Electroencephalography (EEG) is typically viewed through the lens of spectral analysis. Recently, multiple lines of evidence have demonstrated that the underlying neuronal dynamics are characterized by scale-free avalanches. These results suggest that techniques from statistical physics may be used to analyze EEG signals. We utilized a publicly available database of fourteen subjects with waking and sleep stage 2 EEG tracings per subject, and observe that power-law dynamics of critical-state neuronal avalanches are not sufficient to fully describe essential features of EEG signals. We hypothesized that this could reflect the phenomenon of discrete scale invariance (DSI) in EEG large voltage deflections (LVDs) as being more prominent in waking consciousness. We isolated LVDs, and analyzed logarithmically transformed LVD size probability density functions (PDF) to assess for DSI. We find evidence of increased DSI in waking, as opposed to sleep stage 2 consciousness. We also show that the signatures of DSI are specific for EEG LVDs, and not a general feature of fractal simulations with similar statistical properties to EEG. Removing only LVDs from waking EEG produces a reduction in power in the alpha and beta frequency bands. These findings may represent a new insight into the understanding of the cortical dynamics underlying consciousness.

Objective

Psychiatric, medical, and substance use comorbidities are highly prevalent among smokers, and many of these comorbidities have been found to be associated with reduced rate of success in clinical trials for smoking cessation. While much has been established about the best available treatments from these clinical trials, little is known about the effect of concomitant psychiatric medications on quit rates in smoking cessation programs. On the basis of results in populations with tobacco dependence and other substance use disorders, we hypothesized that smokers taking antidepressants would have a lower rate of quitting in an outpatient smoking cessation program.

Method

We performed a naturalistic chart review of veterans (N = 144) enrolled in the Veterans Affairs Greater Los Angeles Mental Health Clinic Smoking Cessation Program from March 2011 through July 2013, who met DSM-IV-TR criteria for nicotine dependence. The primary outcome was smoking cessation with treatment, as evidenced by a patient report of at least 1 week of abstinence and an exhaled carbon monoxide level of ≤ 6 ppm (if available) at the end of acute treatment, with comparators including concomitant psychotropic medication treatment, psychiatric and medical comorbidities, and the presence of a substance use disorder history. We utilized stepwise binary logistic regression as the main statistical technique.

Results

We found that current antidepressant treatment (P = .003) and history of substance use disorder (P = .01) (particularly cocaine [P = .02]) were associated with a lower rate of quitting smoking. Furthermore, the association between antidepressant treatment and reduced rate of smoking cessation was primarily seen in patients with a history of substance use disorder (P = .003).

Conclusions

While preliminary, these results suggest an important clinical interaction meriting future study. If these findings are confirmed, clinicians may want to consider the risk of reduced ability to quit smoking in patients with a history of substance use disorder who are taking antidepressants.

Alzheimer's disease and mild cognitive impairment are increasingly prevalent global health concerns in aging industrialized societies. There are only limited non-invasive biomarkers for the cognitive and functional impairment associated with dementia. Multifractal analysis of EEG has recently been proposed as having the potential to be an improved method of quantitative EEG analysis compared to existing techniques (e.g., spectral analysis). We utilized an existing database of a study of healthy elderly patients (N = 20) who were assessed with cognitive testing (Folstein Mini Mental Status Exam; MMSE) and resting state EEG (4 leads). Each subject's EEG was separated into two 30 s tracings for training and testing a statistical model against the MMSE scores. We compared multifractal detrended fluctuation analysis (MF-DFA) against Fourier Transform (FT) in the ability to produce an accurate classification and regression trees estimator for the testing EEG segments. The MF-DFA-based statistical model MMSE estimation strongly correlated with the actual MMSE when applied to the test EEG parameter dataset, whereas the corresponding FT-based model did not. Using a standardized cutoff value for MMSE-based clinical staging, the MF-DFA-based statistical model was both sensitive and specific for clinical staging of both mild Alzheimer's disease and mild cognitive impairment. MF-DFA shows promise as a method of quantitative EEG analysis to accurately estimate cognition in Alzheimer's disease.

Substantial evidence demonstrates both nicotine's addiction liability and its cognition-enhancing effects. However, the neurobiological mechanisms underlying nicotine's impact on brain function and behavior remain incompletely understood. Elucidation of these mechanisms is of high clinical importance and may lead to improved therapeutics for smoking cessation as well as for a number of cognitive disorders such as schizophrenia. Neuroimaging techniques such as positron emission tomography (PET), single photon emission computed tomography (SPECT), and functional magnetic resonance imaging (fMRI), which make it possible to study the actions of nicotine in the human brain in vivo, play an increasingly important role in identifying these dual mechanisms of action. In this review, we summarize the current state of knowledge and discuss outstanding questions and future directions in human neuroimaging research on nicotine and tobacco. This research spans from receptor-level PET and SPECT studies demonstrating nicotine occupancy at nicotinic acetylcholine receptors (nAChRs) and upregulation of nAChRs induced by chronic smoking; through nicotine's interactions with the mesocorticolimbic dopamine system believed to mediate nicotine's reinforcing effects leading to dependence; to functional activity and connectivity fMRI studies documenting nicotine's complex behavioral and cognitive effects manifest by its actions on large-scale brain networks engaged both during task performance and at rest. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'.

Mild, blast-induced traumatic brain injury (mbTBI) is a common combat brain injury characterized by typically normal neuroimaging findings, with unpredictable future cognitive recovery. Traditional methods of electroencephalography (EEG) analysis (e.g., spectral analysis) have not been successful in detecting the degree of cognitive and functional impairment in mbTBI. We therefore collected resting state EEG (5 minutes, 64 leads) from twelve patients with a history of mbTBI, along with repeat neuropsychological testing (D-KEFS Tower test) to compare two new methods for analyzing EEG (multifractal detrended fluctuation analysis (MF-DFA) and information transfer modeling (ITM)) with spectral analysis. For MF-DFA, we extracted relevant parameters from the resultant multifractal spectrum from all leads and compared with traditional power by frequency band for spectral analysis. For ITM, because the number of parameters from each lead far exceeded the number of subjects, we utilized a reduced set of 10 leads which were compared with spectral analysis. We utilized separate 30 second EEG segments for training and testing statistical models based upon regression tree analysis. ITM and MF-DFA models both generally had improved accuracy at correlating with relevant measures of cognitive performance as compared to spectral analytic models ITM and MF-DFA both merit additional research as analytic tools for EEG and cognition in TBI.

Background

Selective serotonin reuptake inhibitors are often used in alcohol use disorders. Clinical trials with selective serotonin reuptake inhibitors for alcohol use disorders, however, have yielded mixed results. The goal of this project was to assess whether a single i.v. dose of a selective serotonin reuptake inhibitor reduces craving for alcohol and/or simultaneously increases striatal dopamine concentration in individuals with alcohol dependence.

Methods

Alcohol-dependent (DSM-IV-TR criteria) volunteers and matched controls (n = 10/group) underwent a double-blind, placebo-controlled, within-subjects study. Participants received i.v. citalopram (40 mg) or saline (counter-balanced) followed by a cue-induced craving assessment and [18F]-fallypride positron emission tomography scanning.

Results

In the alcohol-dependent individuals, the citalopram (compared with saline) resulted in decreased cue-induced craving for alcohol. For the whole study group, cue-induced alcohol craving was inversely correlated with thalamic (but not striatal) dopamine D2/3 receptor availability.

Conclusions

Acute serotonin reuptake inhibition reduces cue-induced alcohol craving. Furthermore, thalamic dopamine abnormalities and the striatal hyperdopaminergic hypothesis of alcohol use disorder are supported.

Selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed for patients who misuse alcohol, especially in the context of comorbid depressive symptoms. Deficits in impulse control and decision-making are linked to routine alcohol consumption and alcohol dependence. The goal of this study was to determine the effects of a single dose of citalopram on measures of impulsivity, decision-making, and/or brain dopamine receptor availability in alcohol-dependent individuals. A double-blind, placebo-controlled, within-subject, outpatient study was conducted with active alcohol-dependent (DSM-IV-TR criteria) participants (n = 12) and matched healthy controls (n = 13). Serial doses of both citalopram (40 mg) and saline were administered intravenously before laboratory tests of decision-making (Balloon Analogue Risk Task, delay discounting task, and Loss Aversion Gambling Task) and positron emission tomography with [¹⁸F]-fallypride to measure dopamine D_2/3 receptor availability, separated by at least one week. Alcohol-dependent participants demonstrated greater loss aversion than healthy controls, but there were no group differences in risk taking on the Balloon Analogue Risk Task. Citalopram increased delay discounting across groups, with no group difference in the effect. There were no effects of citalopram on risk taking on the Balloon Analogue Risk Task. PET showed a negative correlation between thalamic dopamine D_2/3 receptor availability and loss aversion across groups. The effect of citalopram to decrease the valuation of monetary reward as a function of delay raises the possibility that SSRIs can influence risky decision-making in clinical populations. In addition, these results suggest that altered thalamic dopamine signaling may play an important role in disproportionately valuing losses in patients with Alcohol Use Disorder. This trial is registered under ClinicalTrials.gov registration NCT01657760.

Introduction

The majority of people with schizophrenia have a diagnosis of tobacco dependence during their lifetime. A major obstacle to reducing the burden of cigarette smoking in this population is that these smokers have lower quit rates when undergoing standard treatment compared to smokers with no mental illness. We sought to determine if combination extended treatment (COMB-EXT) and home visits (HV) would lead to improved outcomes in smokers with schizophrenia.

Methods

Thirty-four cigarette smokers with schizophrenia completed either COMB-EXT with HV, COMB-EXT without HV, or treatment as usual (TAU) (random assignment). COMB-EXT consisted of group cognitive-behavioral therapy (CBT), bupropion, nicotine patch, and nicotine lozenge, which were initiated within 2 weeks and continued for 26 weekly visits. HV consisted of biweekly visits to the home with assessment of secondhand smoke (SHS) exposure and brief behavioral therapy with participants and others in the home environment. TAU consisted of group CBT plus serial single or combination medication trials as per standard care.

Results

Smokers with schizophrenia who received COMB-EXT (with or without HV) had greater reductions in cigarettes per day than those treated with TAU (both ps < .01). In addition, 7-day point prevalence abstinence rates for the three groups were 45%, 20%, and 8%, respectively, which was significantly higher for COMB-EXT plus HV than TAU (χ²(1) = 4.8, p = .03). Groups did not differ significantly in the number of adverse events, and HV were easily scheduled.

Conclusion

COMB-EXT improves outcomes for smokers with schizophrenia. HV appeared to provide additional benefit for smoking cessation in this treatment-resistant population.

Implications

The clear benefit found here of rapidly initiated, combination, extended treatment over TAU suggests that aggressive and extended treatment should be considered in clinical practice for smokers with schizophrenia. Furthermore, HV to address SHS exposure showed initial promise for assisting smokers with schizophrenia in maintaining abstinence, indicating that this intervention may be worthy of future research.

Despite the worldwide extent of methamphetamine dependence, no medication has been shown to effectively treat afflicted individuals. One relatively unexplored approach is modulation of cholinergic system function. Animal research suggests that enhancement of central cholinergic activity, possibly at nicotinic acetylcholine receptors (nAChRs), can reduce methamphetamine-related behaviors. Further, preliminary findings indicate that rivastigmine, a cholinesterase inhibitor, may reduce craving for methamphetamine after administration of the drug in human subjects. We therefore performed a double-blind, placebo-controlled, crossover pilot study of the safety and tolerability of varenicline in eight methamphetamine-dependent research subjects. Varenicline is used clinically to aid smoking cessation, and acts as a partial agonist at α4β2 nAChRs with full agonist properties at α7 nAChRs. Oral varenicline dose was titrated over 1 week to reach 1 mg bid, and then was co-administered with 30 mg methamphetamine, delivered in ten intravenous infusions of 3 mg each. Varenicline was found to be safe in combination with IV methamphetamine, producing no cardiac rhythm disturbances or alterations in vital sign parameters. No adverse neuropsychiatric sequelae were detected either during varenicline titration or following administration of methamphetamine. The results suggest that varenicline warrants further investigation as a potential treatment for methamphetamine dependence.