Skip to main content

MINI REVIEW article

Front. Psychol., 30 June 2017
Sec. Psychopathology
This article is part of the Research Topic Binge Drinking in the Adolescent and Young Brain, volume I View all 22 articles

The Burden of Binge and Heavy Drinking on the Brain: Effects on Adolescent and Young Adult Neural Structure and Function

  • 1School of Psychological Science, Oregon State University, Corvallis, OR, United States
  • 2Mental Health Service, VA San Diego Healthcare System, San Diego, CA, United States
  • 3Department of Psychiatry, University of California, San Diego, San Diego, CA, United States

Introduction: Adolescence and young adulthood are periods of continued biological and psychosocial maturation. Thus, there may be deleterious effects of consuming large quantities of alcohol on neural development and associated cognition during this time. The purpose of this mini review is to highlight neuroimaging research that has specifically examined the effects of binge and heavy drinking on adolescent and young adult brain structure and function.

Methods: We review cross-sectional and longitudinal studies of young binge and heavy drinkers that have examined brain structure (e.g., gray and white matter volume, cortical thickness, white matter microstructure) and investigated brain response using functional magnetic resonance imaging (fMRI).

Results: Binge and heavy-drinking adolescents and young adults have systematically thinner and lower volume in prefrontal cortex and cerebellar regions, and attenuated white matter development. They also show elevated brain activity in fronto-parietal regions during working memory, verbal learning, and inhibitory control tasks. In response to alcohol cues, relative to controls or light-drinking individuals, binge and heavy drinkers show increased neural response mainly in mesocorticolimbic regions, including the striatum, anterior cingulate cortex (ACC), hippocampus, and amygdala. Mixed findings are present in risky decision-making tasks, which could be due to large variation in task design and analysis.

Conclusions: These findings suggest altered neural structure and activity in binge and heavy-drinking youth may be related to the neurotoxic effects of consuming alcohol in large quantities during a highly plastic neurodevelopmental period, which could result in neural reorganization, and increased risk for developing an alcohol use disorder (AUD).

Introduction

Magnetic resonance imaging (MRI) studies have highlighted ongoing brain maturation through young adulthood (Gogtay et al., 2004). Decreases in cortical gray matter (GM) from ages 10–12 through adulthood have been attributed to synaptic pruning, a process that prioritizes efficiency and strengthening of connections via proliferation of myelin over the creation of new synaptic connections that occurs in childhood (Amlien et al., 2016). White matter (WM) volume increases linearly through young adulthood, which yields relatively stable total brain volumes after puberty (Giedd et al., 2009). This period of significant cortical modification coincides with increases in behavioral risk taking including the use of alcohol and other substances.

Alcohol use has negative effects on cognition and the brain (Jacobus and Tapert, 2013) and on health and safety (Nhtsa, 2014), yet drinking in high quantities increases during adolescence as nearly 25% of high school seniors report getting drunk in the last 30 days (Johnston et al., 2017). Binge or heavy episodic drinking (i.e., 4 or more standard drinks within a 2 h drinking session for females, 5 or more drinks for males) (NIAAA, 2004)1 leads to increased risk for negative acute effects, such as drunk driving, unsafe sex, and other substance use (Miller et al., 2007). Long-term, adolescent alcohol use is related to serious psychosocial problems, including comorbid psychopathology (Deas and Thomas, 2002), poorer academic success (Kristjansson et al., 2013), and detrimental neurocognitive consequences (Jacobus and Tapert, 2013). Furthermore, binge drinking patterns initiated during late adolescence often persist into early adulthood (Degenhardt et al., 2013) and initiating heavy drinking at an early age significantly increases risk for subsequent adult alcohol use disorders (AUD) and related problems (Hingson et al., 2006).

Given the increase of binge and heavy drinking during adolescence when protracted brain maturation is still underway, understanding the potentially harmful effects of consuming large quantities of alcohol on neural development and associated cognition is of central importance. The purpose of this mini review is to highlight associations that may reflect deleterious effects of binge drinking and also to inform future investigations into the effects of binge drinking on brain development and functioning in young binge/heavy episodic drinkers (BD/HD). Thus, we excluded samples based on diagnostic criteria (e.g., alcohol abuse or AUD), treatment studies, and those that characterized drinking based on non-binge or heavy-drinking criteria (e.g., lifetime alcohol use days).

Structural Brain Imaging

Structural MRI assesses the metrics (e.g., thickness, surface area, and volume) of specific brain tissues at the macrostructure level. Additional techniques utilize the diffusion of water molecules [e.g., diffusion tensor imaging (DTI)] to characterize the microstructure of GM and WM. The majority of studies present cross-sectional data using retrospective reports of drinking experience, while a few recent studies have reported longitudinal changes in brain structure associated with binge drinking (Table 1).

TABLE 1
www.frontiersin.org

Table 1. Structural MRI findings in binge/heavy-drinking adolescents and young adults.

GM and WM Macrostructure

Several cross-sectional studies have examined brain structure and binge and heavy-drinking histories of varying lengths in young drinkers, and the majority have highlighted regions of interest where alcohol-related deficits have been identified in chronic alcoholics (Pfefferbaum et al., 1998). Many studies report smaller volumes or thinner tissue distributed across neocortical regions primarily in frontal cortices, but also in temporal and parietal cortices (see Table 1). For example, a study that followed drinking patterns of young adults for 10 years reported HD exhibited reduced GM volume in the anterior cingulate cortex (ACC), orbitofrontal cortex (OFC), temporal gyrus, and insular cortex compared to light drinkers (LD) (Heikkinen et al., 2017). One study targeting the ACC also reported decreased cortical thickness among BD compared to LD (Mashhoon et al., 2014), while another study found that BD exhibited larger ACC volumes (Doallo et al., 2014). A large cross-sectional study reported that BD (n = 134) exhibited smaller volumes and thinner cortical tissue in total, frontal, and temporal GM as well as thinner cingulate cortex compared to controls (n = 674). In addition, within the BD group the number of binges in the previous year was negatively related to frontal and parietal cortical thickness (Pfefferbaum et al., 2016).

Subcortical regions including the hippocampus, diencephalon, cerebellum and brain stem also exhibit decreased volume among BD. For example, smaller left hippocampal volume in conjunction with greater hippocampal asymmetry in BD compared to controls has been found (Medina et al., 2007). Other studies reported brain stem volumes were smaller in HD compared to LD (Squeglia et al., 2014), and binge drinking episodes were inversely related to cerebellar volume (Lisdahl et al., 2013). Conversely, one study reported increased volume in the ventral striatum and thalamus among BD compared to controls (Howell et al., 2013). Interestingly, two studies found no differences between BD compared to controls/LD, but discovered a BD by sex interaction such that male BD exhibited smaller volumes compared to male controls/LD in several frontal, temporal, and subcortical regions, while female BD had larger volumes than female controls/LD in the same regions (Squeglia et al., 2012b; Kvamme et al., 2016).

Two longitudinal studies were able to examine structural MRI changes in adolescents who had a pre-drinking baseline measure. One reported greater-than-expected decline in cortical thickness in the middle frontal gyrus (MFG) associated with the onset of binge drinking (Luciana et al., 2013), as well as greater increases in several distributed WM regions over 2 years in non-drinkers compared to BD (Luciana et al., 2013). In a larger sample similar accelerated declines in frontal and temporal cortical volumes in BD and slower increases in WM were reported (Squeglia et al., 2015). A co-twin study attempted to parse out effects of drinking from genetic (or other) pre-existing vulnerabilities by examining co-twin deviations, and reported that reduced volume of the ventral diencephalon and middle temporal gyrus could be attributed to drinking, while reduced volume of the right amygdala and increased volume of the left cerebellum appeared to be pre-existing vulnerability for the onset of drinking (Wilson et al., 2015).

Taken together, binge drinking appears to be largely associated with decreased volume and accelerated thinning in the frontal and prefrontal cortices and slowing of expected WM increases. Allocortical and subcortical regions may reflect some specific positive associations with binge drinking (e.g., ventral striatum), and there is some evidence that male and female BD may exhibit an inverse relationship in some frontal and subcortical regions.

GM and WM Microstructure

Among alcohol dependent adults WM integrity tends to be weakened (Pfefferbaum et al., 2006), but fewer studies have examined the effects of binge drinking on WM and GM microstructure (see Table 1). Each study among non-dependent BD has reported WM integrity deficits compared to LD/controls across the majority of WM tracts (Jacobus et al., 2009; Mcqueeny et al., 2009; Bava et al., 2013). Longitudinal studies also support decreased WM integrity among individuals who initiate or increase binge drinking, showing additional declines in fractional anisotropy over time (Jacobus et al., 2013; Luciana et al., 2013). A recent study examining both GM and WM microstructure utilizing orientation dispersion index (ODI) reported that BD had lower ODI in frontal GM but higher ODI in parietal GM and in the ventral striatum (Morris et al., 2017). Thus, overall it appears that binge drinking is associated with decreased WM microstructural integrity, but may be selectively related to increases in microstructural GM in a brain region associated with reward seeking.

Functional Magnetic Resonance Imaging (fMRI)

As structural abnormalities have been related to heavy alcohol use during neuromaturation, it is important to understand whether these findings translate to alterations in the functioning of brain systems across different cognitive domains. We discuss six areas that have included studies of BD/HD: response inhibition, working memory, verbal learning and memory, decision making and reward processing, alcohol cue reactivity, and socio-cognitive/socio-emotional processing (Table 2). Further, in order to focus this section of the mini review on task-related functional magnetic resonance imaging (fMRI) studies, we excluded discussion of functional connectivity (Gorka et al., 2013; Weiland et al., 2014; Morris et al., 2016), acute alcohol administration (Filbey et al., 2008), machine learning (Squeglia et al., 2017), treatment (Feldstein Ewing et al., 2016), and neurofeedback (Kirsch et al., 2016) studies that included young BD/HD, as well as studies where binge drinking was examined, but was not the main variable of interest (Glaser et al., 2014).

TABLE 2
www.frontiersin.org

Table 2. fMRI findings in binge/heavy-drinking adolescents and young adults.

Response Inhibition

The ability to inhibit a pre-potent response or have self-control over impulsive actions is a central facet of executive functioning (Diamond, 2013). Several studies have identified deficits in response inhibition and its neural correlates in individuals with AUD (Lawrence et al., 2009), and these investigations have extended to adolescent and young adult BD/HD, most of which have used Go/NoGo tasks. For example, in a study of 18–20 year old college students, HD showed slower reaction times on both correct Go hits and incorrect NoGo false alarms (Ahmadi et al., 2013). LD had greater response in ACC, supplementary motor area (SMA), MFG, parietal lobe, hippocampus, and superior temporal gyrus (STG) than HD during NoGo correct rejections, suggesting decreased inhibitory control brain activity in HD in a set of brain regions that underlie cognitive and impulse control (Ahmadi et al., 2013).

Variations of the Go/NoGo task have used alcohol-related images as NoGo stimuli and non-alcoholic beverages as Go stimuli. Ames et al. (2014) demonstrated that compared with HD, LD had better Go/NoGo task performance as indexed by d-prime. HD had greater activity in the dorsolateral prefrontal cortex (DLPFC), ACC, and the anterior insula than LD during NoGo trials, suggesting greater reliance on executive functioning, error monitoring, and emotional interoception regions during inhibitory control (Ames et al., 2014). Another task presented the traditional letters used in Go/NoGo tasks overlaid onto black, neutral picture, and alcoholic photo backgrounds. While there were no effects of background context, college HD displayed greater activity in visual and emotional processing regions, such as the amygdala and occipital lobe during failed inhibitions compared with LD (Campanella et al., 2016).

In one longitudinal investigation, HD had greater fronto-parietal and cerebellar activity during response inhibition relative to controls at follow-up but reduced activity in these same regions at baseline, suggesting both markers of vulnerability toward heavy drinking and altered executive functioning activity after the initiation of heavy alcohol use (Wetherill et al., 2013). Task-related fMRI studies have largely reported that HD/BD have increased fronto-parietal and cerebellar response during successful inhibitory control and increased emotional and visual response during unsuccessful response inhibition (except for Ahmadi et al., 2013).

Working Memory

Another key component of executive functioning is working memory (WrkM), the ability to maintain and manipulate information during a short time span (Diamond, 2013). WrkM has been linked with adaptive decision making and deficits in WrkM are associated with vulnerability toward addiction (Nagel et al., 2012). An fMRI n-back task of WrkM was completed by university BD, who showed larger pre-SMA WrkM-related activity than controls, suggesting greater attentional resources devoted to performing the task by the BD to maintain equal performance with the control group (Campanella et al., 2013).

Some studies have reported that sex differences may also be present in WrkM-related activation between male and female BD. Female BD had less spatial WrkM activation in several frontal, temporal, and cerebellar regions compared to female controls and this was linked to poor behavioral performance in the BD, a pattern opposite to what was seen in male BD relative to male controls (Squeglia et al., 2011). The authors argue that this may suggest female vulnerability toward the neurotoxic effects of binge drinking during active periods of neuromaturation.

While longitudinal research is sparse among fMRI studies of BD/HD youth, one study reported reduced baseline fronto-parietal activity in adolescents who later transitioned into heavy drinking. However, HD showed significantly increased activity in these areas at a 3-year follow-up relative to baseline brain response (Squeglia et al., 2012a). Overall, these studies suggest mostly greater WrkM-related brain activity across fronto-parietal regions in BD/HD relative to controls, but some exceptions may be present when examining sex differences and pre-drinking vulnerability.

Learning and Memory

Deficits in learning and memory have been previously reported in individuals with AUD (Pitel et al., 2014), and in investigations of BD youth (Carbia et al., 2017). In the first of three studies examining neural response during verbal or figural encoding, Schweinsburg et al. (2010) found that while learning novel word pairs, BD showed elevated superior frontal and posterior parietal activity compared with controls, a finding that was closely replicated in a subsequent study where BD had greater fronto-parietal activity during novel encoding, with some areas displaying reduced activity relative to controls, such as the inferior frontal gyrus (IFG), precuneus, and ACC (Schweinsburg et al., 2011). These findings suggest some degree of neural reorganization in BD that results in increased reliance on fronto-parietal regions while learning novel word pairs, and decreased activity in other regions.

Pictorial as opposed to verbal stimuli were used in a study of college HD who demonstrated similar patterns of brain activity to previous studies of adolescents, namely greater fronto-parietal activity during encoding of novel stimuli, as well as greater hippocampal response relative to LD (Dager et al., 2014b). This study also examined brain activity associated with recognition for the first time, and found less insular activity during correct recognition in HD vs. LD, a finding the authors believed could reflect less arousal during correct recognition or a different task approach that resulted in similar task performance (Dager et al., 2014b).

Decision Making and Reward Processing

A number of studies have investigated the neural correlates of risky decision making and reward processing across monetary decision making tasks in young BD. A study using the Iowa Gambling Task found that compared with their peers, adolescent BD had greater insular and amygdala activity, suggesting greater emotion-driven decision making in the BD (Xiao et al., 2013), but this task did not permit the dissociation of decision making-related activation from reward processing. A subsequent longitudinal study used a modified Wheel of Fortune Task, in which BD showed reduced dorsal striatum activity during risky vs. safe decision making, and similar to previous studies, reductions in fronto-parietal activity preceded the onset of heavy drinking (Jones et al., 2016). It is possible that feedback during risk taking could modify behavior and cognitive control as young adult BD decreased their risk taking when they were presented with information about potential monetary losses, and this was associated with increased recruitment of IFG (Worbe et al., 2014). Finally, processing of reward receipt was related to decreased cerebellar activity in a longitudinal study of BD, suggesting blunted reward and affect-related responses as a result of heavy episodic drinking (Cservenka et al., 2015). Based on these results, a general pattern that is emerging is related to alterations in cognitive control and emotional processing brain regions that may be modifiable when feedback about the consequences of risk taking are presented.

Alcohol Cue Reactivity

Alcohol cue reactivity studies have found greater neural response in reward and emotional processing brain regions among individuals with AUD (Heinz et al., 2009). Alterations in motivational neurocircuitry are associated with AUD (Koob and Volkow, 2010) and have thus been investigated in young adult and adolescent BD/HD. Dager et al. (2013) reported that young adult HD had greater neural activity in response to alcohol-related images in widespread areas comprised of limbic, visual, frontal, and insular regions compared with LD. Further, in a task where participants were instructed not to focus on alcohol cues, ventral tegmental area activation was elevated in young adult HD compared with neural response seen to soft drink cues, suggesting automatic processing of alcohol-related stimuli that may increase motivational drive in mesolimbic circuitry (Kreusch et al., 2015). Interestingly, response to alcohol cues may be used to predict drinking behavior in young adult HD as those who showed elevated response in fronto-striatal areas and the insula subsequently transitioned into heavy drinking (Dager et al., 2014a). A longitudinal study of adolescent HD showed that increased brain activity to alcohol cues in HD vs. controls diminishes with abstinence from alcohol, indicating that a decline in risky drinking may modify brain activity in response to alcohol-related stimuli (Brumback et al., 2015). Across these studies, there is evidence that mesolimbic and motivational circuitry may be important targets for studies designed to reduce response to alcohol cues in adolescent and young adult HD.

Socio-Cognitive and Socio-Emotional Processing

Research on the effects of binge and heavy drinking on the developing brain are limited in other domains, such as socio-cognitive and socio-emotional processing. While recent meta-analyses highlight deficits in social cognition in individuals with AUD (Onuoha et al., 2016; Bora and Zorlu, 2017), there are a lack of fMRI studies in this area within young BD/HD. In one study, young adult BD categorizing vocal affective stimuli had less activity in STG, but more activity in MFG compared with their peers (Maurage et al., 2013). Given the large gap in the literature specifically focused on socio-cognitive processing in young BD/HD, future research should further investigate this domain.

Conclusions

Binge drinking among youth is associated with smaller/thinner cortical and subcortical structures and decreased WM integrity. Consistent across many fMRI studies of cognitive control, WrkM, and verbal learning, young BD and HD show greater reliance on fronto-parietal systems while performing these tasks (Schweinsburg et al., 2010, 2011; Squeglia et al., 2012a; Wetherill et al., 2013; Dager et al., 2014b). Executive functioning and emotional processing systems are important networks for future investigations related to decision making and reward processing (Xiao et al., 2013; Worbe et al., 2014; Cservenka et al., 2015; Jones et al., 2016), while mesolimbic circuitry is likely involved in the elevated response to alcohol cues in young BD/HD (Dager et al., 2013, 2014a; Brumback et al., 2015; Kreusch et al., 2015). These findings suggest there may be neural alterations as a result of heavy alcohol use or neural risk markers related to vulnerability toward heavy drinking during adolescence and young adulthood. While some findings have been replicated, greater efforts are needed for consistency across task variations, analyses reported, inclusionary criteria for BD/HD, as well as longitudinal studies of this topic.

Author Contributions

AC conducted literature searches, wrote, edited, and revised the section on fMRI findings, wrote the conclusions, and created the table of fMRI findings. TB conducted literature searches, wrote, edited, and revised the section on structural MRI findings, wrote the introduction, and created the table of MRI structural findings. AC edited the final version of the manuscript and wrote the abstract.

Funding

AC was supported by the Oregon Health & Science University Medical Research Foundation New Investigator Grant and TB was supported by the VA Office of Academic Affiliation during the preparation of this manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

1. ^While the definition of a standard drink differs by location outside of the United States (Mongan and Long, 2015). binge drinking episodes result in blood alcohol concentrations (BAC) near.08 gram percent (i.e., minimum of 2–3 ounces or 60–85 grams of pure alcohol).

References

Ahmadi, A., Pearlson, G. D., Meda, S. A., Dager, A., Potenza, M. N., Rosen, R., et al. (2013). Influence of alcohol use on neural response to Go/No-Go task in college drinkers. Neuropsychopharmacology 38, 2197–2208. doi: 10.1038/npp.2013.119

PubMed Abstract | CrossRef Full Text | Google Scholar

Ames, S. L., Wong, S. W., Bechara, A., Cappelli, C., Dust, M., Grenard, J. L., et al. (2014). Neural correlates of a Go/NoGo task with alcohol stimuli in light and heavy young drinkers. Behav. Brain Res. 274, 382–389. doi: 10.1016/j.bbr.2014.08.039

PubMed Abstract | CrossRef Full Text | Google Scholar

Amlien, I. K., Fjell, A. M., Tamnes, C. K., Grydeland, H., Krogsrud, S. K., Chaplin, T. A., et al. (2016). Organizing principles of human cortical development–thickness and area from 4 to 30 years: insights from comparative primate neuroanatomy. Cereb. Cortex 26, 257–267. doi: 10.1093/cercor/bhu214

PubMed Abstract | CrossRef Full Text | Google Scholar

Banca, P., Lange, I., Worbe, Y., Howell, N. A., Irvine, M., Harrison, N. A., et al. (2016). Reflection impulsivity in binge drinking: behavioural and volumetric correlates. Addict. Biol. 21, 504–515. doi: 10.1111/adb.12227

PubMed Abstract | CrossRef Full Text | Google Scholar

Bava, S., Jacobus, J., Thayer, R. E., and Tapert, S. F. (2013). Longitudinal changes in white matter integrity among adolescent substance users. Alcohol. Clin. Exp. Res. 37, E181–E189. doi: 10.1111/j.1530-0277.2012.01920.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Bora, E., and Zorlu, N. (2017). Social cognition in alcohol use disorder: a meta-analysis. Addiction 112, 40–48. doi: 10.1111/add.13486

PubMed Abstract | CrossRef Full Text | Google Scholar

Brumback, T., Squeglia, L. M., Jacobus, J., Pulido, C., Tapert, S. F., and Brown, S. A. (2015). Adolescent heavy drinkers' amplified brain responses to alcohol cues decrease over one month of abstinence. Addict. Behav. 46, 45–52. doi: 10.1016/j.addbeh.2015.03.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Campanella, S., Absil, J., Carbia Sinde, C., Schroder, E., Peigneux, P., Bourguignon, M., et al. (2016). Neural correlates of correct and failed response inhibition in heavy versus light social drinkers: an fMRI study during a go/no-go task by healthy participants. Brain Imaging Behav. doi: 10.1007/s11682-016-9654-y. [Epub ahead of print].

CrossRef Full Text | Google Scholar

Campanella, S., Peigneux, P., Petit, G., Lallemand, F., Saeremans, M., Noel, X., et al. (2013). Increased cortical activity in binge drinkers during working memory task: a preliminary assessment through a functional magnetic resonance imaging study. PLoS ONE 8:e62260. doi: 10.1371/journal.pone.0062260

PubMed Abstract | CrossRef Full Text | Google Scholar

Carbia, C., Cadaveira, F., Caamano-Isorna, F., Rodriguez-Holguin, S., and Corral, M. (2017). Binge drinking during adolescence and young adulthood is associated with deficits in verbal episodic memory. PLoS ONE 12:e0171393. doi: 10.1371/journal.pone.0171393

PubMed Abstract | CrossRef Full Text | Google Scholar

Cservenka, A., Jones, S. A., and Nagel, B. J. (2015). Reduced cerebellar brain activity during reward processing in adolescent binge drinkers. Dev. Cogn. Neurosci. 16, 110–120. doi: 10.1016/j.dcn.2015.06.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Dager, A. D., Anderson, B. M., Rosen, R., Khadka, S., Sawyer, B., Jiantonio-Kelly, R. E., et al. (2014a). Functional magnetic resonance imaging (fMRI) response to alcohol pictures predicts subsequent transition to heavy drinking in college students. Addiction 109, 585–595. doi: 10.1111/add.12437

PubMed Abstract | CrossRef Full Text | Google Scholar

Dager, A. D., Anderson, B. M., Stevens, M. C., Pulido, C., Rosen, R., Jiantonio-Kelly, R. E., et al. (2013). Influence of alcohol use and family history of alcoholism on neural response to alcohol cues in college drinkers. Alcohol. Clin. Exp. Res. 37(Suppl. 1), E161–E171. doi: 10.1111/j.1530-0277.2012.01879.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Dager, A. D., Jamadar, S., Stevens, M. C., Rosen, R., Jiantonio-Kelly, R. E., Sisante, J. F., et al. (2014b). fMRI response during figural memory task performance in college drinkers. Psychopharmacology (Berl) 231, 167–179. doi: 10.1007/s00213-013-3219-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Deas, D., and Thomas, S. (2002). Comorbid psychiatric factors contributing to adolescent alcohol and other drug use. Alcohol Res. Health 26, 116–121. Available online at: https://pubs.niaaa.nih.gov/publications/arh26-2/116-121.htm

Google Scholar

Degenhardt, L., O'loughlin, C., Swift, W., Romaniuk, H., Carlin, J., Coffey, C., et al. (2013). The persistence of adolescent binge drinking into adulthood: findings from a 15-year prospective cohort study. BMJ Open 3:e003015. doi: 10.1136/bmjopen-2013-003015

PubMed Abstract | CrossRef Full Text | Google Scholar

Diamond, A. (2013). Executive functions. Annu. Rev. Psychol. 64, 135–168. doi: 10.1146/annurev-psych-113011-143750

PubMed Abstract | CrossRef Full Text | Google Scholar

Doallo, S., Cadaveira, F., Corral, M., Mota, N., López-Caneda, E., and Holguín, S. R. (2014). Larger mid-dorsolateral prefrontal gray matter volume in young binge drinkers revealed by voxel-based morphometry. PLoS ONE 9:e96380. doi: 10.1371/journal.pone.0096380

PubMed Abstract | CrossRef Full Text | Google Scholar

Feldstein Ewing, S. W., Houck, J. M., Yezhuvath, U., Shokri-Kojori, E., Truitt, D., and Filbey, F. M. (2016). The impact of therapists' words on the adolescent brain: in the context of addiction treatment. Behav. Brain Res. 297, 359–369. doi: 10.1016/j.bbr.2015.09.041

PubMed Abstract | CrossRef Full Text | Google Scholar

Filbey, F. M., Claus, E., Audette, A. R., Niculescu, M., Banich, M. T., Tanabe, J., et al. (2008). Exposure to the taste of alcohol elicits activation of the mesocorticolimbic neurocircuitry. Neuropsychopharmacology 33, 1391–1401. doi: 10.1038/sj.npp.1301513

PubMed Abstract | CrossRef Full Text | Google Scholar

Giedd, J. N., Lalonde, F. M., Celano, M. J., White, S. L., Wallace, G. L., Lee, N. R., et al. (2009). Anatomical brain magnetic resonance imaging of typically developing children and adolescents. J. Am. Acad. Child Adolesc. Psychiatry 48, 465–470. doi: 10.1097/CHI.0b013e31819f2715

PubMed Abstract | CrossRef Full Text | Google Scholar

Glaser, Y. G., Zubieta, J. K., Hsu, D. T., Villafuerte, S., Mickey, B. J., Trucco, E. M., et al. (2014). Indirect effect of corticotropin-releasing hormone receptor 1 gene variation on negative emotionality and alcohol use via right ventrolateral prefrontal cortex. J. Neurosci. 34, 4099–4107. doi: 10.1523/JNEUROSCI.3672-13.2014

PubMed Abstract | CrossRef Full Text | Google Scholar

Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., et al. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proc. Natl. Acad. Sci. U.S.A. 101, 8174–8179. doi: 10.1073/pnas.0402680101

PubMed Abstract | CrossRef Full Text | Google Scholar

Gorka, S. M., Fitzgerald, D. A., King, A. C., and Phan, K. L. (2013). Alcohol attenuates amygdala-frontal connectivity during processing social signals in heavy social drinkers: a preliminary pharmaco-fMRI study. Psychopharmacology (Berl) 229, 141–154. doi: 10.1007/s00213-013-3090-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Heikkinen, N., Niskanen, E., Könönen, M., Tolmunen, T., Kekkonen, V., Kivimäki, P., et al. (2017). Alcohol consumption during adolescence is associated with reduced grey matter volumes. Addiction 112, 604–613. doi: 10.1111/add.13697

PubMed Abstract | CrossRef Full Text | Google Scholar

Heinz, A., Beck, A., Grusser, S. M., Grace, A. A., and Wrase, J. (2009). Identifying the neural circuitry of alcohol craving and relapse vulnerability. Addict. Biol. 14, 108–118. doi: 10.1111/j.1369-1600.2008.00136.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Hingson, R. W., Heeren, T., and Winter, M. R. (2006). Age at drinking onset and alcohol dependence: age at onset, duration, and severity. Arch. Pediatr. Adolesc. Med. 160, 739–746. doi: 10.1001/archpedi.160.7.739

PubMed Abstract | CrossRef Full Text | Google Scholar

Howell, N. A., Worbe, Y., Lange, I., Tait, R., Irvine, M., Banca, P., et al. (2013). Increased ventral striatal volume in college-aged binge drinkers. PLoS ONE 8:e74164. doi: 10.1371/journal.pone.0074164

PubMed Abstract | CrossRef Full Text | Google Scholar

Jacobus, J., Mcqueeny, T., Bava, S., Schweinsburg, B. C., Frank, L. R., Yang, T. T., et al. (2009). White matter integrity in adolescents with histories of marijuana use and binge drinking. Neurotoxicol. Teratol. 31, 349–355. doi: 10.1016/j.ntt.2009.07.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Jacobus, J., Squeglia, L. M., Bava, S., and Tapert, S. F. (2013). White matter characterization of adolescent binge drinking with and without co-occurring marijuana use: a 3-year investigation. Psychiatry Res. 214, 374–381. doi: 10.1016/j.pscychresns.2013.07.014

PubMed Abstract | CrossRef Full Text | Google Scholar

Jacobus, J., and Tapert, S. F. (2013). Neurotoxic effects of alcohol in adolescence. Annu. Rev. Clin. Psychol. 9, 703–721. doi: 10.1146/annurev-clinpsy-050212-185610

PubMed Abstract | CrossRef Full Text | Google Scholar

Johnston, L. D., O'malley, P. M., Miech, R. A., Bachman, J. G., and Schulenberg, J. E. (2017). Monitoring the Future National Survey Results on Drug Use, 1975-2016: Overview, Key Findings on Adolescent Drug Use. (Ann Arbor, MI: Institute for Social Research, The University of Michigan).

Jones, S. A., Cservenka, A., and Nagel, B. J. (2016). Binge drinking impacts dorsal striatal response during decision making in adolescents. Neuroimage 129, 378–388. doi: 10.1016/j.neuroimage.2016.01.044

PubMed Abstract | CrossRef Full Text | Google Scholar

Kirsch, M., Gruber, I., Ruf, M., Kiefer, F., and Kirsch, P. (2016). Real-time functional magnetic resonance imaging neurofeedback can reduce striatal cue-reactivity to alcohol stimuli. Addict. Biol. 21, 982–992. doi: 10.1111/adb.12278

PubMed Abstract | CrossRef Full Text | Google Scholar

Koob, G. F., and Volkow, N. D. (2010). Neurocircuitry of addiction. Neuropsychopharmacology 35, 217–238. doi: 10.1038/npp.2009.110

PubMed Abstract | CrossRef Full Text | Google Scholar

Kreusch, F., Goffaux, V., Siep, N., Houben, K., Quertemont, E., and Wiers, R. W. (2015). Brain activation associated with automatic processing of alcohol-related cues in young heavy drinkers and its modulation by alcohol administration. Alcohol. Clin. Exp. Res. 39, 1957–1966. doi: 10.1111/acer.12835

PubMed Abstract | CrossRef Full Text | Google Scholar

Kristjansson, A. L., Sigfusdottir, I. D., and Allegrante, J. P. (2013). Adolescent substance use and peer use: a multilevel analysis of cross-sectional population data. Subst. Abuse Treat. Prev. Policy 8:27. doi: 10.1186/1747-597X-8-27

PubMed Abstract | CrossRef Full Text | Google Scholar

Kvamme, T. L., Schmidt, C., Strelchuk, D., Chang-Webb, Y. C., Baek, K., and Voon, V. (2016). Sexually dimorphic brain volume interaction in college-aged binge drinkers. NeuroImage Clin. 10, 310–317. doi: 10.1016/j.nicl.2015.12.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Lawrence, A. J., Luty, J., Bogdan, N. A., Sahakian, B. J., and Clark, L. (2009). Impulsivity and response inhibition in alcohol dependence and problem gambling. Psychopharmacology (Berl) 207, 163–172. doi: 10.1007/s00213-009-1645-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Lisdahl, K. M., Thayer, R., Squeglia, L. M., Mcqueeny, T. M., and Tapert, S. F. (2013). Recent binge drinking predicts smaller cerebellar volumes in adolescents. Psychiatry Res. 211, 17–23. doi: 10.1016/j.pscychresns.2012.07.009

PubMed Abstract | CrossRef Full Text | Google Scholar

Luciana, M., Collins, P. F., Muetzel, R. L., and Lim, K. O. (2013). Effects of alcohol use initiation on brain structure in typically developing adolescents. Am. J. Drug Alcohol Abuse 39, 345–355. doi: 10.3109/00952990.2013.837057

PubMed Abstract | CrossRef Full Text | Google Scholar

Mashhoon, Y., Czerkawski, C., Crowley, D. J., Cohen-Gilbert, J. E., Sneider, J. T., and Silveri, M. M. (2014). Binge alcohol consumption in emerging adults: anterior cingulate cortical “thinness” is associated with alcohol use patterns. Alcohol. Clin. Exp. Res. 38, 1955–1964. doi: 10.1111/acer.12475

PubMed Abstract | CrossRef Full Text | Google Scholar

Maurage, P., Bestelmeyer, P. E., Rouger, J., Charest, I., and Belin, P. (2013). Binge drinking influences the cerebral processing of vocal affective bursts in young adults. Neuroimage Clin. 3, 218–225. doi: 10.1016/j.nicl.2013.08.010

PubMed Abstract | CrossRef Full Text | Google Scholar

Mcqueeny, T., Schweinsburg, B. C., Schweinsburg, A. D., Jacobus, J., Bava, S., Frank, L. R., et al. (2009). Altered white matter integrity in adolescent binge drinkers. Alcohol. Clin. Exp. Res. 33, 1278–1285. doi: 10.1111/j.1530-0277.2009.00953.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Medina, K. L., Schweinsburg, A. D., Cohen-Zion, M., Nagel, B. J., and Tapert, S. F. (2007). Effects of alcohol and combined marijuana and alcohol use during adolescence on hippocampal volume and asymmetry. Neurotoxicol. Teratol. 29, 141–152. doi: 10.1016/j.ntt.2006.10.010

PubMed Abstract | CrossRef Full Text | Google Scholar

Miller, J. W., Naimi, T. S., Brewer, R. D., and Jones, S. E. (2007). Binge drinking and associated health risk behaviors among high school students. Pediatrics 119, 76–85. doi: 10.1542/peds.2006-1517

PubMed Abstract | CrossRef Full Text | Google Scholar

Mongan, D., and Long, J. (2015). Standard Drink Measures Throughout Europe: Peoples' Understanding of Standard Drinks and Their Use in Drinking Guidelines, Alcohol Surveys and Labelling, ed H. R. Board (Dublin: Health Research Board).

Morris, L. S., Dowell, N. G., Cercignani, M., Harrison, N. A., and Voon, V. (2017). Binge drinking differentially affects cortical and subcortical microstructure. Addict. Biol. doi: 10.1111/adb.12493. [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

Morris, L. S., Kundu, P., Baek, K., Irvine, M. A., Mechelmans, D. J., Wood, J., et al. (2016). Jumping the gun: mapping neural correlates of waiting impulsivity and relevance across alcohol misuse. Biol. Psychiatry 79, 499–507. doi: 10.1016/j.biopsych.2015.06.009

PubMed Abstract | CrossRef Full Text | Google Scholar

NIAAA (2004). “NIAAA Council approves definition of binge drinking,” in NIAAA Newsletter, ed G. Roa (Bethesda, MD: Office of Research Translation and Communications, NIAAA, NIH, DHHS), 3.

Nhtsa (2014). Traffic Safety Facts 2013: Alcohol-Impaired Driving. Available online at: http://www-nrd.nhtsa.dot.gov/Pubs/812102.pdf.

Nagel, B. J., Herting, M. M., and Cservenka, A. (2012). “Working Memory and Addictive Behavior,” in Working Memory: The Connected Intelligence, eds T. P. Alloway and R. G. Alloway (East Sussex: Psychology Press), 187–206.

Google Scholar

Onuoha, R. C., Quintana, D. S., Lyvers, M., and Guastella, A. J. (2016). A meta-analysis of theory of mind in alcohol use disorders. Alcohol Alcohol. 51, 410–415. doi: 10.1093/alcalc/agv137

PubMed Abstract | CrossRef Full Text | Google Scholar

Pfefferbaum, A., Adalsteinsson, E., and Sullivan, E. V. (2006). Dysmorphology and microstructural degradation of the corpus callosum: interaction of age and alcoholism. Neurobiol. Aging 27, 994–1009. doi: 10.1016/j.neurobiolaging.2005.05.007

PubMed Abstract | CrossRef Full Text | Google Scholar

Pfefferbaum, A., Rohlfing, T., Pohl, K. M., Lane, B., Chu, W., Kwon, D., et al. (2016). Adolescent development of cortical and white matter structure in the NCANDA sample: role of sex, ethnicity, puberty, and alcohol drinking. Cereb. Cortex 26, 4101–4121. doi: 10.1093/cercor/bhv205

PubMed Abstract | CrossRef Full Text | Google Scholar

Pfefferbaum, A., Sullivan, E., Rosenbloom, M. J., Mathalon, D. H., and Lim, K. O. (1998). A controlled study of cortical gray matter and ventricular changes in alcoholic men over a five year interval. Arch. Gen. Psychiatry 55, 905–912. doi: 10.1001/archpsyc.55.10.905

CrossRef Full Text | Google Scholar

Pitel, A. L., Eustache, F., and Beaunieux, H. (2014). Component processes of memory in alcoholism: pattern of compromise and neural substrates. Handb. Clin. Neurol. 125, 211–225. doi: 10.1016/B978-0-444-62619-6.00013-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Schweinsburg, A. D., Mcqueeny, T., Nagel, B. J., Eyler, L. T., and Tapert, S. F. (2010). A preliminary study of functional magnetic resonance imaging response during verbal encoding among adolescent binge drinkers. Alcohol 44, 111–117. doi: 10.1016/j.alcohol.2009.09.032

PubMed Abstract | CrossRef Full Text | Google Scholar

Schweinsburg, A. D., Schweinsburg, B. C., Nagel, B. J., Eyler, L. T., and Tapert, S. F. (2011). Neural correlates of verbal learning in adolescent alcohol and marijuana users. Addiction 106, 564–573. doi: 10.1111/j.1360-0443.2010.03197.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Squeglia, L. M., Ball, T. M., Jacobus, J., Brumback, T., Mckenna, B. S., Nguyen-Louie, T. T., et al. (2017). Neural predictors of initiating alcohol use during adolescence. Am. J. Psychiatry 174, 172–185. doi: 10.1176/appi.ajp.2016.15121587

PubMed Abstract | CrossRef Full Text | Google Scholar

Squeglia, L. M., Pulido, C., Wetherill, R. R., Jacobus, J., Brown, G. G., and Tapert, S. F. (2012a). Brain response to working memory over three years of adolescence: influence of initiating heavy drinking. J. Stud. Alcohol Drugs 73, 749–760. doi: 10.15288/jsad.2012.73.749

PubMed Abstract | CrossRef Full Text | Google Scholar

Squeglia, L. M., Rinker, D. A., Bartsch, H., Castro, N., Chung, Y., Dale, A. M., et al. (2014). Brain volume reductions in adolescent heavy drinkers. Dev. Cogn. Neurosci. 9, 117–125. doi: 10.1016/j.dcn.2014.02.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Squeglia, L. M., Schweinsburg, A. D., Pulido, C., and Tapert, S. F. (2011). Adolescent binge drinking linked to abnormal spatial working memory brain activation: differential gender effects. Alcohol. Clin. Exp. Res. 35, 1831–1841. doi: 10.1111/j.1530-0277.2011.01527.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Squeglia, L. M., Sorg, S. F., Schweinsburg, A. D., Wetherill, R. R., Pulido, C., and Tapert, S. F. (2012b). Binge drinking differentially affects adolescent male and female brain morphometry. Psychopharmacology (Berl) 20, 529–539. doi: 10.1007/s00213-011-2500-4

CrossRef Full Text | Google Scholar

Squeglia, L. M., Tapert, S. F., Sullivan, E. V., Jacobus, J., Meloy, M. J., Rohlfing, T., et al. (2015). Brain development in heavy-drinking adolescents. Am. J. Psychiatry 172, 531–542. doi: 10.1176/appi.ajp.2015.14101249

PubMed Abstract | CrossRef Full Text | Google Scholar

Weiland, B. J., Sabbineni, A., Calhoun, V. D., Welsh, R. C., Bryan, A. D., Jung, R. E., et al. (2014). Reduced left executive control network functional connectivity is associated with alcohol use disorders. Alcohol. Clin. Exp. Res. 38, 2445–2453. doi: 10.1111/acer.12505

PubMed Abstract | CrossRef Full Text | Google Scholar

Wetherill, R. R., Squeglia, L. M., Yang, T. T., and Tapert, S. F. (2013). A longitudinal examination of adolescent response inhibition: neural differences before and after the initiation of heavy drinking. Psychopharmacology (Berl) 230, 663–671. doi: 10.1007/s00213-013-3198-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Wilson, S., Malone, S. M., Thomas, K. M., and Iacono, W. G. (2015). Adolescent drinking and brain morphometry: a co-twin control analysis. Dev. Cogn. Neurosci. 16, 130–138. doi: 10.1016/j.dcn.2015.07.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Worbe, Y., Irvine, M., Lange, I., Kundu, P., Howell, N. A., Harrison, N. A., et al. (2014). Neuronal correlates of risk-seeking attitudes to anticipated losses in binge drinkers. Biol. Psychiatry 76, 717–724. doi: 10.1016/j.biopsych.2013.11.028

PubMed Abstract | CrossRef Full Text | Google Scholar

Xiao, L., Bechara, A., Gong, Q., Huang, X., Li, X., Xue, G., et al. (2013). Abnormal affective decision making revealed in adolescent binge drinkers using a functional magnetic resonance imaging study. Psychol. Addict. Behav. 27, 443–454. doi: 10.1037/a0027892

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: binge drinking, heavy drinking, adolescence, young adulthood, MRI and fMRI

Citation: Cservenka A and Brumback T (2017) The Burden of Binge and Heavy Drinking on the Brain: Effects on Adolescent and Young Adult Neural Structure and Function. Front. Psychol. 8:1111. doi: 10.3389/fpsyg.2017.01111

Received: 25 April 2017; Accepted: 15 June 2017;
Published: 30 June 2017.

Edited by:

Salvatore Campanella, Free University of Brussels, Belgium

Reviewed by:

Anderson Mon, University of Ghana, Ghana
Michela Balconi, Università Cattolica del Sacro Cuore, Italy

Copyright © 2017 Cservenka and Brumback. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Anita Cservenka, YW5pdGEuY3NlcnZlbmthQG9yZWdvbnN0YXRlLmVkdQ==

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.