Functional integration (neurobiology)
Though functional integration frequently relies on anatomic knowledge of the connections between brain areas, the emphasis is on how large clusters of neurons – numbering in the thousands or millions – fire together under various stimuli.
The results can be of clinical value by helping to identify the regions responsible for psychiatric disorders, as well as to assess how different activities or lifestyles affect the functioning of the brain.
[3] Magnetoencephalography (MEG) is an imaging modality that uses very sensitive magnetometers to measure the magnetic fields resulting from ionic currents flowing through neurons in the brain.
[7] Dynamic causal modeling (DCM) is a Bayesian method for deducing the structure of a neural system based on the observed hemodynamic (fMRI) or electrophysiologic (EEG/MEG) signal.
[10] Statistical parametric mapping (SPM) is a method for determining whether the activation of a particular brain region changes between experimental conditions, stimuli, or over time.
The essential idea is simple, and consists of two major steps: first, one performs a univariate statistical test on each individual voxel between each experimental condition.
An important consideration with SPM, however, is that the large number of comparisons requires one to control the false positive rate with a more stringent significance threshold.
This can be done either by modifying the initial statistical test to decrease the α value so as to make it harder for a particular voxel to exhibit a significant difference (e.g., Bonferroni correction), or by modifying the clustering analysis in the second step by only considering a brain region's activation to be significant if it contains a certain number of voxels that exhibit a statistical difference (see random field theory).
Dynamic causal modeling revealed that the hippocampus also exhibited a new level of effective connectivity with the striatum, though there was no learning-related change in any visual area.
[14] These studies can be cross-validated by attempting to locate and assess patients with lesions or other damage in the identified brain region, and examining whether they exhibit functional deficits relative to the population.
Although fMRI studies of people with schizophrenia and bipolar disorder have yielded some insight into the changes in effective connectivity caused by these diseases,[16] a comprehensive understanding of the functional remodelling that occurs has not yet been achieved.
Montague et al.[17] note that the almost "unreasonable effectiveness of psychotropic medication" has somewhat stymied progress in this field, and advocate for a large-scale "computational phenotyping" of psychiatric patients.
Neuroimaging studies of large numbers of these patients could yield brain activation markers for specific psychiatric illnesses, and also aid in the development of therapeutics and animal models.
