive nanomesh of single-walled carbon nanotubes using biological glue

A hydrodynamic phenomenon is used to assemble a large-scale conductive nanomesh of single-walled carbon nanotubes (SWNTs) with exceptional control of the nanostructure. This is accomplished by a biological material with nanoscale features and a strong binding affinity toward SWNTs. The biological material also presents a unique glue effect for the assembly. Unprecedented material characteristics are observed for the nanomesh.

Characterization of topographically specific sleep spindles in mice

STUDY OBJECTIVE

Sleep spindles in humans have been classified as slow anterior and fast posterior spindles; recent findings indicate that their profiles differ according to pharmacology, pathology, and function. However, little is known about the generation mechanisms within the thalamocortical system for different types of spindles. In this study, we aim to investigate the electrophysiological behaviors of the topographically distinctive spindles within the thalamocortical system by applying high-density EEG and simultaneous thalamic LFP recordings in mice.

DESIGN

32-channel extracranial EEG and 2-channel thalamic LFP were recorded simultaneously in freely behaving mice to acquire spindles during spontaneous sleep.

SUBJECTS

Hybrid F1 male mice of C57BL/6J and 129S4/svJae.

MEASUREMENTS AND RESULTS

Spindle events in each channel were detected by spindle detection algorithm, and then a cluster analysis was applied to classify the topographically distinctive spindles. All sleep spindles were successfully classified into 3 groups: anterior, posterior, and global spindles. Each spindle type showed distinct thalamocortical activity patterns regarding the extent of similarity, phase synchrony, and time lags between cortical and thalamic areas during spindle oscillation. We also found that sleep slow waves were likely to associate with all types of sleep spindles, but also that the ongoing cortical decruitment/ recruitment dynamics before the onset of spindles and their relationship with spindle generation were also variable, depending on the spindle types.

CONCLUSION

Topographically specific sleep spindles show distinctive thalamocortical network behaviors.