Effects of caffeine on electrophysiological and neuropsychological indices after sleep deprivation

Efficacy of scalp stimulation for multidomain cognitive impairment in patients with post-stroke cognitive impairment and dementia: A network meta-analysis and meta-regression of moderators

BACKGROUND

Scalp stimulation has gained more traction for post-stroke cognitive impairment and dementia (PSCID); the interaction between stimulation targets and parameters influences the response to the stimulation. However, the most efficacious treatment for improving different domains of cognitive impairment remains unknown.

OBJECTIVE

We aimed to conduct a systematic review and network meta-analysis (NMA) to compare the efficacy of various scalp stimulation protocols used in PSCID treatment.

METHODS

Randomized controlled trials of scalp stimulation in patients with PSCID were searched in eight databases over the past 20 years. Standardized mean differences (SMDs) for global and subdomain cognitive scores were pooled in Bayesian NMA. Moderators were examined using meta-regression analysis.

RESULTS

A total of 90 trials, with 6199 patients, were included. Low-frequency repetitive transcranial magnetic stimulation (rTMS) over the unaffected dorsolateral prefrontal cortex (DLPFC) was highly suggested for alleviating global severity (SMD = 1.11, 95% CI (0.64, 1.57)). High-frequency rTMS over the left DLPFC was recommended for language use (1.85 (1.18, 2.52)), executive function (0.85 (0.36, 1.33)), orientation deficits (0.59 (0.07, 1.13)), and attention (0.85 (0.27, 1.43)). Anodal transcranial direct current stimulation over the affected DLPFC (2.03 (0.72, 3.34)) was recommended for treating memory impairment. Meta-regression analyses showed significant associations within attention, language and orientation.

CONCLUSION

Overall, different cognitive domains have different optimal scalp stimulation prescriptions, and activating the affected key brain regions and inhibiting the unaffected area is still the most effective treatment.

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach

Wearable technologies for measuring digital and chemical physiology are pervading the consumer market and hold potential to reliably classify states of relevance to human performance including stress, sleep deprivation, and physical exertion. The ability to efficiently and accurately classify physiological states based on wearable devices is improving. However, the inherent variability of human behavior within and across individuals makes it challenging to predict how identified states influence human performance outcomes of relevance to military operations and other high-stakes domains. We describe a computational modeling approach to address this challenge, seeking to translate user states obtained from a variety of sources including wearable devices into relevant and actionable insights across the cognitive and physical domains. Three status predictors were considered: stress level, sleep status, and extent of physical exertion; these independent variables were used to predict three human performance outcomes: reaction time, executive function, and perceptuo-motor control. The approach provides a complete, conditional probabilistic model of the performance variables given the status predictors. Construction of the model leverages diverse raw data sources to estimate marginal probability density functions for each of six independent and dependent variables of interest using parametric modeling and maximum likelihood estimation. The joint distributions among variables were optimized using an adaptive LASSO approach based on the strength and directionality of conditional relationships (effect sizes) derived from meta-analyses of extant research. The model optimization process converged on solutions that maintain the integrity of the original marginal distributions and the directionality and robustness of conditional relationships. The modeling framework described provides a flexible and extensible solution for human performance prediction, affording efficient expansion with additional independent and dependent variables of interest, ingestion of new raw data, and extension to two- and three-way interactions among independent variables. Continuing work includes model expansion to multiple independent and dependent variables, real-time model stimulation by wearable devices, individualized and small-group prediction, and laboratory and field validation.

Effects of Caffeine on Event-Related Potentials and Neuropsychological Indices After Sleep Deprivation

Objective: Caffeine is a central nervous system stimulant that can effectively alleviate brain fatigue and low cognitive efficiency induced by total sleep deprivation (TSD). Recent studies have demonstrated that caffeine can improve subjective attention and objective behavioral metrics, such as arousal level, reaction time, and memory efficiency. However, only a few studies have examined the electrophysiological changes caused by the caffeine in humans following sleep disturbance. In this study, an event-related potential (ERP) technique was employed to measure the behavioral, cognitive, and electrophysiological changes produced by caffeine administration after TSD.

Methods: Sixteen healthy subjects within-subject design performed a visual Go/No-Go task with simultaneous electroencephalogram recording. Behavioral and ERP data were evaluated after 36 h of TSD, and the effects of ingestion of either 400 mg of caffeine or placebo were compared in a double-blind randomized design.

Results: Compared with placebo administration, the Go hit rates were significantly enhanced in the caffeine condition. A simple effect analysis revealed that, compared with baseline, the Go-P2 amplitude was significantly enhanced after TSD in the caffeine consumption condition. A significant main effect of the drug was found on No-Go-P2, No-Go-N2 amplitude, and Go-P2 latency before and after TSD.

Conclusion: Our findings indicate that caffeine administration has acute effects on improving the efficiency of individual automatic reactions and early cognitive processes. Caffeine was related to the preservation of an individual’s arousal level and accelerated response-related decisions, while subjects’ higher-level recognition had limited improvement with prolonged awareness.

Caffeine to optimize cognitive function for military mission-readiness: a systematic review and recommendations for the field

Context

In 2001 the Institute of Medicine (IOM) released a report on the use of caffeine during sustained military operations in which recommendations for research and practice were made.

Objective

This systematic review serves as an update on the current quality of the evidence and addresses gaps in the current literature surrounding the effects of caffeinated foods and beverages on cognitive functioning in healthy adult populations exposed to military-like moderators.

Data Sources

PubMed, CINAHL, Embase, PsycInfo, and the Cochrane Library were searched.

Study Selection

Peer-reviewed randomized controlled trials published in the English language since 1998 were eligible.

Data Extraction

Twenty-five trials were included and assessed for methodological quality, and descriptive data were extracted according to each military-like moderator identified.

Data Synthesis

Moderators included sleep deprivation (n = 17), physical or mental exertion (n = 4), sleep deprivation combined with a sustained military operation (n = 3), and physical exertion combined with low ambient temperature (n = 1).

Conclusions

The effects of caffeine supplementation on cognitive functioning in sleep-deprived subjects included improvements in attention and vigilance, complex reaction time, and problem solving and reasoning in the trials reviewed. These findings are consistent with the conclusions reached in the 2001 IOM report. This review contributes to the field by addressing gaps outlined in the IOM report.

Effects of concurrent caffeine and mobile phone exposure on local target probability processing in the human brain

Millions of people use mobile phones (MP) while drinking coffee or other caffeine containing beverages. Little is known about the potential combined effects of MP irradiation and caffeine on cognitive functions. Here we investigated whether caffeine intake and concurrent exposure to Universal Mobile Telecommunications System (UMTS) MP-like irradiation may interactively influence neuro-cognitive function in an active visual oddball paradigm. In a full factorial experimental design, 25 participants performed a simple visual target detection task while reaction time (RT) and electroencephalogram (EEG) was recorded. Target trials were divided into Low and High probability sets based on target-to-target distance. We analyzed single trial RT and alpha-band power (amplitude) in the pre-target interval. We found that RT was shorter in High vs. Low local probability trials, and caffeine further shortened RT in High probability trials relative to the baseline condition suggesting that caffeine improves the efficiency of implicit short-term memory. Caffeine also decreased pre-target alpha amplitude resulting in higher arousal level. Furthermore, pre-target gamma power positively correlated with RT, which may have facilitated target detection. However, in the present pharmacologically validated study UMTS exposure either alone or in combination with caffeine did not alter RT or pre-stimulus oscillatory brain activity.

Effects of dietary caffeine on topographic EEG after controlling for withdrawal and withdrawal reversal

BACKGROUND/AIMS

Despite several decades of research into the effects of caffeine on EEG, few consistent findings have emerged. Notwithstanding the likelihood that differences in methodology may explain some of the inconsistency, confidence in the published findings is undermined by the failure in previous studies to control for the effects of caffeine withdrawal and withdrawal reversal.

METHODS

Participants (n = 22) alternated weekly between ingesting placebo and caffeine (1.75 mg/kg) 3 times daily for 4 consecutive weeks. EEG activity was measured at 32 sites during eyes closed, eyes open, and performance of a vigilance task.

RESULTS

Caffeine was found to have few and modest effects on EEG in the theta and alpha bandwidths, and no effects in the delta and beta bandwidths. Evidence was found of withdrawal, withdrawal reversal, and tolerance in relation to observed increases in theta power during task performance; withdrawal and withdrawal reversal in relation to increases in alpha power during all three behavioural conditions (eyes closed, eyes open, and task performance), and withdrawal-induced adverse effects in relation to aspects of subjective mood.

CONCLUSION

The finding of similar increases in theta power following caffeine challenge and acute caffeine withdrawal casts doubt on whether caffeine may be viewed as having direct stimulant effects. Results could suggest that change in drug state, whether in the form of acute caffeine withdrawal or challenge, may be disruptive to electrophysiological activity in the brain.