Warning message
The subscription service is currently unavailable. Please try again later.Role of anterior cingulate cortex and insula in Cigarette smoking and treatment with Neurofeedback: A new approach
Cigarette smoking, which is an addictive behavior, is the most common cause of morbidity and mortality in the developed world 1. However, many smokers find it difficult to quit even while knowing that the consequences of continuing can be grave 2-3. Quitting smoking can be quite difficult, and even after quitting, the relapse rate is high due to the cravings they experience. The reason for this difficulty in quitting and the high relapse rate appears to be due to long-term changes in specific neural subsystems within the brain. Animal models have shown that changes in regions such as the amygdale, the nucleus acumens, and the mesotelendephalic dopamine system promote the self-administration of harmful drugs4-5-6. Since the cravings are a key factor leading to relapse among smokers who are trying to quit controlling these cravings may be help stopping smoking.
The anterior cingulate cortex (ACC) is a part of the brain’s limbic system. Based on lesion studies in animals and humans this region has been related to affect, on the basis of lesion studies in humans and in animals.
Based on EEG studies a focal negativity develops after an error response leading to the theory that the ACC may be involved in the brain’s error detection and control7.
Neuropsychological studies show that the cognitive version of the Counting Stroop activates the cognitive subdivision of the Emotional Counting Stroop activated the affective subdivision. The cognitive subdivision is part of a distributed attentional network which maintains strong reciprocal interconnections with the lateral prefrontal cortex (BA 46/9), parietal cortex (BA 7), and premotor and supplementary motor areas. The affective division on the other hand (ACad) is activated by affect related tasks as seen in normal volunteer studies of emotional processing and in psychiatric disorders (anxiety, simple phobia and obsessive–compulsive disorder) when their symptoms are provoked. It has also been activated repeatedly by induced sadness in normal subjects and in individuals with major depression. The affective subdivision is connected to the amygdala, periaqueductal gray, nucleus accumbens, hypothalamus, anterior insula, hippocampus and orbitofrontal cortex.
According to functional imaging studies show that areas such as the cingulated cortex, the anterior cingulate cortex, the orbitofrontal cortex, and the insula activate in the presence of drug-associated cures 8-9.
The insula is particularly interesting due to its potential role in conscious urges. This area has been proposed to function in conscious emotional feelings, through its role in the representation of bodily (interoceptive) states10-11-12. Subjective drug urges induced by a cue has been shown to correlate with activity within the insula on both sides of the brain during a simple decision-making task associated with relapse to drug use 13-14 -15 . During a simple decision-making task a high amount of activity in the right insula has been observed which has been associated with drug use16.
It is interesting to note that damage to the insula may lead to a loss of the urge to smoke. According to Dr. Antoine Bechara of the University of Southern California and the University of Iowa, and his colleagues have patients with insula damage were able to quit smoking immediately, easily, and without relapse in comparison to patients with other types of brain injuries.
There are numerous methods available to quit smoking. They range from nicotine replacement therapy to psychotherapy to different self-help and behavior modification programs. However, the success rates for them have been quite low. To achieve total abstinence may take several attempts and even then persons who have quit may have problems staying smoke-free. Although 70% of smokers report wanting to quit, only 5% report being able to do so. The relapse rate is more than 70%17. Daily pressures, environmental factors such as the smell of smoke, and other environmental factors and triggers may induce strong cravings as well as fond memories of smoking which may be difficult to resist. That is why most tobacco cessation programs encourage people to avoid triggers, reduce stress, and find alternatives to cigarettes.
One method that has been found to be effective in altering dependence behavior is neurofeedback. NF is an operant conditioning paradigm whereby patients are given contingent audio/visual rewards for producing specific patterns of brain wave activity. Since the 1960s, studies have shown that through NF patients can be taught to promote normal functioning of the brain by normalizing dysfunctional brainwave patterns characterized by excessive slow wave activity 18-19 or by normalizing patterns which deviate from corresponding age related norms.
NF Presents the user with real-time feedback on brain wave activity, typically in the form of a video display and sound. The aim is to provide real-time information to the Central Nervous System (CNS) as to its current activity. For instance, people are asked to increase beta or sensorimotor rhythm (SMR) and decrease delta and theta. When the desired paradigmis accomplished, the patient is rewarded with a moving display and/or a sound. This is operant conditioning.
Studies using EEG neurofeedback were shown to have positive effects on drug use, treatment compliance, and cue reactivity in patients with cocaine and alcohol dependence20-21-22-23-24.
Neurofeedback, delivered via real-time functional magnetic resonance imaging (rtfMRI), can facilitate self-regulation of internal states by providing feedback from localized regions of interest (ROIs) to individuals while performing a task25-26 -27 -28 -29. In recent years, rtfMRI feedback has demonstrated therapeutic potential by facilitating modulation of brain activation associated with pain30, depression31, and ADHD32-33.
By using neurofeedback (NF) from the anterior cingulated cortex (ACC), a key craving region, Cantebery et al. 34, were able to reduce craving related to brain activation and self-reported craving in one visit35. In another study feedback from a craving related region of interest (ROI) in the ACC was more effective than multiple sessions of simultaneous resistant related feedback of an ROI over the medial prefrontal cortex36. This shows that in order to quit smokers can use feedback methods to effectively modulate the responses of their brain and behavior to smoking cues and that decreasing activity in areas involved in cravings (e.g. ventral anterior cingulate cortex (vACC)) is more effective than increasing activity in regions involved in resisting them (e.g. dorsal medial prefrontal cortex (dmPFC)) because dependence severity, for example, is associated with craving and smoking cessation outcomes37-38 and has been linked with ACC activation during exposure to smoking cues 29- 40. This shows that the severity of nicotine dependence may influence the response to neurofeedback where low-to-moderate nicotine dependent smokers can use neurofeedback targeting the ACC to decrease craving-related activation18-19-20.
[1] Peto R, Lopez AD, Boreham J, Thun M, Heath C Jr. Lancet. 1992; 339:1268. [PubMed: 1349675]
2 American Psychiatric Association (A.P.A.). Diagnostic and Statistical Manual of Mental Disorders Text Revision: DSM-IV-TR. 4. A.P.A; Washington, DC: 2000. p. 191-296.
3 U.S. Department of Health and Human Services. 1988 Surgeon General’s Report: The Health Consequences of Smoking: Nicotine Addiction. Vol. chap 6. U.S. Government Printing Office;Rockville, MD: 1988. p. 377-458.
4Allen, S. S., Bade, T., Hatsukami, D., & Center, B. (2008).Craving, withdrawal, and smoking urges on days immediately prior to smoking relapse. Nicotine & Tobacco Research, 10, 35–45.
5 Ferguson, S. G., & Shiffman, S. (2009). The relevance and treatment of cue-induced cravings in tobacco dependence.Journal of Substance Abuse Treatment, 36, 235–243.
6 Killen, J. D., & Fortmann, S. P. (1997). Craving is associated with smoking relapse: Findings from three prospective studies. Experimental and Clinical Psychopharmacology, 5, 137–142.
7Vogt, B.A. et al. (1992) Functional heterogeneity in cingulate cortex:the anterior executive and posterior evaluative regions. Cereb. Cortex 2, 435–443
8Grant S, et al. Proc Natl Acad Sci USA. 1996; 93:12040. [PubMed: 8876259]
9 Myrick H, et al. Neuropsychopharmacology. 2004; 29:393. [PubMed: 14679386]
10 Damasio AR, et al. Nat Neurosci. 2000; 3:1049. [PubMed: 11017179]
11 Damasio, AR. The Feeling of What Happens: Body and Emotion in the Making of Consciousness. Harcourt; Chicago: 2000
12 Craig AD. Nat Rev Neurosci. 2002; 3:655. [PubMed: 12154366]
13Bonson KR, et al. Neuropsychopharmacology. 2002; 26:376. [PubMed: 11850152]
14Brody AL, et al. Arch Gen Psychiatry. 2002; 59:1162. [PubMed: 12470133]
15 Wang GJ, et al. Life Sci. 1999; 64:775. [PubMed: 10075110]
16 Paulus MP, Tapert SF, Schuckit MA. Arch Gen Psychiatry. 2005; 62:761. [PubMed: 15997017]
17http://www.cdc.gov/tobacco/data_statistics/fact_sheets/cessation/quittin...(CDC+-+Smoking+and+Tobacco+Use+-+Fact+Sheets)
18Lubar JF. Discourse on the development of EEG diagnostics and biofeedback for attention-eficit/hyperactivity disorders. Biofeedback Self Regul. 1991;16(3):201–225.
19Thompson L, Thompson M. Neurofeedback combined with training in metacognitive strategies: effectiveness in students with ADD. Appl Psychophysiol Biofeedback. 1998;23(4):243–263.
20 Peniston,E.G.,andKulkovsky,P.J.(1999).“Neurofeedback in the treatment of addictive disorders,”in Introduction to Quantitative EEG and Neurofeedback, eds A.Abarbarnel and J.R.Evans (London:AcademicPress),157–179.doi:10.1016/B978-012243790-8/50008-0
21 Scott,W.C.,Kaiser,D.,Othmer,S.,andSideroff,S.I. (2005). Effects of an EEG biofeedback protocol on a mixed substance abusing population. Am.J.Drug Alcohol Abuse 31, 455–469.doi:10.1081/ADA-200056807
22 Sokhadze,T.M.,Cannon,R.L.,and Trudeau,D. L. (2008).EEG-Biofeedback as a treatment for substance use disorders: review, rating of efficacy and recommendations for further research. Appl. Psychophysiol. Biofeedback 33, 1–28.doi:10.1007/s10484-007-9047-5
23Arani FD, Rostami R, Nostratabadi M. Effectiveness of neurofeedback training as a treatment for opioid-dependent patients.Clin EEG Neurosci. 2010 Jul;41(3):170-7.
24 Dehghani-Arani F, Rostami R, Nadali H.Neurofeedback training for opiate addiction: improvement of mental health and craving. Appl Psychophysiol Biofeedback. 2013 Jun;38(2):133-41.
25 Li X, Hartwell KJ, Borckardt J, Prisciandaro JJ, Saladin ME, Morgan PS, Johnson KA, Lematty T, Brady KT, George MS. Volitional reduction of anterior cingulate cortex activity produces decreased cue craving in smoking cessation: a preliminary real-time fMRI study. Addict Biol. 2013 Jul;18(4):739-48. Epub 2012 Mar 28.
26 Hartwell KJ, Prisciandaro JJ, Borckardt J, Li X, George MS, Brady KT.Real-time fMRI in the treatment of nicotine dependence: a conceptual review and pilot studies.Psychol Addict Behav. 2013 Jun;27(2):501-9. doi: 10.1037/a0028215. Epub 2012 May 7. Review.
27 Hartwell KJ, Lematty T, McRae-Clark AL, Gray KM, George MS, Brady KT. Resisting the urge to smoke and craving during a smoking quit attempt on varenicline: results from a pilot fMRI study. Am J Drug Alcohol Abuse. 2013 Mar;39(2):92-8. doi: 10.3109/00952990.2012.750665.
28 Hanlon CA, Hartwell KJ, Canterberry M, Li X, Owens M, Lematty T, Prisciandaro JJ, Borckardt J, Brady KT, George MS. Reduction of cue-induced craving through realtime neurofeedback in nicotine users: the role of region of interest selection and multiple visits. Psychiatry Res. 2013 Jul 30;213(1):79-81. Epub 2013 May 15.
29Weiskopf N. Real-time fMRI and its application to neurofeedback.Neuroimage. 2012 Aug 15;62(2):682-92. doi: 10.1016/j.neuroimage.2011.10.009. Epub 2011 Oct 14. Review. PMID: 22019880
30 deCharms RC, Maeda F, Glover GH, Ludlow D, Pauly JM, Soneji D, Gabrieli JD, Mackey SC.Control over brain activation and pain learned by using real-time functional MRI. Proc Natl Acad Sci U S A. 2005 Dec 20;102(51):18626-31. Epub 2005 Dec 13.
31 Linden DE, Habes I, Johnston SJ, Linden S, Tatineni R, Subramanian L, Sorger B, Healy D, Goebel R.
Real-time self-regulation of emotion networks in patients with depression. PLoS One. 2012;7(6):e38115. doi: 10.1371/journal.pone.0038115. Epub 2012 Jun 4.
32 Lévesque J, Beauregard M, Mensour B.Effect of neurofeedback training on the neural substrates of selective attention in children with attention-deficit/hyperactivity disorder: a functional magnetic resonance imaging study.Neurosci Lett. 2006 Feb 20;394(3):216-21. Epub 2005 Dec 15.
33Beauregard M, Lévesque J.Functional magnetic resonance imaging investigation of the effects of neurofeedback training on the neural bases of selective attention and response inhibition in children with attention-deficit/hyperactivity disorder.Appl Psychophysiol Biofeedback. 2006 Mar;31(1):3-20.
34 Canterberry M, Hanlon CA, Hartwell KJ, Li X, Owens M, LeMatty T, Prisciandaro JJ, Borckardt J, Saladin ME, Brady KT, George MS. Sustained reduction of nicotine craving with real-time neurofeedback: exploring the role of severity of dependence. Nicotine Tob Res. 2013 Dec;15(12):2120-4.
35 Li, X., Hartwell, K. J., Borckardt, J., Prisciandaro, J. J., Saladin, M. E., Morgan, P. S., … George, M. S. (2013).
Volitional reduction of anterior cingulate cortex activity produces decreased cue craving in smoking cessation: A preliminary real-time fMRI study. Addiction Biology, 18, 739–748.
36Hanlon CA1, Hartwell KJ, Canterberry M, Li X, Owens M, Lematty T, Prisciandaro JJ, Borckardt J, Brady KT, George MS. Reduction of cue-induced craving through realtime neurofeedback in nicotine users: the role of region of interest selection and multiple visits. Psychiatry Res. 2013 Jul 30;213(1):79-81. doi: 10.1016/j.pscychresns.2013.03.003. Epub 2013 May 15.
37. Predicting smoking cessation and major depression in nicotine-dependent smokers. American Journal of Public Health, 90, 1122–1127.
38 Watson, N. L., Carpenter, M. J., Saladin, M. E., Gray, K. M., & Upadhyaya, H. P. (2010). Evidence for greater cue reactivity among low-dependent vs. high-dependent smokers. Addictive Behaviors, 35, 673–677.
39 McClernon, F. J., Kozink, R. V., & Rose, J. E. (2008). Individual differences in nicotine dependence, withdrawal symptoms, and sex predict transient fMRI-BOLD responses to smoking cues. Neuropsychopharmacology, 33, 2148–2157.
40 Smolka, M. N., Bühler, M., Klein, S., Zimmermann, U., Mann, K., Heinz, A., & Braus, D. (2006). Severity of nicotine dependence modulates cue-induced brain activity in regions involved in motor preparation and imagery. Psychopharmacology, 184, 577–588.