Functional neuroimaging and the associated computing technologies play a principal role in this and other efforts of this kind, with functional magnetic resonance imaging (fMRI) and electro-encephalography (EEG) being the most widely used and thoroughly studied modalities for brain mapping.
Their objectives include analysis of the activity and functional connectivity of the brain, and their popularity arises from their non-invasive nature and their ability to provide maps of high spatial (fMRI) or temporal (EEG) resolution.
Each of these modalities exhibits its own advantages and disadvantages and provides an alternative view of the brain function. fMRI has been used to answer research questions in a wide range of disciplines, such as cognitive neuroscience and experimental psychology.
There are various objectives in the analysis of fMRI data, the most common of which being the localization of brain regions activated by a certain task, the determination of distributed functional brain networks (FBNS) that correspond to certain brain functions, and the prediction of the evolution or outcome of certain diseases, either via classification of the subjects or via computation of diagnostic biomarkers.
Determination of FBNS and activated regions.
During an fMRI experiment and while the subject performs a set of tasks responding to external stimuli (task-related fMRI) or no tasks (resting-state fMRI), a series of 3-D brain images is acquired.
The localization of the activated brain areas is a challenging Blind Source Separation (BSS) problem, in which the sources consist of a combination of spatial maps (areas activated) and time-courses (timings of activation).
During a task-related fMRI acquisition (for example), our brain is not activated only from the task information we process, but also from external and (sometimes) even unconscious stimuli (e.g. heart beating, breathing, thinking of personal and family issues not connected to the task, etc.), hence the separation of the activation directly connected to the hand in task is a difficult and complex problem.
We can perform different types of analysis in order to study the activated areas in single or multi-subject studies.
As mentioned above, the use of the activated areas of subjects can be used in different fields, from psychological analysisto marketing purposes.
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The study of connectivity of the brain is an important factor both το better understand how the human brain works and to delineate areas that need to stay untouched during a brain surgery to prevent severe counter-effects.
Structural (or anatomical) connectivity refers to the existence and structural integrity of tracts connecting different brain areas (i.e. white matter tracts connecting cortical areas/nuclei), while MRI and diffusion MRI are being used in order to study and visualize it.
Functional and effective connectivity are neuroimaging terms. Functional connectivity refers to the statistical dependence – correlation of the signal from different brain areas (usually with the use of resting state fMRI).
Effective connectivity is a bridge between the two different connectivity measures and brings in the element of causation (i.e. a signal, activation in one area directly causes a change or signal, activation or depression, in another area).
We can offer different connectivity analysis and visualizations based on the task at hand.