Until recently, QEEG brain-mapping methodologies had based the interpretation of individual data on comparisons with normative databases, with healthy. This approach was both useful and revolutionary for its time. However, it also has limitations and echoes the traditional DSM-based paradigm of returning an individual to the ‘norm’. Yet, only a small minority of QEEGs are, in fact, normal. 

londonSci Neuro's workshops have taken QEEG analysis and interpretation to the next level. Attendees will be introduced to our unique methodological advantage: Independent Component Analysis, or ICA. ICA is an advanced neuroscience-based signal processing method that separates independent sources linearly mixed by several electrodes, enabling practitioners to estimate sources of electrical activity deep in the brain. We are proud to have transformed practitioners into researchers familiar with sophisticated analytical algorithms traditionally used in research academic labs. You will learn with us how to use ICA algorithms in your clinical practice, as part of the Neuromodulation 3.0 concept for mental health.

When combined with three-dimensional sLORETA imaging tomographies, the ICA algorithm enables key correlations between behaviour and brain functionality and the design of precise neuromodulation protocols, giving the practitio-ner greater clinical control over treatment outcomes. If you would like to attend londonSci Neuro's workshops or discuss your clinical project, please contact us.