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      The Open Access Journal of Behavioral Addictions is open for submissions! Learn more and submit at AKJournals.

      Impact factor 6.6 (Q1)    Scopus CiteScore 12.3 (Q1)        Scimago SJR 2.188 (Q1)

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      Web addiction in the brain: Cortical oscillations, autonomic activity, and behavioral measures

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background and aims

          Internet addiction (IA) was recently defined as a disorder tagging both the impulse control and the reward systems. Specifically, inhibitory deficits and reward bias were considered highly relevant in IA. This research aims to examine the electrophysiological correlates and autonomic activity [skin conductance response (SCR) and heart rate] in two groups of young subjects ( N = 25), with high or low IA profile [tested by the Internet Addiction Test (IAT)], with specific reference to gambling behavior.

          Methods

          Oscillatory brain activity (delta, theta, alpha, beta, and gamma) and autonomic and behavioral measures [response times (RTs) and error rates (ERs)] were acquired during the performance of a Go/NoGo task in response to high-rewarding (online gambling videos and video games) or neutral stimuli.

          Results

          A better performance (reduced ERs and reduced RTs) was revealed for high IAT in the case of NoGo trials representing rewarding cues (inhibitory control condition), probably due to a “gain effect” induced by the rewarding condition. In addition, we also observed for NoGo trials related to gambling and video games stimuli that (a) increased low-frequency band (delta and theta) and SCR and (b) a specific lateralization effect (more left-side activity) delta and theta in high IAT.

          Discussion

          Both inhibitory control deficits and reward bias effect were considered to explain IA.

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          Most cited references92

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          Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain.

          R.D Pascual-Marqui, C.M. Michel, D. Lehmann (1994)
          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.
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            Attentional bias in addictive behaviors: a review of its development, causes, and consequences.

            M. Field, W. Cox (2008)
            A wealth of research from the past two decades shows that addictive behaviors are characterized by attentional biases for substance-related stimuli. We review the relevant evidence and present an integration of existing theoretical models to explain the development, causes, and consequences of addiction-related attentional biases. We suggest that through classical conditioning, substance-related stimuli elicit the expectancy of substance availability, and this expectancy causes both attentional bias for substance-related stimuli and subjective craving. Furthermore, attentional bias and craving have a mutual excitatory relationship such that increases in one lead to increases in the other, a process that is likely to result in substance self-administration. Cognitive avoidance strategies, impulsivity, and impaired inhibitory control appear to influence the strength of attentional biases and subjective craving. However, some measures of attentional bias, particularly the addiction Stroop, might reflect multiple underlying processes, so results need to be interpreted cautiously. We make several predictions that require testing in future research, and we discuss implications for the treatment of addictive behaviors.
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              Introduction to behavioral addictions.

              Jon E. Grant, Marc Potenza, Aviv Malkiel Weinstein … (2010)
              Several behaviors, besides psychoactive substance ingestion, produce short-term reward that may engender persistent behavior, despite knowledge of adverse consequences, i.e., diminished control over the behavior. These disorders have historically been conceptualized in several ways. One view posits these disorders as lying along an impulsive-compulsive spectrum, with some classified as impulse control disorders. An alternate, but not mutually exclusive, conceptualization considers the disorders as non-substance or "behavioral" addictions. Inform the discussion on the relationship between psychoactive substance and behavioral addictions. We review data illustrating similarities and differences between impulse control disorders or behavioral addictions and substance addictions. This topic is particularly relevant to the optimal classification of these disorders in the forthcoming fifth edition of the American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders (DSM-V). Growing evidence suggests that behavioral addictions resemble substance addictions in many domains, including natural history, phenomenology, tolerance, comorbidity, overlapping genetic contribution, neurobiological mechanisms, and response to treatment, supporting the DSM-V Task Force proposed new category of Addiction and Related Disorders encompassing both substance use disorders and non-substance addictions. Current data suggest that this combined category may be appropriate for pathological gambling and a few other better studied behavioral addictions, e.g., Internet addiction. There is currently insufficient data to justify any classification of other proposed behavioral addictions. Proper categorization of behavioral addictions or impulse control disorders has substantial implications for the development of improved prevention and treatment strategies.
              Article 0 comments Cited 329 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (pmc): jba
                Journal ID (publisher-id): JBA
                Title: Journal of Behavioral Addictions
                Abbreviated Title: J Behav Addict
                Publisher: Akadémiai Kiadó (Budapest )
                ISSN (Print): 2062-5871
                ISSN (Electronic): 2063-5303
                Publication date (Electronic, epub): 10 July 2017
                Publication date (Print, ppub): September 2017
                Volume: 6
                Issue: 3
                Pages: 334-344
                Affiliations
                [ 1 ]Department of Psychology, Catholic University of the Sacred Heart , Milan, Italy
                [ 2 ]Research Unit in Affective and Social Neuroscience, Department of Psychology, Catholic University of the Sacred Heart , Milan, Italy
                [ 3 ]Laboratoire de Psychologie Médicale et d’Addictologie, ULB Neuroscience Institute (UNI), CHU Brugmann, Université Libre de Bruxelles (ULB) , Brussels, Belgium
                Author notes
                [* ]Corresponding author: Michela Balconi; Department of Psychology, Catholic University of the Sacred Heart, Largo Gemelli 1, Milan 20123, Italy; Phone: +39 2 72342233; Fax: +39 2 72342280; E-mail: michela.balconi@ 123456unicatt.it
                Article
                DOI: 10.1556/2006.6.2017.041
                PMC ID: 5700716
                PubMed ID: 28718301
                SO-VID: fde65ae0-7333-4ce0-bed4-9c8f1add0077
                Copyright © © 2017 The Author(s)
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited.

                History
                Date: 21 March 2017
                Date received : 06 October 2016
                Date revision received : 13 February 2017
                Date: 21 March 2017
                Date: 23 April 2017
                Date accepted : 11 June 2017
                Page count
                Figures: 4, Tables: 0, Equations: 0, References: 89, Pages: 11
                Funding
                Funding sources: None.
                Categories
                Subject: FULL-LENGTH REPORT

                ScienceOpen disciplines: Evolutionary Biology,Medicine,Psychology,Educational research & Statistics,Social & Behavioral Sciences
                Keywords: rewarding,brain oscillations,Internet addiction,autonomic activity,gambling
                Data availability:
                ScienceOpen disciplines: Evolutionary Biology, Medicine, Psychology, Educational research & Statistics, Social & Behavioral Sciences
                Keywords: rewarding, brain oscillations, Internet addiction, autonomic activity, gambling

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