Large Sample Of Healthy Subjects Research Articles

Similarity in evoked responses does not imply similarity in macroscopic network states.

It is commonplace in neuroscience to assume that if two tasks activate the same brain areas in the same way, then they are recruiting the same underlying networks. Yet computational theory has shown that the same pattern of activity can emerge from many different underlying network representations. Here we evaluated whether similarity in activation necessarily implies similarity in network architecture by comparing region-wise activation patterns and functional correlation profiles from a large sample of healthy subjects (N = 242). Participants performed two executive control tasks known to recruit nearly identical brain areas, the color-word Stroop task and the Multi-Source Interference Task (MSIT). Using a measure of instantaneous functional correlations, based on edge time series, we estimated the task-related networks that differed between incongruent and congruent conditions. We found that the two tasks were much more different in their network profiles than in their evoked activity patterns at different analytical levels, as well as for a wide range of methodological pipelines. Our results reject the notion that having the same activation patterns means two tasks engage the same underlying representations, suggesting that task representations should be independently evaluated at both node and edge (connectivity) levels.

Hyperoxia improves exercise capacity in cardiopulmonary disease: a series of randomised controlled trials.

The aim of this study was to investigate the overall and differential effect of breathing hyperoxia (inspiratory oxygen fraction (F IO2 ) 0.5) versus placebo (ambient air, F IO2 0.21) to enhance exercise performance in healthy people, patients with pulmonary vascular disease (PVD) with precapillary pulmonary hypertension (PH), COPD, PH due to heart failure with preserved ejection fraction (HFpEF) and cyanotic congenital heart disease (CHD) using data from five randomised controlled trials performed with identical protocols. 91 subjects (32 healthy, 22 with PVD with pulmonary arterial or distal chronic thromboembolic PH, 20 with COPD, 10 with PH in HFpEF and seven with CHD) performed two cycle incremental (IET) and two constant work-rate exercise tests (CWRET) at 75% of maximal load (Wmax), each with ambient air and hyperoxia in single-blinded, randomised, controlled, crossover trials. The main outcomes were differences in Wmax (IET) and cycling time (CWRET) with hyperoxia versus ambient air. Overall, hyperoxia increased Wmax by +12 W (95% CI: 9-16, p<0.001) and cycling time by +6:13 min (4:50-7:35, p<0.001), with improvements being highest in patients with PVD (Wmax/min: +18%/+118% versus COPD: +8%/+60%, healthy: +5%/+44%, HFpEF: +6%/+28%, CHD: +9%/+14%). This large sample of healthy subjects and patients with various cardiopulmonary diseases confirms that hyperoxia significantly prolongs cycling exercise with improvements being highest in endurance CWRET and patients with PVD. These results call for studies investigating optimal oxygen levels to prolong exercise time and effects on training.

Cortical electrical activity changes in healthy aging using EEG-eLORETA analysis

Brain aging causes loss of synaptic spines, neuronal apoptosis, and a reduction in neurotransmitter levels. These aging phenomena disturb cortical electrical activity and its synchronization with connected regions. Previous electroencephalography (EEG) studies reported an age-related decrease in electrical activity in the alpha frequency band at occipital, parietal, and temporal areas as well as a decrease in occipital delta activity. However, there is an ongoing debate about whether there is an increase or decrease of the activity in other frequency bands with aging due to inconsistent study findings. In this study, we aimed to detect age-related changes of cortical electrical activities in all five frequency bands (delta, theta, alpha, beta, and gamma) in a large sample of healthy subjects for the first time. Using eLORETA (exact low-resolution brain electromagnetic tomography) analysis, we applied an eLORETA source estimation method to resting-state EEG data in 147 healthy subjects (median age 55, IQR 26.5–67.0) to obtain cortical electrical activity and assessed age-related changes in this activity using correlation analysis with multiple comparison correction. The combination of the eLORETA source estimation method and correlation analysis implemented in eLORETA software detected age-related changes in specific cortical regions for each frequency band: (1) delta and theta cortical electrical activities decreased at the occipital area with age, (2) alpha cortical electrical activity decreased at the occipitoparietotemporal areas with age, (3) beta cortical electrical activity increased at the insula, sensorimotor area, supplementary motor area, premotor area, and right temporal areas with age (most significant correlation at the right insula), (4) gamma cortical electrical activity increased at the frontoparietal and left temporal areas with age. These findings extend previous EEG study findings and provide valuable information related to mechanisms of healthy aging. Overall, our findings revealed that even healthy aging greatly affects cortical electrical activities in a region-specific way.

Brain Structures Associated With Individual Differences in Somatic Symptoms and Emotional Distress in a Healthy Sample.

Stress-related psychosomatic responses are viewed as important risks to our physical health. Growing evidence from structural imaging studies has implicated that stress and trauma exposures have negative effects on brain structural alterations. However, whether stress-related emotional distress and somatic symptoms are related to the structure of brain systems remains unclear. Also, stress-related somatic symptoms have adverse effects on emotional distress. In turn, emotional distress may influence somatic symptom reports via negative cognitive bias. However, whether this relationship is mediated by specific brain morphology remains poorly understood. First, we used voxel-based morphometric approaches to investigate the neuroanatomical basis underlying somatic symptoms and emotional distress in a large sample of healthy subjects (ages 18–27 years). We found that relatively high stress-related somatic symptoms were associated with reduced gray matter volumes (GMVs) in the ventral medial prefrontal cortex (vmPFC), anterior insula, somatosensory cortex, hippocampus, and amygdala. Furthermore, a moderator analysis was performed to investigate the impact of recent stressful life events (moderators) on the association between specific GMVs (independent variables) and emotional distress (dependent variables). Interestingly, high levels of emotional distress were associated with small volumes of the vmPFC, anterior insula, hippocampus, and amygdala in participants with experience with more recent stressful life events. Finally, we performed mediation analyses to investigate the specific brain areas that mediate the association between emotional distress and somatic symptoms. The results showed that the effect of emotional distress on somatic symptoms is mediated by reductions in the volume of the hippocampus, the impact of somatic symptoms on emotional distress is mediated by the volume of the vmPFC. These results provided evidence that higher stress-related somatic symptoms are associated with smaller volume in prefrontal, insula, and limbic regions involved in emotion, interoception, and memory processing. The vmPFC and hippocampus play different roles in the relationship between emotional distress and somatic symptoms.

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender.

Background: Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynamic interaction. To examine the complexity of age-related changes in voice, more advanced techniques based on machine learning have been recently applied to voice recordings but only in a laboratory setting. We here recorded voice samples in a large sample of healthy subjects. To improve the ecological value of our analysis, we collected voice samples directly at home using smartphones. Methods: 138 younger adults (65 males and 73 females, age range: 15–30) and 123 older adults (47 males and 76 females, age range: 40–85) produced a sustained emission of a vowel and a sentence. The recorded voice samples underwent a machine learning analysis through a support vector machine algorithm. Results: The machine learning analysis of voice samples from both speech tasks discriminated between younger and older adults, and between males and females, with high statistical accuracy. Conclusions: By recording voice samples through smartphones in an ecological setting, we demonstrated the combined effect of age and gender on voice. Our machine learning analysis demonstrates the effect of ageing on voice.

Enhancing cognitive control training with transcranial direct current stimulation: a systematic parameter study

BackgroundCognitive control (CC) is an important prerequisite for goal-directed behaviour and efficient information processing. Impaired CC is associated with reduced prefrontal cortex activity and various mental disorders, but may be effectively tackled by transcranial direct current stimulation (tDCS)-enhanced training. However, study data are inconsistent as efficacy depends on stimulation parameters whose implementations vary widely between studies. ObjectiveWe systematically tested various tDCS parameter effects (anodal/cathodal polarity, 1/2 mA stimulation intensity, left/right prefrontal cortex hemisphere) on a six-session CC training combined with tDCS. MethodsNine groups of healthy humans (male/female) received either anodal/cathodal tDCS of 1/2 mA over the left/right PFC or sham stimulation, simultaneously with a CC training (modified adaptive Paced Auditory Serial Addition Task [PASAT]). Subjects trained thrice per week (19 min each) for two weeks. We assessed performance progress in the PASAT before, during, and after training. Using a hierarchical approach, we incrementally narrowed down on optimal stimulation parameters supporting CC. Long-term CC effects as well as transfer effects in a flanker task were assessed after the training period as well as three months later. ResultsCompared to sham stimulation, anodal but not cathodal tDCS improved performance gains. This was only valid for 1 mA stimulation intensity and particularly detected when applied to the left PFC. ConclusionsOur results confirm beneficial, non-linear effects of anodal tDCS on cognitive training in a large sample of healthy subjects. The data consolidate the basis for further development of functionally targeted tDCS, supporting cognitive control training in mental disorders and guiding further development of clinical interventions.

Cerebral microstructural abnormalities in impulsivity: a magnetic resonance study.

Studies that investigated neurobiological parameters subtended to impulsivity trait found their relationship with structural and functional brain alterations. No studies investigated the white matter microstructural attributes of impulsivity in a large sample of healthy subjects. In the present study 1007 subjects from Human Connectome Project public dataset were divided in two groups, impulsive and not impulsive, basing on Delay Discounting task score. For both groups brain morphometric and microstructural characteristics were investigated. A t-test (correct for multiple comparisons) was performed for each brain parcel and impulsivity measure. Magnetic resonance diffusion images were pre-processed and selected to perform a voxelwise analysis on the fractional anisotropy (FA) maps between impulsive and not impulsive groups. Group analysis showed significant differences in morphometric brain data mainly for temporal and frontal lobes. The impulsive group presented higher FA values in four regions: bilateral medial lemniscus and midbrain reticular formation, right superior longitudinal fasciculus, left forceps major, right corticospinal tract. Not impulsive group showed higher FA values in two significant regions: right and left anterior thalamus radiation. Concluding, macroscopic and microstructural brain alterations were assessed, identifying new neuroanatomical substrates for multidimensional impulsivity construct in a large sample of healthy subjects.

Probing the “Default Network Interference Hypothesis” With EEG: An RDoC Approach Focused on Attention

Studies have shown that specific networks (default mode network [DMN] and task positive network [TPN]) activate in an anticorrelated manner when sustaining attention. Related EEG studies are scarce and often lack behavioral validation. We performed independent component analysis (ICA) across different frequencies (source-level), using eLORETA-ICA, to extract brain-network activity during resting-state and sustained attention. We applied ICA to the voxel domain, similar to functional magnetic resonance imaging methods of analyses. The obtained components were contrasted and correlated to attentional performance (omission errors) in a large sample of healthy subjects (N = 1397). We identified one component that robustly correlated with inattention and reflected an anticorrelation of delta activity in the anterior cingulate and precuneus, and delta and theta activity in the medial prefrontal cortex and with alpha and gamma activity in medial frontal regions. We then compared this component between optimal and suboptimal attentional performers. For the latter group, we observed a greater change in component loading between resting-state and sustained attention than for the optimal performers. Following the National Institute of Mental Health Research Domain Criteria (RDoC) approach, we prospectively replicated and validated these findings in subjects with attention deficit/hyperactivity disorder. Our results provide further support for the "default mode interference hypothesis."

Evidence of brain network aberration in healthy subjects with urban upbringing – A multimodal DTI and VBM study

City living represents not only the allegory of modern life, but also – due to attractive living conditions, employment and infrastructure – a crucial reality for a growing portion of the global society. Regarding the remarkable increase of the schizophrenia incidence in individuals exposed to an urban environment during upbringing the understanding of responsible pathogenetic mechanisms is important. Schizophrenia has been conceptualized as a disorder of brain dysconnectivity. We investigated the association between urban upbringing and gray matter as well as white matter in a large sample of healthy subjects (n = 290). Voxelwise analyses revealed a strong inverse correlation of early life urbanicity and gray matter volume of the bilateral dorsolateral prefrontal cortices (DLPFC) and the right inferior parietal lobe (IPL) as well as the white matter characteristics in the left superior longitudinal fasciculus (SLF). A positive correlation was found for the gray matter volume of the left precuneus. These results may point to an altered brain development associated with urban upbringing, which not only affects single brain regions but a fronto-parietal network. Considering a DLPFC susceptibility to stress, our findings support the hypothesis of the pathogenetic role of social stress in an urban environment.

Heart rate variability associated with grey matter volumes in striatal and limbic structures of the central autonomic network

Previous neuroimaging studies have highlighted the functional neural correlates of cardiac vagal activity, providing convergent evidence that the cardiac vagal function is controlled by a number of brain regions in the central autonomic network (CAN). However, it remains largely unknown whether the underlying anatomical basis of those identified regions are associated with individual difference in vagal function. To address the above issue, this study used a large sample of healthy subjects (n = 185) and voxel-based morphometry (VBM) analysis to verify brain morphometry associated with vagal control and the associations varied as a function of gender and age. Our results showed that high frequency component of heart rate variability (HF-HRV) was negatively correlated with grey matter volumes in the right putamen, caudate, amygdala, insula, superior temporal gyrus, temporal pole, and parahippocampal gyrus, demonstrating brain morphological variation in the right-sided striatal and limbic structures of the CAN associated with individual difference in cardiac vagal function. Additionally, gender and age effects on the relationship between cardiac vagal control and brain morphometry were not significant in the current dataset. These findings underscore the importance of striatal and limbic structures in parasympathetic control, and shed light on the underlying anatomical substrates of cardiac vagal activity.

Upper and lower limbs composition: a comparison between anthropometry and dual-energy X-ray absorptiometry in healthy people

The primary aim of this study was to investigate the reliability of some widely available anthropometric measurements in the assessment of body composition (BC) at the limbs, especially in terms of muscle mass, in a large sample of healthy subjects of different age bands and sex, using fat mass (FM) and lean mass (LM) parameters derived by dual-energy X-ray absorptiometry (DXA) as the gold standard. The secondary aim was to collect DXA age- and sex-specific values of BC of left and right limbs (upper and lower) in a healthy Italian population to be used as reference standards. Two hundred fifty healthy volunteers were enrolled. Arm circumference (AC) and thigh circumference (ThC) were measured, and total and regional BC parameters were obtained by a whole-body DXA scan (Lunar iDXA, Madison, WI, USA; enCORE™ 2011 software version 13.6). FM/LM showed only fair correlation with AC and ThC in females (r=0.649 and 0.532, respectively); in males and in the total population, the correlation was low (r=0.360 or lower, and p non-statistically significant). AC and ThC were not well representative of arms LM in both genders (females r=0.452, males r=0.530) independently of age. In general, men of all age groups showed higher values of LM and lean mass index (LMI) in both total and segmental upper and lower limbs. In males, the maximum LM and LMI were achieved in the fifth decade in both upper and lower limbs and then started to decrease with aging. In females, no significant modification with aging was identified in LM and LMI. According to our results, anthropometry is not well representative of LM of arms in both genders, independently of age; therefore, a densitometric examination should be considered for a correct assessment of BC at limbs.

Magnetic resonance imaging-based evaluation of ossification of the medial clavicular epiphysis in forensic age assessment.

Evaluation of the degree of ossification of the medial clavicular epiphysis plays a crucial role in determining with an adequate degree of probability whether legally relevant age boundaries after the age of 17 have been crossed. In view of the need to avoid unnecessary radiation exposure, establishing non-X-ray methods for investigating the clavicle has long been a key objective in forensic age assessment research. Based on magnetic resonance imaging examinations in a large sample of healthy subjects, the current study for the first time presents statistical measures which allow inferences to be drawn for forensic age assessment in both sexes. We undertook a prospective study of a reference sample of 334 female and 335 male German volunteers aged from 12 to 24 using a 3-T MRI scanner. A 3D FFE (fast field echo) T1-weighted sequence with fat saturation was acquired. To stage ossification of the medial clavicular epiphysis, we used the clavicular ossification staging systems described by Schmeling et al. and Kellinghaus et al. Ossification stage IIIc offers a means in both sexes of demonstrating that the age of 18 has been attained prior to complete ossification of the epiphyseal plate. In both sexes, if a subject has reached ossification stage IV, it can be stated that he or she has attained the age of 21. Magnetic resonance imaging is a valid diagnostic procedure for determining the ossification stage of the medial clavicular epiphysis.

Olfactory Function and Age: a Sniffin’ Sticks Extended Test Study Performed in Sardinia

Several studies evaluated the influence of cultural components on the Sniffin’ Sticks Identification Test in different countries. The aim of this study was to analyze the olfactory function in a large sample of healthy subjects living in Sardinia, an island known for its historic genetic isolation, in relation to different age ranges to provide new data in healthy Sardinian subjects. Olfactory perception of 161 participants (108 females and 53 males; age range 19–78 years) was assessed through three different parameters: odor detection threshold, discrimination, and identification by means of the Sniffin’Sticks Extended test (SST). Our results show that young adults were generally normosmic, while in subjects over 55, a statistically significant age-related decrease of all the parameters was observed. Regarding odor identification task, a few, such as leather, apples, lemons, cloves, and pineapples, were frequently incorrectly identified by participants probably due to the similarities between the odors and distractors. Our data provide a comprehensive evaluation of the three olfactory components in the Sardinian population and confirm a decrease in the odor detection threshold, discrimination and identification as well as in the global TDI score in subjects over 55 years of age. These results may be useful in providing normative values for routine clinical use of the SSET in Sardinian subjects.

Dynamic inter-network connectivity in the human brain.

Recently, the field of functional brain connectivity has shifted its attention on studying how functional connectivity (FC) between remote regions changes over time. It is becoming increasingly evident that the human "connectome" is a dynamical entity whose variations are effected over very short timescales and reflect crucial mechanisms which underline the physiological functioning of the brain. In this study, we employ ad-hoc statistical and surrogate data generation methods to quantify whether and which brain networks displayed dynamic behaviors in a very large sample of healthy subjects provided by the Human Connectome Project (HCP). Our findings provided evidences that there are specific pairs of networks and specific networks within the healthy brain that are more likely to display dynamic behaviors. This new set of findings supports the notion that studying the time-variant connectivity in the brain could reveal useful and important properties about brain functioning in health and disease.

Reference Values for Peak Exercise Cardiac Output in Healthy Individuals

Cardiac output (Q˙) is a key parameter in the assessment of cardiac function, its measurement being crucial for the diagnosis, treatment, and prognostic evaluation of all heart diseases. Until recently, Q˙ determination at peak exercise has been possible through invasive methods, so that normal values were obtained in studies based on small populations. Nowadays, peak Q˙ can be measured noninvasively by means of the inert gas rebreathing (IGR) technique. The present study was undertaken to provide reference values for peak Q˙ in the normal general population and to obtain a formula able to estimate peak exercise Q˙ from measured peak oxygen uptake (V˙o2). We studied 500 normal subjects (age, 44.9 ± 1.5 years; range, 18-77 years; 260 men, 240 women) who underwent a maximal cardiopulmonary exercise test with peak Q˙ measurement by IGR. In the overall study sample, peak Q˙ was 13.2 ± 3.5 L/min (men, 15.3±3.3L/min; women, 11.0 ± 2.0 L/min; P< .001) and peak V˙o2 was 95%± 18%of the maximum predicted value (men, 95%± 19%; women, 95%± 18%). Peak V˙o2 and peak Q˙ progressively decreased with age (R2, 0.082; P< .001; and R2, 0.144; P< .001, respectively). The V˙o2-derived formula to measure Q˙ at peak exercise was (4.4× peak V˙o2)+ 4.3 in the overall study cohort, (4.3× peak V˙o2)+ 4.5 in men, and (4.9× peak V˙o2)+ 3.6 in women. The simultaneous measurement of Q˙ and V˙o2 at peak exercise in a large sample of healthy subjects provided an equation to predict peak Q˙ from peak V˙o2 values.

Age prediction on the basis of brain anatomical measures.

In this study, we examined whether age can be predicted on the basis of different anatomical features obtained from a large sample of healthy subjects (n = 3,144). From this sample we obtained different anatomical feature sets: (1) 11 larger brain regions (including cortical volume, thickness, area, subcortical volume, cerebellar volume, etc.), (2) 148 cortical compartmental thickness measures, (3) 148 cortical compartmental area measures, (4) 148 cortical compartmental volume measures, and (5) a combination of the above-mentioned measures. With these anatomical feature sets, we predicted age using 6 statistical techniques (multiple linear regression, ridge regression, neural network, k-nearest neighbourhood, support vector machine, and random forest). We obtained very good age prediction accuracies, with the highest accuracy being R2 = 0.84 (prediction on the basis of a neural network and support vector machine approaches for the entire data set) and the lowest being R2 = 0.40 (prediction on the basis of a k-nearest neighborhood for cortical surface measures). Interestingly, the easy-to-calculate multiple linear regression approach with the 11 large brain compartments resulted in a very good prediction accuracy (R2 = 0.73), whereas the application of the neural network approach for this data set revealed very good age prediction accuracy (R2 = 0.83). Taken together, these results demonstrate that age can be predicted well on the basis of anatomical measures. The neural network approach turned out to be the approach with the best results. In addition, it was evident that good prediction accuracies can be achieved using a small but nevertheless age-representative dataset of brain features. Hum Brain Mapp 38:997-1008, 2017. © 2016 Wiley Periodicals, Inc.

Regional gray matter volume mediates the relationship between family socioeconomic status and depression-related trait in a young healthy sample.

Socioeconomic status (SES) is a complex phenomenon that is predicted by a broad spectrum of variables and is often conceptualized as a combination of financial, occupational, and educational influences. SES is associated with symptoms of depression and depression-related personality traits. Many studies have focused on the relationship between SES and depression symptoms in clinical subjects; however, there are few studies of the neural basis of the relationship between SES and depression-related personality traits in nonclinical subjects. Thus, in the present study, we studied the neural basis of the relationship between SES and depression-related traits. The first step was to use voxel-based morphometry (VBM) to investigate the neuroanatomical basis underlying family SES in a large sample of healthy subjects. We found a significant negative correlation between family SES and the medial prefrontal cortex (mPFC) that extending to the anterior cingulate cortex (ACC). Then, the mediation analysis revealed that the correlation between family SES, especially family income, and depression-related traits were mediated by the region of the mPFC that extending to the ACC volume. These findings suggest that the family income may play more important role in driving depression-related traits than that of parental education. They also suggest that the mPFC extension to the ACC may play an important role in the correlation between familial SES, especially with respect to family income and the depression-related traits.

Quantifying interindividual variability and asymmetry of face-selective regions: A probabilistic functional atlas

Face-selective regions (FSRs) are among the most widely studied functional regions in the human brain. However, individual variability of the FSRs has not been well quantified. Here we use functional magnetic resonance imaging (fMRI) to localize the FSRs and quantify their spatial and functional variabilities in 202 healthy adults. The occipital face area (OFA), posterior and anterior fusiform face areas (pFFA and aFFA), posterior continuation of the superior temporal sulcus (pcSTS), and posterior and anterior STS (pSTS and aSTS) were delineated for each individual with a semi-automated procedure. A probabilistic atlas was constructed to characterize their interindividual variability, revealing that the FSRs were highly variable in location and extent across subjects. The variability of FSRs was further quantified on both functional (i.e., face selectivity) and spatial (i.e., volume, location of peak activation, and anatomical location) features. Considerable interindividual variability and rightward asymmetry were found in all FSRs on these features. Taken together, our work presents the first effort to characterize comprehensively the variability of FSRs in a large sample of healthy subjects, and invites future work on the origin of the variability and its relation to individual differences in behavioral performance. Moreover, the probabilistic functional atlas will provide an adequate spatial reference for mapping the face network.

Cerebellum and personality traits.

Personality traits are multidimensional traits comprising cognitive, emotional, and behavioral characteristics, and a wide array of cerebral structures mediate individual variability. Differences in personality traits covary with brain morphometry in specific brain regions. A cerebellar role in emotional and affective processing and on personality characteristics has been suggested. In a large sample of healthy subjects of both sexes and differently aged, the macro- and micro-structural variations of the cerebellum were correlated with the scores obtained in the Temperament and Character Inventory (TCI) by Cloninger. Cerebellar volumes were associated positively with Novelty Seeking scores and negatively with Harm Avoidance scores. Given the cerebellar contribution in personality traits and emotional processing, we investigated the cerebellar involvement even in alexithymia, construct of personality characterized by impairment in cognitive, emotional, and affective processing. Interestingly, the subjects with high alexithymic traits had larger volumes in the bilateral Crus 1. The cerebellar substrate for some personality dimensions extends the relationship between personality and brain areas to a structure up to now thought to be involved mainly in motor and cognitive functions, much less in emotional processes and even less in personality individual differences. The enlarged volumes of Crus 1 in novelty seekers and alexithymics support the tendency to action featuring both personality constructs. In fact, Novelty Seeking and alexithymia are rooted in behavior and inescapably have a strong action component, resulting in stronger responses in the structures more focused on action and embodiment, as the cerebellum is.

Alpha-theta effects associated with ageing during the Stroop test.

The Stroop effect is considered as a standard attentional measure to study conflict resolution in humans. The response of the brain to conflict is supposed to change over time and it is impaired in certain pathological conditions. Neuropsychological Stroop test measures have been complemented with electroencephalography (EEG) techniques to evaluate the mechanisms in the brain that underlie conflict resolution from the age of 20 to 70. To study the changes in EEG activity during life, we recruited a large sample of healthy subjects of different ages that included 90 healthy individuals, divided by age into decade intervals, which performed the Stroop test while recording a 14 channel EEG. The results highlighted an interaction between age and stimulus that was focused on the prefrontal (Alpha and Theta band) and Occipital (Alpha band) areas. We concluded that behavioural Stroop interference is directly influenced by opposing Alpha and Theta activity and evolves across the decades of life.