The HBI Database is a revolutionary tool enabling the professional
- to
assess electrical activity of brain systems
- to construct protocols of individual treatment
- to monitor intervention effects
The HBI database was developed to
help researchers perform both conventional and quantitative EEG and quantitative ERPs studies. The HBI database is built in
WinEEG software but is an add on.
The HBI database includes the results
of processing more than 3000 EEG recordings collected from more than 1000 health subjects with age from 7 to 89 years old.
EEGs were recorded at 7 different conditions: Eye Opened, Eye Closed tasks and during performing 5 different tasks using for
ERP analysis such as Visual Continuous Performance Task (VCPT), Auditory Task, Reading Task, Mathematical Task and Mismatch
Negativity Task.
The HBI database includes the average spectra, average coherence, average
event related potentials (ERPs) and their variance computed for three different referents: linked ears referent, average referent
and weighted average referent.
Specifications
A 19-channel EEG is recorded in two resting
conditions with eyes open (minimum 3 minutes), eyes closed (minimum 3 minutes), and five different task conditions, including
two stimulus GO/NOGO tasks, arithmetic and reading tasks, auditory recognition and auditory oddball tasks. The characteristics
of QEEG are normalized. The mean values and standard deviations for separate age groups are obtained. Deviations from "normality”
are assessed by computing Z-scores, standardized measures of deviation of individual EEG parameters from the normative data.
Event-Related Potentials
Brain responses (i.e. evoked
potentials) to psychological tasks are decomposed into independent components. The components are associated with distinctive
psychological operations. Comparing the amplitude and latency of the components with the normative data gives new insights
into the different stages of information processing in patients.
In clinical settings the HBI Database is a valuable
resource for individualized treatment planning. An example of such an application is presented in the figure below. Simply
viewing the raw EEG of an ADHD patient (top, left) does not reveal any abnormality; however, compression of the data into
spectra and comparing the spectra with the normative data shows statistically significant (p<0.01) deviation from normality
in the theta frequency range (top, right spectra) which is reflected in the central areas (see map at bottom). The electromagnetic
tomography of the theta activity is presented at the bottom of the Figure.
