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Internship – Advanced EEG Analysis: Dipole source Localization & Controlling for Assumptions on Brain Oscillations
Using data from a study investigating the effects of overnight closed-loop auditory stimulation in sleep, attention, and declarative memory, the latest methodological considerations for accurate EEG analysis are to be applied for sleep and task-related EEG data.
Keywords: EEG
Neuroscience
Declarative memory
Dipole source analysis
Spectral power parameterization
Sleep
Memory
Attention
Data Processing
Data Analysis
Matlab
EEG is an essential imaging modality in neuroscience despite providing low resolution in localizing and characterizing sources of brain activity. In addition, methodological considerations to study neural oscillations using EEG are oftentimes overlooked and may be a reason for mixed results in studies investigating, attention, and declarative memory.
Our group has recently completed a large study investigating the effects of overnight closed-loop auditory stimulation in sleep, attention, and declarative memory. We are currently analyzing both sleep and task-related EEG data and want to consider the latest recommendations for accurate and reproducible EEG results.
Become part of a great and motivated, young research team! This interesting project offers the unique opportunity to gain experience with advanced/state-of-the-art electrophysiological techniques. Our motivated team with backgrounds in biomedical engineering and neuroscience is eager to mentor you in advanced data analysis and statistics.
Your Profile
- Advanced Matlab programming skills and Signal processing experience (computer science or related field of study)
- Background in biomedical engineering/neuroscience is a plus
- Can work independently but also in a team
- Able to work full time is preferred
- Enrolled in a Swiss university
EEG is an essential imaging modality in neuroscience despite providing low resolution in localizing and characterizing sources of brain activity. In addition, methodological considerations to study neural oscillations using EEG are oftentimes overlooked and may be a reason for mixed results in studies investigating, attention, and declarative memory.
Our group has recently completed a large study investigating the effects of overnight closed-loop auditory stimulation in sleep, attention, and declarative memory. We are currently analyzing both sleep and task-related EEG data and want to consider the latest recommendations for accurate and reproducible EEG results.
Become part of a great and motivated, young research team! This interesting project offers the unique opportunity to gain experience with advanced/state-of-the-art electrophysiological techniques. Our motivated team with backgrounds in biomedical engineering and neuroscience is eager to mentor you in advanced data analysis and statistics.
Your Profile
- Advanced Matlab programming skills and Signal processing experience (computer science or related field of study)
- Background in biomedical engineering/neuroscience is a plus
- Can work independently but also in a team
- Able to work full time is preferred
- Enrolled in a Swiss university
With the already collected dataset of both complete night and task-related brain activity recordings using high-density EEG (128 electrodes), the goal of this internship will be to further implement methods that consider assumptions of EEG and neural oscillations (e.g. spectral peak detection, frequency range individualization, controlling for aperiodic activity) and to integrate dipole source analysis (e.g. using LORETA) into our EEG analysis pipeline. The tasks of the internship will be:
- Develop an understanding of the underlying concepts/requirements of power spectra and dipole source analysis in EEG.
- Implementing dipole source analysis and power analysis into our EEG pipeline.
- Carry out independent research on EEG preprocessing/analysis/visualization techniques that may be applicable in the fields of sleep, attention and/or declarative memory.
With the already collected dataset of both complete night and task-related brain activity recordings using high-density EEG (128 electrodes), the goal of this internship will be to further implement methods that consider assumptions of EEG and neural oscillations (e.g. spectral peak detection, frequency range individualization, controlling for aperiodic activity) and to integrate dipole source analysis (e.g. using LORETA) into our EEG analysis pipeline. The tasks of the internship will be:
- Develop an understanding of the underlying concepts/requirements of power spectra and dipole source analysis in EEG.
- Implementing dipole source analysis and power analysis into our EEG pipeline.
- Carry out independent research on EEG preprocessing/analysis/visualization techniques that may be applicable in the fields of sleep, attention and/or declarative memory.
Please send an email with with your CV and short cover letter to manuel.carrodominguez@hest.ethz.ch
with the subject title "Project: Advanced EEG Analysis"
Please send an email with with your CV and short cover letter to manuel.carrodominguez@hest.ethz.ch with the subject title "Project: Advanced EEG Analysis"