There is a growing realization that early life influences have lasting impact on brain function and structure. Recent research has demonstrated that genetic relationships in adults can be used to parcellate the cortex into regions of maximal shared genetic influence, and a major hypothesis is that genetically programmed neurodevelopmental events cause a lasting impact on the organization of the cerebral cortex observable decades later. Here we tested how developmental and lifespan changes in cortical thickness fit the underlying genetic organizational principles of cortical thickness in a longitudinal sample of 974 participants between 4.1 and 88.5 y of age with a total of 1,633 scans, including 773 scans from children below 12 y. Genetic clustering of cortical thickness was based on an independent dataset of 406 adult twins. Developmental and adult age-related changes in cortical thickness followed closely the genetic organization of the cerebral cortex, with change rates varying as a function of genetic similarity between regions. Cortical regions with overlapping genetic architecture showed correlated developmental and adult age change trajectories and vice versa for regions with low genetic overlap. Thus, effects of genes on regional variations in cortical thickness in middle age can be traced to regional differences in neurodevelopmental change rates and extrapolated to further adult aging-related cortical thinning. This finding suggests that genetic factors contribute to cortical changes through life and calls for a lifespan perspective in research aimed at identifying the genetic and environmental determinants of cortical development and aging.here is a growing realization that events during development impact brain and cognition throughout the entire lifespan (1). For instance, the major portion of the relationship between cortical thickness and IQ in old age can be explained by childhood IQ (2), and genotype may explain a substantial part of the lifetime stability in intelligence (3). Effects of genes on the organization of the cortex have been shown in adults (4-6), but it is unknown whether and how regional differences in cortical development correspond to these regional genetic subdivisions.Although consensus has not been reached for the exact trajectories, cortical thickness as measured by MRI appears to decrease in childhood (7-12). The exact foundation for this thinning is not known, as MRI provides merely representations of the underlying neurobiology, and available histological data cannot with certainty be used to guide interpretations of MRI results. Although speculative, apparent thickness decrease may be grounded in factors such as synaptic pruning and intracortical myelination, although the link between established synaptic processes (13-15) and cortical thickness has not been empirically confirmed. After childhood, cortical thinning continues throughout the remainder of the lifespan, speculated to reflect neuronal shrinkage and reductions in number of spines and synapses (16), although sim...

Neurodevelopmental origins of functional variation in older age are increasingly being acknowledged, but identification of how early factors impact human brain and cognition throughout life has remained challenging. Much focus has been on age-specific mechanisms affecting neural foundations of cognition and their change. In contrast to this approach, we tested whether cerebral correlates of general cognitive ability (GCA) in development could be extended to the rest of the lifespan, and whether early factors traceable to prenatal stages, such as birth weight and parental education, may exert continuous influences. We measured the area of the cerebral cortex in a longitudinal sample of 974 individuals aged 4-88 y (1,633 observations). An extensive cortical region was identified wherein area related positively to GCA in development. By tracking area of the cortical region identified in the child sample throughout the lifespan, we showed that the cortical change trajectories of higher and lower GCA groups were parallel through life, suggesting continued influences of early life factors. Birth weight and parental education obtained from the Norwegian Mother-Child Cohort study were identified as such early factors of possible lifelong influence. Support for a genetic component was obtained in a separate twin sample (Vietnam Era Twin Study of Aging), but birth weight in the child sample had an effect on cortical area also when controlling for possible genetic differences in terms of parental height. Our results provide novel evidence for stability in brain-cognition relationships throughout life, and indicate that early life factors impact brain and cognition for the entire life course. development | aging | cortical change I t is well-established that both brain and cognition change with age, and that although there are early gains, older age brings with it decrements in aspects of both (1, 2). Much focus has been on age-specific mechanisms of neural foundations of cognition and their change (3, 4). In contrast, neurodevelopmental origins of functional variation in older age are now increasingly being acknowledged (5-8), but identification of how early factors may impact human brain and cognition throughout the lifespan has remained challenging.General cognitive ability (GCA) is essential to human beings, relates to a multitude of health and social outcomes (9), and necessarily originates in characteristics of the central nervous system at all ages. Paradoxically, even though GCA is highly vulnerable to the influence of aging, there is a remarkable stability in individuals' GCA relative to their same-age peers (10, 11). It has even been shown that childhood GCA can account for GCA-cortical thickness associations in old age (12). Cortical thickness is known to decrease with age monotonously from relatively early childhood through the entire lifespan (6,13,14). This thinning, albeit continuous, signifies different neurobiological events at different stages of life (15, 16), and does not have a stable functional correla...

BackgroundSeveral studies have recently reported on the correlation between objective behavioral features collected via mobile and wearable devices and depressive mood symptoms in patients with affective disorders (unipolar and bipolar disorders). However, individual studies have reported on different and sometimes contradicting results, and no quantitative systematic review of the correlation between objective behavioral features and depressive mood symptoms has been published.ObjectiveThe objectives of this systematic review were to (1) provide an overview of the correlations between objective behavioral features and depressive mood symptoms reported in the literature and (2) investigate the strength and statistical significance of these correlations across studies. The answers to these questions could potentially help identify which objective features have shown most promising results across studies.MethodsWe conducted a systematic review of the scientific literature, reported according to the preferred reporting items for systematic reviews and meta-analyses guidelines. IEEE Xplore, ACM Digital Library, Web of Sciences, PsychINFO, PubMed, DBLP computer science bibliography, HTA, DARE, Scopus, and Science Direct were searched and supplemented by hand examination of reference lists. The search ended on April 27, 2017, and was limited to studies published between 2007 and 2017.ResultsA total of 46 studies were eligible for the review. These studies identified and investigated 85 unique objective behavioral features, covering 17 various sensor data inputs. These features were divided into 7 categories. Several features were found to have statistically significant and consistent correlation directionality with mood assessment (eg, the amount of home stay, sleep duration, and vigorous activity), while others showed directionality discrepancies across the studies (eg, amount of text messages [short message service] sent, time spent between locations, and frequency of mobile phone screen activity).ConclusionsSeveral studies showed consistent and statistically significant correlations between objective behavioral features collected via mobile and wearable devices and depressive mood symptoms. Hence, continuous and everyday monitoring of behavioral aspects in affective disorders could be a promising supplementary objective measure for estimating depressive mood symptoms. However, the evidence is limited by methodological issues in individual studies and by a lack of standardization of (1) the collected objective features, (2) the mood assessment methodology, and (3) the statistical methods applied. Therefore, consistency in data collection and analysis in future studies is needed, making replication studies as well as meta-analyses possible.

Age-related differences in white matter (WM) integrity are substantial, but it is unknown whether between-subject variability in WM integrity influences the capacity for cognitive improvement. We investigated the effects of memory training related to active and passive control conditions in older adults and tested whether WM integrity at baseline was predictive of training benefits. We hypothesized that (1) memory improvement would be restricted to the training group, (2) widespread areas would show greater mean diffusivity (MD) and lower fractional anisotropy in older adults relative to young adults, and (3) within these areas, variability in WM microstructure in the older group would be predictive of training gains. The results showed that only the group receiving training improved their memory. Significant age differences in MD and fractional anisotropy were found in widespread areas. Within these areas, voxelwise analyses showed a negative relationship between MD and memory improvement in 3 clusters, indicating that WM integrity could serve as a marker for the ability to adapt in response to cognitive challenges in aging.

Highly myelinated cortical regions seem to develop early and are more robust to age-related decline. By use of different magnetic resonance imaging (MRI) measures such as contrast between T1- and T2-weighted MRI scans (T1w/T2w) it is now possible to assess correlates of myelin content in vivo. Further, previous studies indicate that gray/white matter contrast (GWC) become blurred as individuals' age, apparently reflecting age-related changes in myelin structure. Here we address whether longitudinal changes in GWC are dependent on initial myelin content within tissue as defined by baseline T1w/T2w contrast, and hypothesize that lightly myelinated regions undergo more decline longitudinally. A sample of 207 healthy adult participants (range: 20-84 years) was scanned twice (interscan interval: 3.6 years). Results showed widespread longitudinal reductions of GWC throughout the cortical surface, especially in the frontal cortices, mainly driven by intensity decay in the white matter. Annual rate of GWC blurring showed acceleration with age in temporal and medial prefrontal regions. Moreover, the anatomical distribution of increased rate of GWC decline with advancing age was strongly related to baseline levels of intracortical myelin. This study provides a first evidence of accelerated regional GWC blurring with advancing age, relates GWC patterns to cortical myeloarchitectonics and supports the hypothesis of increased age-related vulnerability of lightly myelinated areas. Hum Brain Mapp 37:3669-3684, 2016. © 2016 Wiley Periodicals, Inc.

Age differences in human brain plasticity are assumed, but have not been systematically investigated. In this longitudinal study, we investigated changes in white matter (WM) microstructure in response to memory training relative to passive and active control conditions in 183 young and older adults. We hypothesized that (i) only the training group would show improved memory performance and microstructural alterations, (ii) the young adults would show larger memory improvement and a higher degree of microstructural alterations as compared to the older adults, and (iii) changes in memory performance would relate to microstructural alterations. The results showed that memory improvement was specific to the training group, and that both the young and older participants improved their performance. The young group improved their memory to a larger extent compared to the older group. In the older sample, the training group showed less age‐related decline in WM microstructure compared to the control groups, in areas overlapping the corpus callosum, the cortico‐spinal tract, the cingulum bundle, the superior longitudinal fasciculus, and the anterior thalamic radiation. Less microstructural decline was related to a higher degree of memory improvement. Despite individual adaptation securing sufficient task difficulty, no training‐related group differences in microstructure were found in the young adults. The observed divergence of behavioral and microstructural responses to memory training with age is discussed within a supply‐demand framework. The results demonstrate that plasticity is preserved into older age, and that microstructural alterations may be part of a neurobiological substrate for behavioral improvements in older adults. Hum Brain Mapp 38:5666–5680, 2017. © 2018 The Authors Human Brain Mapping Published byWiley Periodicals, Inc.

This paper presents a novel brain-computer interface (BCI) system aiming at the rehabilitation of attention-deficit/hyperactive disorder in children. It uses the P300 potential in a series of feedback games to improve the subjects' attention. We applied a support vector machine (SVM) using temporal and template-based features to detect these P300 responses. In an experimental setup using five subjects, an average error below 30% was achieved. To make it more challenging the BCI system has been embedded inside an immersive 3D virtual reality (VR) classroom with simulated distractions, which was created by combining a low-cost infrared camera and an "off-axis perspective projection" algorithm. This system is intended for kids by operating with four electrodes, as well as a non-intrusive VR setting. With the promising results, and considering the simplicity of the scheme, we hope to encourage future studies to adapt the techniques presented in this study.

Background: A growing population is diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and are currently being treated with psychostimulants. Brain Computer Interface (BCI) is a method of communicating with an external program or device based on measured electrical signals from the brain. A particular brain signal, the P300 potential, can be measured about 300 ms after a voluntary cognitive involvement to external stimuli. By utilizing the P300 potential, we have designed a BCI-assisted exercising tool targeting attention enhancement within an immersive 3D virtual reality (VR) classroom. Methods: Combining a low-cost infrared camera with an "off-axis perspective projection" algorithm to achieve the illusion of 3D, an engaging training environment has been created. The setup also includes a single measurement electrode placed on the scalp above the parietal lobe (Pz). Two sets of experiments have been performed to elicit the P300 potential. One used a system which is a variant of Farwell and Donchin's famous P300 speller and the other used a system where the user is required to search for a specific letter in a series of changing images. A non-linear optimized support vector machine (SVM) classifier has been used to automatically detect the P300 potential. Results: Six subjects have participated in the preliminary experiment to test the prototype system, and an average error rate below 0.30 have been achieved, which is noteworthy considering the simplicity of the scheme. Conclusions:This work has successfully demonstrated a non-intrusive, low-cost, and portable system targeting attention in a motivating and engaging environment.