LORETA Neurofeedback in the Precuneus: Operant Conditioning in Basic Mechanisms of Self-Regulation.

Low-resolution brain electomagnetic tomography (LORETA) neurofeedback provides a mechanism to influence the electrical activity of the brain in intracranial space. The aim of this study was to determine the effects of LORETA neurofeedback (LNFB) in the precuneus as a mechanism for improving self-regulation in controls and a heterogeneous diagnostic group (DX). Thirteen participants completed between 10 and 20 sessions of LNFB training in a 3-voxel cluster in the left precuneus. The participants included 5 nonclinical university students, and 8 adults with heterogeneous psychiatric diagnoses. We assessed the effects of LNFB with neurophysiological measures as well as pre- and post-Personality Assessment Inventory (PAI) subscales and selected subtests from the Delis-Kaplan Executive Function System (DKEFS). There was a significant total relative power increase at the precuneus for baseline contrasts for the control group. The DX group did not reach significant levels. All participants showed improvements in executive functions and tended to report significantly less psychopathology. The basic neural mechanisms of self-regulation are poorly understood. The data obtained in this study demonstrate that LNFB in a heterogeneous population enhances executive functions while concordantly decreasing endorsement of psychological symptoms. The alpha frequency in the brain may represent integrative functioning relative to operant efficiency and self-regulatory mechanisms.

Using quantitative and analytic EEG methods in the understanding of connectivity in autism spectrum disorders: a theory of mixed over- and under-connectivity.

Neuroimaging technologies and research has shown that autism is largely a disorder of neuronal connectivity. While advanced work is being done with fMRI, MRI-DTI, SPECT and other forms of structural and functional connectivity analyses, the use of EEG for these purposes is of additional great utility. Cantor et al. (1986) were the first to examine the utility of pairwise coherence measures for depicting connectivity impairments in autism. Since that time research has shown a combination of mixed over and under-connectivity that is at the heart of the primary symptoms of this multifaceted disorder. Nevertheless, there is reason to believe that these simplistic pairwise measurements under represent the true and quite complicated picture of connectivity anomalies in these persons. We have presented three different forms of multivariate connectivity analysis with increasing levels of sophistication (including one based on principle components analysis, sLORETA source coherence, and Granger causality) to present a hypothesis that more advanced statistical approaches to EEG coherence analysis may provide more detailed and accurate information than pairwise measurements. A single case study is examined with findings from MR-DTI, pairwise and coherence and these three forms of multivariate coherence analysis. In this case pairwise coherences did not resemble structural connectivity, whereas multivariate measures did. The possible advantages and disadvantages of different techniques are discussed. Future work in this area will be important to determine the validity and utility of these techniques.

EEG current source density and the phenomenology of the default network.

In recent years, there has been an increasing line of research dedicated to the investigation of the default mode network (DMN) of the brain and resting state networks. However, the mental activity of the DMN has not been rigorously assessed to date. The specific aims of the current study were 2-fold: First, we sought to determine whether the current source density (CSD) levels in the DMN would correspond to other neuroimaging techniques. Second, we sought to understand the subjective mental activity of the DMN during baseline recordings. This study was conducted with 63 nonclinical participants, 34 female and 29 males with a mean age of 19.2 years (standard deviation = 2.0). The participants were recorded in 8 conditions. First, 4-minute eyes-closed baseline (ECB) and eyes-opened baseline (EOB) were obtained. The participants then completed 3 assessment instruments and 3 image conditions while the electroencephalography (EEG) was continuously recorded. Participants completed subjective reports for baselines and image conditions. These were rated by 3 independent raters and compared for reliability using a random effects model with an absolute agreement definition. The mean CSD between all conditions differed significantly, in many but not all regions of interest in the DMN. Interestingly, as suggested by other studies, the DMN appears preferential to self-relevant, self-specific, or self-perceptive processes. The reliability analyses show α for interrater agreement for ECB at .95 and EOB at .96. The subjective reports obtained from the participants regarding the mental activities employed during baseline recordings correspond to attentional and self-regulatory processes, which may also implicate the resting state or DMN as playing a direct role in the maintenance of a complex behavior (eg, being still, attending, and self-regulating). Thus, attention and self-regulation constitute the phenomenology of the resting state (DMN) in this study. The results also demonstrate that EEG CSD is a useful method to examine the DMN during concept-specific tasks to elucidate the neural activity associated with these concepts. Standardized low-resolution electromagnetic tomography (sLORETA) can localize to 5 mm(3), which is comparable to the findings in functional magnetic resonance imaging (fMRI). However, sLORETA can provide data about the difference in activity between groups, individuals, or populations which in many cases fMRI cannot provide.

Reliability of quantitative EEG (qEEG) measures and LORETA current source density at 30 days.

There is a growing interest for using quantitative EEG and LORETA current source density in clinical and research settings. Importantly, if these indices are to be employed in clinical settings then the reliability of these measures is of great concern. Neuroguide (Applied Neurosciences) is sophisticated software developed for the analyses of power, and connectivity measures of the EEG as well as LORETA current source density. To date there are relatively few data evaluating topographical EEG reliability contrasts for all 19 channels and no studies have evaluated reliability for LORETA calculations. We obtained 4 min eyes-closed and eyes-opened EEG recordings at 30-day intervals. The EEG was analyzed in Neuroguide and FFT power, coherence and phase was computed for traditional frequency bands (delta, theta, alpha and beta) and LORETA current source density was calculated in 1 Hz increments and summed for total power in eight regions of interest (ROI). In order to obtain a robust measure of reliability we utilized a random effects model with an absolute agreement definition. The results show very good reproducibility for total absolute power and coherence. Phase shows lower reliability coefficients. LORETA current source density shows very good reliability with an average 0.81 for ECB and 0.82 for EOB. Similarly, the eight regions of interest show good to very good agreement across time. Implications for future directions and use of qEEG and LORETA in clinical populations are discussed.

The computerized self test (CST): an interactive, internet accessible cognitive screening test for dementia.

The computer self test (CST) is an interactive, internet-based instrument designed to assess functional cognitive domains impaired by Alzheimer's disease (AD) and mild cognitive impairment (MCI). This study consisted of 215 total subjects with a mean age of 75.24. The 84 cognitively impaired patients (excluding patients diagnosed as MCI) met all criteria set forth by NINCDS/ADRDA for the diagnosis of AD. Control participants consisted of 104 age-matched individuals who were cognitively unimpaired. All patients completed the CST prior to other routine neurocognitive procedures. The CST accurately classified 96% of the cognitively impaired individuals as compared to controls, while the Mini-Mental Status Examination (MMSE) accurately classified 71% and the Mini-Cog 69% in the same respect. In addition, the CST accurately classified 91% of the six experimental groups (control, MCI, early AD, mild to moderate, moderate to severe, and severe) as compared to 54% for the MMSE and 48% for the Mini-Cog. In conclusions, the CST demonstrates a high degree of sensitivity and specificity and is capable of accurately identifying cognitive impairment in patients with variable degrees of cognitive abnormality. This interactive internet-based cognitive screening tool may aid in early detection of cognitive impairment in the primary care setting. The ease of use and interpretation may also provide the means to obtain an accurate baseline from which to monitor cognitive changes over time.

Abnormal connectivity in the posterior cingulate and hippocampus in early Alzheimer's disease and mild cognitive impairment.

BACKGROUND: Brain imaging studies of early Alzheimer's disease (AD) have shown decreased metabolism predominantly in the posterior cingulate cortex (PCC), medial temporal lobe, and inferior parietal lobe. This study investigated functional connectivity between these regions, as well as connectivity between these regions and the whole brain. METHODS: Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) studies were performed in subjects with early AD, mild cognitive impairment (MCI), and normal controls. RESULTS: The data indicate both decreased fiber connections and disrupted connectivity between the hippocampus and PCC in early AD. The MCI group showed reduced fiber numbers derived from PCC and hippocampus to the whole brain. CONCLUSIONS: The fMRI and DTI results confirmed decreased connectivity from both the PCC and hippocampus to the whole brain in MCI and AD and reduction in connectivity between these two regions, which plausibly represents an early imaging biomarker for AD.

EEG biofeedback as a treatment for substance use disorders: review, rating of efficacy, and recommendations for further research.

Electroencephalographic (EEG) biofeedback has been employed in substance use disorder (SUD) over the last three decades. The SUD is a complex series of disorders with frequent comorbidities and EEG abnormalities of several types. EEG biofeedback has been employed in conjunction with other therapies and may be useful in enhancing certain outcomes of therapy. Based on published clinical studies and employing efficacy criteria adapted by the Association for Applied Psychophysiology and Biofeedback and the International Society for Neurofeedback and Research, alpha theta training-either alone for alcoholism or in combination with beta training for stimulant and mixed substance abuse and combined with residential treatment programs, is probably efficacious. Considerations of further research design taking these factors into account are discussed and descriptions of contemporary research are given.