An improved screw-free method for electrode implantation and intracranial electroencephalographic recordings in mice

A versatile system for neuromuscular stimulation and recording in the mouse model using a lightweight magnetically coupled headmount

Neural stimulation and recording in rodents are common methods to better understand the nervous system and improve the quality of life of individuals who are suffering from neurological disorders (e.g., epilepsy), as well as for permanent reduction of chronic pain in patients with neuropathic pain and spinal-cord injury. This method requires a neural interface (e.g., a headmount) to couple the implanted neural device with instrumentation system. The size and the total weight of such headmounts should be designed in a way to minimize its effect on the movement of the animal. This is a crucial factor in gait, kinematic, and behavioral neuroscience studies of freely moving mice. Here we introduce a lightweight 'snap-in' electro-magnetic headmount that is extremely small, and uses strong neodymium magnetics to enable a reliable connection without sacrificing the lightweight of the device. Additionally, the headmount requires minimal surgical intervention during the implantation, resulting in minimal tissue damage. The device has demonstrated itself to be robust, and successfully provided direct electrical stimulation of nerve and electrical muscle stimulation and recording, as well as powering implanted LEDs for optogenetic use scenarios.

Visual Evoked Potential Recordings in Mice Using a Dry Non-invasive Multi-channel Scalp EEG Sensor

For scalp EEG research environments with laboratory mice, we designed a dry-type 16 channel EEG sensor which is non-invasive, deformable, and re-usable because of the plunger-spring-barrel structural facet and mechanical strengths resulting from metal materials. The whole process for acquiring the VEP responses in vivo from a mouse consists of four steps: (1) sensor assembly, (2) animal preparation, (3) VEP measurement, and (4) signal processing. This paper presents representative measurements of VEP responses from multiple mice with a submicro-voltage signal resolution and sub-hundred millisecond temporal resolution. Although the proposed method is safer and more convenient compared to other previously reported animal EEG acquiring methods, there are remaining issues including how to enhance the signal-to-noise ratio and how to apply this technique with freely moving animals. The proposed method utilizes easily available resources and shows a repetitive VEP response with a satisfactory signal quality. Therefore, this method could be utilized for longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms.

Development and Experimental Validation of a Dry Non-Invasive Multi-Channel Mouse Scalp EEG Sensor through Visual Evoked Potential Recordings

In this paper, we introduce a dry non-invasive multi-channel sensor for measuring brainwaves on the scalps of mice. The research on laboratory animals provide insights to various practical applications involving human beings and other animals such as working animals, pets, and livestock. An experimental framework targeting the laboratory animals has the potential to lead to successful translational research when it closely resembles the environment of real applications. To serve scalp electroencephalography (EEG) research environments for the laboratory mice, the dry non-invasive scalp EEG sensor with sixteen electrodes is proposed to measure brainwaves over the entire brain area without any surgical procedures. We validated the proposed sensor system with visual evoked potential (VEP) experiments elicited by flash stimulations. The VEP responses obtained from experiments are compared with the existing literature, and analyzed in temporal and spatial perspectives. We further interpret the experimental results using time-frequency distribution (TFD) and distance measurements. The developed sensor guarantees stable operations for in vivo experiments in a non-invasive manner without surgical procedures, therefore exhibiting a high potential to strengthen longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms.

Prediction of antiepileptic drug treatment outcomes using machine learning

OBJECTIVE

Antiepileptic drug (AED) treatments produce inconsistent outcomes, often necessitating patients to go through several drug trials until a successful treatment can be found. This study proposes the use of machine learning techniques to predict epilepsy treatment outcomes of commonly used AEDs.

APPROACH

Machine learning algorithms were trained and evaluated using features obtained from intracranial electroencephalogram (iEEG) recordings of the epileptiform discharges observed in Mecp2-deficient mouse model of the Rett Syndrome. Previous work have linked the presence of cross-frequency coupling (I _CFC) of the delta (2-5 Hz) rhythm with the fast ripple (400-600 Hz) rhythm in epileptiform discharges. Using the I _CFC to label post-treatment outcomes we compared support vector machines (SVMs) and random forest (RF) machine learning classifiers for providing likelihood scores of successful treatment outcomes.

MAIN RESULTS

(a) There was heterogeneity in AED treatment outcomes, (b) machine learning techniques could be used to rank the efficacy of AEDs by estimating likelihood scores for successful treatment outcome, (c) I _CFC features yielded the most effective a priori identification of appropriate AED treatment, and (d) both classifiers performed comparably.

SIGNIFICANCE

Machine learning approaches yielded predictions of successful drug treatment outcomes which in turn could reduce the burdens of drug trials and lead to substantial improvements in patient quality of life.

Support vector machines using EEG features of cross-frequency coupling can predict treatment outcome in Mecp2-deficient mice

Anti-convulsive drug treatments of epilepsy typically produce varied outcomes from one patient to the next, often necessitating patients to go through several anticonvulsive drug trials until an appropriate treatment is found. The focus of this study is to predict treatment outcome using a priori electroencephalogram (EEG) features for a rare genetic model of epilepsy seen in patients with Rett Syndrome. Previous work on Mecp2-deficient mice, exhibiting the symptoms of Rett syndrome, have revealed EEG-based biomarkers that track the pathology well. Specifically the presence of cross-frequency coupling of the delta-like (3-6 Hz) frequency range phase with the fast ripple (400 - 600 Hz) frequency range amplitude in long duration discharges was found to track seizure pathology. Support Vector Machines (SVM) were trained with features generated from phase-amplitude comodulograms and tested on (n=6) Mecp2-deficient mice to predict treatment outcome to Midazolam, a commonly used anti-convulsive drug. Using SVMs it was shown that it is possible to generate a likelihood score to predict treatment outcomes on all of the animal subjects. Identifying the most appropriate treatment a priori would potentially lead to improved treatment outcomes.

Characterization of HFOs in short and long duration discharges recorded from in-vivo MeCP2-deficient mice

Mutations in the X-linked gene encoding methyl CpG-binding protein 2 (MeCP2) have been linked to a neurodevelopmental disorder known as Rett syndrome. The disorder is associated with a number of symptoms, of which epileptic seizures are common. In this study we examined the presence of high frequency oscillations (HFOs) and their interactions with low frequency oscillations (LFOs) during epileptiform-like discharges using intracranial electroencephalogram (iEEG) recordings from male and female Mecp2-deficient mice. The study compared differences in mean HFO power levels normalized to baseline along with LFO-HFO modulation observed in short and long duration discharges. Short duration discharges, common to both male and female Mecp2-deficient mice, showed a decrease in mean HFO power levels compared to baseline levels. During the short duration discharges the theta (7-9 Hz) LFOs were found to modulate fast ripple (350-500 Hz) HFOs predominantly in the female Mecp2-deficient mice. Long duration discharges, predominantly observed in male Mecp2-deficient mice, were found to have elevated mean power levels in the ripple (80-200 Hz) and fast ripple (350-500 Hz) frequency ranges when compared to baseline. During the long duration discharges a lower frequency range theta LFO (4-6 Hz) modulated both the ripple (80-200 Hz) and fast ripple (350-500 Hz) HFOs. These findings suggest that the long duration discharges observed in male Mecp2-deficient mice share biomarkers indicative of seizure-like activity.

A step-wise approach to deep brain stimulation in mice

BACKGROUND

Studies of deep brain stimulation (DBS) in mice are rare due to their small size, agility, aversion to handling, and high anxiety compared to larger species. Studying DBS modulation of neural circuitry in murine models of human behavior may ensure safety, guide stimulatory parameters for clinical trials in humans, and inform a long-eluded mechanism.

METHODS

Stereotactic deep brain electrode implantation in a mouse is performed. Mechanical etching of the skull with a high-speed drill is used with placement of cyanoacrylate glue and molding of dental acrylate to affix the electrode in place. Stimulation experiments are conducted in the home cage after a habituation period. After testing is complete, electrode placement is verified in fixed tissue.

RESULTS

Electrodes can be safely and accurately implanted in mice for DBS experimentation. Previous findings demonstrated accuracy in placement within the nucleus accumbens shell of 93 % [14]. In this study, there were no hardware malfunctions that required interrupting experimentation.

CONCLUSIONS

Stereotactic DBS studies may be safely and effectively performed in mice to investigate neuropsychiatric disorders. In addition, examining the biochemical and molecular mechanisms underlying these disorders may be facilitated by widely available transgenic mouse lines and the Cre-Lox recombination system.

A reliable method for intracranial electrode implantation and chronic electrical stimulation in the mouse brain

BACKGROUND

Electrical stimulation of brain structures has been widely used in rodent models for kindling or modeling deep brain stimulation used clinically. This requires surgical implantation of intracranial electrodes and subsequent chronic stimulation in individual animals for several weeks. Anchoring screws and dental acrylic have long been used to secure implanted intracranial electrodes in rats. However, such an approach is limited when carried out in mouse models as the thin mouse skull may not be strong enough to accommodate the anchoring screws. We describe here a screw-free, glue-based method for implanting bipolar stimulating electrodes in the mouse brain and validate this method in a mouse model of hippocampal electrical kindling.

METHODS

Male C57 black mice (initial ages of 6-8 months) were used in the present experiments. Bipolar electrodes were implanted bilaterally in the hippocampal CA3 area for electrical stimulation and electroencephalographic recordings. The electrodes were secured onto the skull via glue and dental acrylic but without anchoring screws. A daily stimulation protocol was used to induce electrographic discharges and motor seizures. The locations of implanted electrodes were verified by hippocampal electrographic activities and later histological assessments.

RESULTS

Using the glue-based implantation method, we implanted bilateral bipolar electrodes in 25 mice. Electrographic discharges and motor seizures were successfully induced via hippocampal electrical kindling. Importantly, no animal encountered infection in the implanted area or a loss of implanted electrodes after 4-6 months of repetitive stimulation/recording.

CONCLUSION

We suggest that the glue-based, screw-free method is reliable for chronic brain stimulation and high-quality electroencephalographic recordings in mice. The technical aspects described this study may help future studies in mouse models.

Low frequency-modulated high frequency oscillations in seizure-like events recorded from in-vivo MeCP2-deficient mice

Rett syndrome is a neurodevelopmental condition caused by mutations in the gene encoding methyl CpG-binding protein 2 (MeCP2). Seizures are often associated with Rett syndrome and can be observed in intracranial electroencephalogram (iEEG) recordings. To date most studies have focused on the low frequencies oscillations (LFOs), however recent findings in epilepsy studies link high frequency oscillations (HFOs) with epileptogenesis. In this study, we examine the presence of HFOs in the male and female MeCP2-deficient mouse models of Rett syndrome and their interaction with the LFOs present during seizure-like events (SLEs). Our findings indicate that HFOs (200-600 Hz) are present during the SLEs and in addition, we reveal strong phase-amplitude coupling between LFOs (6-10 Hz) and HFOs (200-600 Hz) during female SLEs in the MeCP2-deficient mouse model.