Research

Neuroimaging

Neuroimages are in-vivo pictures of the nervous system, mostly of the brain. They can be structural i.e. anatomical, or functional i.e. those representing some aspect of brain activity. A number of neuroimaging modalities exist diferring in their underlying physical principles e.g. MRI, EEG, MEG, PET, SPECT, NIRS, etc. Despite differing in their physical principles upon which image formation occurs, common to all neuroimaging modalities, the path from acquisition to understanding involves reconstruction, processing, analysis and interpretation of neurological data, whether structural and functional. The divisory lines among these steps is most times fuzzy, but roughly;

  • Image reconstruction entails decoding the histo-physiological information from the raw physical measurements, whether optical, nuclear resonance or electrical.
  • Processing corresponds to generating a modified version of the image preserving the input domain often aiming at enhancing the signal of interest over some background noise.
  • Analysis extracts summary information from the data mapping to a descriptive domain.
  • Finally, interpretation, by far the most complex procedure, involves knowledge, and perhaps even wisdom, generation from the data.
From formation to interpretation

Each modality has advantages and disadvantages, with their respectives temporal and spatial resolution being a critical element to define their suitability to research different aspects of brain anatomy and function. My interest cover the following:

Functional Near Infrared Spectroscopy (fNIRS)
Neuroimaging We cover most of the information lifecycle from acquisition to interpretation developing new reconstruction models, semi-virtual registration algorithms, analysis tools and interpretation approaches the latter with emphasis on effective (causal) connectivity.
Functional Magnetic Resonance Imaging (fMRI)
Functional reorganization strategies With special interest in neurorehabilitation, we have explored the functional reorganization of the brain following stroke, and the impact at cortical level of using botulin toxin as an adjuvant for the therapy.
Electroencephalography (EEG)
Project LACCIR Automatic detection (segmentation) of cognitive subprocesses with applications to attention detection for intelligent tutors systems and understanding the process of transfer of training in virtual environments.

Links of interest


© 2013-16, Felipe Orihuela-Espina
Page created: 8-Dec-2013; Last modified: 20-Mar-2017