Software to measure, describe and visualize human brain dynamics.
EMSE is a suite of advanced, powerful, and useable software tools to measure, describe, and visualize human brain dynamics, used worldwide for research in neuroscience, neurotechnology, and clinical neurophysiology. We specialize in multimodal source estimation techniques, enabling the researcher to combine EEG and MRI datasets to better answer where things are happening in the brain, and when things change.
Conventional neuroimaging (for example magnetic resonance imaging, or MRI) can answer the where question, but not the when question. Electroencephalography (EEG) and the closely allied Event-Related Potentials (ERP’s) can tell you when something happened with an accuracy of thousandths of a second, but isn’t very good at the where questions. EMSE combines MRI and EEG to answer both when and where in a way that neither method can answer alone. We call this process multimodal dynamic functional brain imaging or source estimation.
EMSE Suite is offered as a scalable desktop application at three levels:
- Data Editor+ is a tool for sensor space
preprocessing of EEG and MEG raw data (with task-related events and intervals) for time, frequency, and
time-frequency analyses, including nonparametric statistical tests.
- EMSE Source Standard performs various inverse solutions using FEM standard head models (in MNI space) for researchers without
- EMSE Source MRI constructs individualized BEM and FEM models that map to and from standard MNI space.
- Basic and advanced preprocessing
- IIR and FIR time-domain filtering
- Digital re-referencing
- Polynomial detrending
- Artifact rejection or removal using ICA, spatial filtering, or legacy methods
- Time, frequency, and time-frequency signal analysis
- Template matching
- Manual copy/paste steps in interactive mode or create scripts for programmatic automation
- Create maps on realistic standardized or individual head surfaces
- Map voltages, currents, magnitude over frequency ranges, time-frequency bins, statistical p levels, r levels, and more
- Utilize standardized electrode positions or incorporate individually measured electrode positions
- Import individual MRI slices or utilize standard volumetric image sets.
- Segmentation Wizard automates tissue classification.
- Brain Extraction Tool (BET) is an automated algorithm for finding the brain within a volumetric dataset.
- Hidden Markov random field algorithm automates cortical tissue classification into disjoint regions (e.g., CSF, gray matter, white matter).
- Inner/Outer Skull and Scalp Wizards complete the picture, enabling you to generate a complete finite element model for the MR volume.
- Combine EEG / MEG + MRI + electrode positions
- Create head model from individual MRI or use a standardized model
- Visualize source reconstruction results in the context of the selected MRI image set
EMSE 6.4 is the current stable release of our flagship EEG and MEG signal processing and source estimation software platform.Read More
A wide range of new features are available, from BDF+ support and Phase-Locking Angle (PLA) in time-frequency analysis, to heart-rate variability script commands, automarking of blinks/clean/heog and integration with FreeSurfer.Read More
EMSE EEG / MEG analysis software (8)
EMSE’s Development Plan emerges from three main streams. First, we listen to your needs and requests (e.g., you might show us what you want during a remote technical/scientific support session). Second, we periodically update and upgrade existing features (e.g., update of boundary element head models; upgrade from 32-bit to 64-bit code). Third, we’re envisioning an integrative role for EMSE in the larger field of human neurophysiology and neuroimaging, so that: (a) EMSE shall perform live analysis and automatic archiving during data acquisition; and (b) EMSE shall cooperate with other tools in an ecosystem based on FAIR (Findable, Accessible, Interoperable, Reusable) principles.
EMSE is developed by Cortech Solutions. We are an agile team with more than 50 years combined experience in the field. Principal developers are Mark Pflieger and Li Gao, who have worked on the EMSE project for 17+ years and 21+ years, respectively. Richard Greenblatt initiated the EMSE project in the early 1990s with roots from the MEG community.
EMSE reads all major research EEG and MEG data formats.
No. EMSE is a self-contained graphical program written in C++ “under the hood” for efficiency. To optimize the speed of standard matrix and math operations, EMSE leverages the Intel® Math Kernel Library.
No, EMSE is modular. The ERP Bundle (Data Editor plus Visualizer) is a powerful and affordable package for discovering and confirming space-time-frequency phenomena at the scalp level, with integrated nonparametric statistics. The Basic Source Estimation Bundle adds the Source Estimator module for brain level modeling. The Locator module digitizes electrode locations, which may be co-registered with MRI using MR Viewer. The Image Processor module can segment head tissues for constructing individual cortex and volume conductor models.
If EEG/ERP is a new addition to your lab, you can use EMSE to rapidly master all of the steps that can lead you to discover and visualize new phenomena in your experimental data. Have you already identified phenomena at the scalp? Then you can use source reconstruction and source signal estimation tools in EMSE to understand where and when these phenomena arise in the cortex. Going further, if you have participant MRIs, then you can use EMSE to sort out meaningful individual differences from incidental differences that derive from personal cortical folding patterns. In all cases, we can remotely assist with the steps.
EMSE is great for helping you, first, to identify robust space-time-frequency phenomena in your EEG or MEG data, and then to interpret those phenomena in brain space by constructing source models, by estimating regional activity, and by deriving inter-regional connectivities. EMSE can use MRI data to construct realistic volume conductor models of the head. Importantly, EMSE reproducibly automates and documents your analysis workflows, including: (a) signal processing pipelines; (b) experimental event logic pipelines; (c) event-related component measurements; and (d) nonparametric statistical hypothesis testing. EMSE is a professionally supported Windows application. We can remotely assist your data analysis process.
EMSE stands for ElectroMagnetic Source Estimation (and we say “MC”).