Child and Adult Reference Database for spectral analysis, event related potentials (ERPs). Includes 100 comparisons. The normative data base includes 3 minute fragments of EEG recorded in eye open, eyes closed conditions and in four different tasks (two stimulus GO/NOG task, Math, Reading and Acoustic tasks). The results of comparison are presented as maps of deviations from normality. From 6 to 60 years old
EEG spectra, coherence and ERP components computed for a given patient can be compared with the Human Brain Institute (HBI) normative data base.
The results of comparison are presented as maps of deviations from normality.
The normative data base includes 3 minute fragments of EEG recorded in eye open, eyes closed conditions and in four different tasks (two stimulus GO/NOG task, Math, Reading and Acoustic tasks). The results of comparison are presented as maps of deviations from normality. From 6 to 60 years old.
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 effect
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.
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.
A Unique Database for ICA Components
An example of comparing the components of evoked potentials is presented below. The Fig. depicts time dynamics of four different components for an ADHD patient (thin line) in comparison to norms (thick line). The components are associated with comparison operation, attentional shift, engagement, and monitoring operations. The maps of the components for these patients and norms are presented in the middle. Electromagnetic tomographies of the components are presented at the right. Only one component is selectively reduced in this patient, as shown by the red fill-in. Our studies show that the entire ADHD population can be separated into distinct categories, each characterized by selective suppression of a distinct component, and each responding to a specific medication.
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.
