scholarly journals High-density EEG Recordings of the Freely Moving Mice using Polyimide-based Microelectrode

10.3791/2562 ◽  
2011 ◽  
Author(s):  
Mina Lee ◽  
Dongwook Kim ◽  
Hee-Sup Shin ◽  
Ho-Geun Sung ◽  
Jee Hyun Choi
Keyword(s):  
High Density ◽  
Freely Moving ◽  
Eeg Recordings

scholarly journals 0446 A Novel System for Enabling High-Density EEG Recordings in a Mouse

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A170-A171
Author(s):  
S Thankachan ◽  
L Gerashchenko ◽  
D Gerashchenko
Keyword(s):  
Signal Generator ◽  
High Density ◽  
Electrode Arrays ◽  
Neuroscience Research ◽  
Different Types ◽  
Mems Technology ◽  
Freely Moving ◽  
Eeg Recordings ◽  
Micro Electromechanical System ◽  
Electrical Connections

Abstract Introduction Recent advances in micro-electromechanical system (MEMS) technology have promoted the development of microelectrode arrays (MEA) that allow high resolution recordings in neuroscience research. However, applying MEA in studies in freely moving mice remains very challenging due to the large number of electrical connections required in this type of studies. The use of commutators for a large number of connections is not practical, and headmounts/loggers placed on the animal head are too heavy for small animals such as mice. Therefore, there is a need for a better compact system for using MEA in mice. Herein, we designed such a system and successfully recorded high-density-EEG in freely moving mice. Methods We designed a system in which forty flexible ultrathin wires are connected to the headstage enclosed in a container held close to the mouse. The container also houses a logger and battery connected to the headstage. This recording system allows minimizing weighted pressure on the animal using a counterbalance, so that the animal can freely move in the cage. Results We tested the system using a signal generator and mouse EEG arrays (NeuroNexus). When potentials produced by the signal generator were recorded via the wires, recorded traces were indistinguishable from the traces that were recorded when the signal generator was connected directly to the logger. We then implanted mice with EEG electrode arrays under surgical anesthesia. The high-density EEG recordings were performed one and four weeks after the surgery. High-quality EEG signals were observed in all the channels of the 32-channel logger (SpikeGadgets) in freely moving mice. Conclusion We successfully developed and tested a novel system for enabling high-density EEG recordings in freely moving mice. We expect that this system will be useful for recording biopotentials from different types of MEA in freely moving mice. Support NIH 1R43OD023231 (LG), NIH 1RF1AG061774 (DG), and NIH 5R21NS106406 (DG)

Microdialysis of Excitatory Amino Acids During EEG Recordings in Freely Moving Rats

10.3791/58455 ◽  
2018 ◽  
Author(s):  
Marie Soukupová ◽  
Chiara Falcicchia ◽  
Francesca Lovisari ◽  
Selene Ingusci ◽  
Mario Barbieri ◽  
...  
Keyword(s):  
Amino Acids ◽  
Excitatory Amino Acids ◽  
Freely Moving Rats ◽  
Freely Moving ◽  
Eeg Recordings

scholarly journals A low-cost, multiplexedμECoG system for high-density recordings in freely moving rodents

2016 ◽  
Vol 13 (2) ◽  
pp. 026030 ◽  
Author(s):  
Michele Insanally ◽  
Michael Trumpis ◽  
Charles Wang ◽  
Chia-Han Chiang ◽  
Virginia Woods ◽  
...  
Keyword(s):  
Low Cost ◽  
High Density ◽  
Freely Moving

scholarly journals Noninvasive EEG Recordings from Freely Moving Piglets

10.3791/58226 ◽  
2018 ◽  
Author(s):  
Nora V. de Camp ◽  
Silke Dietze ◽  
Markus Klaßen ◽  
Jürgen Bergeler
Keyword(s):  
Freely Moving ◽  
Eeg Recordings

scholarly journals Contribution of ictal source imaging for localizing seizure onset zone in patients with focal epilepsy patients

Neurology ◽  
2020 ◽  
pp. 10.1212/WNL.0000000000011109
Author(s):  
Shuai Ye ◽  
Lin Yang ◽  
Yunfeng Lu ◽  
Michal T. Kucewicz ◽  
Benjamin Brinkmann ◽  
...  
Keyword(s):  
Surgical Resection ◽  
Focal Epilepsy ◽  
High Density ◽  
Concordance Rate ◽  
Added Value ◽  
Seizure Onset ◽  
Source Imaging ◽  
Intracranial Eeg ◽  
Seizure Onset Zone ◽  
Eeg Recordings

ObjectiveTo determine whether seizure onset zone can be accurately localized prior to surgical planning in focal epilepsy patients, we performed non-invasive EEG recordings and source localization analyses on 39 patients.MethodsIn a total of 39 focal epilepsy patients, we recorded and extracted 138 seizures and 1,325 interictal epileptic discharges using high-density EEG. We have investigated a novel approach for directly imaging sources of seizures and interictal spikes from high density EEG recordings, and rigorously validated it for noninvasive localization of seizure onset zone (SOZ) determined from intracranial EEG findings and surgical resection volume. Conventional source imaging analyses were also performed for comparison.ResultsIctal source imaging showed a concordance rate of 95% when compared to intracranial EEG or resection results. The average distance from estimation to seizure onset (intracranial) electrodes is 1.35 cm in patients with concordant results, and 0.74 cm to surgical resection boundary in patients with successful surgery. About 41% of the patients were found to have multiple types of interictal activities; coincidentally, a lower concordance rate and a significantly worse performance in localizing SOZ were observed in these patients.ConclusionNoninvasive ictal source imaging with high-density EEG recording can provide highly concordant results with clinical decisions obtained by invasive monitoring or confirmed by resective surgery. By means of direct seizure imaging using high-density scalp EEG recordings, the added value of ictal source imaging is particularly high in patients with complex interictal activity patterns, who may represent the most challenging cases with poor prognosis.

scholarly journals Power spectral density changes and language lateralization during covert object naming tasks measured with high-density EEG recordings

2009 ◽  
Vol 14 (1) ◽  
pp. 54-59 ◽  
Author(s):  
C. Ramon ◽  
M. Holmes ◽  
Walter J. Freeman ◽  
Maciej Gratkowski ◽  
K.J. Eriksen ◽  
...  
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
High Density ◽  
Object Naming ◽  
Language Lateralization ◽  
Power Spectral ◽  
Eeg Recordings ◽  
Naming Tasks

scholarly journals Information Optimized Multilayer Network Representation of High Density Electroencephalogram Recordings

2021 ◽  
Vol 1 ◽  
Author(s):  
Francesc Font-Clos ◽  
Benedetta Spelta ◽  
Armando D’Agostino ◽  
Francesco Donati ◽  
Simone Sarasso ◽  
...  
Keyword(s):  
Mental Health ◽  
High Density ◽  
Edge Density ◽  
Occipital Region ◽  
Health Issues ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Control Subjects ◽  
Mental Health Issues ◽  
Eeg Recordings

High-density electroencephalography (hd-EEG) provides an accessible indirect method to record spatio-temporal brain activity with potential for disease diagnosis and monitoring. Due to their highly multidimensional nature, extracting useful information from hd-EEG recordings is a complex task. Network representations have been shown to provide an intuitive picture of the spatial connectivity underlying an electroencephalogram recording, although some information is lost in the projection. Here, we propose a method to construct multilayer network representations of hd-EEG recordings that maximize their information content and test it on sleep data recorded in individuals with mental health issues. We perform a series of statistical measurements on the multilayer networks obtained from patients and control subjects and detect significant differences between the groups in clustering coefficient, betwenness centrality, average shortest path length and parieto occipital edge presence. In particular, patients with a mood disorder display a increased edge presence in the parieto-occipital region with respect to healthy control subjects, indicating a highly correlated electrical activity in that region of the brain. We also show that multilayer networks at constant edge density perform better, since most network properties are correlated with the edge density itself which can act as a confounding factor. Our results show that it is possible to stratify patients through statistical measurements on a multilayer network representation of hd-EEG recordings. The analysis reveals that individuals with mental health issues display strongly correlated signals in the parieto-occipital region. Our methodology could be useful as a visualization and analysis tool for hd-EEG recordings in a variety of pathological conditions.

scholarly journals Occipital sleep spindles predict sequence learning in a visuo-motor task

SLEEP ◽  
2021 ◽  
Author(s):  
Nicolas D Lutz ◽  
Marie Admard ◽  
Elsa Genzoni ◽  
Jan Born ◽  
Karsten Rauss
Keyword(s):  
Sequence Learning ◽  
Motor Task ◽  
Internal Models ◽  
High Density ◽  
Event Related Potential ◽  
Sleep Spindles ◽  
Future Events ◽  
Spatio Temporal ◽  
Eeg Recordings ◽  
Human Participants

Abstract Study Objectives The brain appears to use internal models to successfully interact with its environment via active predictions of future events. Both internal models and the predictions derived from them are based on previous experience. However, it remains unclear how previously encoded information is maintained to support this function, especially in the visual domain. In the present study, we hypothesized that sleep consolidates newly encoded spatio-temporal regularities to improve predictions afterwards. Methods We tested this hypothesis using a novel sequence-learning paradigm that aimed to dissociate perceptual from motor learning. We recorded behavioral performance and high-density electroencephalography (EEG) in male human participants during initial training and during testing two days later, following an experimental night of sleep (n = 16, including high-density EEG recordings) or wakefulness (n = 17). Results Our results show sleep-dependent behavioral improvements correlated with sleep-spindle activity specifically over occipital cortices. Moreover, event-related potential (ERP) responses indicate a shift of attention away from predictable to unpredictable sequences after sleep, consistent with an enhanced automaticity in the processing of predictable sequences. Conclusions These findings suggest a sleep-dependent improvement in the prediction of visual sequences, likely related to visual cortex reactivation during sleep spindles. Considering that controls in our experiments did not fully exclude oculomotor contributions, future studies will need to address the extent to which these effects depend on purely perceptual versus oculomotor sequence learning.

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