Green tea is being recognized as a beverage with potential benefits for human health and cognitive functions. In vivo studies provide preliminary evidence that green tea intake may have a positive role in improving effects on cognitive functions. We aimed to examine the neural effects of green tea extract on brain activation in humans.
Functional magnetic resonance imaging was recorded while 12 healthy volunteers performed a working memory task following administration of 250 or 500 ml of a milk whey based green tea containing soft drink or milk whey based soft drink without green tea as control in a double-blind, controlled repeated measures within-subject design with counterbalanced order of substance administration. A whole-brain analysis with a cluster-level threshold of P<0.001 (unadjusted) was followed by an a priori-defined region of interest (ROI) analysis of the dorsolateral prefrontal cortex (DLPFC) including a cluster-level threshold of P<0.05 and family-wise error (FWE) adjustment for multiple comparisons.
Whole-brain analyses revealed no significant effects after correction for multiple comparisons (FWE P<0.05). Using a ROI approach, green tea extract increased activation in the DLPFC relative to a control condition (FWE P<0.001). This neural effect was related to green tea dosage. Green tea extract was not associated with any significant attenuation in regional activation relative to control condition.
These data suggest that green tea extract may modulate brain activity in the DLPFC, a key area that mediates working memory processing in the human brain. Moreover, this is the first neuroimaging study implicating that functional neuroimaging methods provide a means of examining how green tea extract acts on the brain.
Green tea is being recognized as a beverage with potential benefits for human health. Studies in vitro, in vivo as well as clinical trials provide preliminary evidence that green tea polyphenols may have a role in the risk and pathogenesis of several chronic diseases.1 Moreover, previous studies gave some indications of improving effects of green tea on cognitive function.2, 3
To date, two studies were published analyzing the association between green tea consumption and cognitive functioning in humans. The first study analyzed data from 1003 Japanese subjects (>70 years), who gave information about the frequency of green tea consumption, whereas their cognitive function was evaluated by using the Mini-Mental State Examination test.4 The authors found that higher consumption of green tea is associated with a lower prevalence of cognitive impairment. Comparable results were obtained in another study including 2501 Chinese aged >55 years.5 The authors showed by similar methods that the intake of green tea is significantly related to a lower prevalence of cognitive impairment. Taken together, there is preliminary evidence in the literature that the intake of green tea or its main ingredients have a positive impact on cognitive functions. Green tea mainly consists of polyphenols, particularly catechins such as (−)-epigallocatechin gallate, (−)-epicatechin, (−)-epigallocatechin and (−)-epicatechin gallate, caffeine and tannin (flavonols), as well as 300 additional ingredients. As previous studies indicate that green tea extract enhances cognition, we aimed to examine the neural mechanisms of green tea extract on brain activation in humans. Examination of the neurophysiological basis is nowadays possible, thanks to neuroimaging techniques. Neuroimaging investigations of functional brain abnormalities may underlie the neurocognitive effects related to green tea. As functional neuroimaging provides a means of examining how green tea extract acts on the brain, we used functional magnetic resonance imaging (fMRI) to study healthy volunteers while they performed a working memory task following intra-gastric administration of either 250 or 500 ml milk whey based soft drink containing green tea extract (G)(Rivella AG, Rothrist, Switzerland), or a milk whey based soft drink without green tea extract (Rivella AG) as sham condition (C) in a double-blind, controlled design. Based on the literature on pharmacological and behavioral effects of green tea, we hypothesized—a priori—that green tea extract would subtly modulate the engagement of the dorsolateral prefrontal cortex (DLPFC), a brain region critically involved in many cognitive functions such as working memory processing.
Methods and materials
A double-blind, controlled, within-subject study with counterbalanced order of substance administration using an established protocol6, 7, 8, 9, 10, 11 was conducted over four sessions (250 or 500 ml G (including green tea extract; G), 250 or 500 ml C). Each participant was scanned four times with a 1-week interval between scans. The order of substance administration across sessions was counterbalanced across subjects, such that equal numbers followed each substance sequence.
Composition of test drinks
Rivella is a carbonated soft drink on the basis of milk whey. In 1999, a variety (G) with a 0.05% addition of standardized green tea extract was introduced. Of the other varieties, C is most similar to G and, apart from the green tea extract, differs primarily in its lower carbohydrate content (2.5 g/100 ml difference).
In detail, C contains the following ingredients: water, milk whey 35%, lactic acid, carbon dioxide, calcium cyclamat, acesulfam K and the following minerals: sodium 130 mg/l, potassium 450 mg/l, magnesium 35 mg/l, calcium 165 mg/l and chloride 330 mg/l. G contains additionally the following ingredients: green tea extract 0.05%, ascorbic acid 120 mg/l, pyridoxine 30 mg/l and fructose 25 g/l. Green tea extract is prepared form the dried green leaves of Camellia sinensis with a drug : extract ratio of 5.5=1, 47.5–52.5% m/m polyphenols (high-pressure liquid chromatography), 5.0–10.0% m/m coffein (high-pressure liquid chromatography), 0.3–1.2% m/m theobromin (high-pressure liquid chromatography) and 1.0–3.0% m/m theanine (high-pressure liquid chromatography). One gram of extract corresponds to 5.5 g of green tea leaves.
Control treatments were supplemented with 6.25 or 12.5 g of crystal sugar for 250 and 500 ml, respectively. To additionally blind volunteers to treatments, 250 ml treatments and controls were diluted to 500 ml with 250 ml of uncarbonated spring mineral water. This preparatory step also ensures equivalent rates of gastric emptying. Treatments were heated to room temperature and freed from carbon dioxide by stirring.
In total, 12 healthy Caucasian right-handed males, aged between 21 and 28 years (average 24.1 years, s.d. 2.6), completed the study. All participants were native German speakers and non-smokers. Participants were told to abstain from any substance use for the duration of the study, and from the intake of alcohol, caffeine, green tea products and citrus juices for 24 and 12 h before each study day, respectively. At the start of the study, a urine sample was collected for screening for amphetamines, benzodiazepines, cocaine, methamphetamine, opiates and Δ-9-tetrahydrocannabinol using immunometric assay kits. None of the participants tested positive on any of the sessions. Participants were carefully screened using a semi-structured clinical interview to exclude psychiatric or physical illness or a family history of psychiatric illness. Volunteers, who regularly use green tea or green tea products, or took any regular medication including over-the-counter drugs, had ever used any illicit psychotropic substances, who consumed >5 units daily or 20 units of alcohol per week, or had any psychiatric, neurological or severe medical illness history were excluded. The local State Ethical Committee (Ethikkommission Beider Basel) approved the study and all participants gave their informed written consent after the study procedure had been explained to them in detail. The study was registered with clinicaltrials.gov (identifier: NCT01615289).
Before each scanning session, participants swallowed a feeding tube for application of the test solutions (G and C). The doses of 250 (that were diluted to 500 ml to control for volume effects) and 500 ml were selected to produce an effect on regional brain functioning order functions without provoking any toxic, psychiatric or physical symptoms, which might have confounded interpretation of the fMRI data and caused difficulties for participants to tolerate the procedure. As the intra-gastric administration bypassed the sensory systems, volunteers were prevented from guessing which treatment they were being given.
An intravenous line was inserted in the non-dominant arm of each participant at the start of the testing session to monitor substance whole-blood levels. All participants were physically examined before testing and their heart rate and blood pressure were monitored at regular intervals (5 min, 1 h) throughout each session. Plasma concentrations of theanine after administration of test drinks were determined by liquid chromatography–mass spectrometry revealing low concentrations (data not shown). Of the 15 subjects initially included in the study, three reported nausea following placement of the feeding tube and could not tolerate the subsequent scanning procedure. These three subjects scanned and subsequently withdrawn from the study. The final sample of 12 subjects completed all parts of the study and only their data were analysed.
Magnetic resonance image acquisition
We acquired the n-back task elicited images on a 3 T scanner (Siemens Magnetom Verio, Siemens Healthcare, Erlangen, Germany) using an echo planar sequence with a repetition time (TR) of 2.5 s, echo time (TE) of 28 ms, matrix 76 × 76, 126 volumes and 38 slices with 0.5 mm interslice gap, providing a resolution of 3 × 3 × 3 mm3 and a field of view 228 × 228 cm2. Images were acquired in an axial orientation and a dummy data acquisition scan was run before the first analyzable functional volumes were acquired.
Functional MRI activation paradigm: working memory n-back task
A rapid, mixed trial, event-related fMRI design was used with jittered inter-stimulus intervals incorporating random event presentation to optimize statistical efficiency.12 The n-back paradigm is known to engage working memory and activates a number of areas including the DLPFC.13, 14 In this task, subjects were presented with a series of letters and were required to indicate via a button press whether each stimulus was the same as the one previously presented in n trials (Figure 1). With an inter-stimulus interval of 2 s, all subjects saw the series of black letters on the white background in a prismatic mirror. Each stimulus was presented for 2 s. During a baseline (0-back) condition, subjects were required to press the button with the right hand when the letter ‘X’ appeared. During 1-back and 2-back conditions, participants were instructed to press the button if the currently presented letter was the same as that presented 1 (1-back condition) or 2 (2-back condition) trials beforehand. The three conditions were presented in 10 alternating 30 s blocks (2 × 1-back, 3 × 2-back and 5 × 0-back) matched for the number of target letters per block (that is, 2 or 3).
Image processing and statistical analysis
We analyzed functional MRI data using the Statistical Parametric Mapping software package (SPM8; Wellcome Department of Cognitive Neurology, London, UK). All volumes were realigned to the first volume, adjusted for motion artefacts, mean adjusted by proportional scaling, normalized into standard stereotactic space (template provided by the Montreal Neurological Institute) and smoothed using a 8-mm full-width at half-maximum Gaussian kernel. After exclusion of error trials, we convolved the onset times for each trial in seconds with a canonical hemodynamic response function.
Using first level 2-back>0-back contrast images, we provided an SPM analysis of covariance analyses. We chose 2-back>0-back t-contrasts as attention-independent modality with higher load level to search differences across conditions. To specify the WM-associated network of activation, we used the ‘main-effect of n-back task’ (full-factorial model; P<0.001, family-wise error (FWE)-adjusted) as a mask for second level analyses. Statistical significance was assessed at the cluster-level using the non-stationary random field theory.15 For the initial whole-brain analysis, we applied a cluster-level inference strategy consisting of identifying spatially contiguous voxels at a threshold of P<0.001, unadjusted (cluster-forming threshold).16
In addition to the whole-brain analysis, the DLPFC was used as an a priori-defined ROI to examine between-group differences in the key area, which had previously been identified in studies of working memory.
We used the coordinates from the previous studies reporting the most significant effects and used only this region for any statistical analysis. Within the DLPFC, statistical inferences were made at cluster-extent threshold of P<0.05 after FWE correction for multiple comparisons. To label the regions of brain activation MNI coordinates were transformed into Talairach space (www.ebire.org/hcnlab/cortical-mapping; Talairach Demon software).17
Demographic data analyses
SPSS version 16.0 (SPSS Inc., Chicago, IL, USA) was used to analyze demographic data. Data were analyzed using repeated measures analysis of variances. When significant differences were found (level of significance P<0.05), the Tukey test for pair-wise comparisons was applied.
As there for this study, no prior information was available of the true effect size and its variability, sample size of this study was chosen on the assumption that it should allow to detect large differences (>50%) between the treatments conditions. The sample size estimation was based on the assumption of a continuous response variable from matched pairs of study subjects. Furthermore, it was assumed that the difference in the response of matched pairs is normally distributed with s.d. 30%. If the true difference in the mean response of matched pairs is at least 35%, a sample size of 10 subjects was estimated (for the paired t-test) to be sufficient to reject the null hypothesis that this response difference is zero with probability (power) of 90%. The Type I error probability associated with of this null hypothesis is 0.05. Sample size was calculated according to Dupont and Plummer.18 To account for possible dropouts, a sample size of 12 subjects was chosen for this trial.
Functional MRI—whole-brain analysis
Main effect of task
The main effect of task (2-back>0-back) in all 12 subjects delineates the network of activated areas independent of group (P<0.001, FWE-adjusted). We used this contrast image as a mask to constrain subsequent group analyses to a working memory network.
Effects of green tea extract on activation (G (500 ml) vs C (500 ml))
Compared with control (C), green tea extract (G) increased activation in the DLPFC (P<0.001 unadjusted) and the middle frontal gyrus (P<0.002 unadjusted) and inferior parietal lobule bilaterally (P<0.001 unadjusted; Table 1, Figure 2a). G was not associated with any significant attenuation in regional activation relative to control. Using a more stringent statistical threshold corrected for multiple comparisons (FWE correction P<0.05) whole-brain analyses revealed no significant effects (Table 1).
Difference between high and low green tea dosage (G (500 ml) vs G (250 ml))
Relative to G (250 ml), containing more green tea extract G (500 ml) showed a relatively increased brain activation in fronto-parietal brain areas (P<0.01 unadjusted; Table 2). Using a more stringent statistical threshold corrected for multiple comparisons (FWE correction P<0.05) whole-brain analyses revealed no significant effects (Table 2).
Functional MRI—ROI analysis of the DLPFC
To further study the effects of green tea extract on activation in a key region for working memory processing, we used an a priori-defined ROI approach for the DLPFC. Compared with control (C), green tea extract (G) significantly increased (P<0.001, FWE-adjusted) activation in the DLPFC bilaterally (Figure 2b).
N-back task performance
There was no difference among the conditions in behavioral performance with respect to the number of errors and reaction times.
In this study, we used fMRI to investigate how green tea extract modulates brain function during working memory processing. We used a double-blind, controlled and repeated measures within-subject design, measuring the blood oxygen level dependent response while subjects performed an n-back paradigm following intra-gastric challenge with green tea extract (G) or control (C). Consistent with our a priori hypothesis, we found that green tea extract significantly increased brain activation in the DLPFC. Green tea extract was not associated with any significant attenuation in regional activation relative to control.
Direct effects of green tea extract on cerebral blood flow
As this is the first neuroimaging study in humans investigating the neural effects of green tea extract no comparable previous neuroimaging findings are known. The present findings were significant only at an unadjusted statistical level and not unexpected as we hypothesized only subtle general whole-brain neural effects of green tea extract. Instead we focused—a priori—on the DLPFC, the key region for working memory processing. It is important to note that fMRI measures the blood oxygen level dependent response, which reflects the local vascular response to neural activity rather than neural activity per se. This raises the possibility that the effects of green tea extract we observed were secondary to the modulation of cerebral blood flow as opposed to neural activity. However, the analysis controlled for variation in global blood flow, and the effects of the substance was region-specific. It thus seems unlikely that the modulation of activation we observed with green tea extract was a consequence of vascular effects.
Mechanisms linking pharmacologic action to neural activity of green tea extract
Animal studies in rodents support the idea of improved working memory and learning mediated by green tea intake.19, 20, 21, 22, 23 Also, as green tea catechins are known to promote antioxidative activity in the brain it was investigated whether these substances can prevent Aβ-induced cognitive impairment.24, 25 Oral treatment with epigallocatechin gallate, the main polyphenolic constituent of green tea, decreased Aβ levels and plaques in mice, suggesting an activation of the α-secretase proteolytic pathway preventing the generation of Aβ plaques.26 As symptoms of Alzheimer’s disease can be improved by inhibiting acetylcholinesterase in the brain, animal studies were performed to analyse the impact of green tea on the activity of this enzyme. After 8 weeks of oral administration of 0.5% green tea extract, a decline in AchE activity was observed in the cerebrum of young rats.20 Feeding mice with tea polyphenol (0.2%) for 7 weeks also resulted in a reduced AchE activity in the brain.27 This potential pathway of beneficial effects on cognition and the symptoms of Alzheimer’s disease may work via induction of cellular neutral endopeptidase activity in vitro.28, 29 Neutral endopeptidase is one of the major β-amyloid-degrading enzymes, thereby preventing the deposition of senile plaques in the brain.
In addition, the central glutamatergic activity is crucial to cognitive function. Chou et al.30 investigated the effect of green tea extract on the release of endogenous glutamate, using purified nerve terminals from rat cerebral cortex. It was demonstrated that epigallocatechin gallate promoted a facilitation of glutamate release from glutamatergic terminals.
As in previous functional neuroimaging studies, our group sizes were modest as these controlled repeated measures within-subject design studies are logistically demanding. However, there is a clear rational that led to the sample size in this study. Estimation of statistical power in functional MRI requires knowledge of the expected per cent signal change between two conditions, as well as estimates of the variability in per cent signal change. The sample size estimation was based on the assumption of a continuous response variable from matched pairs of study subjects. Furthermore, it was assumed that the difference in the response of matched pairs is normally distributed with s.d. 30%. It should be noted that we used the same basis for calculating statistical sample size and statistical thresholds in previous pharmaco-fMRI studies.6, 7, 8
Although the statistical power of fMRI data has been shown to be sufficient to detect changes at the physiological level and to be relatively robust with small subjects numbers, this is not the case for behavioral measures.31 As this study was powered to detect substance effects on brain activation rather than on task performance, we did not measure task performance and cannot compare green tea effects on blood oxygen level dependent with effects on cognitive function. A further caveat is that there is a difference between using a soft drink containing green tea and a pure green tea extract. Oral ingestion of pure green tea extract would have avoided any cross effects or effects of other components as caffeine that may be involved in the positive effect of green tea extract on cognitive performance. However, our aim was to use a formula that would be associated with only subtle effects on neurocognitive functioning to avoid any behavioural-related confounding effects on blood oxygen level dependent as possible.
The key message of this manuscript is—using functional MRI methods—to show that green tea increases brain activation in the DLPFC relative to a control condition. This neural effect suggests that green tea extract may modulate brain activity in the DLPFC, a key area that mediates working memory processing in the human brain. This is the first neuroimaging study implicating that functional neuroimaging methods provide a means of examining how green tea extract acts on the brain and that green tea extract enhances the engagement of brain regions that mediate working memory processing.
This initiator-driven (CB) study was sponsored by the University of Basel and supported by grants from the Rivella Ltd, Rothrist, Switzerland. We would like to thank Doris Blaser for her help to prepare the manuscript.
JD and CB designed the research, FH and SJB collected the data, KS provided essential materials. SJB analyzed data and performed statistical analysis. All authors wrote the paper. SJB and CB had primary responsibility for the final content.
The sponsor of the study had no role in the study design, the collection, analysis and interpretation of data, the writing of this report, or in the decision to submit the paper for publication.
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