Genetic influences on dynamic complexity of brain oscillations

The heritability and structural correlates of resting-state fMRI complexity

The complexity of fMRI signals quantifies temporal dynamics of spontaneous neural activity, which has been increasingly recognized as providing important insights into cognitive functions and psychiatric disorders. However, its heritability and structural underpinnings are not well understood. Here, we utilize multi-scale sample entropy to extract resting-state fMRI complexity in a large healthy adult sample from the Human Connectome Project. We show that fMRI complexity at multiple time scales is heritable in broad brain regions. Heritability estimates are modest and regionally variable. We relate fMRI complexity to brain structure including surface area, cortical myelination, cortical thickness, subcortical volumes, and total brain volume. We find that surface area is negatively correlated with fine-scale complexity and positively correlated with coarse-scale complexity in most cortical regions, especially the association cortex. Most of these correlations are related to common genetic and environmental effects. We also find positive correlations between cortical myelination and fMRI complexity at fine scales and negative correlations at coarse scales in the prefrontal cortex, lateral temporal lobe, precuneus, lateral parietal cortex, and cingulate cortex, with these correlations mainly attributed to common environmental effects. We detect few significant associations between fMRI complexity and cortical thickness. Despite the non-significant association with total brain volume, fMRI complexity exhibits significant correlations with subcortical volumes in the hippocampus, cerebellum, putamen, and pallidum at certain scales. Collectively, our work establishes the genetic basis and structural correlates of resting-state fMRI complexity across multiple scales, supporting its potential application as an endophenotype for psychiatric disorders.

Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications

BACKGROUND

There is a growing consensus that chronological age (CA) is not an accurate indicator of the aging process and that biological age (BA) instead is a better measure of an individual's risk of age-related outcomes and a more accurate predictor of mortality than actual CA. In this context, BA measures the "true" age, which is an integrated result of an individual's level of damage accumulation across all levels of biological organization, along with preserved resources. The BA is plastic and depends upon epigenetics. Brain state is an important factor contributing to health- and lifespan.

METHODS AND OBJECTIVE

Quantitative electroencephalography (qEEG)-derived brain BA (BBA) is a suitable and promising measure of brain aging. In the present study, we aimed to show that BBA can be decelerated or even reversed in humans (N = 89) by using customized programs of nutraceutical compounds or lifestyle changes (mean duration = 13 months).

RESULTS

We observed that BBA was younger than CA in both groups at the end of the intervention. Furthermore, the BBA of the participants in the nutraceuticals group was 2.83 years younger at the endpoint of the intervention compared with their BBA score at the beginning of the intervention, while the BBA of the participants in the lifestyle group was only 0.02 years younger at the end of the intervention. These results were accompanied by improvements in mental-physical health comorbidities in both groups. The pre-intervention BBA score and the sex of the participants were considered confounding factors and analyzed separately.

CONCLUSIONS

Overall, the obtained results support the feasibility of the goal of this study and also provide the first robust evidence that halting and reversal of brain aging are possible in humans within a reasonable (practical) timeframe of approximately one year.

Unraveling the Contribution of Serotonergic Polymorphisms, Prefrontal Alpha Asymmetry, and Individual Alpha Peak Frequency to the Emotion-Related Impulsivity Endophenotype

The unique contribution of the serotonin transporter-linked polymorphic region (5-HTTLPR), intronic region 2 (STin2), and monoamine oxidase A (MAO-A) genes to individual differences in personality traits has been widely explored, and research has shown that certain forms of these polymorphisms relate to impulsivity and impulsivity-related disorders. Humans showing these traits are also described as having an asymmetrical prefrontal cortical activity when compared to others. In this explorative study, we examine the relationship between serotonergic neurotransmission polymorphisms, cortical activity features (prefrontal alpha asymmetry, individual alpha peak frequency [iAPF]), emotion-related and non-emotion-related impulsivity in humans. 5-HTTLPR, MAO-A, and STin2 polymorphisms were assessed in blood taken from 91 participants with high emotion-related impulsivity levels. Sixty-seven participants completed resting electroencephalography and a more comprehensive impulsivity index. In univariate analyses, iAPF correlated with both forms of emotion-related impulsivity. In multiple linear regression models, 5-HTTLPR polymorphism (model 1, adj. R² = 15.2%) and iAPF were significant interacting predictors of emotion-related impulsivity, explaining a large share of the results’ variance (model 2, adj. R² = 21.2%). Carriers of the low transcriptional activity 5-HTTPLR and MAO-A phenotypes obtained higher emotion-related impulsivity scores than others did. No significant results were detected for non-emotion-related impulsivity or for a form of emotion-related impulsivity involving cognitive/motivational reactivity to emotion. Our findings support an endophenotypic approach to impulsivity, showing that tri-allelic 5-HTTLPR polymorphism, iAPF, and their interaction are relevant predictors of one form of emotion-related impulsivity.

Interdisciplinary Approach to Biological and Health Implications in Selected Professional Competences

Everyday life’s hygiene and professional realities, especially in economically developed countries, indicate the need to modify the standards of pro-health programs as well as modern hygiene and work ergonomics programs. These observations are based on the problem of premature death caused by civilization diseases. The biological mechanisms associated with financial risk susceptibility are well described, but there is little data explaining the biological basis of neuroaccounting. Therefore, the aim of the study was to present relationships between personality traits, cognitive competences and biological factors shaping behavioral conditions in a multidisciplinary aspect. This critical review paper is an attempt to compile biological and psychological factors influencing the development of professional competences, especially decent in the area of accounting and finance. We analyzed existing literature from wide range of scientific disciplines (including economics, psychology, behavioral genetics) to create background to pursuit multidisciplinary research models in the field of neuroaccounting. This would help in pointing the best genetically based behavioral profile of future successful financial and accounting specialists.

Causes and Consequences of Interindividual Response Variability: A Call to Apply a More Rigorous Research Design in Acute Exercise-Cognition Studies

The different responses of humans to an apparently equivalent stimulus are called interindividual response variability. This phenomenon has gained more and more attention in research in recent years. The research field of exercise-cognition has also taken up this topic, as shown by a growing number of studies published in the past decade. In this perspective article, we aim to prompt the progress of this research field by (i) discussing the causes and consequences of interindividual variability, (ii) critically examining published studies that have investigated interindividual variability of neurocognitive outcome parameters in response to acute physical exercises, and (iii) providing recommendations for future studies, based on our critical examination. The provided recommendations, which advocate for a more rigorous study design, are intended to help researchers in the field to design studies allowing them to draw robust conclusions. This, in turn, is very likely to foster the development of this research field and the practical application of the findings.

The Electrical Brain Activity in Men with Different Alpha-Rhythm Characteristics during Manual Movements Executed by the Subdominant Hand

Background

The ability to control motor actions and flexibly interact with the environment is considered one of the main components of the human brain executive functions. The spontaneous electroencephalogram (EEG) is among the physiological techniques making it possible to formulate a direct estimation of specific features of the activity of the human brain during manual movements.

Purpose

This study is devoted to an investigation of brain processes in men with a high or a low individual α-frequency determined during manual movements executed by the subdominant hand.

Methods

A test group consisting of 104 right-handed healthy men from the ages of 19 to 21 was divided into 2 groups in terms of the average magnitude of their individual α-frequency (ІαF) - groups with high (n = 53, IαF ≥10.04 Hz) and low (n = 51, IαF ≤10.04 Hz) values of ІαF. The power and coherence of the electrical activity of the cerebral cortex as well as the differences between the groups were evaluated by the testees during manual movements executed by the subdominant hand.

Results

Manual movements executed by the subdominant hand in response to the sensory signals are generally accompanied by the increased coherence of the EEG frequency components, especially, in the frontal, anterior temporal and central brain regions in men with different α-activity characteristics. Under these conditions, it has been found some electrogenesis power lowering in the cortical areas responsible for the sensory analysis, motor programming, sensory and motor information integration. Such changes have been combined with the local power increase of θ-, α1-oscillations in the frontal leads. Additionally, men with a low IαF were characterized by the local growth of α3-activity in the frontal areas of their cortex. Men from both groups also had the generalized increase in the capacity of the high-frequency β2- and γ-oscillations. Some higher power and coherence of the EEG frequency components have been registered in men with the low IαF in comparison with men having some high α-frequency.

Conclusion

The functional content of the established differences may generally reflect some relatively lower tone of the cortex activation in men with a low IαF and can be specifically compensated by some increased "intensity" and the redundancy of brain processes.

Neural complexity as a potential translational biomarker for psychosis

BACKGROUND

The adaptability of the human brain to the constantly changing environment is reduced in patients with psychotic disorders, leading to impaired cognitive functions. Brain signal complexity, which may reflect adaptability, can be readily quantified via resting-state functional magnetic resonance imaging (fMRI) signals. We hypothesized that resting-state brain signal complexity is altered in psychotic disorders, and is correlated with cognitive impairment.

METHODS

We assessed 156 healthy controls (HC) and 330 probands, including 125 patients with psychotic bipolar disorder (BP), 107 patients with schizophrenia (SZ), 98 patients with schizoaffective disorder (SAD) and 230 of their unaffected first-degree relatives (76 BPR, 79 SADR, and 75 SZR) from four sites of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium. Using multi-scale entropy analysis, we determined whether patients and/or relatives had pathologic differences in complexity of resting-state fMRI signals toward regularity (reduced entropy in all time scales), or toward uncorrelated randomness (increased entropy in fine time scales that decays as the time scale increases) and how these complexity differences might be associated with cognitive impairment.

RESULTS

Compared to HC subjects, proband groups showed either decreased complexity toward regularity or toward randomness. SZ probands showed decreased complexity toward regular signal in hypothalamus, and BP probands in left inferior occipital, right precentral and left superior parietal regions, whereas no brain region with decreased complexity toward regularity was found in SAD probands. All proband groups showed significantly increased brain signal randomness in dorsal and ventral prefrontal cortex (PFC), and unaffected relatives showed no complexity differences in PFC regions. SZ had the largest area of involvement in both dorsal and ventral PFC. BP and SAD probands shared increased brain signal randomness in ventral medial PFC, BP and SZ probands shared increased brain signal randomness in ventral lateral PFC, whereas SAD and SZ probands shared increased brain signal randomness in dorsal medial PFC. Only SZ showed increased brain signal randomness in dorsal lateral PFC. The increased brain signal randomness in dorsal or ventral PFC was weakly associated with reduced cognitive performance in psychotic probands.

CONCLUSION

These observations support the loss of brain complexity hypothesis in psychotic probands. Furthermore, we found significant differences as well as overlaps of pathologic brain signal complexity between psychotic probands by DSM diagnoses, thus suggesting a biological approach to categorizing psychosis based on functional neuroimaging data.

Making Brains run Faster: are they Becoming Smarter?

A brief overview of structural and functional brain characteristics related to g is presented in the light of major neurobiological theories of intelligence: Neural Efficiency, P-FIT and Multiple-Demand system. These theories provide a framework to discuss the main objective of the paper: what is the relationship between individual alpha frequency (IAF) and g? Three studies were conducted in order to investigate this relationship: two correlational studies and a third study in which we experimentally induced changes in IAF by means of transcranial alternating current stimulation (tACS). (1) In a large scale study (n = 417), no significant correlations between IAF and IQ were observed. However, in males IAF positively correlated with mental rotation and shape manipulation and with an attentional focus on detail. (2) The second study showed sex-specific correlations between IAF (obtained during task performance) and scope of attention in males and between IAF and reaction time in females. (3) In the third study, individuals’ IAF was increased with tACS. The induced changes in IAF had a disrupting effect on male performance on Raven’s matrices, whereas a mild positive effect was observed for females. Neuro-electric activity after verum tACS showed increased desynchronization in the upper alpha band and dissociation between fronto-parietal and right temporal brain areas during performance on Raven’s matrices. The results are discussed in the light of gender differences in brain structure and activity.

Electrical Activity of the Cerebral Cortex during the Low-Frequency Acoustic Stimulation in Women with Different Characteristics of Alpha Rhythm

BACKGROUND

Human functional capabilities, to a certain extent, depend on an individual's nervous system. The recording of the spontaneous electroencephalogram (EEG) makes it possible to estimate specific features of the nervous system, and in particular the activity of the human brain.

PURPOSE

This study is aimed at investigating the brain in women with a high or a low individual α-frequency (ІαF), determined in a quiescent state during low-frequency acoustic stimulation.

METHODS

The study group consisted of 113 right-handed healthy women in the age group 19-21 years. The study group was divided into 2 categories in terms of the average magnitude of ІαF - groups with high (n = 59, IαF ≥10.25 Hz) and low (n = 54, IαF ≤10.25 Hz) values of ІαF. The power and coherence of electrical activity of the cerebral cortex as well as the differences between the groups were evaluated in a quiescent state during low-frequency acoustic stimulation.

RESULTS

In case of low-frequency acoustic stimulation, a high rate of EEG θ-, β2-power, γ-waves in the cortex, α1-oscillations - in frontal areas were registered in women with a high α-frequency, while the power α2-, α3- and β1-activity became lower in the cortex. Women with a low α-frequency had a decrease of the cerebral cortex α-θ-, α- and β-activity. This was recorded as more generalized, and the expression of γ-waves was more localized. All the participants had increased values of coherence of the EEG frequency components in the cortex. Some overexertion on the right side was detected in the right hemisphere posterior structures. Some local reduction of the coherence of θ-, α1-, α3-oscillations was found in women with a high α-frequency and α1-activity among the study group members with a low α-frequency in the frontal and anterior temporal areas.

CONCLUSION

The establishment of common factors in the study group is an important step towards defining clear prognostic criteria for the physiological capabilities of people based on the congenital features of brain function.

Interactive effect of 5-HTTLPR genotype and age on sources of cortical rhythms in healthy women

This study was aimed to localize the effects of 5-HTTLPR (serotonin-transporter-linked polymorphic region) on the age differences of spontaneous EEG activity in women using neuroimaging analysis sLORETA (Standardized Low Resolution brain Electromagnetic Tomography). DNA samples extracted from cheek swabs and resting-state EEG recorded at 60 standard leads were collected from young (YW, N=86, 18-35years) and older (OW, N=45; 55-80years) healthy women. We have shown that advanced age was associated with increased posterior EEG desynchronization in S'/S'. S' (LG allele was grouped with S alleles owing to its functional equivalence and this group was labeled as S') genotype carriers denoted by decrease of delta - beta1 current source density, and to a lesser extent in L/L homozygotes denoted by decrease in delta activity. In heterozygotes OW, as compared with heterozygotes YW, higher source density estimates of beta1 in frontal and temporal cortex were observed. Age differences were more pronounced in the right hemisphere in S'/S' and L/L carriers and in the left hemisphere in heterozygotes. We also found that in OW, current source density estimates of theta, alpha1, alpha2, alpha3 and beta1 sources in the right occipital lobe were higher in S'/L than in S'/S' carriers. These results may have implications for understanding 5-HTT-dependent variation in the effect of aging on brain activity.

Normalization of Pain-Evoked Neural Responses Using Spontaneous EEG Improves the Performance of EEG-Based Cross-Individual Pain Prediction

An effective physiological pain assessment method that complements the gold standard of self-report is highly desired in pain clinical research and practice. Recent studies have shown that pain-evoked electroencephalography (EEG) responses could be used as a readout of perceived pain intensity. Existing EEG-based pain assessment is normally achieved by cross-individual prediction (i.e., to train a prediction model from a group of individuals and to apply the model on a new individual), so its performance is seriously hampered by the substantial inter-individual variability in pain-evoked EEG responses. In this study, to reduce the inter-individual variability in pain-evoked EEG and to improve the accuracy of cross-individual pain prediction, we examined the relationship between pain-evoked EEG, spontaneous EEG, and pain perception on a pain EEG dataset, where a large number of laser pulses (>100) with a wide energy range were delivered. Motivated by our finding that an individual's pain-evoked EEG responses is significantly correlated with his/her spontaneous EEG in terms of magnitude, we proposed a normalization method for pain-evoked EEG responses using one's spontaneous EEG to reduce the inter-individual variability. In addition, a nonlinear relationship between the level of pain perception and pain-evoked EEG responses was obtained, which inspired us to further develop a new two-stage pain prediction strategy, a binary classification of low-pain and high-pain trials followed by a continuous prediction for high-pain trials only, both of which used spontaneous-EEG-normalized magnitudes of evoked EEG responses as features. Results show that the proposed normalization strategy can effectively reduce the inter-individual variability in pain-evoked responses, and the two-stage pain prediction method can lead to a higher prediction accuracy.

Gender differences in association between serotonin transporter gene polymorphism and resting-state EEG activity

Human brain oscillations represent important features of information processing and are highly heritable. Gender has been observed to affect association between the 5-HTTLPR (serotonin-transporter-linked polymorphic region) polymorphism and various endophenotypes. This study aimed to investigate the effects of 5-HTTLPR on the spontaneous electroencephalography (EEG) activity in healthy male and female subjects. DNA samples extracted from buccal swabs and resting EEG recorded at 60 standard leads were collected from 210 (101 men and 109 women) volunteers. Spectral EEG power estimates and cortical sources of EEG activity were investigated. It was shown that effects of 5-HTTLPR polymorphism on electrical activity of the brain vary as a function of gender. Women with the S/L genotype had greater global EEG power compared to men with the same genotype. In men, current source density was markedly different among genotype groups in only alpha 2 and alpha 3 frequency ranges: S/S allele carriers had higher current source density estimates in the left inferior parietal lobule in comparison with the L/L group. In women, genotype difference in global power asymmetry was found in the central-temporal region. Contrasting L/L and S/L genotype carriers also yielded significant effects in the right hemisphere inferior parietal lobule and the right postcentral gyrus with L/L genotype carriers showing lower current source density estimates than S/L genotype carriers in all but gamma bands. So, in women, the effects of 5-HTTLPR polymorphism were associated with modulation of the EEG activity in a wide range of EEG frequencies. The significance of the results lies in the demonstration of gene by sex interaction with resting EEG that has implications for understanding sex-related differences in affective states, emotion and cognition.

Longitudinal study of EEG frequency maturation and power changes in children on the Russian North

The aim of the study was to reveal longitudinal changes in electroencephalogram spectral power and frequency (percentage frequency composition of EEG and alpha peak frequency) patterns in normal children from northern Russia. Fifteen children (9 girls and 6 boys) participated in the study. The resting state (eyes closed) EEGs were recorded yearly (2005-2013) from age 8 to age 16-17 for each child. EEG frequency patterns were estimated as the percentages of waves with a 1 Hz step revealed by measuring the interval durations between points crossing zero (isoline) by a curve. EEG spectral power changes were analyzed for delta (1.5-4 Hz), theta (4-7.5 Hz), alpha-1 (7.5-9.5 Hz), alpha-2 (9.5-12.5 Hz), beta-1 (12.5-18 Hz) and beta-2 (18-30 Hz) bands. According to the frequency composition of the EEG signals fast synchronous, polymorphous synchronous, polymorphous desynchronous and slow synchronous types of children EEG were revealed. These EEG types were relatively stable during adolescence. In these EEG types, the frequency patterns and spectral power dynamics with age had several common and specific features. Slow wave percentage and spectral power in the delta band remarkably decreased with age in all groups. Starting from the theta band the EEG types were characterized by different EEG spectral power changes with age. In fast synchronous EEG type, the theta and alpha-1 EEG power decreased, and the alpha-2 power increased in the occipital and parietal areas. The polymorphous synchronous type was characterized by increased both the alpha-1 and alpha-2 power with regional peculiarities. In the polymorphous desynchronous type spectral power in all bands decreased with age, and in the slow synchronous type, the alpha-1 power massively increased with age. Obtained results suggest predictive strength of the spatial-frequency patterns in EEG for its following maturation through the years.

Genetic psychophysiology: advances, problems, and future directions

This paper presents an overview of historical advances and the current state of genetic psychophysiology, a rapidly developing interdisciplinary research linking genetics, brain, and human behavior, discusses methodological problems, and outlines future directions of research. The main goals of genetic psychophysiology are to elucidate the neural pathways and mechanisms mediating genetic influences on cognition and emotion, identify intermediate brain-based phenotypes for psychopathology, and provide a functional characterization of genes being discovered by large association studies of behavioral phenotypes. Since the initiation of this neurogenetic approach to human individual differences in the 1970s, numerous twin and family studies have provided strong evidence for heritability of diverse aspects of brain function including resting-state brain oscillations, functional connectivity, and event-related neural activity in a variety of cognitive and emotion processing tasks, as well as peripheral psychophysiological responses. These data indicate large differences in the presence and strength of genetic influences across measures and domains, permitting the selection of heritable characteristics for gene finding studies. More recently, candidate gene association studies began to implicate specific genetic variants in different aspects of neurocognition. However, great caution is needed in pursuing this line of research due to its demonstrated proneness to generate false-positive findings. Recent developments in methods for physiological signal analysis, hemodynamic imaging, and genomic technologies offer new exciting opportunities for the investigation of the interplay between genetic and environmental factors in the development of individual differences in behavior, both normal and abnormal.

Electrical activity of the distal muscles of the hand in men having high or low output alpha-frequencies while performing usual manual movements in response to sensory signals

Background

Human functional capabilities largely depend upon genetic qualities of person’s nervous system. The registration of the spontaneous electroencephalogram (EEG) is among the physiological techniques allowing making a direct estimation of specific features of the nervous system, in particular, the human brain activity.

Purpose

Research is dedicated to the study of distal muscles of the hand, in particular, its functional ability in men with a high or low background EEG α-frequency being in quiescent state or while performing usual manual movements in response to sensory signals.

Methods

A test group consisting of 104 healthy men from the ages of 19 to 21 was divided into two groups according to the magnitude of their individual α- frequency (IAF) median – groups with high (n = 53, IA≥10,04 Hz) and low (n = 51, IAF≤10,03 Hz) levels of IAF. Subjects’ psychodynamic properties of their nervous processes have been evaluated as well as any background and level of changes in the average amplitude of EMG while performing usual manual movements in response to sensory signals and intergroup differences were studied.

Results

It has been found that higher levels of speed and accuracy of the sensorimotor response in men with a high IAF are associated with increased lateral and reciprocal significant differences both in the background muscle activity and efficiency of the distal arm muscles primarily functioning as flexors. But on the contrary, the inverse dynamics appears in men having the low-frequency which is correlated with a lower mobility and balanced nervous processes in their sensorimotor response.

Conclusion

The establishment of such common factors in the experiments groups is an important step towards defining prognostic criteria for the functionality of motor area based on EMG activity of the distal muscles of the hand.

Peak individual alpha frequency qualifies as a stable neurophysiological trait marker in healthy younger and older adults

The individual alpha frequency (IAF) of the human EEG reflects systemic properties of the brain, is highly heritable, and relates to cognitive functioning. Not much is known about the modifiability of IAF by cognitive interventions. We report analyses of resting EEG from a large-scale training study in which healthy younger (20-31 years, N = 30) and older (65-80 years, N = 28) adults practiced 12 cognitive tasks for ∼100 1-h sessions. EEG was recorded before and after the cognitive training intervention. In both age groups, IAF (and, in a control analysis, alpha amplitude) did not change, despite large gains in cognitive performance. As within-session reliability and test-retest stability were high for both age groups, imprecise measurements cannot account for the findings. In sum, IAF is highly stable in healthy adults up to 80 years, not easily modifiable by cognitive interventions alone, and thus qualifies as a stable neurophysiological trait marker.

Lifespan differences in nonlinear dynamics during rest and auditory oddball performance

Electroencephalographic recordings (EEG) were used to assess age-associated differences in nonlinear brain dynamics during both rest and auditory oddball performance in children aged 9.0-12.8 years, younger adults, and older adults. We computed nonlinear coupling dynamics and dimensional complexity, and also determined spectral alpha power as an indicator of cortical reactivity. During rest, both nonlinear coupling and spectral alpha power decreased with age, whereas dimensional complexity increased. In contrast, when attending to the deviant stimulus, nonlinear coupling increased with age, and complexity decreased. Correlational analyses showed that nonlinear measures assessed during auditory oddball performance were reliably related to an independently assessed measure of perceptual speed. We conclude that cortical dynamics during rest and stimulus processing undergo substantial reorganization from childhood to old age, and propose that lifespan age differences in nonlinear dynamics during stimulus processing reflect lifespan changes in the functional organization of neuronal cell assemblies.

Individual variation in cognitive performance: developmental and evolutionary perspectives

Animal cognition experiments frequently reveal striking individual variation but rarely consider its causes and largely ignore its potential consequences. Studies often focus on a subset of high-performing subjects, sometimes viewing evidence from a single individual as sufficient to demonstrate the cognitive capacity of a species. We argue that the emphasis on demonstrating species-level cognitive capacities detracts from the value of individual variation in understanding cognitive development and evolution. We consider developmental and evolutionary interpretations of individual variation and use meta-analyses of data from published studies to examine predictors of individual performance. We show that reliance on small sample sizes precludes robust conclusions about individual abilities as well as inter- and intraspecific differences. We advocate standardization of experimental protocols and pooling of data between laboratories to improve statistical rigour. Our analyses show that cognitive performance is influenced by age, sex, rearing conditions and previous experience. These effects limit the validity of comparative analyses unless developmental histories are taken into account, and complicate attempts to understand how cognitive traits are expressed and selected under natural conditions. Further understanding of cognitive evolution requires efforts to elucidate the heritability of cognitive traits and establish whether elevated cognitive performance confers fitness advantages in nature.

Investigation of changes in EEG complexity during memory retrieval: the effect of midazolam

The aim of this study is applying nonlinear methods to assess changes in brain dynamics in a placebo-controlled study of midazolam-induced amnesia. Subjects injected with saline and midazolam during study, performed old/new recognition memory tests with EEG recording. Based on previous studies, as midazolam causes anterograde amnesia, we expected that midazolam would affect the EEG's degree of complexity. Recurrence quantification analysis, and approximate entropy were used in this assessment. These methods compare with other nonlinear techniques such as computation of the correlation dimension, are suitable for non-stationary EEG signals. Our findings suggest that EEG's complexity decreases during memory retrieval. Although this trend is observed in nonlinear curves related to the midazolam condition, the overall complexity were greater than in the saline condition. This result implies that impaired memory function caused by midazolam is associated with greater EEG's complexity compared to normal memory retrieval in saline injection.

A strong parietal hub in the small-world network of coloured-hearing synaesthetes during resting state EEG

We investigated whether functional brain networks are different in coloured-hearing synaesthetes compared with non-synaesthetes. Based on resting state electroencephalographic (EEG) activity, graph-theoretical analysis was applied to functional connectivity data obtained from different frequency bands (theta, alpha1, alpha2, and beta) of 12 coloured-hearing synaesthetes and 13 non-synaesthetes. The analysis of functional connectivity was based on estimated intra-cerebral sources of brain activation using standardized low-resolution electrical tomography. These intra-cerebral sources of brain activity were subjected to graph-theoretical analysis yielding measures representing small-world network characteristics (cluster coefficients and path length). In addition, brain regions with strong interconnections were identified (so-called hubs), and the interconnectedness of these hubs were quantified using degree as a measure of connectedness. Our analysis was guided by the two-stage model proposed by Hubbard and Ramachandran (2005). In this model, the parietal lobe is thought to play a pivotal role in binding together the synaesthetic perceptions (hyperbinding). In addition, we hypothesized that the auditory cortex and the fusiform gyrus would qualify as strong hubs in synaesthetes. Although synaesthetes and non-synaesthetes demonstrated a similar small-world network topology, the parietal lobe turned out to be a stronger hub in synaesthetes than in non-synaesthetes supporting the two-stage model. The auditory cortex was also identified as a strong hub in these coloured-hearing synaesthetes (for the alpha2 band). Thus, our a priori hypotheses receive strong support. Several additional hubs (for which no a priori hypothesis has been formulated) were found to be different in terms of the degree measure in synaesthetes, with synaesthetes demonstrating stronger degree measures indicating stronger interconnectedness. These hubs were found in brain areas known to be involved in controlling memory processes (alpha1: hippocampus and retrosplenial area), executive functions (alpha1 and alpha2: ventrolateral prefrontal cortex; theta: inferior frontal cortex), and the generation of perceptions (theta: extrastriate cortex; beta: subcentral area). Taken together this graph-theoretical analysis of the resting state EEG supports the two-stage model in demonstrating that the left-sided parietal lobe is a strong hub region, which is stronger functionally interconnected in synaesthetes than in non-synaesthetes. The right-sided auditory cortex is also a strong hub supporting the idea that coloured-hearing synaesthetes demonstrate a specific auditory cortex. A further important point is that these hub regions are even differently operating at rest supporting the idea that these hub characteristics are predetermining factors of coloured-hearing synaesthesia.

Functional brain network efficiency predicts intelligence

The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

The neuroscience of human intelligence differences

Neuroscience is contributing to an understanding of the biological bases of human intelligence differences. This work is principally being conducted along two empirical fronts: genetics--quantitative and molecular--and brain imaging. Quantitative genetic studies have established that there are additive genetic contributions to different aspects of cognitive ability--especially general intelligence--and how they change through the lifespan. Molecular genetic studies have yet to identify reliably reproducible contributions from individual genes. Structural and functional brain-imaging studies have identified differences in brain pathways, especially parieto-frontal pathways, that contribute to intelligence differences. There is also evidence that brain efficiency correlates positively with intelligence.

Genetic contributions to long-range temporal correlations in ongoing oscillations

The amplitude fluctuations of ongoing oscillations in the electroencephalographic (EEG) signal of the human brain show autocorrelations that decay slowly and remain significant at time scales up to tens of seconds. We call these long-range temporal correlations (LRTC). Abnormal LRTC have been observed in several brain pathologies, but it has remained unknown whether genetic factors influence the temporal correlation structure of ongoing oscillations. We recorded the ongoing EEG during eyes-closed rest in 390 monozygotic and dizygotic twins and investigated the temporal structure of ongoing oscillations in the alpha- and beta-frequency bands using detrended fluctuation analysis (DFA). The strength of LRTC was more highly correlated in monozygotic than in dizygotic twins. Statistical analysis attributed up to approximately 60% of the variance in DFA to genetic factors, indicating a high heritability for the temporal structure of amplitude fluctuations in EEG oscillations. Importantly, the DFA and EEG power were uncorrelated. LRTC in ongoing oscillations are robust, heritable, and independent of power, suggesting that LRTC and oscillation power are governed by distinct biophysical mechanisms and serve different functions in the brain. We propose that the DFA method is an important complement to classical spectral analysis in fundamental and clinical research on ongoing oscillations.