The two images below show the referential and sequential montage display of an active right temporal-parietal spike and slow wave focus, seen in a child clinically diagnosed with an attachment disorder. There was no history of convulsion, nor any suspicion of the actual underlying pathophysiological basis for the behavioral presentation.

The focus cortical area is normally involved in comprehension of facial expression and body language, as well as the prosodic (emotive) aspects of language. Any disturbance in that cortical area’s function generally has social contextual implications for behavior due to “prosodic blindness”. (see: Van Bloem, L. QEEG in Children with Reactive Attachment Disorder,

Journal of Neurotherapy, 4(4), 2001.

The implications for treatment option with this pathophysiological source for the behavioral presentation which could really only be discovered through the EEG are enormous. The use of an anticonvulsant or an approach with one of the proven efficacious applications of Neurofeedback in treating epilepsy can be used to target the underlying cause, rather than trying to effect some symptomatic control with antipsychotic or antidepressant medications so commonly used in these situations of severe attachment disorder. (see a review of SMR applied to epilepsy by Dr. M. Barry Sterman, Professor Emeritus, UCLA, from 2000 in Clinical Electroencephalography’s special edition on Neurofeedback)

In these images the referential focus is seen associated with the largest waveform, though in the sequential data the 180 degree phase reversal points to the focus.

EEG & Epilepsy - Referential Montage Display

EEG & Epilepsy - Sequential Montage Display

In modern neuroscience centers, the EEG is still the tool of choice in evaluation of convulsive epilepsy, as well as some other non-convulsive forms, such as staring episodes seen in “absence epilepsy” typically as a 3/second spike and wave dominant anteriorly, or temporal lobe epilepsy, which is seen as a “notched” slow wave discharge fronto-temporally.

The EEG can now be processed through algorithms, such as spike dipole localization software, to identify the “seizure focus” cortically, or spectral averaging to look for changes in the underlying EEG rhythmicity due to the disorder.

One of the difficulty with the two later categories is that they are not always identified as forms of epilepsy, and thus can be mis-diagnosed based on behavior alone as some other disorders, including ADD/ADHD in absence epilepsy “spells” where the attentional process is disturbed by the discharge taking segments of time out of the cognitive streaming of perception, or from discharge in sensory areas.  These segments being removed do not have any conscious awareness of the event for the person experiencing the blips missing from their cognitive process, and they will have trouble tracking on-going events, like driving or listening to a speech or lecture.  Imagine missing a few here and there, to tens of seconds from your awareness, and see if you don’t have “attentional deficits”.

The other major areas of misdiagnosis are of a “schizophrenic” or “psychotic” nature.  This occurs when the discharges are frontal or temporal and disturbing local cortical function, and may be seen as a range of presentations from hallucinations or emotional outbursts of rage, or even “fits of laughter” in “Gelastic seizures”.   Temporal Lobe Epilepsy (TLE) is a particularly difficult one to properly diagnose in the absence of the EEG.

The importance of these missed-diagnoses can be quite severe, with the use of medications to treat the symptoms often being contra-indicated by the epilepsy.  One example of this is TLE that is assumed to be psychosis, since antipsychotic medications lower the seizure threshold, and make the person worse, which can then be responded to with more antipsychotics, spiraling the person into a progressively worsened condition.  The use of stimulants in epilepsy is a controversial area, as the effect of stimulants for inattention in known and treated epileptics may be acceptable, though throwing a stimulant at an undiagnosed epileptic can have severe negative consequences.

The real issue is that IF YOU DO NOT LOOK, YOU WILL NOT SEE… and in epilepsy, looking requires the EEG, as the gold standard.

In surgical approaches, the EEG is used to identify whether there are multiple foci, which generally will preclude a good outcome (you remove the brain tissue and the seizures do not change).

I will post some images of the WIDE variety of morphologic presentation that epilepsy can take, so that some understanding of the task of the Electroencephalographer and Epileptologist can be better appreciated by those who think it is straight-forward.

Thanks for your attention to these obscure issues.

Jay

This may not surprise too many old-time NF practitioners, except that it is now being proven with well done studies in the traditional neuroscience literature!  Neurofeedback can induce changes in brain plasticity!

Jay

First Direct Evidence of Neuroplastic Changes Following Brainwave Training

ScienceDaily (Mar. 12, 2010) — Significant changes in brain plasticity have been observed following alpha brainwave training.

A pioneering collaboration between two laboratories from the University of London has provided the first evidence of neuroplastic changes occurring directly after natural brainwave training. Researchers from Goldsmiths and the Institute of Neurology have demonstrated that half an hour of voluntary control of brain rhythms is sufficient to induce a lasting shift in cortical excitability and intracortical function.

Remarkably, these after-effects are comparable in magnitude to those observed following interventions with artificial forms of brain stimulation involving magnetic or electrical pulses. The novel finding may have important implications for future non-pharmacological therapies of the brain and calls for a serious re-examination and stronger backing of research on neurofeedback, a technique which may be promising tool to modulate cerebral plasticity in a safe, painless, and natural way.

Continued at http://www.sciencedaily.com/releases/2010/03/100310114936.htm

An excellent story regarding the use of Neurofeedback in sports.  The Mind Room utilizes the Thought Technology Procomp Infiniti equipment.

All of these new tools will require clinical validation prior to being able to be considered standard techniques within our field’s armamentarium of efficacious techniques and clinical applications. All of these techniques offer great hope at this time with preliminary results, but careful clinical outcome studies remain to be performed.

In this brief note I will discuss Z-score feedback. This promising technique offers to set normative boundaries around the mean of many features of the EEG, and allow feedback to be controlled by these parameters. This obviously offers great hope to clinical outliers, as their Z-score divergence should be related to their pathology. One difficulty is that database Z-scores also show divergence when an adaptive or counter-balancing feature is used to cope with an abnormal finding. A crutch is not a normal finding, but you can’t walk without it if you have a broken leg.

This suggests that the selection of which Z-score features to include as feedback contingencies and which to “ignore” will become an important feature in clinical decision making using these new tools. Training away an adaptive coping mechanism is not a proper NF Z-score targeting choice.

One area which is not very well discussed in the field of qEEG is how poorly the databases are at characterizing shifts in the frequency “tuning” of the EEG. The NeuroGuide database reports peak frequency, but the calculation is not for the peak, but for a “centroid” which is more related to the Mean than the Peak frequency. Nx-link does not report the peak, but uses a mean frequency calculation. BRC database uses a peak frequency of alpha statistic, but it is constrained to looking within the alpha predefined band.

Databases report “too much” and “not enough” amplitude/magnitude/power, but they do not tell you if this value would be normal at a different frequency tuning. An example is in order to illustrate this important concept. Take a normal amount of 9.5 Hz sinusoidal alpha seen dominant posteriorly, with normal coherence relationships… let’s arbitrarily say there is 50 microvolts of amplitude in the alpha spindles. Now, take this alpha tuning and shift it 2 Hz slower, so 7.5 Hz is the sinusoidal frequency, and what does the database tell you?

Databases will say there is too much 7.5 Hz power, and that it is hypercoherent, since the database does not expect alpha at 7.5 Hz. In reality, the alpha frequency is slow, but the fact that it is 50 microvolts is not too much power for the background, and it really is not hypercoherent, it is just too slow.

Frequency tuning issues are so poorly described in databases that the databases will not do a good job of normalizing the client’s function… dropping the background’s normal power and coherence relationships is not appropriate, but the database would use these values as their contingencies for NF based on the database.

This would suggest that frequency shifted clients may comprise another group that will require special adaptations for Z-score based feedback to be properly applied.

One other area that deserves some discussion is the use of NF in non-medical applications for “peak performance”. By definition, these peak states are not a common occurrence, as they are seen in uniquely gifted athletes, scholars, and business leaders that are not that common in the first place, and then these states are not always seen in these individuals in their average states. These states that are being trained for are not statistically “Mean-oriented” states, but rather exist as a unique pattern of outliers which are not capable of being reported in univariate statistics such as Z-scores. It requires a flexible nervous system to achieve these outlier states, and a resilient nervous system to “return” or “recover” and continue to function “normally”.

These observations suggest that peak performance may not be the best application for Z-score feedback, though this is hypothetical, and requires the validation only achieved with experience over the years.

The database selected also will become an issue, as the NeuroGuide is severely restricted in the frequency range, with the amplifier response stopping at 28Hz, as seen in the FRC curve(Fig 1). It is not possible to do gamma based feedback with Z-scores of the database used does not go to gamma.

Figure 1

What is clear at this time is that Z-score feedback remains experimental until the validation studies are performed, and though it is a promising new application utility, there are areas which deserve special attention even in this early stage of the evaluation of this emerging technique, including coping mechanisms, frequency shifts, peak performance applications, and database limitations.

The vendors who promote Z-score feedback are all adamant that the Z-score feedback does not preclude the need for client evaluation, but rather that is increases the complexity of the evaluation as various features are selected or de-selected for being feedback contingencies to account for client coping mechanisms, and the various frequency shifting issues and other database inadequacies.

Welcome to the New World of high tech clinical application tools, please check your expectation that this will be “quick and easy” at the door. More on LORETA and ICA based neurofeedback later.

In Part 2 you see how Noah parents learn there are alternatives to Ritalin and other drugs that may be given to their child. Learn about how Neurofeedback and EEG Brain Mapping may be able to help without the use of dangerous pharmaceutical drugs.

Dr. Linden is a Clinical Psychologist and Nationally Certified in Neurofeedback and Biofeedback. He is the director of The Attention Learning Center, which has offices located in San Juan Capistrano, Irvine and Carlsbad, California.

Dr. Linden is a regular contributor to the Journal of Neurotherapy and has been a speaker in many seminars and conferences related to ADD/ADHD and neurotherapy.

It’ll be the first Neuroscience Multidisciplinary Meeting hosted by the Brainmech Foundation in Spain after the last conference held in Holland in 2007. This is a unique oppurtunity for professionals to learn today what investigators and scientists on neuroscience are preparing for the future.

It’ll be the meeting point for Psychiatrists, Psychologists, Neurologists and Pediatricians that will have the chance to learn from the authors about the last investigations and researches on the human brain, new methods of diagnosis, new diagnosis criteria on mental disorders proposed for the DSM-V, neurobiologist database of the ADHD, bipolar disorder, as well as the new treatments and therapy for neurological illness and psychiatric malfunctions.

This video was recently shown again on CBS 60 Minutes. It is a great video talking about using brain controlled interfaces.

Neurofeedback is a treatment where real-time feedback is provided for specific brain activity (most often EEG) in order to learn the brain to suppress or produce specific brain activity. This method was initially discovered for the treatment of Epilepsy and from 1976 investigated further for the treatment of ADHD. This technique has become more popular by clinicians worldwide, and is currently provided for the treatment of several disorders. Critics have often questioned the efficacy of Neurofeedback and whether it can be considered an Evidence Based treatment or not.

In collaboration with researchers from Tübingen University (Germany), Radboud University (Nijmegen, the Netherlands), Brainclinics and EEG Resource Institute a so-called meta-analysis was conducted on all published research about Neurofeedback treatment in ADHD. This meta-analysis included 15 studies and 1194 ADHD patients. Based on this study – which will be published in the July issue of EEG and Clinical Neuroscience – it could be concluded that Neurofeedback can indeed be considered an Evidence-Based treatment for ADHD. The results show that neurofeedback treatment has large and clinically significant effects on Impulsivity and Inattention and a modest improvement of Hyperactivity.

These findings apply to Neurofeedback treatment for ADHD, but do not automatically imply that Neurofeedback can be considered evidence based for any disorder. The efficacy of Neurofeedback has to be assessed separately for each disorder. For example, a meta-analysis of EEG biofeedback in Epilepsy is published in the same issue of EEG and Clinical Neuroscience demonstrating clinical efficacy in the treatment of epilepsy.

Interested clients are advised to make an informed choice regarding Neurofeedback therapists, since there is a large heterogeneity in neurofeedback treatment approaches and clinicians. It is advised to look for psychologists or physicians who are at least a member of a professional organization such as the International Society for  Neurofeedback and Research (ISNR: www.isnr.org) or other professional organizations and who use investigated methods.

Literature Arns, M., de Ridder, S., Strehl, U., Breteler, M. & Coenen, A. Efficacy of Neurofeedback Treatment in ADHD: The effects on Inattention, Impulsivity and Hyperactivity: a Meta-Analysis. EEG and Clinical Neuroscience; 40(3), 180-189.

I’d like to just throw out there a few other findings that were discovered in a few exploratory investigations while working on some studies with our colleague Alicia Townsend, at the time at Univ. of North Texas. Lexicor funded these projects and now the arrangements are such that I can’t disclose more than was published in the abstracts from our talks at ISNR and AAPB.  I did at least want to point to these very preliminary findings because theoretically they are in concert with your explanations.

First, we explored 10 participants between the ages of 65 and 85 were recruited at the University of North Texas Health Science Center.  Each was diagnosed by the Alzheimer’s Disease Assessment Scale and a medical interview.  The aim of the study was to identify current source density markers in AD.  EEG recording of the eyes closed condition of an AD group was compared to an age-sex matched control group using within-subject multiple t-test procedures. sLORETA difference maps in nine frequency bands were investigated. Interestingly the results showed that there was a significant increase in current source density in the delta and theta bands in the Brodmann Area (BA) 39 of the right temporal lobe and BA 31, the cingulate gyrus respectively.  Additionally there were decreases in alpha in the BA 21 of the right temporal lobe and right inferior parietal lobule (Sherlin, Townsend & Hall, 2006).

This was corroborative previous findings of increased delta and theta and decreased alpha from a single case study of AD I analyzed with Tom Budzynski  (Budzyski, Budzynski, & Sherlin, 2002).  Results varied from previous studies that showed diffuse differences although the temporal lobe slowing is replicated.  We recognized that the proximity of the significant locations to the precuneus and fusiform gyrus which are both important in facial recognition and processing social information.  The precuneus is also involved in episodic memory retrieval and imagery of motor functions. A correlation study found similar patterns with sLORETA.

I believe that future investigation for patterns in different types of dementia (vascular vs. alzheimer’s vs. frontal lobe vs. mild cognitive impairment) may increase our ability to differentially diagnose.

The second study we completed was to examine the relationship between memory loss and brain electrical activity that was not AD diagnosable. Eighty-four participants between the ages of 50 and 85 were recruited for the original study. Participants were administered the Alzheimer’s Disease Assessment Scale – Cognitive (ADAS-Cog), a QEEG, and a clinical interview. The cross spectra was averaged and LORETA correlation maps.  Correlations were computed for each individual’s ADAS-Cog score compared to each voxel (7×7x7 mm) of their baseline sLORETA.

What we found were significant positive correlations between ADAS-Cog scores and frontal and parietal delta activity, and theta activity in the precuneus. Significant negative correlations were found between ADAS-Cog scores and temporal alpha. This corroborated prior findings and further alluded that as our memory continues to become impaired we expect frontal and parietal delta as well as anterior midline theta to increase. And that alpha will decrease as impairment grows (Townsend, Sherlin & Hall, 2006). This is exactly as you reported as expectations in the EEG.

Budzinski, T., Budzinski, H., & Sherlin, L. (2002).  Short and Long Term effects of Audio Visual Stimulation (AVS) on an Alzheimer’s Patient as documented by Quantitative Electroencephalography (QEEG) and Low Resolution Electromagnetic brain Tomography (LORETA) [Abstract].  Journal of Neurotherapy. Vol 6:1.

Sherlin, L. ,Townsend, A., & Hall, J. (2006). LORETA Analysis of Alzheimer’s Disease. [Abstract].  Journal of Neurotherapy. Vol 9:4.

Townsend, A., Sherlin, L., & Hall, J.  (2006).  LORETA and QEEG Correlations with the Alzheimer’s Disease Assessment Scale. [Abstract].  Journal of Neurotherapy. Vol 9:4.