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LORETA is a functional tomography that computes from EEG and/or MEG measurements, the 3D distribution of electrical neuronal activity. Although extracranial electric and magnetic measurements do not contain enough information for a unique determination of the sources of activity, information is sufficient for a low spatial resolution estimate. In particular, up to the present, LORETA is the only tomography (within the class of instantaneous EEG/MEG, 3D discrete, linear inverse solutions) that can recover fairly well superficial sources, and even deep sources if they have a signal power comparable to (or larger than) that of superficial sources. A new statistical upgrade of LORETA is now available and is a significant enhancement (sLORETA). LORETA-KEY©¨ LORETA-KEY©¨ is free academic software, unrelated to any form of profit-making undertakings. LORETA-KEY©¨ is FreeBrainWare. ABOUT: October 1998 (update: January 2000) now referred to as sLORETA Program by R.D. Pascual-Marqui The Key Institute for Brain-Mind Research University Hospital of Psychiatry Lenggstr. 31, CH-8029, Zurich, Switzerland Tel: +41-1-3843334 FAX: +41-1-3842447 [email protected] , http://www.keyinst.unizh.ch/loreta.htm

You can find some information about LORETA on the WWW site (see address above). Also, from that homepage, you can download some papers on LORETA. This version of LORETA corresponds to the Talairach head model. Computations are made in this head model, with an approximate lead field. There is no cross-registration between a sphere and the realistic Talairach head; although the lead field is approximate. The lead field is not LORETA. Better lead fields will be incorporated in the future. General References 1. Pascual-Marqui, RD, Michel, CM, Lehmann, D. Int. J. Psychophysiol., 1994, 18:49-65 2. Pascual-Marqui, RD. ISBET Newsletter [ISSN 0947-5133], 1995, pp.16-28 3. Ary JP, Klein SA, Fender DH. IEEE Trans. Biomed. Eng., 1981, BME-28:447-452 4. Talairach J, Tournoux P. Co-planar Stereotaxic Atlas of the Human Brain. Stuttgart, Thieme, 1988 5. Towle VL, Bolanos J, Suarez D, Tan K, Grzeszczuk R, Levin DN, Cakmur R, Frank SA, Spire JP. Electroenceph. Clin. Neurophysiol., 1993, 86:1-6 6. Lancaster, JL, Rainey, LH, Summerlin, JL, Freitas, CS, Fox, PT, Evans, AC, Toga, AW, Mazziotta, JC. Human Brain Mapping, 1997, 5:238-242

Low Resolution Electromagnetic Tomography (LORETA), a Powerful Method for Visualizing Intracortical Generators of Surface EEG – Applications for Evaluation of Attentional Disorders, Depression, Autistic Disorders, and other Psychiatric Disorders Joel F. Lubar, Ph.D., University of Tennessee, USA and Judith O. Lubar, LCSW-BCD, Southeastern Biofeedback and Neurobehavioral Institute, USA To be presented February 2003 at the 7th annual Biofeedback Foundation of Europe meeting. LORETA developed by Roberto Marquis Pascal in the mid 1990’s is a technique based on the best of the inverse solutions which allows quantification and visualization of intracortical activity including paleocortical activity derived from scalp electrodes. Areas that can be evaluated include the cingulate gyrus and orbital-frontal cortices. The technique divides the cortex into 2,394 7 x 7 x 7 millimeter voxels (cubes). The inverse solution can be obtained from 19 electrodes and is comparable to that obtained with denser surface electrode arrays. This presentation will show the relationship between LORETA and quantitative EEG in the evaluation of a number of disorders that can be treated by neurofeedback.

FREQUENCY STRUCTURE AND NEURONAL GENERATORS OF EYES-CLOSED EEG R.D. Pascual-Marqui PhD, M. Esslen PhD, D. Lehmann, Dr. med., Dr. med. h.c., Professor The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Switzerland [email protected] Introduction. Awake, eyes-closed EEG is usually analyzed in the frequency domain. At first, the classical EEG frequency bands were defined as: delta (0.5-3.5 Hz), theta (3.5-7.5 Hz), alpha (7.5-12.5 Hz), beta1 (12.5-18.0 Hz), and beta2 (18.0-30.0 Hz). Later, by means of a factor analysis performed on power spectra, Herrmann, Fichte, & Kubicki. (1978) found different bands: delta (1.5-6.0 Hz), theta (6.5-8.0 Hz), alpha1 (8.5-10.0 Hz), alpha2 (10.5-12.0 Hz), beta1 (12.5-18.0 Hz), beta2 (18.5-21.0 Hz), and beta3 (21.5-30.0 Hz). Unlike the original definition of frequency bands, the latter definition of Herrmann was based on an objective quantitative methodology. Aims. 1. To attempt to replicate the results of Herrmann using factor analysis and objective hierarchical clustering methods 2. To segment the EEG frequencies by using the microstate segmentation technique applied to the frequency domain, and to compare with the results of Herrmann. 3. To find the electric neuronal generators of the different EEG frequency components. Material. Twenty-five channels eyes-closed EEG was recorded from 17 healthy normal subjects. 20 artifact-free two- second EEG epochs were selected from each subject. Results. We were able to replicate the results of Herrmann by factor-analyzing our data, and by employing a hierarchical clustering method. However, microstate segmentation produced different results: delta (1.5-2.5 Hz), theta (3.0-7.0 Hz), alpha1 (7.5-9.5 Hz), alpha2 (10.0-12.0 Hz), beta1 (12.5-15.5 Hz), beta2 (16.0-24.0 Hz), and beta3 (24.5-30 Hz). Low resolution brain electromagnetic tomography (LORETA) was used for the comparison of the generators of the successive frequency bands obtained by microstate segmentation by means of a statistical non-parametric mapping approach. Delta generators were widespread distributed frontal, theta generators were midline frontal, alpha generators were occipital, while beta generators were fronto-temporal. Conclusion. A methodology is proposed for characterizing the spatio-frequency structure of the EEG, which avoids the analysis of all discrete frequencies, and objectively determines relevant frequency bands. Reference. Herrmann, W. M., Fichte, K. & Kubicki, S. (1978). The mathematical rationale for the clinical EEG-frequency-bands. 1. Factor analysis with EEG-power estimations for determining frequency bands. EEG-EMG Zeitschrift fur Elektroenzephalographie Elektromyographie und Verwandte Gebiete. 9, 146-154.

SHALL WE TRUST THE Z-SCORES OF NORMATIVE DATABASES? AN ALTERNATIVE SOLUTION AND A SIMULATION STUDY ON ACCURACY MARCO CONGEDO, MA The University of Tennessee, Knoxville, Tennessee [email protected] Presentation: Society for Neuronal Regulation, September 2002 Introduction. Quantitative Electroencephalography (qEEG) as a tool for the diagnosis of neurological and psychiatric disorders is receiving an increased interest. While qEEG analysis is restricted to the scalp, the recent development of electromagnetic tomographies (ET) allows the study of the electrical activity of cortical structures. Electrical measures of a patient can be compared to a normative database derived on a large sample of healthy individuals. The deviance from the database’s norms provides a probabilistic measure of the likelihood that the patient’s electrical activity reflects normal brain functioning. The focus of this presentation is the method for estimating such deviance. Method. The traditional method based on z-scores (“parametric”) is reviewed and a new method based on percentiles (“non-parametric”) is proposed. The parametric and the non-parametric methods are compared using simulated data. The accuracy of both methods is assessed as a function of normative sample size and gaussianity for three different alpha levels. Results. Results suggest that the performance of the parametric method is unaffected by sample size, given that the sample size is large enough (N > 100), but that non-gaussianity jeopardizes accuracy even if the normative distribution is close to gaussianity. On the contrary the performance of the non-parametric method is unaffected by non-gaussianity, but is a function of sample size only. It is shown that, with N > 160, the non-parametric method can be considered always preferable. Conclusions. Results will be discussed taking into consideration technical issues related to the peculiar nature of qEEG and ET data. It will be suggested that the sample size is the only constant across EEG frequency bands, measurement locations, and kind of quantitative measures. As a consequence, for a given database, the error rate of the non-parametric database is homogeneous; however the same is not true for the parametric method.

QEEG SUBTYPES OF MATH LEARNING DISABILITY AND TREATMENT IMPLICATIONS Robert Gurnee, MSW ADD Clinic, Scottsdale, Arizona [email protected] Introduction. An analysis was done of 50 randomly selected ADHD client’s QEEG topographic brain maps to determine if any unique patterns are present separate from ADHD to differentiate Math learning disabilities from ADHD. Method. Fifty randomly selected ADHD clients with Math Learning Disabilities (MLD) who had QEEG topographic brain maps were evaluated for abnormalities they shared in common different from those expected to be present secondary to their ADHD. The New York University E. Roy John Normative Data Base was used and a minimum of one standard deviation discrepancy from normal was utilized. MLD was defined as 20 standard score units discrepancy between math achievement test scores and the higher of the clients’ verbal or abstract reasoning IQ scores, when math achievement was at least two years below average. Results. The following patterns emerged: Elevated Parietal Delta: 6% Elevated Parietal Theta: 26% Elevated Parietal Alpha: 50% Elevated Parietal Beta: 20% There were also coherence abnormalities. Conclusion. Ninety-six per cent of this sample appeared to have MLD QEEG abnormalities in the parietal lobes suggesting that down training the particular elevated bandwidth might expedite the treatment of MLD.

SPECT VS. QEEG MAP VS. QEEG SCAN: WHICH IS THE MOST ACCURATE AND BEST VALUE FOR ADHD? Michael K. Linden, PhD ADD Treatment Centers, San Juan Capistrano, California [email protected] Introduction. The use of brain imaging techniques is becoming more widely accepted as accurate diagnostic techniques and predictors of treatment in the field of ADHD. Daniel Amen (1993) theorized six subtypes of ADHD using SPECT imaging and developed unique treatment recommendations (medications, neurofeedback) for each subtype. Monastra, Lubar & Linden (2001) have completed numerous studies using a QEEG Scan technique to differentially diagnose ADHD and predict medication response. Several researchers (Chabot & Serfontein, 1996; Mann, Lubar, Zimmerman, Miller & Muenchen, 1992; Lubar, Swartwood, Swartwood & Timmermann, 1995) have completed research using QEEG maps to help diagnosis ADHD and have suggested that up to 12 subtypes of ADHD may exist. Method. This presentation will review the past and current research using these brain imaging techniques with children and adults with ADHD. Case example of results of all three imaging techniques will be discussed. Results. This is not a research study; only a review of past literature and current case examples will be presented. No comparative statistics will be performed. Conclusion. QEEG mapping, QEEG scans and SPECT can be used effectively to accurately diagnose ADHD in children and adults. These techniques can also lead to predictions of medication response and specific neurofeedback protocol development. The QEEG scan is the most efficient test to diagnosis simple ADD/ADHD. QEEG maps are the best technique to develop neurofeedback protocols in complex cases with comorbid disorders or when patients are taking medications which cannot be discontinued for assessment. SPECT is best used to predict the type of medications to be successful. References. Amen, D., Paldi, J., & Thisted, R. (1993). Evaluating ADHD with brain SPECT imaging. Journal of the American Academy of Child and Adolescent Psychiatry, 32 (5), 1080-1081. Chabot, R. & Serfontein, G. (1996). QEEG profiles of children with ADHD. Biological Psychiatry, 40, 951-963. Lubar, J., Swartwood, M., Swartwood, J., & Timmerman, D. (1996). QEEG and auditory ERPs in the evaluation of ADHD: Effects of methylphenidate and implications for neurofeedback training. Journal of Psychoeducational Assessment, (Monograph: Assessment of AD-HD), 143-160. Mann, C., Lubar, J., Zimmerman, A., Miller, C. & Muenchen, R. (1992). Quantitative analysis of EEG in boys with ADHD: Controlled study with clinical implications. Pediatric Neurology, 8, 30-36. Monastra, V., Lubar, J., Linden, M., Van Deusen, P., Green, G., Wing, W. et al. (1999). Assessing ADHD via QEEG: An initial validation study. Journal of Neuropsychology, 13 (3), 424-433. Monastra, V., Lubar, J., & Linden, M. (2001). The development of a QEEG scanning process for ADHD: Reliability and validity studies. Journal of Neuropsychology, 15 (1), 136-144. QEEG REFERENCE DATABASE EVALUATION OF ADULT ADHD: FOLLOW-UP ANALYSES WITH LORETA J. Noland White, PhD Georgia College & State University, Milledgeville, Georgia [email protected] Introduction. White and Lubar (2002) suggested that QEEG normative reference databases may potentially provide additional markers for adult ADHD other than traditional amplitude or power ratios. In that study, both eyes-closed and eyes-open EEG baselines were analyzed with the NeuroRep QEEG Analysis and Report System (Hudspeth, 2000) and the Sterman-Kaiser Imaging Laboratory’s (SKIL) Topometric Software Package (Sterman & Kaiser, 2000). The most notable potential markers identified were right prefrontal hypo-phase in the 13 to 22 Hz band and frontal hypercomodulation at the dominant frequency, which was often in the 9 to 10 Hz range (White & Lubar). Method. The present study further investigates potential QEEG markers by incorporating the use of Low Resolution Electromagnetic Tomography (LORETA) for the same 10 adults with ADHD. The previous results gained from comparison against the Adult QEEG Reference Database (Hudspeth, 2000) and the SKIL adult database (Sterman & Kaiser, 2000) will be used to guide the present investigation of current source density as measured by LORETA. All LORETA image files will be created with the aid of the EEG Workstation (Congedo, 2001) and viewed with the LORETA-KEY software (Pascual-Marqui, Michel, & Lehmann, 1994). Results & Conclusion. Results of the LORETA analyses for each individual’s eyes-closed and eyes-open baseline dominant frequency revealed that the modal location of the current source density generators were typically in visual association cortex. For the eyes-closed condition, the modal generator was found in Brodmann Area 19, primarily the lingual gyrus. For the eyes-open condition, the modal generators were in Brodmann Areas 19 and 30, including the lingual gyrus, posterior cingulate, and parrahippocampal gyrus. These results and possible implications will be discussed with regard to the previous QEEG findings. References. Congedo, M. (2001). EEG Workstation (Version 2.0) [Computer software]. Knoxville, TN: Nova Tech EEG, Inc. Hudspeth, W. J. (2000). NeuroRep QEEG Analysis and Report System (Version 4.0) [Computer software]. Los Osos, CA: Grey Matter, Inc. Pascual-Marqui, R. D., Michel, C. M., & Lehmann, D. (1994). Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain. International Journal of Psychophysiology, 18 (1), 49-65. Sterman, M. B., & Kaiser, D. A. (2000). SKIL QEEG analysis software (Version 2.05) [Computer software]. Bel Air, CA: Sterman-Kaiser Imaging Laboratory. White, J. N., & Lubar, J. F. (2002). QEEG reference database evaluation of adult ADHD [Abstract]. Journal of Neurotherapy, 6 (1), 104-107.

USING LORETA AND THE COUNTING STROOP TO STUDY EARLY STAGE ALZHEIMER’S PATIENTS Kerry Towler, MA University of Tennessee, Knoxville, Tennessee [email protected] Introduction. The U.S. population is aging and the diagnostic and health care costs related to diseases associated with aging are frightening to contemplate for the future. Developing inexpensive diagnostic and study methods for these diseases is clearly desirable.. One disease in particular that is currently difficult to identify with available brain imaging and behavioral diagnostics is Alzheimer’s Disease (AD). The gold standard for AD diagnosis is still autopsy in which diseased brains show evidence of the pathology: senile plaques and neurofibrillary tangles. The research being reported utilized a technique called Low Resolution Tomographic Analysis (LORETA) to study early stage AD patients and similar aged, healthy controls during the Counting Stroop, a cognitive task that is analogous to the Color-Word Stroop (Bush et al. 2000), to evaluate its efficacy as a diagnostic and study tool in the early stages of Alzheimer’s disease. Method. Participants were early stage AD patients (n=6) and similar aged healthy Controls (n=8). EEG recordings were conducted with Lexicor’s V4.1E software and a 19-channel electrode cap utilizing the 10-20 international electrode placement system. Impedance was kept below 5 kilo-ohms and the sampling rate was 128 samples per second. Relative power bands were defined as delta (2 -3.5 Hz), theta (4-7.5 Hz) and beta 1 (13-21.5 Hz).The computerized stimuli came from the Counting Stroop: incongruent stimuli (IS) and the neutral stimuli (NS). Within groups statistical evaluation was accomplished by subtracting the NS data from IS data for the group aggregate and non-parametric T-tests performed with LORETA Wizard. The LORETA-KEY was used to provide 3-dimensional images of intracerebral EEG-data. Results. Between groups comparisons demonstrated obvious pattern and relative power differences that support current research in the AD field. However, the within group T-score comparisons did not reveal any significant activation differences between the IS (hard task) and the NS (easy task) across all 3-D neural locations. The two groups, AD and healthy Controls, differed in the use of what is typically labeled as Delta, Theta and Beta 1 activity. In particular, the AD group produced 2 to 3.5 Hz , 4 to 7.5 Hz, and 13 to 21.5 Hz frequencies during the IS task in the left and right temporal lobes while the Controls produced it during the NS task. Also, the AD group turned on 2 to 3.5 Hz activity at the anterior cingulate (Brodmann area 24) during the IS task while the Control group demonstrated the activity during the NS task. As of the date of the submission of this abstract, a statistical program to compare the two groups’ patterns within the LORETA purview is being developed by a colleague, Marco Congedo, M.A. These results will be added to the presentation if available. Conclusions. In the literature, one of the primary relative power differences observed with Quantitative Electroencephalography (QEEG) between patients with moderate AD and their healthy contemporaries is that AD patients produce more 4 to 7.5 Hz (Theta) activity during eyes-closed resting conditions. As the severity of the disease progresses 2-3.5 Hz (Delta) activity increases and 13 – 21.5 Hz (Beta 1) activity decreases (Coben, Danziger, & Storandt, 1985; Jelic et al. 2000). Though the outcomes of this investigation were the result of cognitive tasking, this study found between group differences in each of those frequency ranges. These results were obtained with AD patients in the early stages of the disease. The temporal lobe is one of the first cortical areas to show evidence of atrophy in AD patients (Kaye et al., 1997). According to research by Kaye et al., the temporal lobe volume (measured without the hippocampal tissue or parahippocampal gyrus regions) in preclinical dementia participants changed more over time (decreased) than that of the healthy participants. Their supposition is that the disease process may be in motion (e.g. temporal lobe volume loss) as much as six years prior to the onset of clinical dementia symptoms. This project’s demonstration of cognitive task activation differences in the Delta, Theta and Beta 1 bands between the early stage AD group and the Control group lend support to the conclusions of Kaye and colleagues. Finally, the Counting Stroop has been demonstrated with fMRI to show increased anterior cingulate activity during the IS task in healthy normal people (Bush et al., 1998). The cingulate has been implicated in neural attention circuitry. This project has demonstrated a differential use of the 2 to 3.5 Hz (Delta) activity between the groups during the IS task. The AD group turned on the lower frequency during the IS task while the Control group utilized it during the NS task. The NS task is the easier of the two tasks and doesn’t instigate the attentional conflict and as such would not be expected to demonstrate activity above that of the IS task at the cingulate. References. Bush, G., Whalen, P. J., Rosen, B. R., Jenike, M. A., McInerney, S. C., & Rauch, S. L. (1998). The counting stroop: An interference task specialized for functional neuroimaging-validation study with functional MRI. Human Brain Mapping, 6, 270-282. Coben, L. A., Danziger, W., & Stroandt, M. (1985). A longitudinal EEG study of mild senile dementia of Alzheimer type: Changes at 1 year and at 2.5 years. Electroencephalography and Clinical Neurophysiology, 61, 101-112. Jelic,V., Johansson, S.-E., Almkvist, O., Shigeta, M., Julin, P., Nordberg, A. et al. (2000). Quantitative electroencephalography in mild cognitive impairment: longitudinal changes and possible prediction of Alzheimer’s disease. Neurobiology of Aging, 21(4), 533-540. Kaye, J. A., Swihart, T., Howieson, D., Dame, A., Moore, M. M., Karnos, T. et al. (1997) Volume loss of the hippocampus and temporal lobe in healthy elderly persons destined to develop dementia. American Academy of Neurology, 48 (5), 1297-1304. SIX CASE STUDIES EXAMINING THE EFFECTIVENESS OF A COMPREHENSIVE ADAPTIVE APPROACH TO NEUROFEEDBACK FOR ATTENTION DEFICIT IN AN EDUCATIONAL SETTING Shannon Warwick, MA candidate Union Institute and University at Vermont College, Asheville, North Carolina [email protected] Introduction. Six AD/HD elementary school students completed 19 hours of neurofeedback training over six months averaging 45 sessions. Five of the six students measurably improved in parent/teacher report and/or objective data relatively congruent with QEEG analysis. Improvement seemed related to lower theta/beta ratios. This comprehensive adaptive approach is theoretically based upon restoring neurological flexibility and resilience, allowing circadian rhythms to renormalize and functionality to emerge (Brown, 2002). Method. Three male and three females, ranging 9-12 years old, attending a private learning center specializing in dyslexia were previously diagnosed with AD/HD. Five out of six were taking 15-20mgs of various psychostimulant medications. Evaluation measures included QEEG analysis with theta/beta ratios (Monastra, et. al, 1999; Lubar et al, 2001), IVA, Stroop, WISC-III ACID subtests, ADDES behavior ratings and a Likert scale of improvement evaluation. QEEG data was analyzed in terms of absolute and relative magnitude, as well as in terms of theta/beta ratios. Theta-beta ratios averaged across 19 channels ranged from 1.40 to 7.69. Active electrodes sited at C3 and C4, referenced and grounded on ipsilateral ear lobes, input to two channels of the ProComp+ that fed data to a KeyData laptop accommodating NeuroCarePro software with dual monitor capability. Approximately thirty-second baselines were recorded before and after each session. Inhibits targeted 2-6 Hz delta/theta, 8-13 Hz alpha under eyes open conditions, and 23-38 Hz high beta at all times, producing visual and auditory feedback when the emergent median remained within a neighborhood defined by no more than 80% divergence. Feedback for all targets, including augments, was disabled by default if excursions occurred outside inhibit boxes. Visual and auditory information also reflected feedback if the mean of the median remained within 12-15 Hz SMR on the right, 16-20 Hz beta on the left, 21 Hz and 40 Hz, either separately or simultaneously using comprehensive portals. Excursions outside augment boxes had no effect on other targets. Changes were monitored by NeuroCarePro snapshot spectral analysis comparatives. Results. Medication titration began within 7-10 sessions. The only child not on medication maintained unprecendented straight A’s and is returning to mainstream schooling. One student discontinued medication and four reduced to half the original dosage, two of which demonstrated consistent success in cognitive measures, transfer of benefit, and stabilization of medication reductions. Two with severe theta/beta ratios were inconsistent in measures and returned to two-thirds and original dosage levels respectively with positive report the last two weeks of school. QEEG analysis echoed other measures in varying degrees consistent with previous findings (Chabot, Merkin, Wood, Davenport, & Serfontein, 1996). Conclusions. Without a control group cross-validating results, a systematic simultaneous procedure under relatively controlled conditions with single case studies can be regarded as a between-person replication of objective and subjective data (Barabasz, Barabasz, & Blampied, 1996). The present study replicates findings five out of six times in support of previous results found in neurofeedback research (Lubar & Lubar, 1984; Lubar, Swartwood, Swartwood, & O’Donnell, 1995; Linden, Habib, & Radojevic, 1996; Thompson & Thompson, 1998). That training effects were replicated with varying degrees of severity, on different types of psychostimulants, within a rotating schedule, following an adaptive protocol, increases confidence in the effectiveness of this comprehensive approach to neurofeedback for AD/HD. One and possibly three-year follow up will assess longevity. Further research may confirm the seeming correlation between consistency of success and degree of theta/beta ratio. References. Barabasz, M., Barabasz, A., & Blampied, N. (1996). A primer of case study research in neurotherapy. Journal of Neurotherapy, 1 (4), 12-14. Brown, V. (2002). The mean of the median: A new metric for targeting in clinical neurofeedback? [Abstract] Journal of Neurotherapy 6 (1), 53-54. Chabot, R. J., Merkin, H., Wood, L. M., Davenport, T. L., & Serfontein, G. (1996). Sensitivity and specificity of QEEG in children with attention deficit or specific developmental learning disorders. Clinical EEG, 27 (1), 26-34. Linden, M., Habib, T., & Radojevic, V. (1996). A controlled study of the effects of EEG biofeedback on the cognition and behavior of children with attention deficit disorders and learning disabilities. Biofeedback and Self Regulation, 21(1), 35-49. Lubar, J.O. & Lubar, J.F. (1984). Electroencephalographic biofeedback of SMR and beta for treatment of attention deficit disorders in a clinical setting. Biofeedback and Self Regulation, 9, 1-23. Lubar, J. F., Monastra, V .J., & Linden, M. (2001). The development of a quantitative electroencephalographic scanning process for attention deficit-hyperactivity disorder: Reliability and validity studies. Neuropsychology, 15, (1), 136-144. Lubar, J. F., Swartwood, M. O., Swartwood, J. N., & O’Donnell, P. H. (1995). Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in T.O.V.A. scores, behavioral ratings, and WISC-R performance. Biofeedback & Self-Regulation, 20 (1) 83-99. Monastra, V., Lubar, J., Linden, M., VanDeusen, P., Green, G., Wing, W. et al. (1999). Assessing attention deficit hyperactivity disorder via quantitative electroencephalography: An initial validation study. Neuropsychology, 13 (3), 424-433. Thompson, L. & Thompson, M. (1998). Neurofeedback combined with training in metacognitive strategies: Effectiveness in students with ADD. Applied Psychophysiology and Biofeedback, 23 (4), 243-263.

Society for Neuronal Regulation, 8th Annual ConferenceSt. Paul, Minnesota, September 20-24, 2000 Abstracts of Invited Presentations on LORETA by Roberto D. Pascual-Marqui Low resolution brain electromagnetic tomography (LORETA):the technique, its validation, and methods of analysisRoberto D. Pascual-MarquiThe KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, SuisseMulti-channel recordings of scalp electric potential differences (EEG/ERPs) provide insufficient information for determining uniquely the three-dimensional distribution of electric neuronal activity in brain. This means that infinitely many possible solutions exist for this inverse problem. Many particular solutions have been published in the literature, each one characterized by its own set of assumptions. In general, if the assumptions are incorrect, then the solution can be meaningless.It is a well-known fact from electrophysiology that the fundamental reason why EEG can be measured on the scalp is the occurrence of highly synchronized post-synaptic potentials in clusters of cortical pyramidal neurons. By taking this single electrophysiological fact into account, i.e. synchronization, a new inverse solution is obtained: low resolution brain electromagnetic tomography (LORETA).With the development of LORETA, it can now be shown that the scalp electric potential provides sufficient information for obtaining a low spatial resolution estimate of the electric neuronal activity. From a mathematical viewpoint, LORETA yields a spatial low-pass filtered version of the cortical current density, with correct localization. From an electrophysiological viewpoint, LORETA is consistent with the highly synchronized activity of neighboring neuronal populations. From an empirical viewpoint, functional LORETA images yield correct neuroanatomical localization in visual and auditory evoked potential experiments.The LORETA method currently implemented makes use of the human head model described in the Talairach brain atlas. By means of cross-registration techniques, EEG measurements made on any human head can be adjusted to the geometry of the Talairach reference brain.A LORETA image corresponding to the P100 visual evoked potential peak (data kindly provided by Koenig and Lehmann, 1996) is shown in the figure (maximum current density in Brodmann area 17): Once the validity of the method is established, LORETA can be used as a relatively trustworthy tool for the study of brain function, as is carried out with other well-established methods, such as PET and fMRI. However, unlike PET and fMRI, which provide metabolic information, LORETA images provide high time resolution electric neuronal activity information.Methods of analysis of LORETA images for event related potential data and spontaneous EEG data are reviewed. In the case of ERP data, LORETA images are usually computed at peak latencies, offering information about the location and distribution of the electrically active neurons that generated the ERP component. Instantaneous LORETA images can also be computed for EEG. These images are of interest when analyzing, e.g., epileptic spikes. However, it is also often relevant to compute “frequency band” LORETA images, which offer information about the location and distribution of the electrically active neurons that generated, e.g., the alpha rhythm.

Functional localization and functional connectivity with LORETA:comparison of normal controls and “pure” schizophrenicsR.D. Pascual-Marqui*, M. Koukkou**, D. Lehmann*, K. Kochi**The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Suisse**Brain Mapping Lab., University Hospital of Psychiatry, Bern, SuisseTwo important general questions arise when studying the human brain: what function does each part have, and how do these different parts interact. Answers to both questions can be obtained with an EEG-based functional imaging technique: low resolution brain electromagnetic tomography (LORETA). This method provides high time-resolution information on the three-dimensional distribution of electric neuronal activity in the brain.In this report, 9 acute, neuroleptic-naive, first-episode, productive schizophrenics were compared to 36 normal controls. 19-channel EEG was recorded during resting condition.In a first step, the neuronal generators of different EEG frequency bands were examined, with the purpose of identifying brain regions (“parts”) with deviant activity of different functional significance. Patients showed an excess of Delta frequency band generators (inhibitory pattern) in anterior brain areas; deficit of Theta, Alpha1 and 2 (normal resting pattern) in anterior-inferior areas for Theta, and in anterior left for Alpha1 and 2; excess of Beta1, 2 and 3 (excitatory pattern) in posterior-superior right areas.In a second step, “interactions between parts” were investigated. Functional connection between two brain regions was quantified by the correlation between current density signals computed at those sites. The spatial correlation structure was modeled in terms of contributions from isotropic connections (short range connections between any two neighboring regions in the brain), and from long range connections. Patients exhibited significantly decreased functional connections in the Theta band for the following features: the global whole-brain functional connectivity, and the spatial extent of short-range connectivity. In particular, connections between anterior brain regions were impaired in the patients, as shown in the figure: Brodmann Areas underlying electrodes:A: 8,6,32,9,24; B: 8,9,6,46,10 (right); C, D: 4,3,6,2,1,40,44 (left and right)

NeuroImage Human Brain Mapping 2002 Meeting Poster No.: 10113 CDRSPM: STATISTICAL PARAMETRIC MAPPING OF LORETA USING HIGH DENSITY EEG AND INDIVIDUAL MRI HAE-JEONG PARK , JUN SOO KWON , TAK YOUN , MYUNG SUN KIM , JAE-JIN KIM Human Life Sciences Department of Psychiatry Clinical Cognitive Neuroscience Center, Seoul National University, College of Medicine

Subject: Imaging Techniques

Abstract This paper describes a tool (CDRSPM) for the statistical parametric mapping of LORETA (low resolution electromagnetic tomography) using high density EEG and individual MRI. First, LORETA was calculated by Curry 4.1(Neuroscan soft, USA), using a realistic head model of the boundary element method with individual anatomy in order to estimate the current density maps from the scalp topography of the 128 channel EEG. From the current density maps that covered the whole cortical gray matter, up to 20,000 points, volumetric current density images were reconstructed. Intensity normalization of the smoothed current density images was used to reduce the compounding effect of subject specific global activity. After transforming each image into a standard stereotactic anatomical space, we performed statistical parametric mapping of the normalized current density images. We applied this method to the source localization of MMN in schizophrenia. The MMN generators, produced by a deviant tone of 1,200 Hz (5% of 1600 trials) under the standard tone of 1,000 Hz, 80dB binaural stimuli with 300 msec of interstimulus interval, were measured in fourteen right-handed schizophrenic subjects and fourteen age-, sex-, handedness matched controls. We found that the schizophrenic group exhibited significant current density reductions of MMN in the left superior temporal gyrus and the left inferior parietal gyrus (p NeuroImage Human Brain Mapping 2002 Meeting Poster No.: 10103 ABNORMAL PARALLEL CORTICAL GENERATION OF HIGH AND LOW EEG RHYTHMS IN AD: A MULTI-CENTRIC LORETA STUDY

Claudio Babiloni , Fabio Babiloni , Filippo Carducci , Daniele Cerboneschi , Paola Chiovenda , Febo Cincotti , Gloria Dal Forno , Matilde Ercolani , Fabrizio Eusebi , Raffaele Ferri|| , Bartolo Lanuzza , Carlo Miniussi , Davide Moretti , Franca Nobili , Roberto Pasqual-Marqui||||, Patrizio Pasqualetti , Flavia Pauri , Nicola Quattrini , Guido Rodriguez , GianLuca Romani , Serenella Salinari , Franca Tecchio , Pedro ValdŽs-Sosa||||||, Paolo Vitali , Filippo Zappasoldi , PaoloMaria Rossini , PaoloMaria Rossini Dip. Fisiologia Umana e Farmacologia, Univ. La Sapienza Rome, Italy

CNR-A.Fa.R. CRCCS- Osp. FBF; Isola Tiberina, Rome, Italy

Clinica neurologica, Univ. Campus Biomedico, Roma, Italy; || Dept of Neurology, Oasi Institute for Research on Mental Retardation and Brain Aging (IRCCS), Troina-Italy

IRCCS Division of Clinical Neurophysiology (DIMI), University of Genova, Italy

||||The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland

ITAB Univ. Chieti, Italy

Dipartimento INFOCOM Univ. La Sapienza, Rome-Italy, Roma, Italy

||||||Cuban Neuroscience Center (CNC)

Abstract Background. We have been developing a WEB “on-line” databa project (ASP tech) aimed at evaluating the localization of brain generators of EEG/MEG rhythms in normal, Alzheimer disease (AD) and vascular dementia subjects and at verifying the utility of such a localization for an objective differential diagnosis of dementia, for the assessment of the dementia degree (mild to moderate), and for the monitoring of therapeutic regimes (http://hreeg.ifu.uniroma1.it/Alzheimer.htm). Statistical queries on the group data will be available for internet users. Whereas, passwords will regulate the access to individual data, to protect anonymity of patients’ data.

Aim. Previous evidence has shown a frontalization of alpha and beta EEG rhythms in AD, based on scalp spectral data or single dipole spectral solutions. Here cortical sources of EEG rhythms were investigated by a modern source estimation technique (low resolution brain electromagnetic tomography, LORETA) in AD and normal subjects, to localize in Talairach space the regions of abnormal rhythmicity in AD.

Methods. EEG data (5min, rest condition, closed-eyes) were recorded from 19 electrodes (10-20 system) in right-handed volunteers (27 AD patients and 26 age-matched normal subjects). All AD patients met the DSM-III-R or DSM-IV criteria for primary degenerative dementia and the standard NINCDS-ADRDA criteria for possible to probable AD. Spectral analysis of delta (2-4Hz), theta (4-8Hz), alpha (8-13Hz), beta1 (13-20Hz), and beta2 (20-30Hz) EEG data was performed by FFT on artifact-free (2sec) EEG segments. To model cortical sources of EEG data, LORETA used a three-shell spherical head model and a brain source space (2394 dipoles in corresponding voxels). This space was co-registered to the Talairach brain Montreal atlas. Statistical t maps were computed to evaluate inter-group differences.

Results and Conclusions: Compared to normative data (Fig.1), AD delta and theta power was stronger and circumscribed in posterior cortical regions, (highest t values being in occipital lingual gyrus; BA 17 for delta and BA 18 for theta). Furthermore, AD delta and theta power was lower in middle and superior frontal gyri (BA 6 for delta and theta). Noteworthy, the inter-group LORETA differences in high frequencies regarded different cortical regions. With respect to normative data, AD alpha and beta power was lower in parietal (highest t values in BA 7 for alpha and beta 1) and parieto-occipital (highest t values in BA 19 for beta2) precuneus. Also, AD alpha and beta power was stronger in medial frontal gyrus (highest t values in BA 10 for alpha and beta 1 and in BA 32 for beta2) and in anterior cingulum (highest t values in BA 19 for beta2). These results extend previous evidence of a coarse frontalization of alpha and beta rhythms in AD, although spatial resolution of LORETA is less accurate than that of SPECT, PET, and fMRI. Indeed, our LORETA findings support the novel idea that, in AD, the increment of low (high) rhythms had a diverse spatial localization from the decrement of high (low) rhythms. This disclosed an abnormality in parallel (subcortico-)cortical generation of low and high EEG rhythms, impinging upon prefrontal, premotor, parietal, and occipital regions

Topographical analysis of the EEG using LORETA and Hidden Markov Models SCHLATTMANN P, HERGERL U, GALLINAT J Freie UniversitŠt Berlin, – Institut fŸr Soziale Medizin -, Arbeitsgruppe Epidemiol ogie, [email protected] Session: Medical signal and image processing – 2, Sept. 13, 15:00 LORETA (Low resolution electromagnetic tomography) [Pasqual-Marqui et al, 1994] provides a three-dimensional reconstruction of the electric activity of the brain in a standardised way. For each three-dimensional voxel the electrical activity is estimated and reconstructed from scalp measurements. An interesting question is how to localise regions of high or low activity based on the estimated activity for each voxel. This leads to the problem of identifying spatial heterogeneity for the three dimensional tomogram. An obvious approach is to categorise the voxels into percentiles and to assign colours or grey-scales accordingly. As a result we may have a colourful tomogram even if constant activity is present. Frequently “Significance Probability Maps” [Duffy et al., 1981] are used for spatial representation of EEG data based on z- or t- Statistics. Here we have the problem of multiple testing, which leads to an inflation of the type I error. Using a Bonferroni correction leads to a dramatic loss of power. Alternatively we make use of mixture models as proposed in geographic epidemiology [Schlattmann and Bšhning, 1993]. Mixture models may be seen as hidden Markov random fields which seems a natural approach to the problem at hand and which provide a consistent estimate of heterogeneity. In this setting we make use of the normal distribution as mixing kernel. The estimation of the mixture model may be done with the program C.A.MAN [Bšhning et al., 1992, 1998] which allows the estimation of mixture models for various densities from the exponential family. The construction of the tomogram is achieved using the posterior probability of component membership for each voxel applying a maximum rule. We present the methodology using data on patients 24 suffering from Alzheimer«s Disease and 24 healthy controls [Gallinat et al, 1998]. References Bšhning D, Schlattmann P and Lindsay BG (1992):”C.A.MAN – Computer Assisted Analysis of Mixtures: Statistical Algorithms”,Biometrics, 48, 283-303 Bšhning D, Dietz E, Schlattmann P (1998):”Recent developments in Computer Assisted Mixture Analyis: CAMAN”, Biometrics, 54, 525-536. Duffy FH, Bartels PH, Burchfield J(1981): “Significance probability mapping: An aid in the topographic analysis of brain electrical activity. Eletroencephalogr Clin Neurophysiol, 60, 455-463 Gallinat J, Schulz C, Schršter A, Hampel H, Buch K, Nolde T, Mavrogiorgou P, StŸbner S, Padberg F, Mšller HJ, Hegerl, U (1998): “Quantitative EEG in patients with Alzheimers disease, depression and healthy subjects. International Congress on Alzheimer«s Disease, Munich Pasqual-Marqui RD, Michel CM, Lehmann D (1994). Low resolution electromagnetic tomography: a new method for localizing electrical activity. International journal of Psychophysiology, 18, 49-65 Schlattmann P and Bšhning D(1993): “Mixture Models and Disease Mapping”, Statistics in Medicine., 12, 1943-1950

1: Neuroimage 2002 Jul;16(3 Pt 1):678-95 Anatomically informed basis functions for EEG source localization: combining functional and anatomical constraints.

Phillips C, Rugg MD, Friston KJ.

Institute of Cognitive Neuroscience, Wellcome Department of Cognitive Neurology, Institute of Neurology, University College London, London, United Kingdom.

Distributed linear solutions have frequently been used to solve the source localization problem in EEG. Here we introduce an approach based on the weighted minimum norm (WMN) method that imposes constraints using anatomical and physiological information derived from other imaging modalities. The anatomical constraints are used to reduce the solution space a priori by modeling the spatial source distribution with a set of basis functions. These spatial basis functions are chosen in a principled way using information theory. The reduced problem is then solved with a classical WMN method. Further (functional) constraints can be introduced in the weighting of the solution using fMRI brain responses to augment spatial priors. We used simulated data to explore the behavior of the approach over a range of the model’s hyperparameters. To assess the construct validity of our method we compared it with two established approaches to the source localization problem, a simple weighted minimum norm and a maximum smoothness (Loreta-like) solution. This involved simulations, using single and multiple sources that were analyzed under different levels of confidence in the priors. ——————————————————————————–

2: C R Biol 2002 Apr;325(4):273-82 EEG source identification: frequency analysis during sleep. Coatanhay A, Soufflet L, Staner L, Boeijinga P. FORENAP, Institute for Research in Neuroscience and Psychiatry, 27, rue du 4e-RSM, 68250 Rouffach, France. This article deals with a new approach in sleep characterization that combines EEG source localisation methods with standard frequency analysis of multielectrode EEGs. First, we describe the theoretical methodology and the benefits that we get from a three-dimensional image (LORETA) of the cerebral activity related to a frequency band. Then, this new application is used as signal-processing technique on sleep EEG recordings obtained from young male adults using four frequency bands (delta 0.5-3.5 Hz, theta 4.0-7.5 Hz, alpha 8.0-12.5 Hz and beta 13.0-32.0 Hz) in different sleep stages. Finally, we show that the obtained results are highly consistent with other physiological assessments (standard EEG mapping, functional magnetic resonance imaging, etc.), but give us more realistic additional information on the generators of electromagnetic cerebral activity. ——————————————————————————–

3: Acta Neurobiol Exp (Warsz) 2001;61(4):299-308 Event-related current density in primary insomnia.

Szelenberger W, Niemcewicz S.

Department of Psychiatry, Medical University of Warsaw, 00-665 Warsaw, 27 Nowowiejska St., Poland. [email protected]

Using Low Resolution Electromagnetic Tomography (LORETA), event-related current density was investigated in 14 patients with primary insomnia and 14 controls matched for age, gender and education level. All subjects were rated on the Athens Insomnia Scale, the Hyperarousal Scale, the Hamilton Depression Rating Scale and the Beck Depression Inventory. They also completed the Selective Reminding Test and the Continuous Attention Test. Only minor elevations on depression scales were found in patients. The Continuous Attention Test did not reveal any between group differences. However, insomniacs required more trials before all the Selective Reminding Test items were learned. Insomniacs showed less event-related current density in orbitofrontal, medial prefrontal and anterior cingulate cortex, i.e. brain regions of relevance for cognition and affect. Earliest group differences appeared in the P1 time range and then were observed at the N1, N2 and P3 stages of stimulus processing. These stimulus processing differences correlated most consistently with severity of insomnia. Neuropsychological impairment correlated most strongly with less current density in Brodmann area 10. ——————————————————————————–

4: Ann Biomed Eng 2001 Nov;29(11):1019-27 A self-coherence enhancement algorithm and its application to enhancing three-dimensional source estimation from EEGs.

Yao D, He B.

Department of Bioengineering, The University of Illinois at Chicago, 60607, USA.

In this paper a new algorithm is proposed to enhance the spatial resolution of solutions of the underdetermined EEG inverse problem. Termed the self-coherence enhancement algorithm (SCEA), the present algorithm provides a self-coherence solution, which is a function of the high order self-coherence estimate of an unbiased smooth estimate of the underdetermined EEG inverse solution. The order of the high order self-coherence function is determined by the blurring level of the actual source distribution as represented by a normalized blurring index. The proposed SCEA algorithm may be used to enhance the spatial resolution of an inverse solution obtained by any inverse reconstruction algorithm. Computer simulation studies have been conducted to evaluate the performance of the SCEA and to compare its performance to that of the LORETA and the FOCUSS algorithms.

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5: Eur J Neurol 2001 Nov;8(6):587-94 Cognitive response control in writer’s cramp.

Berg D, Herrmann MJ, Muller TJ, Strik WK, Aranda D, Koenig T, Naumann M, Fallgatter AJ.

Department of Neurology, Bayerische Julius-Maximilians-Universitat Wurzburg, Wurzburg, Germany.

Disturbances of the motor and sensory system as well as an alteration of the preparation of movements have been reported to play a role in the pathogenesis of dystonias. However, it is unclear whether higher aspects of cortical – like cognitive – functions are also involved. Recently, the NoGo-anteriorization (NGA) elicited with a visual continuous performance test (CPT) during recording of a 21-channel electroencephalogram has been proposed as an electrophysiological standard-index for cognitive response control. The NGA consists of a more anterior location of the positive area of the brain electrical field associated with the inhibition (NoGo-condition) compared with that of the execution (Go-condition) of a prepared motor response in the CPT. This response control paradigm was applied in 16 patients with writer’s cramp (WC) and 14 age matched healthy controls. Topographical analysis of the associated event-related potentials revealed a significant (P < 0.05) NGA effect for both patients and controls. Moreover, patients with WC showed a significantly higher global field power value (P < 0.05) in the Go-condition and a significantly higher difference-amplitude (P < 0.05) in the NoGo-condition. A source location analysis with the low resolution electromagnetic tomography (LORETA) method demonstrated a hypoactivity for the Go-condition in the parietal cortex of the right hemisphere and a hyperactivity in the NoGo-condition in the left parietal cortex in patients with WC compared with healthy controls. These results indicate an altered response control in patients with WC in widespread cortical brain areas and therefore support the hypothesis that the pathogenesis of WC is not restricted to a pure sensory-motor dysfunction. ——————————————————————————–

6: Psychiatry Res 2001 Nov 30;108(2):111-21 Brain sources of EEG gamma frequency during volitionally meditation-induced, altered states of consciousness, and experience of the self.

Lehmann D, Faber PL, Achermann P, Jeanmonod D, Gianotti LR, Pizzagalli D.

The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Lenggstr. 31, CH-8029 Zurich, Switzerland. [email protected]

Multichannel EEG of an advanced meditator was recorded during four different, repeated meditations. Locations of intracerebral source gravity centers as well as Low Resolution Electromagnetic Tomography (LORETA) functional images of the EEG ‘gamma’ (35-44 Hz) frequency band activity differed significantly between meditations. Thus, during volitionally self-initiated, altered states of consciousness that were associated with different subjective meditation states, different brain neuronal populations were active. The brain areas predominantly involved during the self-induced meditation states aiming at visualization (right posterior) and verbalization (left central) agreed with known brain functional neuroanatomy. The brain areas involved in the self-induced, meditational dissolution and reconstitution of the experience of the self (right fronto-temporal) are discussed in the context of neural substrates implicated in normal self-representation and reality testing, as well as in depersonalization disorders and detachment from self after brain lesions. ——————————————————————————–

7: Neuropsychobiology 2001;44(4):192-8 EEG source localization and global dimensional complexity in high- and low- hypnotizable subjects: a pilot study.

Isotani T, Lehmann D, Pascual-Marqui RD, Kochi K, Wackermann J, Saito N, Yagyu T, Kinoshita T, Sasada K.

The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland. [email protected]

Individuals differ in hypnotizability. Information on hypnotizability-related EEG characteristics is controversial and incomplete, particularly on intracerebral source localization and EEG dimensionality. 19-channel, eyes-closed resting EEGs from right-handed, healthy, 8 high- and 4 low-hynotizable subjects (age: 26.7 +/- 7.3 years) were analyzed. Hypnotizability was rated after the subjects’ ability to attain a deep hypnotic stage (amnesia). FFT Dipole Approximation analysis in seven EEG frequency bands showed significant differences (p < 0.04) of source gravity center locations for theta (6.5-8 Hz, more posterior and more left for highs), beta-1 and beta-2 frequencies (12.5-18 and 18.5-21 Hz; both more posterior and more right for highs). Low Resolution Electromagnetic Tomography (LORETA) specified the cortical anteriorization of beta-1 and beta-2 in low hypnotizables. Power spectral analysis of Global Field Power time series (curves) showed no overall power differences in any band. Full-band Global Dimensional Complexity was higher in high-hypnotizable subjects (p < 0.02). Thus, before hypnosis, high and low hypnotizables were in different brain electric states, with more posterior brain activity gravity centers (excitatory right, routine or relaxation left) and higher dimensional complexity (higher arousal) in high than low hypnotizables. Copyright 2001 S. Karger AG, Basel ——————————————————————————–

8: Psychiatry Res 2001 Oct 1;107(3):165-71 Limbic activity in slow wave sleep in a healthy subject with alpha-delta sleep.

Connemann BJ, Mann K, Pascual-Marqui RD, Roschke J.

Department of Psychiatry, University of Mainz, Untere Zahlbacher Str. 8, D-55131, Mainz, Germany. [email protected]

All-night electroencephalographic (EEG) activity was recorded in a healthy subject with known alpha-delta sleep. Recordings were made from all 19 of the 10/20 system electrode sites, and low resolution electromagnetic tomography (LORETA) was used to estimate intracerebral current densities. Sleep stages were compared within classical frequency bands by statistical parametric mapping (SPM). With the onset of sleep, occipital alpha abated. With increasing depth of sleep, alpha power increased in a region comprising the left frontal lobe, the anterior and parietal cingulum, and the anterior and medial right front lobe. In slow wave sleep (SWS), frontal alpha power was much greater than in wakefulness. The maximum of frontal alpha power of SWS was localised symmetrically in the left and right anterior cingulum. The observed alpha activity was different from the occipital alpha characteristic of wakefulness; it was a distinct activity of separate origin. The anterior limbic lobes seemed to play an active part in SWS in this healthy volunteer with an alpha-delta sleep pattern. ——————————————————————————–

9: Hum Brain Mapp 2001 Nov;14(3):152-65 Localization of MDMA-induced brain activity in healthy volunteers using low resolution brain electromagnetic tomography (LORETA).

Frei E, Gamma A, Pascual-Marqui R, Lehmann D, Hell D, Vollenweider FX.

University Hospital of Psychiatry, Zurich, Switzerland.

3,4-Methylenedioxymethamphetamine (MDMA; ‘Ecstasy’) is a psychostimulant drug producing heightened mood and facilitated social communication. In animal studies, MDMA effects are primarily mediated by serotonin (5-HT), but also by dopamine (DA) and possibly noradrenaline (NA). In humans, however, the neurochemical and neurophysiological basis of acute MDMA effects remains unknown. The distribution of active neuronal populations after administration of a single dose of MDMA (1.7 mg/kg) or placebo was studied in 16 healthy, MDMA-naive volunteers. Thirty-one-channel scalp EEGs during resting with open and closed eyes was analyzed in the different EEG frequency bands. Scalp maps of power showed significant, global differences between MDMA and placebo in both eye conditions and all frequency bands. Low resolution brain electromagnetic tomography (LORETA) was used to compute 3D, functional images of electric neuronal activity from the scalp EEG data. MDMA produced a widespread decrease of slow and medium frequency activity and an increase of fast frequency activity in the anterior temporal and posterior orbital cortex, concomitant with a marked enhancement of mood, emotional arousal and increased extraversion. This activation of frontotemporal areas indicates that the observed enhancement of mood and possibly the increased extroversion rely on modulation of limbic orbitofrontal and anterotemporal structures known to be involved in emotional processes. Comparison of the MDMA-specific EEG pattern with that of various 5-HT, DA, and NA agonists indicates that serotonin, noradrenaline, and, to a lesser degree, dopamine, contribute to the effects of MDMA on EEG, and possibly also on mood and behavior. Copyright 2001 Wiley-Liss, Inc. ——————————————————————————–

10: Zh Nevrol Psikhiatr Im S S Korsakova 2001;101(5):24-31 [Change of bioelectric brain activity registered at the distance from the focus of cerebral tissue injury]

[Article in Russian]

Pirlik GP, Gnezditskii VV, Koptelov IuM, Bodykhov MK, Skvortsova VI.

The focal delta-waves and the remote influences of the stroke in the form of the sinusoidal flashes of delta-waves with a maximal amplitude exceeding an amplitude of the focal delta-waves (frontal flashes–FF) in frontal-polar leads were investigated in 51 patients (22 men, 29 women) by means of mapping, dipole location (BrainLoc) and LORETA methods. The patients were examined in dynamics during the acute period of hemispheric stroke on days 1-3, 14 and 21 after the onset of the disease. The usage of the modern computer methods of EEG analysis permits to consider FF as an independent electrophysiological phenomenon and to localize a zone of the sources of such flashes, which does not coincide with the zone of generation of the focal delta-activity that corresponds to the perifocal zone of the stroke. According to the data of the three-dimensional location a probable zone of FF generation corresponds to the frontal pole and medial-basal areas of the frontal lobe. Comparison with the MRI data leads to the conclusion that a damage of anterior white substance was the most frequent cause of FF development, probably by deafferentation mechanism. FF may be an electrophysiological manifestation of the influence of the damage of the different brain structures on the frontal lobes according to diaschisis mechanism. ——————————————————————————–

11: Neuropsychobiology 2001;44(2):108-12 Spatial structure of brain electric fields during intermittent photic stimulation.

Hirota T, Yagyu T, Pascual-Marqui RD, Saito N, Kinoshita T.

Department of Neuropsychiatry, Kansai Medical University, Moriguchi, Osaka, Japan. [email protected]

EEG changes in 27 young healthy male right-handed volunteers on intermittent photic stimulation (IPS) were estimated using global field power (GFP), EEG microstate modeling and analysis (EMMA), and low-resolution electromagnetic brain tomography (LORETA). The GFP significantly increased at flashing frequency and high harmonics. Three model maps were extracted with the EMMA procedure, from which high alternation rates of each microstate were observed. Moreover, two of the three model maps contributed very highly, occurring most frequently. LORETA imaging of the three model maps obtained from the EMMA procedure showed that both visual dominant cortical areas were activated, especially in the left hemisphere. These results suggest that IPS does not cause peculiar spatial configurations of the brain electric field, but does cause acceleration and deviation of the microstate alternation. Also, a functional laterality between hemispheres might be enhanced by symmetric IPS. Copyright 2001 S. Karger AG, Basel ——————————————————————————–

12: Brain Res Cogn Brain Res 2001 Aug;12(1):55-60 Differences in EEG current density related to intelligence.

Jausovec N, Jausovec K.

Univerza v Mariboru, Pedagoska fakulteta, Koroska 160, 2000 Maribor, Slovenia. [email protected]

Differences in current density between high intelligent (IQ=127), and low intelligent individuals (IQ=87), while solving two oddball tasks (auditive and visual) were analyzed with low resolution brain electromagnetic tomography (LORETA). In highly intelligent individuals a decrease in the volume of activated cortical gray matter between the P300 onset and the P300 peak amplitude was observed. The EEG of low intelligent individuals showed a reverse pattern of cortical activity. In the auditive oddball task the decrease in the activated cortical volume in high intelligent individuals was accompanied by an increase in current density, and a more left hemispheric source location at maximum current density. The results suggest that high intelligent individuals more efficiently distributed their cognitive resources needed to cope with the oddball tasks. ——————————————————————————–

13: Int J Neurosci 2001 Apr;107(3-4):161-71 Frequency domain equivalence between potentials and currents using LORETA.

Gomez JF, Thatcher RW.

Bay Pines VA Medical Center, Bay Pines, FL 33744, USA.

Analyzing the preferences of brain regions to oscillate at specific frequencies gives important functional information. Application of discrete inverse solutions for the EEG/MEG inverse problem in the frequency domain usually involves the use of many current sources (sometimes 10(4) or more) restricted to gray matter points, as the solution space for the possible generators. This number can progressively increase with the level of detail of the MRI when it is used in co-registration with EEG/MEG. However, the computation of the Fourier transform to all these sources is computationally intensive. We illustrate with a simple example how this procedure can be simplified by applying the Fourier transform to the signals in the sensors using a popular inverse method (LORETA). We also suggest how the search space of current sources at specific frequencies of oscillation can be limited to some regions constrained by other technologies such as fMRI, PET and SPECT. ——————————————————————————–

14: Int J Psychophysiol 2001 Jun;41(2):143-53 Source localization of EEG activity during hypnotically induced anxiety and relaxation.

Isotani T, Tanaka H, Lehmann D, Pascual-Marqui RD, Kochi K, Saito N, Yagyu T, Kinoshita T, Sasada K.

The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Lenggstrasse 31, CH-8029, Zurich, Switzerland. [email protected]

The engagement of different brain regions which implement subjectively experienced emotional states in normals is not completely clarified. Emotional states can conveniently be induced by hypnosis-based suggestions. We studied brain electric activity during hypnotically induced anxiety and relaxation in 11 right-handed normals (5 males, 6 females, mean age 26.5+/-7.6 years). After induction of light hypnosis, anxiety and then relaxation was suggested using a standardized text (reverse sequence in half of the subjects). Nineteen-channel, eyes-closed EEG (20 artifact-free s/subject) was analyzed (source localization using FFT approximation and low resolution electromagnetic tomography, LORETA). Global tests revealed the strongest difference (P 15: Neuroimage 2001 Apr;13(4):589-600 Reduced event-related current density in the anterior cingulate cortex in schizophrenia.

Mulert C, Gallinat J, Pascual-Marqui R, Dorn H, Frick K, Schlattmann P, Mientus S, Herrmann WM, Winterer G.

Laboratory for Clinical Psychophysiology, Free University, Berlin, Germany. [email protected]

There is good evidence from neuroanatomic postmortem and functional imaging studies that dysfunction of the anterior cingulate cortex plays a prominent role in the pathophysiology of schizophrenia. So far, no electrophysiological localization study has been performed to investigate this deficit. We investigated 18 drug-free schizophrenic patients and 25 normal subjects with an auditory choice reaction task and measured event-related activity with 19 electrodes. Estimation of the current source density distribution in Talairach space was performed with low-resolution electromagnetic tomography (LORETA). In normals, we could differentiate between an early event-related potential peak of the N1 (90-100 ms) and a later N1 peak (120-130 ms). Subsequent current-density LORETA analysis in Talairach space showed increased activity in the auditory cortex area during the first N1 peak and increased activity in the anterior cingulate gyrus during the second N1 peak. No activation difference was observed in the auditory cortex between normals and patients with schizophrenia. However, schizophrenics showed significantly less anterior cingulate gyrus activation and slowed reaction times. Our results confirm previous findings of an electrical source in the anterior cingulate and an anterior cingulate dysfunction in schizophrenics. Our data also suggest that anterior cingulate function in schizophrenics is disturbed at a relatively early time point in the information-processing stream (100-140 ms poststimulus). Copyright 2001 Academic Press. ——————————————————————————–

16: Childs Nerv Syst 2001 Feb;17(3):139-44 The clinical value of electroencephalogram/magnetic resonance imaging co-registration and three-dimensional reconstruction in the surgical treatment of epileptogenic lesions.

Sgouros S, Seri S, Natarajan K.

Institute of Child Health and Department of Neurosurgery, Birmingham Children’s Hospital, UK. [email protected]

With the rapid developments in image processing, new clinical applications of manipulation and three-dimensional (3-D) reconstruction of neuro-imaging are evolving. Combination with other non-invasive techniques aimed at localising electric sources in the brain is of particular interest. These techniques rely on the recording of brain electrical activity and/or the associated magnetic fields from multiple areas on the scalp. Data obtained from an electroencephalogram (EEG) or from magnetoencephalography (MEG) can be fused in 3-D arrangement with anatomical [magnetic resonance imaging/computerised tomography (MRI/CT)] and/or metabolic [positron emission tomography (PET)] data. Such techniques highlight information on the functional correlates of anatomical or space-occupying lesions and their role in the localisation of related symptomatic epilepsy. In the present study we report on methodological issues and preliminary clinical data on spectral EEG/MRI co-registration procedures, offering two examples of children presenting with hemispheric lesions, one frontal tumour and one temporal arterio-venous malformation. The EEG was acquired from 32/64 electrode location. The electrode position and that of four reference points were measured with a dual sensor Polhemus 3D Isotrak digitiser. Sources of EEG activity were determined in 3-D space with the inverse solution method low resolution electromagnetic tomography (LORETA), providing for each frequency component, the topographic distribution of active electrical sources. The positions of the reference points were also measured on MRI, and co-registration of EEG and MRI was achieved using a transformation algorithm. The reconstructed 3-D images of co-registered EEG/MRI clearly demonstrate the relationship between the space-occupying lesion and the epileptic activity. Preliminary results show that in all the patients it was possible to identify with a remarkable accuracy the 3-D topographic relationship between lesion and cortical areas showing localised abnormalities on the EEG. The present method could further enhance the understanding of the effect of resective treatment of structural lesions on brain functioning. The new combined images can be used in combination with image-guided surgery equipment to modify effective surgical resection. ——————————————————————————–

17: Hum Brain Mapp 2001 Mar;12(3):144-56 Low-resolution electrical tomography of the brain during psychometrically matched verbal and spatial cognitive tasks.

Koles ZJ, Flor-Henry P, Lind JC.

Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.

EEGs were recorded from 75 normal, young, female subjects during psychometrically matched verbal (WF) and spatial (DL) cognitive tasks to elicit the differences in the electrical source distribution inside the brain. Recordings were obtained using 43 EEG and 3 guard electrodes then visually edited and spatially filtered to remove extracerebral artifacts. Twenty 1-sec artifact-free epochs were obtained and analyzed from 42 and 60 subjects during WF and DL respectively. Of these subjects, 20 were placed in a training set and the remainder into a test set. The baseline for the comparison of the two tasks was established by factoring the average cross-spectral matrices of the training-set EEGs, computed in the theta, alpha, and beta frequency bands into spatial patterns common to the two tasks. Only those spatial patterns that contributed to the correct classification of subjects in the test set were included in the source analysis. The source-current density distributions were obtained using the LORETA-KEY algorithm. The results show that the source-current density distribution is related to the putative functional activity in the brain in all three frequency bands. The electrical effects of the tasks are both most highly localized and lateralized in the theta band. The effects in the alpha and beta bands are much more generalized and are strongly lateralized only during one and the other of the tasks respectively. The conclusion is that WF is mainly a left central and bilateral frontal cerebral process while DL is mainly a right central and bilateral posterior cerebral process. Copyright 2001 Wiley-Liss, Inc. ——————————————————————————–

18: Psychiatry Res 2000 Dec 4;100(2):81-96 Effect of the 5-HT(1A) partial agonist buspirone on regional brain electrical activity in man: a functional neuroimaging study using low-resolution electromagnetic tomography (LORETA).

Anderer P, Saletu B, Pascual-Marqui RD.

Department of Psychiatry, Division of Sleep Research and Pharmacopsychiatry, University of Vienna, Vienna, Austria. [email protected]

In a double-blind, placebo-controlled study, the effects of 20 mg buspirone – a 5-HT(1A) partial agonist – on regional electrical generators within the human brain were investigated utilizing three-dimensional EEG tomography. Nineteen-channel vigilance-controlled EEG recordings were carried out in 20 healthy subjects before and 1, 2, 4, 6 and 8 h after drug intake. Low-resolution electromagnetic tomography (LORETA; Key Institute for Brain-Mind Research, software: http://www.keyinst.unizh.ch) was computed from spectrally analyzed EEG data, and differences between drug- and placebo-induced changes were displayed as statistical parametric maps. Data were registered to the Talairach-Tournoux human brain atlas available as a digitized MRI (McConnell Brain Imaging Centre: http://www.bic.mni.mcgill.ca). At the pharmacodynamic peak (1st hour), buspirone increased theta and decreased fast alpha and beta sources. Areas of theta increase were mainly the left temporo-occipito-parietal and left prefrontal cortices, which is consistent with PET studies on buspirone-induced decreases in regional cerebral blood flow and fenfluramine-induced serotonin activation demonstrated by changes in regional cerebral glucose metabolism. In later hours (8th hour) with lower buspirone plasma levels, delta, theta, slow alpha and fast beta decreased, predominantly in the prefrontal and anterior limbic lobe. Whereas the results of the 1st hour speak for a slight CNS sedation (more in the sense of relaxation), those obtained in the 8th hour indicate activation. Thus, LORETA may provide useful and direct information on drug-induced changes in central nervous system function in man. ——————————————————————————–

19: Brain Topogr 2000 Summer;12(4):273-82 Localization of the epileptic focus by low-resolution electromagnetic tomography in patients with a lesion demonstrated by MRI.

Worrell GA, Lagerlund TD, Sharbrough FW, Brinkmann BH, Busacker NE, Cicora KM, O’Brien TJ.

Department of Neurology, Mayo Clinic and Mayo Foundation, Rochester, Minnesota 55905, USA.

Patients with medically intractable partial epilepsy and well-defined symptomatic MRI lesions were studied using phase-encoded frequency spectral analysis (PEFSA) combined with low-resolution electromagnetic tomography (LORETA). Ten patients admitted to the epilepsy monitoring unit with MRI-identified lesions and intractable partial epilepsy were studied using 31-electrode scalp EEG. The scalp electrodes were located in three-dimensional space using a magnetic digitizer and coregistered with the patient’s MRI. PEFSA was used to obtain a phase-encoded scalp map for the ictal frequencies. The ictal generators were obtained from the scalp map using LORETA. In addition, the generators of interictal epileptogenic spikes were identified using time-domain LORETA. The LORETA generators were rostral to the MRI lesion in 87% (7/8) of patients with temporal lobe lesions, but all were located in the mesial temporal lobe in concordance with the patients’ MRI lesions. In patients with frontal lobe epilepsy, the ictal generators at the time that the spectral power was maximal localized to the MRI lesions. Eight of 10 patients had interictal spikes, of which 4 were bilateral independent temporal lobe spikes. Only generators of the interictal spikes that were ipsilateral to seizure onset correlated with the ictal generators. LORETA combined with PEFSA of the ictal discharge can localize ictal EEG discharges accurately and improve correlation with brain anatomy by allowing coregistration of the ictal generator with the MRI. Analysis of interictal spikes was less useful than analysis of the ictal discharge. ——————————————————————————–

20: Clin Neurophysiol 2000 Mar;111(3):521-31 Face-elicited ERPs and affective attitude: brain electric microstate and tomography analyses.

Pizzagalli D, Lehmann D, Koenig T, Regard M, Pascual-Marqui RD.

Department of Neurology, University Hospital, CH-8091, Zurich, Switzerland. [email protected]

OBJECTIVES: Although behavioral studies have demonstrated that normative affective traits modulate the processing of facial and emotionally charged stimuli, direct electrophysiological evidence for this modulation is still lacking. METHODS: Event-related potential (ERP) data associated with personal, traitlike approach- or withdrawal-related attitude (assessed post-recording and 14 months later) were investigated in 18 subjects during task-free (i.e. unrequested, spontaneous) emotional evaluation of faces. Temporal and spatial aspects of 27 channel ERP were analyzed with microstate analysis and low resolution electromagnetic tomography (LORETA), a new method to compute 3 dimensional cortical current density implemented in the Talairach brain atlas. RESULTS: Microstate analysis showed group differences 132-196 and 196-272 ms poststimulus, with right-shifted electric gravity centers for subjects with negative affective attitude. During these (over subjects reliably identifiable) personality-modulated, face-elicited microstates, LORETA revealed activation of bilateral occipito-temporal regions, reportedly associated with facial configuration extraction processes. Negative compared to positive affective attitude showed higher activity right temporal; positive compared to negative attitude showed higher activity left temporo-parieto-occipital. CONCLUSIONS: These temporal and spatial aspects suggest that the subject groups differed in brain activity at early, automatic, stimulus-related face processing steps when structural face encoding (configuration extraction) occurs. In sum, the brain functional microstates associated with affect-related personality features modulate brain mechanisms during face processing already at early information processing stages. ——————————————————————————-

21: Neuroreport 2000 Jan 17;11(1):157-62 Mood state and brain electric activity in ecstasy users.

Gamma A, Frei E, Lehmann D, Pascual-Marqui RD, Hell D, Vollenweider FX.

KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland.

Resting EEG during open and closed eyes and subsequent mood ratings were obtained from 15 Ecstasy users and 14 Ecstasy-naive controls. Absolute spectral power on the scalp, and the three-dimensional, intracerebral distribution of neuroelectric activity using low resolution brain electromagnetic tomography (LORETA) were computed. LORETA revealed global increases of theta, alpha 1 and beta 2/3 power during eyes open in Ecstasy users, and spectral analyses revealed a right-posterior increase of alpha 2 power (confirmed by LORETA) and increased beta band activity during open eyes. Ecstasy users had higher levels of state depressiveness, emotional excitability and a trend-level increase in state anxiety. The observed differences may be related to regular exposure to Ecstasy or other illicit drugs, or may be pre-existing. ——————————————————————————–

22: Psychiatry Res 1999 Jun 30;90(3):169-79 Low resolution brain electromagnetic tomography (LORETA) functional imaging in acute, neuroleptic-naive, first-episode, productive schizophrenia.

Pascual-Marqui RD, Lehmann D, Koenig T, Kochi K, Merlo MC, Hell D, Koukkou M.

The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland. [email protected]

Functional imaging of brain electrical activity was performed in nine acute, neuroleptic-naive, first-episode, productive patients with schizophrenia and 36 control subjects. Low-resolution electromagnetic tomography (LORETA, three-dimensional images of cortical current density) was computed from 19-channel electroencephalographic (EEG) activity obtained under resting conditions, separately for the different EEG frequencies. Three patterns of activity were evident in the patients: (1) an anterior, near-bilateral excess of delta frequency activity; (2) an anterior-inferior deficit of theta frequency activity coupled with an anterior-inferior left-sided deficit of alpha-1 and alpha-2 frequency activity; and (3) a posterior-superior right-sided excess of beta-1, beta-2 and beta-3 frequency activity. Patients showed deviations from normal brain activity as evidenced by LORETA along an anterior-left-to-posterior-right spatial axis. The high temporal resolution of EEG makes it possible to specify the deviations not only as excess or deficit, but also as inhibitory, normal and excitatory. The patients showed a dis-coordinated brain functional state consisting of inhibited prefrontal/frontal areas and simultaneously overexcited right parietal areas, while left anterior, left temporal and left central areas lacked normal routine activity. Since all information processing is brain-state dependent, this dis-coordinated state must result in inadequate treatment of (externally or internally generated) information. ——————————————————————————–

23: Clin Neurophysiol 1999 Feb;110(2):329-41 Attention-sensitive visual event-related potentials elicited by kinetic forms. Wang J, Jin Y, Xiao F, Fan S, Chen L.

Beijing Laboratory of Cognitive Science, University of Science and Technology of China, People’s Republic of China. [email protected]

Previous event-related potential (ERP) studies have shown that selectively attending to a relevant stimulus feature was associated with selection negativity (SN) components. The present study aimed at investigating the ERP indices of attentional selection based on forms defined by motion (kinetic forms). ERPs were recorded from subjects who attended selectively to sequentially presented kinetic forms of bars in one visual field and detected occasional tilted bar targets. Two kinds of kinetic forms were used as the visual stimuli in separate experiments. The main findings were that spatial attention enhanced the amplitude of early ERP components 1 and N1 as well as the late component N2. Topographic maps of voltage and low resolution electromagnetic tomography (LORETA) of the dN2 wave (difference waveform between N2 under attended condition and N2 under unattended condition) suggested an origin in the right occipitotemporal cortex. According to its timing and morphology, the dN2 wave was considered to be an endogenous ERP (like the SN) and was interpreted as reflecting attentional facilitation of the processing of forms defined by motion primarily involving the right occipitotemporal areas. ——————————————————————————–

24: Behav Brain Res 1998 Jul;94(1):111-25 Neuroelectric mapping reveals precursor of stop failures in children with attention deficits. Brandeis D, van Leeuwen TH, Rubia K, Vitacco D, Steger J, Pascual-Marqui RD, Steinhausen HC.

Department of Child and Adolescent Psychiatry, University of Zurich, Switzerland. [email protected]

Children with attention deficit disorders (ADD) may have specific problems with response inhibition in the STOP task. This task requires that subjects stop responses to a primary task if a second signal follows. However, it is unclear whether these problems reflect an impairment of the stopping process per se, whether they are related to reduced frontal lobe activation and whether they are confined to severe and pervasive forms of ADD. In 11 ADD and nine control children, 32 channel event-related EEG potentials (ERPs) were recorded in a STOP and a delayed GO task. Mapping revealed that both tasks evoked a similar sequence of neuroelectric microstates, i.e. of time segments with stable map topography. Adaptive segmentation identified the transition between these microstates. Reliable group differences were found in several microstates and in both tasks despite matched performance. In the GO task, ADD children had topographically altered P2/N2 microstates and attenuated P300-type microstates. In the STOP task, a topographically altered N1 microstate which coincided with the onset of the stop signal preceded the stop failures of ADD children. The timing of this microstate is too early to reflect deficits in actual stop signal processing and instead suggests altered initial orienting of attention to the primary signal in ADD children. Imaging with low resolution tomography (LORETA) during this microstate to stop failures indicated mainly posterior activation for both groups and increased rather than reduced frontal activation in ADD children. For a later microstate (P550), LORETA indicated strong frontal activation after successful stopping, but no group differences. The results suggest that information processing of ADD children deviates during activation of posterior mechanisms which may be related to the orienting of attention and which precedes and partly determines inhibitory control problems in ADD. ——————————————————————————–

25: Electroencephalogr Clin Neurophysiol 1997 May;102(5):414-22 Extracranial localization of intracranial interictal epileptiform activity using LORETA (low resolution electromagnetic tomography).

Lantz G, Michel CM, Pascual-Marqui RD, Spinelli L, Seeck M, Seri S, Landis T, Rosen I. Department of Clinical Neurophysiology, Lund University Hospital, Sweden.

Besides the standard clinical methods of EEG waveshape analysis, mathematical models for reconstruction of dipolar sources from the digitized surface EEG have been introduced in epilepsy research. Although useful for localizing focal sources, these methods are inadequate for analyzing widespread epileptiform activity. A recently introduced alternative method called LORETA (low resolution electromagnetic tomography, Pascual-Marqui et al., 1994), directly computes the current distribution throughout the full brain volume, assuming that neighboring neuronal populations are simultaneously and synchronously activated. In mathematical terms the method selects the smoothest of all possible 3-dimensional current distributions, inherently introducing a certain amount of dispersion. In 7 patients, undergoing simultaneous EEG recording from 10 intracranial (subdural) and 22 extracranial electrodes, 111 subdural discharges (61 subtemporal and 50 lateral temporal) were identified. The exact time point of maximal intracranial activity was automatically identified, and the LORETA solution at that timepoint was computed from the surface EEG. Statistical comparison revealed significantly higher LORETA current density in the area corresponding to the subdurally recorded spike compared to other areas, and a more anterior and more medial LORETA location for subtemporal compared to lateral temporal spikes. This study indicates that the LORETA technique may become a useful method to localize electrical activity in the brain. ——————————————————————————–

26: IEEE Trans Biomed Eng 1997 May;44(5):374-85 A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem.

Baillet S, Garnero L.

Unite de Psychophysiologie Cognitive, Hopital de la Salpetriere, CNRS URA 654, LENA-Universite Paris VI, France. [email protected]

In this paper, we present a new approach to the recovering of dipole magnitudes in a distributed source model for magnetoencephalographic (MEG) and electroencephalographic (EEG) imaging. This method consists in introducing spatial and temporal a priori information as a cure to this ill-posed inverse problem. A nonlinear spatial regularization scheme allows the preservation of dipole moment discontinuities between some a priori noncorrelated sources, for instance, when considering dipoles located on both sides of a sulcus. Moreover, we introduce temporal smoothness constraints on dipole magnitude evolution, at time scales smaller than those of cognitive processes. These priors are easily integrated into a Bayesian formalism, yielding a maximum a posteriori (MAP) estimator of brain electrical activity. Results from EEG simulations of our method are presented and compared with those of classical quadratic regularization and a now popular generalized minimum-norm technique called low-resolution electromagnetic tomography (LORETA). ——————————————————————————–

27: Int J Psychophysiol 1994 Oct;18(1):49-65 Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain.

Pascual-Marqui RD, Michel CM, Lehmann D.

Department of Neurology, University Hospital, Geneva, Switzerland.

This paper presents a new method for localizing the electric activity in the brain based on multichannel surface EEG recordings. In contrast to the models presented up to now the new method does not assume a limited number of dipolar point sources nor a distribution on a given known surface, but directly computes a current distribution throughout the full brain volume. In order to find a unique solution for the 3-dimensional distribution among the infinite set of different possible solutions, the method assumes that neighboring neurons are simultaneously and synchronously activated. The basic assumption rests on evidence from single cell recordings in the brain that demonstrates strong synchronization of adjacent neurons. In view of this physiological consideration the computational task is to select the smoothest of all possible 3-dimensional current distributions, a task that is a common procedure in generalized signal processing. The result is a true 3-dimensional tomography with the characteristic that localization is preserved with a certain amount of dispersion, i.e., it has a relatively low spatial resolution. The new method, which we call Low Resolution Electromagnetic Tomography (LORETA) is illustrated with two different sets of evoked potential data, the first showing the tomography of the P100 component to checkerboard stimulation of the left, right, upper and lower hemiretina, and the second showing the results for the auditory N100 component and the two cognitive components CNV and P300. A direct comparison of the tomography results with those obtained from fitting one and two dipoles illustrates that the new method provides physiologically meaningful results while dipolar solutions fail in many situations. In the case of the cognitive components, the method offers new hypotheses on the location of higher cognitive functions in the brain.

Number 2, Volume 1, 1999 HOME Cover Page Table of Contents Reply to Comments Made by R. Grave De Peralta Menendez and S.L. Gozalez Andino Roberto Domingo Pascual-Marqui The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Lenggstr. 31, CH-8029, Zurich, Switzerland ______________________________ c) Quoting from [10], comment “c)”: “The superposition principle cannot be applied to a non linear relationship….” c) My Reply: The principles of linearity and superposition for localization are illustrated in Figure 1. These results (and their generalization) can be replicated by the interested reader, using software that has been available upon request to the author since June 1998 ( http://www.keyinst.unizh.ch/loreta.htm). Figures 1a and 1b show LORETA point spread functions for two sources at different depths. The deep source is more blurred than the shallow source. The only way LORETA can resolve both simultaneously active sources is by increasing the strength of the deep source, as shown in Figure 1c (which is the same as Figure 4 in [1]). In general, LORETA can resolve two sources if they are sufficiently separated, and if their estimated strengths are comparable. This is the essence and main property of Low Resolution Brain Electromagnetic Tomography (LORETA): it will always produce a blurred (approximate) image of reality. Blurring will not always allow resolving all maxima. There was never any pompous claim of “high” or “optimum” resolution in LORETA. The main property of LORETA holds. 1.1. Quoting from [10]: “The study of all possible spread functions is equivalent to the analysis of all the resolution kernels [2],[3].” 1.1. My reply: Grave de Peralta Menendez and Gonzalez Andino quote themselves for this statement. They have falsified the truth: this statement is not to be found in their papers [2] and [3]. This statement can be found in my paper [1] (in section “The resolution matrix”). Actually, Grave de Peralta Menendez and Gonzalez Andino have made statements quite to the contrary, scorning the information contained in the point spread functions. For instance, in [2] they state: “The information contained on the impulse responses concerns exclusively single point sources,…” (Note: impulse response and point spread function have the same meaning.) 1.2. Quoting from [10]: “However, the analysis presented by Pascual-Marqui in [1] and [6] to evaluate the solutions is not really using the spread functions but a measure derived from them: The dipole localization error…..” 1.2. My reply: In [1] I present an exhaustive analysis of all point spread functions, based on the feature which I consider most relevant to the aim of EEG inverse solutions: localization error. The “dispersion” of point spread functions was defined, studied, and reported in [6]. The computer programs used and offered to the reader in [1] (available upon request to the author since June 1998: http://www.keyinst.unizh.ch/loreta.htm), allow the full and complete exhaustive evaluation of all point spread functions, including amplitudes (see Figure 1). I define “first order localization errors” of an instantaneous 3D discrete linear inverse solution as the set of localization errors for each point spread function. My methodology for comparing solutions belonging to this class starts with the following two principles: (1) high first order localization errors indicate the inadequacy of a solution; (2) the converse is not true. One essential fact must stressed: while low errors do not indicate adequacy of a solution, they do constitute a necessary (but not sufficient) condition for adequacy of a solution. 2.1. Quoting from [10]: “About the “futility of trying to design near ideal averaging kernels”….” 2.1. My reply: The averaging (or resolution) kernels are harmonic functions. This fact was published in [1], and it proves that in a 3D solution space, the averaging kernels can not be optimized. Therefore, all efforts towards optimization in a 3D solution space, as published and “extensively discussed in the literature ([8], [2], [3])”, have been futile. This fact of nature holds and cannot be changed for a 3D solution space. Any insistence in the rationality of optimization in 3D space is pointless. I wish to emphasize that the “curse of harmonic resolution kernels” was reported in [1]. It was not reported in the papers by Grave de Peralta Menendez and Gonzalez Andino, a fact that can be confirmed by reading carefully their self-quoted papers. For instance, in [3] they state: “A certain eccentricity value seems to exist below which all solutions fail to obtain adequately centered resolution kernels around the target point.” This statement is a far cry away from the full mathematical characterization implied by the harmonic character of the resolution kernels reported in [1]. One word of caution with respect to the equivalence of resolution kernel and point spread function optimization: Resolution kernels can not be optimized in 3D space, because of their harmonic character. Point spread functions might be amenable to optimization, since, in general, they are not harmonic. However, for optimization to take effect, one must find the proper functional. The WROP functionals in [3] may not necessarily be the best ones. Other functionals for optimizing the full resolution matrix exist, such as the one reported in equation 10, in [1]. This optimization, with the proper weight, produces LORETA, which satisfies “the minimum necessary condition” of low first order localization errors. 2.2. Quoting from [10]: “We are pleased to see that in this paper [1], the author coincides with us….” 2.2. My reply: First, it is worth emphasizing that the definition and interpretation of the averaging kernels for any linear inverse problem were published by Backus and Gilbert [8]. This contribution was not made by Grave de Peralta Menendez and Gonzalez Andino, as they so pretentiously imply. Second, all averaging kernel features emphatically proposed in ([2], [3], [4], [5]) are practically non-informative in 3D space, due to the fact that the averaging kernels are harmonic [1]. 3.1. Quoting from [10]: “It is not true that we “omitted an explicit equation of the inverse solution for the case of an unknown vector field”…..” 3.1. My reply: Substitution of the proper weights (given by the unidentified equation following equation 14 in [3]), into equation 14 in [3], is undefined. The authors did not specify in their paper the definition of the product of a Kronecker delta with a lead field. The correct form of equations was originally defined by Backus in Gilbert (see equation (4.10) in [8]), where such a product was specified. The correct explicit equations can also be found in [1]. 3.2. Quoting from [10]: “Finally, the author fails to realize that the WROP method is not a particular inverse solution but an strategy…..” 3.2. My reply: Grave de Peralta Menendez et al. proposed the WROP method in [3]. They claimed “optimum resolution”. They did not indicate how to choose the “so-called” weights in WROP. Furthermore, they presented results that are not reproducible by other researchers, since they did not specify the particular weights that were used in creating their Figures. Now the authors claim that the WROP method-strategy is very general. For the researcher interested in testing concrete inverse solutions, the only practical issue is: which WROP weights should be used for realistic (non-spherical) head geometry? Whatever the case may be, the results in [1] show that the WROP strategy is doomed to failure because in 3D space, optimization is pointless. Moreover, using the WROP strategy with a particular choice of weights [1] was shown to produce an inverse solution incapable of correct first order localization. As of this moment, a new software package for the fair comparison of instantaneous 3D discrete linear inverse solutions (for current density) is available upon request to the author ( http://www.keyinst.unizh.ch/loreta.htm). This package is based on a somewhat more realistic head model: the average human brain Talairach MRI atlas from McGill University. The approximate EEG lead field was computed numerically using the boundary element method (BEM). No use is made here of “spherical” approximations. Appendix-I includes some new, unambiguously specified, inverse solutions that can be found in the package. Also included here (Appendix-II) is the treatment of the regularization issue. Using a 7 mm resolution grid for the cortical grey matter solution space, the mean localization errors for LORETA and minimum norm were 11.45 and 18.61 mm, respectively. Figure 2 illustrates LORETA and minimum norm images (non-regularized and regularized) due to a point source, in the case of noisy measurements. Regularization was estimated via minimum cross-validation error. Once Grave de Peralta Menendez and Gonzalez Andino publish a completely specific and unambiguous instantaneous 3D discrete linear inverse solution for current density in non-spherical head models, it will be included in the Talairach package. 3.3. Quoting from [10]: “Then, the conclusion of Pascual-Marqui [1], that “the low localization error, in the sense defined here constitutes a minimum necessary condition” even if apparently reasonable, is not justifiable on theoretical or simulation grounds.” 3.3. My reply: Grave de Peralta Menendez and Gonzalez Andino failed to remember, again, that the principles of linearity and superposition hold (see my reply to comment “c)” above). 3.4. Quoting from [10]: “Earlier conclusions about LORETA (the main properties of LORETA [9]) conjectured on the basis of the dipole localization error have proved to be false.” 3.4. My reply: “Blurring” is certainly equivalent to “distortion”. LORETA produces blurred images (low resolution) of reality (see my reply to comment “c)” above), and therefore, the main properties of LORETA hold. References [1] Pascual-Marqui, R.D. “Review of methods for solving the EEG inverse problem”. International Journal of Bioelectromagnetism. No. 1, Vol.1, 1999. [2] Grave de Peralta Menendez R and Gonzalez Andino SL. “A critical analysis of linear inverse solutions”. IEEE Trans. Biomed. Engn. Vol 4: 440-48. 1998. [3] Grave de Peralta Menendez R, Hauk O, Gonzalez Andino, S, Vogt H and Michel. CM: “Linear inverse solutions with optimal resolution kernels applied to the electromagnetic tomography.” Human Brain Mapping, Vol 5: 454-67. 1997. [4] Grave de Peralta Menende R., Gonzalez Andino SL. “Distributed source models: Standard solutions and new developments”. In: Uhl C, ed. Analysis of Neurophysiological Brain Functioning. Heidelberg: Springer Verlag. 1998. [5] Grave de Peralta Menendez R., Gonzalez Andino SL and LŸtkenhšnner B. “Figures of merit to compare linear distributed inverse solutions”. Brain Topography. Vol. 9. No. 2:117-124. 1996 [6] Pascual-Marqui, R.D. “Reply to comments by HŠmŠlŠinen, Ilmoniemi and Nunez. In ISBET Newsletter No. 6, December 1995. Ed: W. Skrandiws. 16-28. [7] Grave de Peralta Menendez R, Gonzalez Andino SL, (1998c). Basic limitations of linear inverse solutions: A case study. Proceedings of the 20th annual international conference of the Engineering and Biology Society (EMBS). [8] Backus G and Gilbert F: The resolving power of gross earth data. Geophys. J. R. Astr. Soc. 16:169-205, 1968. [9] Pascual Marqui, RD and Michel, CM (1994) LORETA: New Authentic 3D functional images of the brain. In: ISBET Newsletter No. 5, November 1994. Ed: W. Skrandies. 4-8. [10] Grave de Peralta Menendez R and Gonzalez Andino SL. “Comments on “Review of methods for solving the EEG inverse problem” by R.D. Pascual-Marqui”. [11] C.R. Rao and S.K. Mitra. Theory and application of constrained inverse of matrices. SIAM J. Appl. Math., 1973, 24: 473-488. [12] Stone, M. Journal of the Royal Statistical Society, Series B, 1974, 36:111-147. ______________________________ Appendix IAppendix IIFigures

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