Modification of EEG functional connectivity and EEG power spectra in overweight and obese patients with food addiction: An eLORETA study

Food addiction and the physical and mental health status of adults with overweight and obesity

Background

Overweight and obesity now affect more than a third of the world's population. They are strongly associated with somatic diseases, in particular increasing the risk of many metabolic and cardiovascular diseases, but also with mental disorders. In particular, there is a strong association between obesity and depression. As a result, more attention is paid to the neurobiological, behavioural, and psychological mechanisms involved in eating. One of these is food addiction (FA). Research comparing lifestyle elements, physical and mental health problems of excess body weight and individuals with FA is limited and has focused on younger people, mainly students. There is also a lack of studies that relate actual metabolic parameters to FA. To better understand the problem of FA also in older adults, it is important to understand the specific relationships between these variables.

Methods

A cross-sectional survey was conducted with 172 adults with overweight and obesity (82% female) aged 23-85 years. The mean age of all subjects was M = 59.97 years (SD = 11.93), the mean BMI was M = 32.05 kg/m2 (SD = 4.84), and the mean body fat was M = 39.12% (SD = 6.48). The following questionnaires were used: Food Frequency Questionnaire-6 (FFQ-6), Global Physical Activity Questionnaire (GPAQ), Three Factor Eating Questionnaire-R18 (TFEQ-R18), Yale Food Addiction Scale 2. 0 (YFAS 2.0), Zung Self-Rating Depression Scale (SDS). Body composition, anthropometry, fasting glucose, lipid profile, and blood pressure were measured.

Results

A total of 22.7% of participants with overweight and obesity had symptoms of depression according to the SDS, and 18.6% met the criteria for FA according to YFAS 2.0. FA was statistically significantly more common among people up to 50 years. BMI, body fat mass, diastolic blood pressure and sedentary behaviour were statistically significantly higher in people with FA symptoms. Those who were sedentary for 301-450 min per day were significantly more likely to have depressive symptoms, and those who were sedentary for more than 450 min per day were significantly more likely to have FA symptoms.

Conclusions

Our findings complement the current literature on FA, particularly in older adults and metabolic parameters, and suggest further research directions. Although our cross-sectional study design does not allow causal interpretations, increasing physical activity appears to be particularly important in the management of people with overweight or obesity and FA. This may be even more important than for people with depression alone, but future research is needed to explore these relationships further.

Multimodal-based machine learning approach to classify features of internet gaming disorder and alcohol use disorder: A sensor-level and source-level resting-state electroencephalography activity and neuropsychological study

OBJECTIVES

Addictions have recently been classified as substance use disorder (SUD) and behavioral addiction (BA), but the concept of BA is still debatable. Therefore, it is necessary to conduct further neuroscientific research to understand the mechanisms of BA to the same extent as SUD. The present study used machine learning (ML) algorithms to investigate the neuropsychological and neurophysiological aspects of addictions in individuals with internet gaming disorder (IGD) and alcohol use disorder (AUD).

METHODS

We developed three models for distinguishing individuals with IGD from those with AUD, individuals with IGD from healthy controls (HCs), and individuals with AUD from HCs using ML algorithms, including L1-norm support vector machine, random forest, and L1-norm logistic regression (LR). Three distinct feature sets were used for model training: a unimodal-electroencephalography (EEG) feature set combined with sensor- and source-level feature; a unimodal-neuropsychological feature (NF) set included sex, age, depression, anxiety, impulsivity, and general cognitive function, and a multimodal (EEG + NF) feature set.

RESULTS

The LR model with the multimodal feature set used for the classification of IGD and AUD outperformed the other models (accuracy: 0.712). The important features selected by the model highlighted that the IGD group had differential delta and beta source connectivity between right intrahemispheric regions and distinct sensor-level EEG activities. Among the NFs, sex and age were the important features for good model performance.

CONCLUSIONS

Using ML techniques, we demonstrated the neurophysiological and neuropsychological similarities and differences between IGD (a BA) and AUD (a SUD).

Effects of anodal tDCS on resting state eeg power and motor function in acute stroke: a randomized controlled trial

BACKGROUND

Anodal transcranial direct current stimulation (tDCS) is a beneficial adjunctive tool in stroke rehabilitation. However, only a few studies have investigated its effects on acute stroke and recruited only individuals with mild motor deficits. This study investigated the effect of five consecutive sessions of anodal tDCS and conventional physical therapy on brain activity and motor outcomes in individuals with acute stroke, with low and high motor impairments.

METHODS

Thirty participants were recruited and randomly allocated to either the anodal or sham tDCS group. Five consecutive sessions of tDCS (1.5 mA anodal or sham tDCS for 20 min) were administered, followed by conventional physical therapy. Electroencephalography (EEG), Fugl-Meyer Motor Assessment (FMA), and Wolf Motor Function Test (WMFT) were performed at pre-, post-intervention (day 5), and 1-month follow-up. Sub-analyses were performed on participants with low and high motor impairments. The relationship between EEG power and changes in motor functions was assessed.

RESULTS

Linear regression showed a significant positive correlation between beta bands and the FMA score in the anodal group. Elevated high frequency bands (alpha and beta) were observed at post-intervention and follow-up in all areas of both hemispheres in the anodal group, while only in the posterior area of the non-lesioned hemisphere in the sham group; however, such elevation induced by tDCS was not greater than sham. Lower limb function assessed by FMA was improved in the anodal group compared with the sham group at post-intervention and follow-up only in those with low motor impairment. For the upper limb outcomes, no difference between groups was found.

CONCLUSIONS

Five consecutive days of anodal tDCS and physical therapy in acute stroke did not result in a superior improvement of beta bands that commonly related to stroke recovery over sham, but improved lower extremity functions with a post-effect at 1-month follow-up in low motor impairment participants. The increase of beta bands in the lesioned brain in the anodal group was associated with improvement in lower limb function.

TRIAL REGISTRATION

NCT04578080, date of first registration 10/01/2020.

Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments

One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.

Measurement of craving among gamers with internet gaming disorder using repeated presentations of game videos: a resting-state electroencephalography study

BACKGROUND

Internet gaming disorder (IGD) is receiving increasing attention owing to its effects on daily living and psychological function.

METHODS

In this study, electroencephalography was used to compare neural activity triggered by repeated presentation of a stimulus in healthy controls (HCs) and those with IGD. A total of 42 adult men were categorized into two groups (IGD, n = 21) based on Y-IAT-K scores. Participants were required to watch repeated presentations of video games while wearing a head-mounted display, and the delta (D), theta (T), alpha (A), beta (B), and gamma (G) activities in the prefrontal (PF), central (C), and parieto-occipital (PO) regions were analyzed.

RESULTS

The IGD group exhibited higher absolute powers of D_C, D_PO, T_C, T_PO, B_C, and B_PO than HCs. Among the IGD classification models, a neural network achieves the highest average accuracy of 93% (5-fold cross validation) and 84% (test).

CONCLUSIONS

These findings may significantly contribute to a more comprehensive understanding of the neurological features associated with IGD and provide potential neurological markers that can be used to distinguish between individuals with IGD and HCs.

Preventable risk factors for type 2 diabetes can be detected using noninvasive spontaneous electroretinogram signals

Given the ever-increasing prevalence of type 2 diabetes and obesity, the pressure on global healthcare is expected to be colossal, especially in terms of blindness. Electroretinogram (ERG) has long been perceived as a first-use technique for diagnosing eye diseases, and some studies suggested its use for preventable risk factors of type 2 diabetes and thereby diabetic retinopathy (DR). Here, we show that in a non-evoked mode, ERG signals contain spontaneous oscillations that predict disease cases in rodent models of obesity and in people with overweight, obesity, and metabolic syndrome but not yet diabetes, using one single random forest-based model. Classification performance was both internally and externally validated, and correlation analysis showed that the spontaneous oscillations of the non-evoked ERG are altered before oscillatory potentials, which are the current gold-standard for early DR. Principal component and discriminant analysis suggested that the slow frequency (0.4-0.7 Hz) components are the main discriminators for our predictive model. In addition, we established that the optimal conditions to record these informative signals, are 5-minute duration recordings under daylight conditions, using any ERG sensors, including ones working with portative, non-mydriatic devices. Our study provides an early warning system with promising applications for prevention, monitoring and even the development of new therapies against type 2 diabetes.

Food-Induced Brain Activity in Children with Overweight or Obesity versus Normal Weight: An Electroencephalographic Pilot Study

BACKGROUND

Although increased food cue reactivity is evidenced to be crucial to the development and maintenance of pediatric obesity, virtually nothing is known about the underlying neurophysiological aspects of food cue reactivity in children with obesity. Therefore, this study aimed at investigating neural characteristics in children with overweight or obesity using electroencephalography (EEG).

METHODS

Electrophysiological brain activity was measured using EEG frequency band analysis in n = 9 children with overweight or obesity versus n = 16 children with normal weight (8-13 years) during the presentation of high- and low-calorie food pictures and images of appealing non-food stimuli.

RESULTS

Children with overweight or obesity showed significantly increased relative central beta band activity induced by high-calorie foods and appealing non-food stimuli compared to children with normal weight. Beyond significant effects of the scalp region on EEG activity, non-significant effects of stimulus category or weight status were seen for theta and alpha frequency bands.

CONCLUSIONS

This study demonstrated elevated beta band activity in children with overweight or obesity when viewing high-calorie food stimuli. Beta band activity may, thus, be a valuable target for neuromodulatory interventions in children with overweight or obesity.

Combination of Group Singular Value Decomposition and eLORETA Identifies Human EEG Networks and Responses to Transcranial Photobiomodulation

Transcranial Photobiomodulation (tPBM) has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram (EEG) networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm². In data processing, a novel methodology by combining group singular value decomposition (gSVD) with the exact low-resolution brain electromagnetic tomography (eLORETA) was implemented and performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components (PCs) projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band (delta, theta, alpha, beta and gamma) were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes.

Decreased excitability of leptin-sensitive anterior insula pyramidal neurons in a rat model of compulsive food demand

Compulsive eating is an overlapping construct with binge eating that shares many characteristics with substance use disorders. Compulsive eating may impact millions of Americans; presenting in some cases of binge eating disorders, overweight/obesity, and among individuals who have not yet been diagnosed with a recognized eating disorder. To study the behavioral and neurobiological underpinnings of compulsive eating, we employ a published rodent model using cyclic intermittent access to a palatable diet to develop a self-imposed binge-withdrawal cycle. Here, we further validated this model of compulsive eating in female Wistar rats, through the lens of behavioral economic analyses and observed heightened demand intensity, inelasticity and essential value as well as increased food-seeking during extinction. Using electrophysiological recordings in the anterior insular cortex, a region previously implicated in modulating compulsive-like eating in intermittent access models, we observed functional adaptations of pyramidal neurons. Within the same neurons, application of leptin led to further functional adaptations, suggesting a previously understudied, extrahypothalamic role of leptin in modulating feeding-related cortical circuits. Collectively, the findings suggest that leptin may modulate food-related motivation or decision-making via a plastic cortical circuit that is influenced by intermittent access to a preferred diet. These findings warrant further study of whether behavioral economics analysis of compulsive eating can impact disordered eating outcomes in humans and of the translational relevance of a leptin-sensitive anterior insular circuit implicated in these behaviors.

Highly processed food addiction: A concept analysis

AIM

This concept analysis aims to clarify the highly processed food addiction (HPFA) concept and discuss its implications for treating obesity.

BACKGROUND

Emerging empirical evidence suggests addictive-like eating may contribute to obesity in some individuals, increasing interest in HPFA's role in obesity. Clarifying the HPFA concept will aid in developing individualized interventions for patients with obesity and HPFA.

DESIGN

This concept analysis followed Walker and Avant's approach. The case studies are of participants in a study that included individuals with and without HPFA (Yale Food Addiction Scale 2.0-diagnosed).

DATA SOURCE

We searched PubMed, CINAHL, PsychInfo, and Ebscohost databases. Keywords were "food addiction" and "food addiction concept."

REVIEW METHODS

Criteria included recent reviews and empirical studies that measured HPFA and focused on HPFA characteristics and/or treatment implications.

RESULTS

The model case displayed all 11-substance use disorder (SUD) symptoms and clinical significance, supporting a severe HPFA diagnosis. The contrary case was negative for all YFAS 2.0 symptoms and clinical significance and did not eat compulsively or experience cravings. The borderline case met the minimum symptom criteria for severe HPFA but not clinical significance. Clinical interviews may help determine whether such individuals truly exhibit addictive-like eating behaviors.

CONCLUSIONS

Growing empirical evidence and our case studies support the HPFA concept and the utility of the YFAS/YFAS 2.0 for identifying a distinct subset of individuals with overweight/obesity who may benefit from interventions developed to treat established SUDs. Future research should examine HPFA separately and in relation to obesity and eating disorders and include longitudinal studies and gender-balanced samples.

The Effect of Food Composition and Behavior on Neurobiological Response to Food: a Review of Recent Research

PURPOSE OF REVIEW

Controversy surrounds the construct of food addiction. The current review examines neurobiological evidence for the existence of food addiction as a valid diagnosis.

RECENT FINDINGS

Recent neuroimaging studies suggest significant overlap in the areas of the brain that are activated in relation to both food and drug addiction. Specifically, areas of the brain implicated in executive functioning (e.g., attention, planning, decision-making, inhibition), pleasure and the experience of reward, and sensory input and motor functioning display increased activation among individuals with symptoms of both food and drug addiction. Proposed symptoms of food addiction mirror those comprising other substance use disorder diagnoses, with similar psychological and behavioral sequelae. Results of neuroimaging studies suggest significant overlap in the areas of the brain that are activated in relation to both food and drug addiction, providing support for continued research into the construct of food addiction.

High fructose corn syrup alters behavioural and neurobiological responses to oxycodone in rats

There are indications that sugars in the diet can play a role in vulnerability to opioid abuse. The current study examined a range of neuro-behavioural interactions between oxycodone (OXY) and high fructose corn syrup (HFCS). Male Sprague-Dawley rats had access to HFCS (0 or 50%) over 26 days in their home cages and were subsequently tested on place conditioning induced by 0, 0.16 and 2.5 mg/kg OXY (3 pairings of drug and saline, each 30 min), as well as on locomotor responses to 0, 0.16 and 2.5 mg/kg OXY, and in-vivo microdialysis was employed to measure dopamine (DA) levels in the nucleus accumbens (NAc) in response to 0 and 2.5 mg/kg OXY. A complex set of interactions between HFCS exposure and responses to OXY were observed: HFCS increased place preference induced by OXY, it enhanced the suppressant effect of OXY on locomotion, and it attenuated OXY-induced elevation in DA overflow in the NAc. Taken together, these findings suggest that nutrition has the potential to influence some responses to opioids which may be relevant to their abuse.

Delta resting-state functional connectivity in the cognitive control network as a prognostic factor for maintaining abstinence: An eLORETA preliminary study

BACKGROUND

Cortical regions that support cognitive control are increasingly well recognized, but the functional mechanisms that promote such control over emotional and behavioral hyperreactivity to alcohol in recently abstinent alcohol-dependent patients are still insufficiently understood. This study aimed to identify neurophysiological biomarkers of maintaining abstinence in alcohol-dependent individuals after alcohol treatment by investigating the resting-state EEG-based functional connectivity in the cognitive control network (CCN).

METHODS

Lagged phase synchronization between CCN areas by means of eLORETA as well as the Barratt Impulsiveness Scale (BIS-11) and Beck Depression Inventory (BDI) were assessed in abstinent alcohol-dependent patients recruited from treatment centers. A preliminary prospective study design was used to classify participants into those who did and did not maintain abstinence during a follow-up period (median 12 months) after discharge from residential treatment.

RESULTS

Alcohol-dependent individuals, who maintained abstinence (N = 18), showed significantly increased lagged phase synchronization between the left dorsolateral prefrontal cortex (DLPFC) and the left posterior parietal cortex (IPL) as well as between the right anterior insula cortex/frontal operculum (IA/FO) and the right inferior frontal junction (IFJ) in the delta band compared to those who later relapsed (N = 16). Regression analysis showed that the increased left frontoparietal delta connectivity in the early period of abstinence significantly predicted maintaining abstinence over the ensuing 12 months. Furthermore, right frontoinsular delta connectivity correlated negatively with impulsivity and depression measures.

CONCLUSIONS

These results suggest that the increased delta resting-state functional connectivity in the CCN may be a promising neurophysiological predictor of maintaining abstinence in individuals with alcohol dependence.

Electroencephalographic (EEG) alterations in young women with high subclinical eating pathology levels: a quantitative EEG study

PURPOSE

To explore electroencephalographic (EEG) alterations in young women with different eating disorder (ED) psychopathology levels.

METHODS

Thirty-seven young women completed general and ED psychopathology (i.e., the ED Examination Questionnaire; EDE-Q) measures. EEG power spectra data were investigated in two conditions: (a) 5 min of resting state (RS) and (b) 5 min of RS after a single taste of a milkshake (ML-RS). EEG analyses were performed using exact Low-Resolution Electromagnetic Tomography software (eLORETA).

RESULTS

Cluster analysis performed on the EDE-Q responses revealed a group of 17 women with high levels of ED pathology falling into the subclinical (i.e., sub-threshold) EDs category and a group of 20 women with low levels of ED pathology (controls). In the RS conditions, no significant modifications were observed between groups. Compared to controls, women with subclinical EDs showed an increase in theta activity in the parieto-occipital areas in the ML-RS condition. After controlling for body mass index and general psychopathology, theta activity in these brain structures was positively associated with EDE-Q global and subscale (restraint, shape and weight concern) scores.

CONCLUSIONS

Our results may reflect the neurophysiological substrate of ED psychopathology core features like shape/weight concerns. Previous brain imaging and qEEG studies with full-syndrome ED patients also underscored the involvement of parieto-occipital areas in ED pathophysiology. These studies also found brain alterations in the RS condition, not observed here. This is notable given that full-syndrome and subclinical EDs are considered as different manifestations of the same disease along a severity spectrum.

LEVEL OF EVIDENCE

Level V, cross-sectional, electroencephalographic, descriptive study.

Altered brain network topology related to working memory in internet addiction

BACKGROUND AND AIMS

The working memory (WM) ability of internet addicts and the topology underlying the WM processing in internet addiction (IA) are poorly understood. In this study, we employed a graph theoretical framework to characterize the topological properties of the IA brain network in the source cortical space during WM task.

METHODS

A sample of 24 subjects with IA and 23 matched healthy controls (HCs) performed visual 2-back task. Exact Low Resolution Electromagnetic Tomography was adopted to project the pre-processed EEG signals into source space. Subsequently, Lagged phase synchronization was calculated between all pairs of Brodmann areas, the graph theoretical approaches were then employed to estimate the brain topological properties of all participants during the WM task.

RESULTS

We found better WM behavioral performance in IA subjects compared with the HCs. Moreover, compared to the HC group, more integrated and hierarchical brain network was revealed in the IA subjects in alpha band. And altered regional centrality was mainly resided in frontal and limbic lobes. In addition, significant relationships between the IA severity and the significant altered graph indices were found.

CONCLUSIONS

In conclusion, these findings provide evidence to support the notion that altered topological configuration may underline changed WM function observed in IA.

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

: Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD.

Increased Resting State Triple Network Functional Connectivity in Undergraduate Problematic Cannabis Users: A Preliminary EEG Coherence Study

An increasing body of experimental data have suggested that aberrant functional interactions between large-scale networks may be the most plausible explanation of psychopathology across multiple mental disorders, including substance-related and addictive disorders. In the current research, we have investigated the association between problematic cannabis use (PCU) and triple-network electroencephalographic (EEG) functional connectivity. Twelve participants with PCU and 24 non-PCU participants were included in the study. EEG recordings were performed during resting state (RS). The exact Low-Resolution Electromagnetic Tomography software (eLORETA) was used for all EEG analyses. Compared to non-PCU, PCU participants showed an increased delta connectivity between the salience network (SN) and central executive network (CEN), specifically, between the dorsal anterior cingulate cortex and right posterior parietal cortex. The strength of delta connectivity between the SN and CEN was positively and significantly correlated with higher problematic patterns of cannabis use after controlling for age, sex, educational level, tobacco use, problematic alcohol use, and general psychopathology (r_p = 0.40, p = 0.030). Taken together, our results show that individuals with PCU could be characterized by a specific dysfunctional interaction between the SN and CEN during RS, which might reflect the neurophysiological underpinnings of attentional and emotional processes of cannabis-related thoughts, memories, and craving.

Neural correlates of inhibitory control in youth with symptoms of food addiction

Prior research has found that food addiction is associated with reward-related neural differences, but research has yet to examine whether there are also neural differences in inhibitory control. This may be particularly relevant during adolescence as it is a key developmental period where difficulties in inhibitory control are more prevalent. The Yale Food Addiction Scale is a self-report questionnaire that applies substance use disorder diagnostic criteria to certain foods that has also been adapted for children. Here we investigate the association between addictive-like eating and brain functioning during inhibitory control in youth. Seventy-six right-handed participants 8.2-17.8 years (44 male) were recruited. Participants performed a go/no-go task during functional magnetic resonance imaging and completed the Yale Food Addiction Scale for Children, after which they were categorized into two groups according to their scores (No Symptom Group = 0; YFAS-C Group: score ≥ 1). Inhibitory control was probed with a contrast of correct no-go versus go trials. An independent-samples t-test comparing groups revealed a significant difference in three primary clusters, all exclusively in the left hemisphere (No Symptom Group > YFAS-C Group): middle temporal gyrus/occipital gyrus, precuneus/calcarine sulcus, and inferior frontal gyrus. Specifically, the YFAS-C Group showed deactivation in all three clusters. Adolescents who endorse food addiction appear to show hypo-activation in response to the inhibitory control portion of a go/no-go task, which suggests possible inhibitory control difficulties.

Executive functioning and psychological symptoms in food addiction: a study among individuals with severe obesity

Food addiction (FA) has recently emerged as a new field in the study of obesity. Previous studies have contributed to identifying psychological correlates of FA. However, few researchers have examined the cognitive profile related to this condition; up until now, attentional biases related to food cues and a poorer performance monitoring have been observed. The present study aimed to examine the psychological profile and executive functioning related to FA in individuals with severe obesity and awaiting bariatric surgery. Participants (N = 86) were split into two groups, according to their level of FA symptoms (low FA vs high FA). Groups were compared on questionnaires measuring binge eating, depression and anxiety symptoms, and impulsivity as well as on measures reflecting executive functioning (D-KEFS and BRIEF-A). The relationship between FA groups and patterns of errors during the D-KEFS' Color-Word Interference Test was further analyzed. Individuals within the high FA group reported significantly more binge eating, depressive and anxiety symptoms, and more metacognitive difficulties. They also tended to show a poorer inhibition/cognitive flexibility score and a typical pattern of errors, characterized by an increased number of errors as the tasks' difficulty rose as opposed to a decreased number of errors, which characterizes an atypical pattern of errors. The present results show that the inability to learn from errors or past experiences is related to the severity of FA and overall impairments.Level of evidence Level V, descriptive study.

What Is the Evidence for "Food Addiction?" A Systematic Review

The diagnostic construct of “food addiction” is a highly controversial subject. The current systematic review is the first to evaluate empirical studies examining the construct of “food addiction” in humans and animals. Studies were included if they were quantitative, peer-reviewed, and in the English language. The 52 identified studies (35 articles) were qualitatively assessed to determine the extent to which their findings indicated the following addiction characteristics in relation to food: brain reward dysfunction, preoccupation, risky use, impaired control, tolerance/withdrawal, social impairment, chronicity, and relapse. Each pre-defined criterion was supported by at least one study. Brain reward dysfunction and impaired control were supported by the largest number of studies (n = 21 and n = 12, respectively); whereas risky use was supported by the fewest (n = 1). Overall, findings support food addiction as a unique construct consistent with criteria for other substance use disorder diagnoses. The evidence further suggests that certain foods, particularly processed foods with added sweeteners and fats, demonstrate the greatest addictive potential. Though both behavioral and substance-related factors are implicated in the addictive process, symptoms appear to better fit criteria for substance use disorder than behavioral addiction. Future research should explore social/role impairment, preoccupation, and risky use associated with food addiction and evaluate potential interventions for prevention and treatment.

Food and beverage consumption and food addiction among women in the Nurses' Health Studies

BACKGROUND AND AIMS

Previous studies have not addressed a fundamental component of a food addiction disorder: the compulsive relationship between eating and potentially positively reinforcing foods. We aimed to evaluate the association between food consumption and food addiction.

METHODS

We conducted cross-sectional analyses merging data from the Nurses' Health Study (n = 58,625) and Nurses' Health Study II (n = 65,063), two prospective cohort studies of female nurses in the United States. Diet was assessed in 2006-2007 using a food frequency questionnaire, and food addiction was assessed in 2008-2009 using the Modified Yale Food Addiction Scale.

RESULTS

The prevalence of food addiction was 5.4%. The odds of food addiction were strongest among nurses consuming 5+ servings/week (compared with <1 serving/month) of hamburgers (multivariable odds ratio (MVOR) 4.08; 95% CI, 2.66-6.25), French fries (MVOR, 2.37; 95% CI, 1.59-3.51) and pizza (MVOR, 2.49; 95% CI, 1.67-3.69). Consumption of red/processed meat, low/no fat snacks/desserts, and low calorie beverages was positively associated with food addiction, while consumption of refined grains, sugar-sweetened beverages and fruits, vegetables, and legumes was inversely associated with food addiction.

CONCLUSIONS

This epidemiologic study was the largest to examine food consumption and food addiction. Food addiction was positively associated with consumption of many hypothesized positively reinforcing foods that include a combination of carbohydrates and fats such as snacks, "fast foods," and candy bars. However, it was inversely or not associated with certain sweet foods, refined grains, and sugar-sweetened beverages, which is consistent with literature suggesting that carbohydrates (without other ingredients) are less associated with food addiction. Longitudinal analyses will help untangle the temporal order between food consumption and food addiction, as some relationships in our analyses were difficult to interpret due to the cross-sectional design.

The neural correlates of the unified percept of alcohol-related craving: a fMRI and EEG study

Alcohol addiction is accompanied by aberrant neural activity. Previously, task-based fMRI and resting-state EEG studies have revealed that craving, a critical component of addiction, is linked to abnormal activity in cortical regions including the dorsal anterior cingulate cortex (dACC), nucleus accumbens (NAcc), posterior cingulate cortex (PCC) and pregenual anterior cingulate cortex (pgACC), etc. In this study, we combine these two imaging techniques to investigate a group of alcohol-addicted patients and provide convergent evidence for the neural correlates of craving not only in alcohol but substance abuse in general. We observe abnormal BOLD signal levels in the dACC, NAcc, pgACC, PCC, amygdala, and parahippocampus (PHC) in a cue-reactivity fMRI experiment. These findings are consistent with increased beta-band activity in the dACC and pgACC in resting-state EEG. We further observe desynchronization characterized by decreased functional connectivity in cue-based fMRI and hypersynchronization characterized by increased functional connectivity between these regions in the theta frequency band. The results of our study show a consistent pattern of alcohol craving elicited by external cues and internal desires. Given the advantage of superior spatial and temporal resolution, we hypothesize a "central craving network" that integrates the different aspects of alcohol addiction into a unified percept.

Machine Learning Based Classification of Deep Brain Stimulation Outcomes in a Rat Model of Binge Eating Using Ventral Striatal Oscillations

Neuromodulation-based interventions continue to be evaluated across an array of appetitive disorders but broader implementation of these approaches remains limited due to variable treatment outcomes. We hypothesize that individual variation in treatment outcomes may be linked to differences in the networks underlying these disorders. Here, Sprague-Dawley rats received deep brain stimulation separately within each nucleus accumbens (NAc) sub-region (core and shell) using a within-animal crossover design in a rat model of binge eating. Significant reductions in binge size were observed with stimulation of either target but with significant variation in effectiveness across individuals. When features of local field potentials (LFPs) recorded from the NAc were used to classify the pre-defined stimulation outcomes (response or non-response) from each rat using a machine-learning approach (lasso), stimulation outcomes could be classified with greater accuracy than expected by chance (effect sizes: core = 1.13, shell = 1.05). Further, these LFP features could be used to identify the best stimulation target for each animal (core vs. shell) with an effect size = 0.96. These data suggest that individual differences in underlying network activity may relate to the variable outcomes of circuit based interventions, and measures of network activity could have the potential to individually guide the selection of an optimal stimulation target to improve overall treatment response rates.

Food-Related Impulsivity in Obesity and Binge Eating Disorder-A Systematic Update of the Evidence

The specific eating pattern of Binge Eating Disorder (BED) patients has provoked the assumption that BED might represent a phenotype within the obesity spectrum that is characterized by increased impulsivity. Following the guidelines of the PRISMA statement (preferred reporting items for systematic reviews and meta-analyses), we here provide a systematic update on the evidence on food-related impulsivity in obese individuals, with and without BED, as well as normal-weight individuals. We separately analyzed potential group differences in the impulsivity components of reward sensitivity and rash-spontaneous behavior. Our search resulted in twenty experimental studies with high methodological quality. The synthesis of the latest evidence consolidates conclusions drawn in our initial systematic review that BED represents a distinct phenotype within the obesity spectrum that is characterized by increased impulsivity. Rash-spontaneous behavior in general, and specifically towards food, is increased in BED, while food-specific reward sensitivity is also increased in obese individuals without BED, but potentially to a lesser degree. A major next step for research entails the investigation of sub-domains and temporal components of inhibitory control in BED and obesity. Based on the evidence of impaired inhibitory control in BED, affected patients might profit from interventions that address impulsive behavior.

Relation of insulin resistance to neurocognitive function and electroencephalography in obese children

BACKGROUND

Childhood obesity may lead to neuronal impairment in both the peripheral and the central nervous system. This study aimed to investigate the impact of obesity and insulin resistance (IR) on the central nervous system and neurocognitive functions in children.

METHODS

Seventy-three obese children (38 male and 35 female) and 42 healthy children (21 male and 21 female) were recruited. Standard biochemical indices and IR were evaluated. The Wechsler Intelligence Scale for Children-Revised (WISC-R) and electroencephalography (EEG) were administered to all participants. The obese participants were divided into two groups based on the presence or absence of IR, and the data were compared between the subgroups.

RESULTS

Only verbal scores on the WISC-R in the IR+ group were significantly lower than those of the control and IR- groups. There were no differences between the groups with respect to other parameters of the WISC-R or the EEG. Verbal scores of the WISC-R were negatively correlated with obesity duration and homeostatic model assessment-insulin resistance (HOMA-IR) values. EEGs showed significantly more frequent 'slowing during hyperventilation' (SDHs) in obese children than non-obese children.

CONCLUSIONS

Neurocognitive functions, particularly verbal abilities, were impaired in obese children with IR. An early examination of cognitive functions may help identify and correct such abnormalities in obese children.

Electroencephalography Source Functional Connectivity Reveals Abnormal High-Frequency Communication Among Large-Scale Functional Networks in Depression

BACKGROUND

Functional magnetic resonance imaging studies of resting-state functional connectivity have shown that major depressive disorder (MDD) is characterized by increased connectivity within the default mode network (DMN) and between the DMN and the frontoparietal network (FPN). However, much remains unknown about abnormalities in higher frequency (>1 Hz) synchronization. Findings of abnormal synchronization in specific frequencies would contribute to a better understanding of the potential neurophysiological origins of disrupted functional connectivity in MDD.

METHODS

We used the high temporal resolution of electroencephalography to compare the spectral properties of resting-state functional connectivity in individuals with MDD (n = 65) with healthy control subjects (n = 79) and examined the extent to which connectivity disturbances were evident in a third sample of individuals in remission from depression (n = 30). Exact low resolution electromagnetic tomography was used to compute intracortical activity from regions within the DMN and FPN, and functional connectivity was computed using lagged phase synchronization.

RESULTS

Compared to control subjects, the MDD group showed greater within-DMN beta 2 band (18.5-21 Hz) connectivity and greater beta 1 band (12.5-18 Hz) connectivity between the DMN and FPN. This hyperconnectivity was not observed in the remitted MDD group. However, greater beta 1 band DMN-FPN connectivity was associated with more frequent depressive episodes since first depression onset, even after controlling for current symptom severity.

CONCLUSIONS

These findings extend our understanding of the neurophysiological basis of abnormal resting-state functional connectivity in MDD and indicate that elevations in high-frequency DMN-FPN connectivity may be a neural marker linked to a more recurrent illness course.

Increased Alpha Band Functional Connectivity Following the Quadrato Motor Training: A Longitudinal Study

Quadrato Motor Training (QMT) is a new training paradigm, which was found to increase cognitive flexibility, creativity and spatial cognition. In addition, QMT was reported to enhance inter- and intra-hemispheric alpha coherence as well as Fractional Anisotropy (FA) in a number of white matter pathways including corpus callosum. Taken together, these results seem to suggest that electrophysiological and structural changes induced by QMT may be due to an enhanced interplay and communication of the different brain areas within and between the right and the left hemisphere. In order to test this hypothesis using the exact low-resolution brain electromagnetic tomography (eLORETA), we estimated the current neural density and lagged linear connectivity (LLC) of the alpha band in the resting state electroencephalography (rsEEG) recorded with open (OE) and closed eyes (CE) at three different time points, following 6 and 12 weeks of daily QMT. Significant changes were observed for the functional connectivity. In particular, we found that limbic and fronto-temporal alpha connectivity in the OE condition increased after 6 weeks, while it enhanced at the CE condition in occipital network following 12-weeks of daily training. These findings seem to show that the QMT may have dissociable long-term effects on the functional connectivity depending on the different ways of recording rsEEG. OE recording pointed out a faster onset of Linear Lag Connectivity modulations that tend to decay as quickly, while CE recording showed sensible effect only after the complete 3-months training.

The brain, obesity and addiction: an EEG neuroimaging study

Obesity is among the greatest challenges facing healthcare systems with 20% of the world’s population afflicted. Great controversy exists whether obesity can be regarded as an addictive disorder or not. Recently the Yale Food Addiction Scale questionnaire has been developed as a tool to identify individuals with traits of addiction towards food. Using clinical and source localized EEG data we dichotomize obesity. Brain activity in food-addicted and non-food-addicted obese people is compared to alcohol-addicted and non-addicted lean controls. We show that food addiction shares common neural brain activity with alcohol addiction. This ‘addiction neural brain activity’ consists of the dorsal and pregenual anterior cingulate cortex, parahippocampal area and precuneus. Furthermore, common neural obesity neural brain activity exists as well. The ‘obesity neural brain activity’ consists of dorsal and pregenual anterior cingulate cortex, posterior cingulate extending into the precuneus/cuneus as well as the parahippocampal and inferior parietal area. However food-addicted differ from non-food-addicted obese people by opposite activity in the anterior cingulate gyrus. This food addiction and non-food-addiction obesity dichotomy demonstrates there is at least 2 different kinds of obesity with overlapping network activity, but different in anterior cingulate cortex activity.

Childhood trauma in obese and overweight women with food addiction and clinical-level of binge eating

Childhood trauma (CT) is considered a major risk factor for several disorders as well as for the development of eating psychopathology and adult obesity. The main aims of the present study were to assess in overweight and obese women: (i) the independent association between CT and food addiction (FA), and (ii) CT in patients with both FA and clinical-level of binge eating (BE), versus patients who only engage in FA or BE. Participants were 301 overweight and obese women seeking low-energy-diet therapy. All of the patients were administered self-report measures investigating FA, BE, CT, anxiety and depressive symptoms. CT severity was moderately and positively associated with both FA (r=0.37; p<0.001) and BE (r=0.36; p<0.001) severity. The association between FA and CT remained significant after controlling for potential confounding variables. Furthermore, compared to patients without dysfunctional eating patterns, the co-occurrence of FA and BE was associated with more severe CT as well as with more severe psychopathology (i.e., anxiety and depressive symptoms) and higher BMI. Our results suggest that clinicians should carefully assess the presence of CT in individuals who report dysfunctional eating patterns in order to develop treatment approaches specifically for obese and overweight patients with a history of CT.

Neurobiology of KB220Z-Glutaminergic-Dopaminergic Optimization Complex [GDOC] as a Liquid Nano: Clinical Activation of Brain in a Highly Functional Clinician Improving Focus, Motivation and Overall Sensory Input Following Chronic Intake

Background

With neurogenetic and epigenetic tools utilized in research and neuroimaging, we are unraveling the mysteries of brain function, especially as it relates to Reward Deficiency (RDS). We encourage the development of pharmaceuticals or nutraceuticals that promote a reduction in dopamine resistance and balance brain neurochemistry, leading to dopamine homeostasis. We disclose self-assessment of a highly functional professional under work-related stress following KB220Z use, a liquid (aqua) nano glutaminergic-dopaminergic optimization complex (GDOC).

Case presentation

Subject took GDOC for one month. Subject self-administered GDOC using one-half-ounce twice a day. During first three days, unique brain activation occurred; resembling white noise after 30 minutes and sensation was strong for 45 minutes and then dissipated. He described effect as if his eyesight improved slightly and pointed out that his sense of smell and sleep greatly improved. Subject experienced a calming effect similar to meditation that could be linked to dopamine release. He also reported control of going over the edge after a hard day’s work, which was coupled with a slight increase in energy, increased motivation to work, increased focus and multi-tasking, with clearer purpose of task at hand. Subject felt less inhibited in a social setting and suggested Syndrome that GDOC increased his Behavior Activating System (reward), while having a decrease in the Behavior Inhibition System (caution).

Conclusion

These results and other related studies reveal an improved mood, work-related focus, and sleep. These effects as a subjective feeling of brain activation maybe due to direct or indirect dopaminergic interaction. While this case is encouraging, we must await more research in a larger randomized placebo-controlled study to map the role of GDOC, especially in a nano-sized product, to determine the possible effects on circuit inhibitory control and memory banks and the induction of dopamine homeostasis independent of either hypo- or hyper-dopaminergic traits/states.