The brain, obesity and addiction: an EEG neuroimaging study

Ridder, Dirk De; Manning, Patrick J.; Leong, Sook Ling; Ross, Samantha; Sutherland, W. H. F.; Horwath, Caroline C.; Vanneste, Sven

doi:10.1038/srep34122

Cited by 43 publications

(40 citation statements)

References 82 publications

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“…Anthropometric measures for the non-TCD group are reported in supplementary table 1 . Obesity has been associated with brain changes, but as far as we know, has not been associated with TCD 41 . Hence, we selected this group as a control measure to cross-validate our TCD-related disorders model (i.e., tinnitus, pain, Parkinson’s disease, and depression).…”

Section: Methodsmentioning

confidence: 78%

Thalamocortical dysrhythmia detected by machine learning

2018

Self Cite

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Thalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. It is characterized by a common oscillatory pattern in which resting-state alpha activity is replaced by cross-frequency coupling of low- and high-frequency oscillations. We undertook a data-driven approach using support vector machine learning for analyzing resting-state electroencephalography oscillatory patterns in patients with Parkinson’s disease, neuropathic pain, tinnitus, and depression. We show a spectrally equivalent but spatially distinct form of TCD that depends on the specific disorder. However, we also identify brain areas that are common to the pathology of Parkinson’s disease, pain, tinnitus, and depression. This study therefore supports the validity of TCD as an oscillatory mechanism underlying diverse neurological disorders.

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Section: Methodsmentioning

confidence: 78%

Thalamocortical dysrhythmia detected by machine learning

2018

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“…Increasingly, psychological factors are being investigated in the etiology of obesity [ 10 , 11 ]. Studies have found similarities in personality types, behavioral traits, and functional neural abnormalities between obese individuals and those with addictive disorders such as drug or alcohol dependence [ 12 , 13 , 14 ]. This has led to an increased amount of research investigating that an addictive process in relation to food and/or eating—“food addiction”—may contribute to the development of obesity in susceptible individuals.…”

Section: Introductionmentioning

confidence: 99%

Addictive Eating and Its Relation to Physical Activity and Sleep Behavior

Pursey

Duncan

et al. 2018

Nutrients

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The obesity epidemic has led to the exploration of factors contributing to its etiology. Addictive eating, physical activity, and sleep behaviors have all been independently associated with obesity, and recent research suggests plausible interrelationships between food addiction, physical activity, and sleep. This study aims to investigate the relationship between food addiction with physical activity and sleep behavior. Australian adults were invited to complete an online survey which collected information including: demographics, food addiction symptoms, physical activity, sitting time and sleep behavior items. The sample comprised 1344 individuals with a mean age of 39.8 ± 13.1 years (range 18–91), of which 75.7% were female. Twenty-two percent of the sample met the criteria for a diagnosis of food addiction as per the Yale Food Addiction Scale (YFAS 2.0) criteria, consisting of 0.7% with a “mild” addiction, 2.6% “moderate”, and 18.9% classified as having a “severe” food addiction. Food-addicted individuals had significantly less physical activity (1.8 less occasions walking/week, 32 min less walking/week, 58 min less moderate to vigorous physical activity (MVPA)/week; p < 0.05), reported sitting for longer on weekends (83 min more on weekends/week; p < 0.001), and reported significantly more symptoms of poorer-quality sleep (more likely to snore, more likely to have fallen asleep while driving, reported more days of daytime falling asleep; p < 0.05) compared to non-food-addicted individuals. These differences were also observed in those with a “severe” food addiction classification. The present study suggests frequency and duration of physical activity, time spent sitting and sleep duration are associated with food addiction.

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“…These Brodmann areas, 13, 24, 25, 32, 44, 45, 46, 47, include the insular cortex and PFC pathways, which are integral to executive functioning and inhibitory control in humans [21]. These areas participate in varying degrees to the craving, bingeing, and withdrawal behaviours seen in addiction [21] [22]. The advantage to using Z-scores in LORETA biofeedback is the ability to receive instant comparisons using a reference database of healthy individuals Z-scores [23].…”

Section: Discussionmentioning

confidence: 99%

Normalizing the Neural Correlates of Binge-Eating Disorder with Lisdexamfetamine: A Case Report and Literature Review

Brucar¹,

Hyder²,

Birmingham³

2018

OJPsych

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The brain regions associated with binge-eating disorder (BED) and those targeted by Lisdexamfetamine (LDX) overlap. The present paper reviews the psychobehavioural and neuropharmacological mechanisms at play in BED and compulsive eating behaviours, along with the mechanisms of action LDX is thought to play. We present one case of chronic BED and highlight the EEG scans pre-and post-LDX treatment. The normalization of the patient's electroencephalogy (EEG) activity associated with BED after LDX supports theorized mechanisms of LDX action, further explaining its efficacy in treatment. A significant decrease in theta band power was observed in the patient after treatment with LDX. Specifically, this decrease was modulated by changes in the F8 electrode corresponding to the orbitofrontal cortex (OFC)-An area associated with deficits in inhibitory function, seen in addictions and BED. A better understanding of the psychobehavioural and neuropharmacological mechanisms involved in BED and LDX treatment has the potential to significantly enhance our knowledge of the underlying pathogenesis, potential prevention, and optimal treatment options for patients.

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The brain, obesity and addiction: an EEG neuroimaging study

Cited by 43 publications

References 82 publications

Thalamocortical dysrhythmia detected by machine learning

Thalamocortical dysrhythmia detected by machine learning

Addictive Eating and Its Relation to Physical Activity and Sleep Behavior

Normalizing the Neural Correlates of Binge-Eating Disorder with Lisdexamfetamine: A Case Report and Literature Review

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