Hyper-resting brain entropy within chronic smokers and its moderation by Sex

Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers’ brains, however less is known about the temporal dynamics within smokers’ brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking.

[1]  R. Doty Second annual meeting of society for neuroscience , 1973 .

[2]  S. Sandler Chemical and engineering thermodynamics , 1977 .

[3]  M. Mintun,et al.  Brain blood flow measured with intravenous H2(15)O. II. Implementation and validation. , 1983, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[4]  J. Palca Nicotine addiction , 1988, Nature.

[5]  L. Kozlowski,et al.  The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire. , 1991, British journal of addiction.

[6]  P. Hrdina Basic Neurochemistry: Molecular, Cellular and Medical Aspects. , 1996 .

[7]  N. Benowitz,et al.  Cardiovascular toxicity of nicotine: implications for nicotine replacement therapy. , 1997, Journal of the American College of Cardiology.

[8]  I. Rezek,et al.  Stochastic complexity measures for physiological signal analysis , 1998, IEEE Transactions on Biomedical Engineering.

[9]  D. Ji,et al.  Synaptic Plasticity and Nicotine Addiction , 2001, Neuron.

[10]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[11]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[12]  M. P. Griffin,et al.  Sample entropy analysis of neonatal heart rate variability. , 2002, American journal of physiology. Regulatory, integrative and comparative physiology.

[13]  Matthew L. Ho,et al.  Brain metabolic changes during cigarette craving. , 2002, Archives of general psychiatry.

[14]  E. Nestler From neurobiology to treatment: progress against addiction , 2002, Nature Neuroscience.

[15]  Yingli Lu,et al.  Regional homogeneity approach to fMRI data analysis , 2004, NeuroImage.

[16]  N. Volkow,et al.  Drug addiction: the neurobiology of behaviour gone awry , 2004, Nature Reviews Neuroscience.

[17]  Raymond J. Dolan,et al.  Information theory, novelty and hippocampal responses: unpredicted or unpredictable? , 2005, Neural Networks.

[18]  A. Brody Functional brain imaging of tobacco use and dependence. , 2006, Journal of psychiatric research.

[19]  R. Ehrman,et al.  Limbic Activation to Cigarette Smoking Cues Independent of Nicotine Withdrawal: A Perfusion fMRI Study , 2007, Neuropsychopharmacology.

[20]  C. Sánchez,et al.  Regional Analysis of Spontaneous MEG Rhythms in Patients with Alzheimer’s Disease Using Spectral Entropies , 2007, Annals of Biomedical Engineering.

[21]  J. Detre,et al.  Neural Substrates of Abstinence-Induced Cigarette Cravings in Chronic Smokers , 2007, The Journal of Neuroscience.

[22]  Ze Wang,et al.  Empirical optimization of ASL data analysis using an ASL data processing toolbox: ASLtbx. , 2008, Magnetic resonance imaging.

[23]  J. Becker,et al.  Sex differences in drug abuse , 2008, Frontiers in Neuroendocrinology.

[24]  E. Yang,et al.  Neuroimaging, genetics and the treatment of nicotine addiction , 2008, Behavioural Brain Research.

[25]  H. Gu,et al.  Association of nicotine addiction and nicotine's actions with separate cingulate cortex functional circuits. , 2009, Archives of general psychiatry.

[26]  J. A. Dani,et al.  Synaptic plasticity within midbrain dopamine centers contributes to nicotine addiction. , 2009, Nebraska Symposium on Motivation. Nebraska Symposium on Motivation.

[27]  N. Volkow,et al.  Neurocircuitry of Addiction , 2010, Neuropsychopharmacology.

[28]  T. Ortiz,et al.  Complexity Analysis of Spontaneous Brain Activity in Alzheimer Disease and Mild Cognitive Impairment: An MEG Study , 2010, Alzheimer Disease and Associated Disorders.

[29]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[30]  Ian J. Deary,et al.  Inter-individual Differences in fMRI Entropy Measurements in Old Age , 2011, IEEE Transactions on Biomedical Engineering.

[31]  R. Ehrman,et al.  Modulation of resting brain cerebral blood flow by the GABA B agonist, baclofen: a longitudinal perfusion fMRI study. , 2011, Drug and alcohol dependence.

[32]  Eric Nyberg,et al.  Nicotine effects on default mode network during resting state , 2011, Psychopharmacology.

[33]  M. Kaufman,et al.  Prefrontal and limbic resting state brain network functional connectivity differs between nicotine-dependent smokers and non-smoking controls. , 2012, Drug and alcohol dependence.

[34]  Mark W. Woolrich,et al.  FSL , 2012, NeuroImage.

[35]  R. Hornero,et al.  Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures , 2012, Journal of neural engineering.

[36]  B. Xu,et al.  The Increase of the Functional Entropy of the Human Brain with Age , 2013, Scientific Reports.

[37]  Jonathan D. Power,et al.  Evidence for Hubs in Human Functional Brain Networks , 2013, Neuron.

[38]  D. Linden,et al.  Resting state fMRI entropy probes complexity of brain activity in adults with ADHD , 2013, Psychiatry Research: Neuroimaging.

[39]  Danny J. J. Wang,et al.  Multiple time scale complexity analysis of resting state FMRI , 2013, Brain Imaging and Behavior.

[40]  P. Tu,et al.  Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis , 2013, Neurobiology of Aging.

[41]  J. Detre,et al.  Brain Entropy Mapping Using fMRI , 2014, PloS one.

[42]  B. Mazoyer,et al.  Sex-related and tissue-specific effects of tobacco smoking on brain atrophy: assessment in a large longitudinal cohort of healthy elderly , 2014, Front. Aging Neurosci..

[43]  K. Jagannathan,et al.  Sex differences in resting state neural networks of nicotine-dependent cigarette smokers. , 2014, Addictive behaviors.

[44]  Moses O. Sokunbi,et al.  Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia , 2014, PloS one.

[45]  Jenna M. Sullivan,et al.  Sex Differences in the Brain's Dopamine Signature of Cigarette Smoking , 2014, The Journal of Neuroscience.

[46]  J. Qiu,et al.  The Neural Mechanisms Underlying the Acute Effect of Cigarette Smoking on Chronic Smokers , 2014, PloS one.

[47]  Jesse J. Suh,et al.  A hyper-connected but less efficient small-world network in the substance-dependent brain. , 2015, Drug and alcohol dependence.

[48]  D. Eagleman,et al.  Alterations in interhemispheric functional and anatomical connectivity are associated with tobacco smoking in humans , 2015, Front. Hum. Neurosci..

[49]  A. Beltz,et al.  Sex differences in resting state brain function of cigarette smokers and links to nicotine dependence. , 2015, Experimental and clinical psychopharmacology.

[50]  H. Lei,et al.  Altered brain functional networks in heavy smokers , 2015, Addiction biology.

[51]  John R. Fedota,et al.  Resting‐state functional connectivity and nicotine addiction: prospects for biomarker development , 2015, Annals of the New York Academy of Sciences.

[52]  V. Calhoun,et al.  Reduced executive and default network functional connectivity in cigarette smokers , 2015, Human brain mapping.

[53]  F. Lin,et al.  Altered spontaneous brain activity in heavy smokers revealed by regional homogeneity , 2015, Psychopharmacology.

[54]  S. Whitfield-Gabrieli,et al.  Lower gray matter density and functional connectivity in the anterior insula in smokers compared with never smokers , 2016, Addiction biology.

[55]  M. Grossman,et al.  Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis , 2016, PloS one.

[56]  K. Yuan,et al.  Altered resting state functional connectivity of anterior insula in young smokers , 2016, Brain Imaging and Behavior.

[57]  Y. Liu,et al.  Resting-state functional connectivity between the dorsal anterior cingulate cortex and thalamus is associated with risky decision-making in nicotine addicts , 2016, Scientific Reports.

[58]  S. Sandler Chemical, Biochemical, and Engineering Thermodynamics , 2017 .