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BrainDx qEEG Report Generator

  • Expertly analyzes artifacted EEG readings
  • Input compared to a 10,000+ patient normative database
  • Gives detailed EEG analysis, brain mapping statistics
  • Interpretive reports based on Neurometric Analysis
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BDX BRAINDX

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BrainDx IS a modular system that allows evaluation of brain function on many levels of analysis which can assist in the classification of an individual in terms of psychiatric disorders and neurological conditions. BrainDx is an lifetime subscription.

The BDx Report generator software produces an interpretive report based upon Neurometric Analysis as well as sLORETA analysis. This tool for quantitative electroencephalography (qEEG ) is a software-based, healthcare technology that will facilitate the diagnosis and treatment monitoring of a number of psychiatric, developmental, and neurological brain disorders

BrainDx includes the work of some of the original researchers in the field of QEEG. BrainDx brings the ability to help define the presence of brain dysfunction as it can be related to problems with thinking and behavior. The system has been designed to make such information available worldwide, inexpensively, to be used toward the optimization of treatment of many of the neurological and behavioral conditions common to all cultures.

Principal features of the BDx qEEG Report Generating Software

  • Acceptance of Raw 19 channel EEG data from most major manufacturers.
  • Automated Artifact Rejection, Multiple Edits allowed for each file, Multiple Montages allowed for each file of Raw qEEG information.
  • Patient History form
  • Comparative analysis of a single qEEG to the Pediatric and Adult BDx Normative Databases.
  • Comparative analysis using multivariate discriminant methodology of a single qEEG to multiple clinically relevant BDx databases.
  • 3D, rotational volumetric visualization of the brain as mapped from the qEEG interpretation through the high resolution z-score sLORETA algorithm.
  • 19 channel bivariate relationship mapping for, Absolute Power, Relative Power, Phase, Asymmetry, Coherence and Frequency.
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BrainDx was formed by internationally recognized Neurophysiological researchers and clinicians for the purpose of making readily available the knowledge derived from the evolution of the field of quantitative electrophysiology, translating it from the research laboratory to clinical practice.Fundamental to this effort was the research and development conducted at the Brain Research Laboratories of New York University School of Medicine. The outcome of this research has been presented at innumerable professional society meetings internationally, published extensively and widely across disciplines, in peer-reviewed journals and textbooks, and has been applied in many areas of health care, instrumentation, education, and forensics.

BrainDx has developed a modular system that allows the client to evaluate brain function on many levels of analysis which can assist in the classification of an individual in terms of psychiatric disorders and neurological conditions. Using 3-D source localization methods, the mathematically most probable underlying sources of the scalp recorded data can be identified, and used to further understand the pathophysiology of the disorder, and thereby aid in optimization and evaluation of therapeutic techniques including medications. The BrainDx technology produces an interpretive report that can be used by clinicians to document neurofunctional status related to an individual's behavior and performance capacities.

Part of the report generation process includes comparing the results of a patient's brain functional profile to a database of age matched normal individuals. Then, incorporating information from the patient's history, statistical comparisons are made to the appropriate clinical databases comparing the QEEG profile of the individual patient to those with known disorders, assessing the probability that the patient statistically resembled such patients, and thereby assisting the diagnostic process. Further, clinical guidelines for therapeutic intervention can be offered based on these profiles to assist the end user with the task of prioritizing treatment options.

For example, if a patient presents with general complaints about memory loss or says that their work is not going well, the BrainDx system can objectively evaluate their brain function relative to age expected normal values, and suggest the statistical probability that the EEG profile seen in this patient is consistent with that of a patient with dementia, rather than a patient with clinical depression. A non-invasive, 20-30 minute QEEG brain evaluation can generate with statistical accuracy the probability that a patient with particular symptoms matches others in the database with similar symptoms and an objective diagnosis. For example, in the case of pediatric concerns, differentiate Learning Disorder (LD) from Normal or Attention-Deficit/Hyperactivity Disorder (ADHD) from Autism Spectrum Disorder (ASD). ,etc. In addition BrainDx can also provide the ability to evaluate brain function,when the patient is in two different states; a quantitative assessment of the change in brain function between the two states, for example, on and off a medication.

These software tools are provided to operate on different platforms and made affordable for a variety of clinical purposes as well as a tool for research programs worldwide. Get answers you are seeking from your EEG data in seconds and explore the universe of questions regarding brain-behavior relationships.

EEG Acquisition remains the same, using standard and accepted guidelines.

Currentlythere are over well over 100,000 publications in the National Library of Medicine, the vast majority includes studies using digitized EEG. A large number of these, while titled as "EEG", are actually techniques of Quantitative EEG studies. These publications represent peer reviewed journals and an array of textbooks.

Foundations of Measurement:BrainDx combines historic applications of systems theory with cutting edge advances in imaging and statistical prediction

Validity- the accuracy in which meaningful and relevant measurements can be made both face and construct, convergent.

Reliability- the reproducibility of conditions or findings using a method of measurement that incorporates test- re-test and cross validation.

Methods used in Neurometrics:Data

Digital EEG collected from 19 regions of the International 10/20 placement system 
Impedances all below 5000Ωs 
Referenced to linked ears 
Bandpass = 0.5 to 50 Hz, Sample rate >= 100Hz 
20-30 min. EEG recorded 

State = eyes closed resting 
selection of 1-2 min of artifact-free data

Computation of Features

Power Spectrum and related features including: 
Absolute power 
Relative power 
Mean frequency 
Intra- and Inter-hemispheric symmetry 
Intra- and Inter-hemispheric coherence 

Computed for Each Bandpass 
Delta (1.5-3.5Hz), Theta (3.5-7.5 Hz), Alpha (7.5-12.5 Hz), Beta (12.5-25 Hz) and Beta2(25-35Hz) Source Localization 
Measures from LORETA Regions of interest (ROIs). for narrow frequency bands,and precisley time coded events.Additional non-linear features include measures of complexity and connectivity

Analysis

Approach to Norming

Child and Adult norming followed the same procedures as described in published articles. Initial norming was done under government funding (BEH, NSF, NIA) and followed strict protocols for inclusion/exclusion criteria and data acquisition (details given in publications). The following points are important to note:

Norms were constructed using split-half approach where regression equations were formed on one half and tested on the other (independent replication) – with the expectation that less than the expected random number of "hits" (z-values <0.05) were obtained on the second half. The two halves were then combined and final equations constructed

Subjects were added to the population until adding more subjects (across the age range) did not change the regression equation. Thus, the size of the population required to norm were statistically determined. As expected many more children were required (more rapid change across age) than adults

Additional evaluations were used to demonstrate high test/retest reliablity and stability of the norms

Over the years since initial norming additional subjects have been added to the child and adult populations to represent advances in amplifiers, etc. All new subjects were recruited according to the same criteria as the initial projects

Adult Sample

N = 154 Selected based on extensive psychiatric and neuropsychological evaluations Psychiatric/Neurologic examination Evaluations of achievement, dominance (hand,eye, foot) IQ had to be normal

Detailed developmental, medical, psychosocial histories

Exclusion variables: use of drugs, history of head injury or loss of consciousness, previous EEG or neurological examination, febrile convulsions

Child Sample

N = 310 Normal Medical and Developmental histories

Excluded extreme prenatal or perinatal trauma High febrile illness 
Loss of consciousness (concussions, convulsions) Extreme behavior problems 
Failure at any school level 
WRAT scores below 90 on any skill

John, 1987 (Handbook Chapter);John et. al, 1988;

Age Distribution of Norming Subjects, Closed Eyes Condition 
sLORETA Norming

LORETA (Low Resolution Electromagnetic Tomographic Analyses) is a source localization inverse problem method for localizing the mathematically most probable source of the voltages recorded from the scalp.

Working together with Roberto Pascual-Marqui at the BRL, voxel norms were computed using the same BRL/NYU normative database

The methodology described in Neurometrics was applied to the sLORETA norming, allowing the z-transformation of each voxel in the model which can be displayed as statistical color-coded images of the mathematically most probable underlying sources of the scalp recorded EEG data

For each voxel, an individual's values are compared statistically to the expected norms for their age; Statistical significance for each voxel is encoded in color superimposed upon slices from a Probabilistic MRI Atlas; Extensive literature exists demonstrating similar findings with conventional neuroimaging and EEG source localization

The age regression equations that were developed help standardize the quantitative EEG measures so that they may be interpreted independent of the subjects age.

The sLORETA images below are plots of the correlation of subject-wise relative power grey matter voxels with age over the range of 16 to 80 years (N = 154). The regression is linear (a straight line fit) with the logarithm of age.

The two volumes shown each comprise 20% of the grey matter volume.

All the voxels in the red volume have a positive correlation with age greater than .48 at the frequency 17.2 Hz. The maximum value of .58 is in the left Insula.

All the voxels in the blue volume have correlation less than -.44 at the frequency of 10.2 Hz.

In general this illustrates an increase in Beta in the temporal lobes and and a decrease in Alpha with increasing age.

The current density estimate of each voxel is divided by the total energy of the EEG, (subject-wise relative power), thus removing the influence of the overall size of the EEG from this measure.

Application

Multivariate Measures

Using Z-scores allows a common metric that allows computation of multivariate "system" features. These Multivariate computations form a super-set of features that are often important in summarizing concepts like degree of abnormality and they make important contributions to the discriminant functions described below.more typos:

Discriminant Functions

BrainDx offers the use of Multivariate discriminant Analyses to statistically evaluate the match of patient qEEG profile with specifically defined clinical profiles to augment diagnostic processes. It is important to note that this methodology is not intended to be used as a substitute for current psychiatric or psychological diagnostic methods but strictly as a supplemental tool to help with the confirmation of a diagnostic consideration. There are strict criteria for the use of these discriminant functions and the BrainDx software will direct the user to be able to use only those functions which meet history and symptom criteria.

Examples of Discriminate Functions for DSM Clinical Groups

Primary Progressive Dementia (Alzheimer's Type Dementia)

  • Depression as distinguished from Dementia
  • Vascular Dementia

Major Affective Disorders (Depression)

  • Unipolar as distinguished from Bipolar Depression

Schizophrenia

Learning Disabilities (LD)

  • Normal vs LD
  • Normal vs ADHD
  • Stimulant (e.g., Ritalin) Responder as distinguished from non-Responder

Autism Spectrum Disorder (ASD)

  • ASD as distinguished from ADHD

Co-morbid Alcohol Abuse

Obsessive Compulsive Disorder

Post-Traumatic Stress Disorder vs Post Concussive Syndrome (In Development)

Localization

Applying Z-score statistics with source localization, the degree of functional deviation for age can be better visualized and compared to other forms of neuroimaging when desired

BrainDx software is developed to produce an interpretive report based upon Neurometric Analysis. This tool for quantitative electroencephalography (QEEG ) is a software-based, healthcare technology that will facilitate the diagnosis and treatment monitoring of a number of psychiatric, developmental, and neurological brain disorders.

Technology

Two to three minutes of artifact-free digital Electroencephalogram (EEG) input is compared to a continually refined and expanded, normative database and a clinical database of over 10,000 patients with DSM/ICD diagnosed brain dysfunction. Used in addition to other data derived from the individual patient history, the software interactively generates a clinical report on any computer.

Use

Data is imported (translated) from files generated by most commercial EEG equipment. All translators have been adjusted to compensate for significant differences in transfer functions (frequency response). Results are presented in a structured and adjustable format with annotated illustrations, documentation, and opportunities to insert clinical observations.

Patient Information

Demographics

The Subject [ID: GE-70-09262-] was 68.95 years old on the date of testing 07/08/2013. An EEG recording of 18.0 minutes was acquired and 2.0 minutes of artifact free data was selected for analysis.

History

  • No - Current Medication
  • No - Head Injury
  • No - Neurological Disease
  • No - Convulsions
  • No - Confusion
  • Yes - Memory Difficulties
  • Yes - Depression
  • No - Delusions, Hallucinations or Thought Disorders
  • No - Drug Abuse / Addiction
  • No - Alcohol Abuse / Addiction
  • No - Learning Disability
  • No - Previous EEG
  • No - Hyperactivity, Attention or Impulse Control problems
  • No - Memory Difficulties

Discriminant Functions

Discriminant functions provide a quantitative estimate of the similarity between a patient’s profile and characteristic patterns found during extensive research on groups of patients with various disorders. Classification by this algorithm is restricted to disorders relevant to the diagnosis or symptoms indicated in the patient history This patient's discriminant scores suggest the presence of Primary Degenerative Dementia. (p

The features making the largest contribution to the Dementia statement are:

Normed Bipolar Relative Power Theta for Head,

Normed Monopolar Relative Power Theta for Cz,

Normed Bipolar Coherence Combined for Anterior

This classification is a multivariate statistical summary of a neurometric evaluation and serves only as an adjunct to other clinical evaluations. Please refer to the enclosed Appendix or the referred bibliography for a more precise definition of the respective measures.

Neurometric QEEG Images

Neurometric images

A summary of the QEEG results for this patient is provided by these topographic images, displaying the Z-Scored features computed from 19 standardized electrode positions, as viewed from above with the nose at the top, and left on the left. The Scale is set at +/- 3.0 Z

Narrowband Spectra

The high resolution frequency spectra are shown below at each scalp location for Z-Score Log Power Spectra. The Cursor is at 7.03 Hz. The Maximum value at for this frequency is at F2.

sLORETA of Narrowband Spectra

sLORETA of Narrowband Spectra

The Blue Volume encloses 20% of the Grey matter with Z value Less than -2.0. The minimum value is -3.1Z at 22.3 Hz. The minimum is located at Limbic Lobe, Parahippocampal Gyrus, Brodmann area 28.

The Red Volume encloses 20% of the Grey matter with Z value greater than 5.1. The maximum value is 6.4Z at 6.6 Hz. The maximum is located at Temporal Lobe, Superior Temporal Gyrus, Brodmann area 39.

Measures of Cortical Connectivity

Measures of Cortical Connectivity

Each image summarizes results for the gradient between a labeled region and all other regions. Shown is the measure of Coherence for the Theta Band.

Measures of Cortical Connectivity 2

Each image summarizes results for the gradient between a labeled region and all other regions. Shown is the measure of Phase for the Theta Band.

Numerical Tables

Monopolar

QEEG tabular data monopolar

Selected Z-Score Measures of Absolute Power, Relative Power, and Mean Frequency. Cells are Red when Z > 1.96 and Blue when Z < 1.96.

Bipolar

QEEG Tabular Data Bipolar

Numerical Tables: Selected Z-Scored Measures of Bipolar power, Asymmetry and Coherence. Cells are Red when Z > 1.96 and Blue when Z < 1.96

Sample QEEG

Qualitative Electroencephalographic Evaluation:

The enclosed results represent statistical deviations in electrophysiological measures of brain activity from expected values for this age. Dysfunction of brain regions as indicated typically correspond to functional or behavior problems. Neuropsychological performance testing should be considered whenever possible to delineate functional or behavior impairments and to establish pre-treatment performance levels which can be used to establish treatment efficacy from follow-up treatment. This report is intended to provide a guideline for clinical use and should not be used as the sole source of information for clinical diagnosis or treatment selection. BrainDx will not be held responsible for any fault in the clinical diagnosis or failed treatment resulting from statements in this report for the service provider. Should the clinician be concerned about the presence of epilepsy, neurological abnormalities or the findings described below referral for a conventional EEG may be warranted.

  • Lifetime subscription to BrainDx

Manuals and Data Sheets

BrainDx Features Sheet

Specifications

Methods used in Neurometrics:

Data

  • Digital EEG collected from 19 regions of the International 10/20 placement system 
  • All impedance below 5000Ωs 
  • Referenced to linked ears 
  • Bandpass = 0.5 to 50 Hz, Sample rate >= 100Hz 
  • 20-30 min. EEG recorded

State

  • eyes closed resting 
  • selection of 1-2 min of artifact-free data

Computation of Features

Power Spectrum and related features including:

  • Absolute power 
  • Relative power 
  • Mean frequency 
  • Intra and Inter hemispheric symmetry 
  • Intra and Inter hemispheric coherence

Computed for Each Bandpass

  • Delta (1.5-3.5Hz)
  • Theta (3.5-7.5 Hz)
  • Alpha (7.5-12.5 Hz)
  • Beta (12.5-25 Hz) 
  • Beta2(25-35Hz)

Source Localization

  • Measures from LORETA Regions of interest (ROIs)
  • For narrow frequency bands, and precisely time coded events.

Additional non-linear features

  • include measures of complexity and connectivity.