LORETA Neurofeedback for Addiction and the Possible Neurophysiology of Psychological Processes Influenced: A Case Study and Region of Interest Analysis of LORETA Neurofeedback in Right Anterior Cingulate Cortex

Cannon, Rex; Lubar, Joel F.; Sokhadze, Estate M.; Baldwin, Debora R.

doi:10.1080/10874200802501948

Cited by 25 publications

(19 citation statements)

References 75 publications

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“…In addition, LORETA neurofeedback can be implemented in regions in both attentional networks and the DMN including the anterior cingulate gyrus and precuneus (Cannon, Baldwin, & Lubar, 2009;Cannon et al, 2007;Cannon, Lubar, Sokhadze, & Baldwin, 2008). The current study utilizes center coordinates from the Raichle Raichle et al (2001) DMN study.…”

Section: Introductionmentioning

confidence: 96%

sLORETA and fMRI Detection of Medial Prefrontal Default Network Anomalies in Adult ADHD

Cannon¹,

Kerson²,

Hampshire³

2011

Journal of Neurotherapy

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Attention deficit hyperactivity disorder (ADHD) is a developmental psychiatric disorder thought to affect approximately 5 to 10% of school-age children, of whom 30 to 65% continue to exhibit symptoms into adulthood. The prevalence of ADHD in adults is also an estimated 4%, second only to depression. Across studies there appear to be significant network dysfunctions involved in ADHD. Typically the foci of interest in ADHD included the insular cortices, frontal lobes, basal ganglia, and cerebellum. More recently, attention has been directed to the default network of the brain and its functional integrity in ADHD with focus on the precuneus and parietal lobes and interactions with medial prefrontal cortices. Functional magnetic resonance imaging (fMRI) measures neurovascular coupling as measured by the blood oxygenated level dependent signal (BOLD). Electroencephalogram (EEG) measures brain electrical information. Because fMRI is an indirect measure of neuronal activity and EEG is a direct measure, combining the results from these two imaging modalities under the same task conditions may provide a more complete story as to the what (EEG) and where (fMRI) activity exists. This article discusses the benefits of using standardized low resolution electromagnetic tomography (sLORETA) analysis of the EEG as compared to fMRI. The goal of the study, the data from which we use for our justification, was to discover the functional differences in ADHD and non-ADHD brains with different brain imaging modalities. We hoped to elucidate functional connectivity patterns by interpreting the data acquired with the EEG using sLORETA and the data acquired with the fMRI scans. We further hoped to find correlation with the sLORETA and fMRI interpretations so as to confirm that EEG is an adequate stand-alone methodology to evaluate ADHD. Participants included 6 ADHD and 7 non-ADHD subjects. They were initially interviewed by phone and administered the Connors Rating Scale and the Mini International Neuropsychiatric Interview to determine accuracy of symptom reporting and to rule out psychological comorbidities. Exclusion criteria consisted of previous head trauma, recent drug or alcohol abuse (14 days), or neurological syndromes. We recorded sequential 19-channel EEG and fMRI during the eyes-open and eyes-closed states and while performing the Stroop test. The QEEG results were evaluated with comparison to a normative database and with sLORETA analysis.Functional connectivity was assessed using the seed-based approach in sLORETA. The fMRI results were evaluated using Brain Voyager TM and other neuroimaging software packages. sLORETA and fMRI data identify a region in medial Brodmann Area (BA) 10 of the default network. Furthermore, regional frontal differences extend to medial BA 32 with more emphasis to left prefrontal. sLORETA determines there is less current source density at BA 10 in the ADHD participants than controls. sLORETA is adequate in localizing the sources of the EEG in the default network as contrasted with fMRI. It is impor...

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Section: Introductionmentioning

confidence: 96%

sLORETA and fMRI Detection of Medial Prefrontal Default Network Anomalies in Adult ADHD

Cannon¹,

Kerson²,

Hampshire³

2011

Journal of Neurotherapy

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“…However, as reviewed in later sections, there are more than 700 peer reviewed publications [202] that use the same voxel sizes for EEG distributed inverse solutions at 7 mm 3 and with spatial resolutions of approximately 1-3 cm 3 [15,34,35]. By contrast, the best spatial resolution of fMRI is approximately 4 mm 3 under the most ideal circumstances, but is often several centimeters, which is a similar spatial resolution as tEEG [90,91]. The advantage of electrical neuroimaging over fMRI and PET is the reduced cost and the marked improvement in temporal resolution.…”

Section: Clinical Applications Of Electrical Neuroimagingmentioning

confidence: 96%

“…EEG BCI and NF clinical treatment is based on the use of reinforcement and operant conditioning to train patients to modify specific EEG frequencies and phases at particular scalp locations, including the use of 3D source ana lysis to modify the EEG generated in specific brain regions such as the anterior cingulate gyrus or lateral prefrontal lobes, among others [85][86][87][88][89][90][91][92]. Operant conditioning of specific brain regions has also been used with fMRI, but this method is very expensive with low temporal resolution and long delays between brain changes and reinforcement [93].…”

Section: Normative Qeeg Databasesmentioning

confidence: 99%

Neuropsychiatry and quantitative EEG in the 21st Century

Thatcher¹

2011

Neuropsychiatry

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The human brain weighs approximately 3 lbs and consumes 40-60% of blood glucose. This disproportionate amount of energy is used to create electricity in approximately 100 billion interconnected neurons. Quantitative EEG is a real-time movie of the electrical activity of the preconscious and conscious mind at frequencies of approximately 1-300 Hz. Numerous studies have cross-validated electrical neuroimaging by structural MRI, functional MRI and diffusion spectral imaging and thereby demonstrated how quantitative EEG can aid in linking a patient's symptoms and complaints to functional specialization in the brain. Electrical neuroimaging provides an inexpensive millisecond measure of functional modules, including the animation of structures through phase shift and phase lock. Today, neuropsychiatrists use these methods to link a patient's symptoms and complaints to functional specialization in the brain and use this information to implement treatment via brain-computer interfaces and neurofeedback technology. †

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“…Several studies indicate alpha to be associated with visual processing, attentional orienting, and cognitive control in normal controls and ADHD (Mazaheri et al, 2010;Zhang, Wang, Bressler, Chen, & Ding, 2008). In addition, it has been suggested to play an important role in memory; attention; self-perception; and a variety of cognitive, attentional, and affective processes Cannon, Lubar, Thornton, Wilson, & Congedo, 2005;Cannon, Lubar, Sokhadze, & Baldwin, 2008;Sauseng, Klimesch, Gerloff, & Hummel, 2009;Sauseng et al, 2005). Although the mechanisms of ADHD remain unclear, advancing technologies and interdisciplinary approaches combining methods may aid in developing a less ambiguous understanding of ADHD and its synchronous neural etiology.…”

Section: Discussionmentioning

confidence: 99%

Pilot Data Assessing the Functional Integrity of the Default Network in Adult ADHD with fMRI and sLORETA

Cannon¹,

Kerson²,

Hampshire³

et al. 2012

Journal of Neurotherapy

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LORETA Neurofeedback for Addiction and the Possible Neurophysiology of Psychological Processes Influenced: A Case Study and Region of Interest Analysis of LORETA Neurofeedback in Right Anterior Cingulate Cortex

Cited by 25 publications

References 75 publications

sLORETA and fMRI Detection of Medial Prefrontal Default Network Anomalies in Adult ADHD

sLORETA and fMRI Detection of Medial Prefrontal Default Network Anomalies in Adult ADHD

Neuropsychiatry and quantitative EEG in the 21st Century

Pilot Data Assessing the Functional Integrity of the Default Network in Adult ADHD with fMRI and sLORETA

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