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Neurofeedback: Significance for Psychiatry: Page 4 of 7

Neurofeedback: Significance for Psychiatry: Page 4 of 7

Based on QEEG, 5 protocols were used for ADHDTable – Based on QEEG, 5 protocols were used for ADHD where effect siz...
images of changes in theta after 11 sessions of LORETA neurofeedbackFigure 1
Movement of z scores in a 12-year-old boy with ADHD after 11 sessions.Figure 2

In 1994, Pascual-Marqui26,30 devised accurate estimates of the deep (lower) brain sources of the EEG patterns in small regional voxels co-registered to MRI slices. He transformed these raw EEG signals into 3-D images that were then co-registered on the Talairach MRI atlas—thus LORETA was born.31 LORETA allows a clinician to translate QEEG data into a figure that corresponds with and looks like the images on fMRI that are associated with the same disease state. During neurofeedback, as waveforms are adjusted toward normal, the images generated by LORETA also become more consistent with a normal fMRI.29

The field continues to advance, and 3-D images now include voxels within the interior of the brain to monitor changes before and after neurofeedback. Figure 1 shows the before and after changes of theta in a 12-year-old boy with ADHD after 11 sessions. Figure 2 is the movement of the z score over the 11 sessions; session 1 is the first calibration, the initial z score based on the QEEG is not seen until session 2, where active training begins.

Surface QEEG neurofeedback targets amplitude frequencies or rhythms (ie, changing theta to beta frequencies). Training targets the abnormal calculated real-time QEEG z scores (standard deviations identified above or below the mean). Instead of changing a specific frequency, the focus is on changing QEEG z-score metrics toward normal or the mean (z = 0). Z score neurofeedback allows for more metrics to be targeted in a neurofeedback protocol, including:

• Active training components (up to 10 frequency bands)

• Absolute power (when too little or too much activity occurs in more bands)

• Relative power ratios (when too low or too high a ratio occurs between bands)

• The connectivity metrics of asymmetry (ie, the difference between alpha power in homologous sites that may be indicated in such things as depression)

• Coherence (when too much or too little information is shared between parts of the brain)

• Phase lag (when electrical activity is moving too fast or too slow between parts of the brain)

Three types of Z score neurofeedback utilize QEEG: surface 4 channel Z score neurofeedback (4ZNF), surface 19 channel Z score neurofeedback (19ZNF), and LORETA Z score neurofeedback (LZNF). Although similar in many respects, there is a fundamental difference between ZNF and LZNF.

 
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