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Contains fulltext : 249538.pdf (Publisher’s version ) (Open Access) Recently, cognitive neuroscience has experienced unprecedented growth in the availability of large-scale datasets. These developments hold great methodological and theoretical promise: they allow increased statistical power, the use of nonparametric and generative models, the examination of individual differences, and more. Nevertheless, unlike most ´traditional´ cognitive neuroscience research, which uses controlled experimental designs, large-scale projects often collect neuroimaging data not directly related to a particular task (e.g., resting state). This creates a gap between small- and large-scale studies that is not solely due to differences in sample size. Measures obtained with large-scale studies might tap into different neurocognitive mechanisms and thus show little overlap with the mechanisms probed by small-scale studies. In this opinion article, we aim to address this gap and its potential implications for the interpretation of research findings in cognitive neuroscience. 10 p.

Environmental factors may play a role in how the personality trait sensory processing sensitivity (SPS) relates to different health-related outcomes. To better understand vulnerability and resilience in different environments, we investigated associations of SPS with stress-related and neurodevelopmental disorder traits, well-being, and somatic health in a population-based sample of 252 adults. We then tested SPS interactions with lifetime or current measures of positive or negative environments. Overall, higher SPS related to more burnout, anxiety, depression, stress, health complaints and nonprescription medication use, but not to neurodevelopmental disorder traits. Associations with burnout, anxiety, and health complaints remained after controlling for neuroticism. In unfavorable environments, higher SPS related to worse health while, in favorable environments, it related to better health, supporting the theory of SPS as a factor for differential susceptibility to environments. Our work demonstrates that SPS may be a risk factor for stress-related and somatic symptoms, independent of neuroticism.

A common finding in the aging literature is that of the brain's decreased within‐ and increased between‐network functional connectivity. However, it remains unclear what is causing this shift in network organization with age. Given the essential role of the ascending arousal system (ARAS) in cortical activation and previous findings of disrupted ARAS functioning with age, it is possible that age differences in ARAS functioning contribute to disrupted cortical connectivity. We test this possibility here using resting state fMRI data from over 500 individuals across the lifespan from the Cambridge Center for Aging and Neuroscience (Cam‐CAN) population‐based cohort. Our results show that ARAS‐cortical connectivity declines with age and, consistent with our expectations, significantly mediates some age‐related differences in connectivity within and between association networks (specifically, within the default mode and between the default mode and salience networks). Additionally, connectivity between the ARAS and association networks predicted cognitive performance across several tasks over and above the effects of age and connectivity within the cortical networks themselves. These findings suggest that age differences in cortical connectivity may be driven, at least in part, by altered arousal signals from the brainstem and that ARAS–cortical connectivity relates to cognitive performance with age., A common finding in the aging literature is that of the brain's decreased within‐ and increased between‐network functional connectivity. However, it remains unclear what is causing this shift in network organization with age. Our findings suggest that age differences in cortical connectivity may be driven, at least in part, by altered arousal signals from the brainstem and that ARAS–cortical connectivity relates to cognitive performance with age.

Although beta-band activity during motor planning is known to be modulated by uncertainty about where to act, less is known about its modulations to uncertainty about how to act. To investigate this issue, we recorded oscillatory brain activity with EEG while human participants (n = 17) performed a hand choice reaching task. The reaching hand was either predetermined or of participants' choice, and the target was close to one of the two hands or at about equal distance from both. To measure neural activity in a motion artifact-free time window, the location of the upcoming target was cued 1,000-1,500 ms before the presentation of the target, whereby the cue was valid in 50% of trials. As evidence for motor planning during the cuing phase, behavioral observations showed that the cue affected later hand choice. Furthermore, reaction times were longer in the choice trials than in the predetermined trials, supporting the notion of a competitive process for hand selection. Modulations of beta-band power over central cortical regions, but not alpha-band or theta-band power, were in line with these observations. During the cuing period, reaches in predetermined trials were preceded by larger decreases in beta-band power than reaches in choice trials. Cue direction did not affect reaction times or beta-band power, which may be due to the cue being invalid in 50% of trials, retaining effector uncertainty during motor planning. Our findings suggest that effector uncertainty modulates beta-band power during motor planning.NEW & NOTEWORTHY Although reach-related beta-band power in central cortical areas is known to modulate with the number of potential targets, here we show, using a cuing paradigm, that the power in this frequency band, but not in the alpha or theta band, is also modulated by the uncertainty of which hand to use. This finding supports the notion that multiple possible effector-specific actions can be specified in parallel up to the level of motor preparation.

Working memory is critical to higher-order executive processes and declines throughout the adult lifespan. However, our understanding of the neural mechanisms underlying this decline is limited. Recent work suggests that functional connectivity between frontal control and posterior visual regions may be critical, but examinations of age differences therein have been limited to a small set of brain regions and extreme group designs (i.e., comparing young and older adults). In this study, we build on previous research by using a lifespan cohort and a whole-brain approach to investigate working memory load-modulated functional connectivity in relation to age and performance. The article reports on analysis of the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data. Participants from a population-based lifespan cohort (N=111, age 23-86) performed a visual short-term memory task during functional magnetic resonance imaging. Visual short-term memory was measured with a delayed recall task for visual motion with three different loads. Whole-brain load-modulated connectivity was estimated using psychophysiological interactions in a hundred regions of interest, sorted into seven networks (Schaefer et al., 2018, Yeo et al., 2011). Results showed that load-modulated functional connectivity was strongest within the dorsal attention network followed by the visual network during encoding and maintenance. With increasing age, load-modulated functional connectivity strength decreased throughout the cortex. Within the dorsal attention network, increased load-modulated connectivity strength was related to better task performance in an age-invariant way. Our results demonstrate the widespread negative impact of age on the modulation of functional connectivity by working memory load. Older adults might already be close to ceiling in terms of their resources at the lowest load and therefore less able to further increase connectivity with increasing task demands.HighlightsWe examine visual short-term memory load-related functional connectivityAnd how age and performance affect modulation of connectivity by memory loadModulation of connectivity is strongest in dorsal attention and visual networksLoad-modulated connectivity strength decreases with increasing ageLoad-modulated connectivity in the dorsal attention network relates to performance

Working memory and episodic memory are two different processes, although the nature of their interrelationship is debated. As these processes are predominantly studied in isolation, it is unclear whether they crucially rely on different neural substrates. To obtain more insight in this, 81 adults with sub-acute ischemic stroke and 29 elderly controls were assessed on a visual working memory task, followed by a surprise subsequent memory test for the same stimuli. Multivariate, atlas- and track-based lesion-symptom mapping (LSM) analyses were performed to identify anatomical correlates of visual memory. Behavioral results gave moderate evidence for independence between discriminability in working memory and subsequent memory, and strong evidence for a correlation in response bias on the two tasks in stroke patients. LSM analyses suggested there might be independent regions associated with working memory and episodic memory. Lesions in the right arcuate fasciculus were more strongly associated with discriminability in working memory than in subsequent memory, while lesions in the frontal operculum in the right hemisphere were more strongly associated with criterion setting in subsequent memory. These findings support the view that some processes involved in working memory and episodic memory rely on separate mechanisms, while acknowledging that there might also be shared processes. Supplementary Information The online version contains supplementary material available at 10.1007/s00429-021-02281-0.

Because of the high dimensionality of neuroimaging data, identifying a statistical test that is both valid and maximally sensitive is an important challenge. Here, we present a combination of two approaches for functional magnetic resonance imaging (fMRI) data analysis that together result in substantial improvements of the sensitivity of cluster‐based statistics. The first approach is to create novel cluster definitions that optimize sensitivity to plausible effect patterns. The second is to adopt a new approach to combine test statistics with different sensitivity profiles, which we call the min(p) method. These innovations are made possible by using the randomization inference framework. In this article, we report on a set of simulations and analyses of real task fMRI data that demonstrate (a) that the proposed methods control the false‐alarm rate, (b) that the sensitivity profiles of cluster‐based test statistics vary depending on the cluster defining thresholds and cluster definitions, and (c) that the min(p) method for combining these test statistics results in a drastic increase of sensitivity (up to fivefold), compared to existing fMRI analysis methods. This increase in sensitivity is not at the expense of the spatial specificity of the inference., We present a combination of two approaches for functional magnetic resonance imaging data analysis that together result in substantial improvements of the sensitivity of cluster‐based statistics. The first approach is to create novel cluster definitions that optimize sensitivity to plausible effect patterns. The second is the min(p) method, which is a novel way of combining test statistics with different sensitivity profiles.

Background: Variability in cognitive functions in healthy and pathological aging is often explained by educational attainment. However, it remains unclear to which extent different disease states alter protective effects of education. We aimed to investigate whether protective effects of education on cognition depend on (1) clinical diagnosis severity, and (2) the neuropathological burden within a diagnosis in a memory clinic setting.Methods: In this cross-sectional study, we included 108 patients with subjective cognitive decline [SCD, median age 71, IQR (66–78), 43% men], 190 with mild cognitive impairment [MCI, median age 78, IQR (73–82), 44% men], and 245 with Alzheimer’s disease dementia (AD) [median age 80, IQR (76–84), 35% men]. We combined visual ratings of hippocampal atrophy, global atrophy, and white matter hyperintensities on MRI into a single neuropathology score. To investigate whether the contribution of education to cognitive performance differed across SCD, MCI, and AD, we employed several multiple linear regression models, stratified by diagnosis and adjusted for age, sex, and neurodegeneration. We re-ran each model with an additional interaction term to investigate whether these effects were influenced by neuropathological burden for each diagnostic group separately. False discovery rate (FDR) corrections for multiple comparisons were applied.Results: We observed significant positive associations between education and performance for global cognition and executive functions (all adjusted p-values < 0.05). As diagnosis became more severe, however, the strength of these associations decreased (all adjusted p-values < 0.05). Education related to episodic memory only at relatively lower levels of neuropathology in SCD (β = −0.23, uncorrected p = 0.02), whereas education related to episodic memory in those with higher levels of neuropathology in MCI (β = 0.15, uncorrected p = 0.04). However, these interaction effects did not survive FDR-corrections.Conclusions: Altogether, our results demonstrated that positive effects of education on cognitive functioning reduce with diagnosis severity, but the role of neuropathological burden within a particular diagnosis was small and warrants further investigation. Future studies may further unravel the extent to which different dimensions of an individual’s disease severity contribute to the waxing and waning of protective effects in cognitive aging.

Visual representations can be generated via feedforward or feedback processes. The extent to which these processes result in overlapping representations remains unclear. Previous work has shown that imagined stimuli elicit similar representations as perceived stimuli throughout the visual cortex. However, while representations during imagery are indeed only caused by feedback processing, neural processing during perception is an interplay of both feedforward and feedback processing. This means that any overlap could be due to overlap in feedback processes. In the current study we aimed to investigate this issue by characterizing the overlap between feedforward- and feedback-initiated category-representations during imagery, conscious perception and unconscious processing using fMRI. While all three conditions elicited stimulus representations in left lateral occipital cortex (LOC), significant similarities were only observed between imagery and conscious perception in this area. Furthermore, PPI-analyses revealed stronger connectivity between frontal areas and left LOC during conscious perception and imagery compared to unconscious processing. Together, these findings can be explained by the idea that long-range feedback modifies visual representations, thereby reducing neural overlap between purely feedforward and feedback-initiated stimulus representations measured by fMRI. Neural representations caused by feedback, either stimulus-driven (perception) or internally-driven (imagery), are however relatively similar.

Naturalistic stimuli (e.g., movies) provide the opportunity to study lifelike experiences in the lab. While young adults respond to these stimuli in a highly synchronized manner [as indexed by intersubject correlations (ISC) in their neural activity], older adults respond more idiosyncratically. Here, we examine whether eye-movement synchrony (eye-ISC) also declines with age during movie-watching and whether it relates to memory for the movie. Our results show no age-related decline in eye-ISC, suggesting that age differences in neural ISC are not caused by differences in viewing patterns. Both age groups recalled the same number of episodic details from the movie, but older adults recalled proportionally fewer episodic details due to their greater output of semantic and false information. In both age groups, higher eye-ISC related to a higher proportion of internal details and a lower proportion of false information being recalled. Finally, both older and younger adults showed better cued recall for cues taken from within the same event than those spanning an event boundary, further confirming that events are stored in long-term memory as discrete units with stronger associations within than across event boundaries. Taken together, these findings suggest that naturalistic stimuli drive perception in a similar way in younger and older adults, but age differences in neural synchrony further up the information processing stream may contribute to subtle differences in event memory. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Contains fulltext : 226126.pdf (Publisher’s version ) (Open Access) The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical phenotype such as age-group, disease condition or mental state. To do so reliably, it is necessary to determine the features of the connectivity structure that are common across a group of brain scans. Given the complex interdependencies inherent in network data, this is not a straightforward task. Some studies construct a group-representative network (GRN), ignoring individual differences, while other studies analyse networks for each individual independently, ignoring information that is shared across individuals. We propose a Bayesian framework based on exponential random graph models (ERGM) extended to multiple networks to characterise the distribution of an entire population of networks. Using resting-state fMRI data from the Cam-CAN project, a study on healthy ageing, we demonstrate how our method can be used to characterise and compare the brain’s functional connectivity structure across a group of young individuals and a group of old individuals. 12 p.

Contains fulltext : 230769.pdf (Publisher’s version ) (Open Access) Visual memory for objects involves the integration, or binding, of individual features into a coherent representation. We used a novel approach to assess feature binding, using a delayed-reproduction task in combination with computational modeling and lesion analysis. We assessed stroke patients and neurotypical controls on a visual working memory task in which spatial arrays of colored disks were presented. After a brief delay, participants either had to report the color of one disk cued by its location or the location of one disk cued by its color. Our results demonstrate that, in the controls, report imprecision and swap errors (non-target reports) can be explained by a single source of variability. Stroke patients showed an overall decrease in memory precision for both color and location, with only limited evidence for deviations from the predicted relationship between report precision and swap errors. These deviations were primarily deficits in reporting items rather than selecting items based on the cue. Atlas-based lesion-symptom mapping showed that selection and reporting deficits, precision in reporting color, and precision in reporting location were associated with different lesion profiles. Deficits in binding are associated with lesions in the left somatosensory cortex, deficits in the precision of reporting color with bilateral fronto-parietal regions, and no anatomical substrates were identified for precision in reporting location. Our results converge with previous reports that working memory representations are widely distributed in the brain and can be found across sensory, parietal, temporal, and prefrontal cortices. Stroke patients demonstrate mostly subtle impairments in visual working memory, perhaps because representations from different areas in the brain can partly compensate for impaired encoding in lesioned areas. These findings contribute to understanding of the relation between memorizing features and their bound representations. 12 p.

Contains fulltext : 237528.pdf (Publisher’s version ) (Open Access) Visual representations can be generated via feedforward or feedback processes. The extent to which these processes result in overlapping representations remains unclear. Previous work has shown that imagined stimuli elicit similar representations as perceived stimuli throughout the visual cortex. However, while representations during imagery are indeed only caused by feedback processing, neural processing during perception is an interplay of both feedforward and feedback processing. This means that any representational overlap could be due to overlap in feedback processes. In the current study we aimed to investigate this issue by characterizing the overlap between feedforward- and feedback-initiated category-representations during imagery, conscious perception and unconscious processing using fMRI in humans of either sex. While all three conditions elicited stimulus representations in left lateral occipital cortex (LOC), significant similarities were only observed between imagery and conscious perception in this area. Furthermore, connectivity analyses revealed stronger connectivity between frontal areas and left LOC during conscious perception and imagery compared to unconscious processing. Together, these findings can be explained by the idea that long-range feedback modifies visual representations, thereby reducing representational overlap between purely feedforward and feedback-initiated stimulus representations measured by fMRI. Neural representations influenced by feedback, either stimulus-driven (perception) or purely internally-driven (imagery), are however relatively similar.Significance statementPrevious research has shown substantial neural overlap between imagery and perception, suggesting overlap between bottom-up and top-down processes. However, because conscious perception also involves top-down processing, this overlap could instead reflect similarity in feedback processes. In this study, we showed that the overlap between perception and imagery disappears when stimuli are rendered unconscious via backward masking, suggesting reduced overlap between purely bottom-up and top-down generated representations. 13 p.

Contains fulltext : 237452.pdf (Publisher’s version ) (Open Access) Healthy aging is accompanied by progressive decline in cognitive performance and concomitant changes in brain structure and functional architecture. Age-accompanied alterations in brain function have been characterized on a network level as weaker functional connections within brain networks along with stronger interactions between networks. This phenomenon has been described as age-related differences in functional network segregation. It has been suggested that functional networks related to associative processes are particularly sensitive to age-related deterioration in segregation, possibly related to cognitive decline in aging. However, there have been only a few longitudinal studies with inconclusive results. Here, we used a large longitudinal sample of 284 participants between 25 to 80 years of age at baseline, with cognitive and neuroimaging data collected at up to three time points over a 10-year period. We investigated age-related changes in functional segregation among two large-scale systems comprising associative and sensorimotor-related resting-state networks. We found that functional segregation of associative systems declines in aging with exacerbated deterioration from the late fifties. Changes in associative segregation were positively associated with changes in global cognitive ability, suggesting that decreased segregation has negative consequences for domain-general cognitive functions. Age-related changes in system segregation were partly accounted for by changes in white matter integrity, but white matter integrity only weakly influenced the association between segregation and cognition. Together, these novel findings suggest a cascade where reduced white-matter integrity leads to less distinctive functional systems which in turn contributes to cognitive decline in aging. 13 p.

Segmenting perceptual experience into meaningful events is a key cognitive process that helps us make sense of what is happening around us in the moment, as well as helping us recall past events. Nevertheless, little is known about the underlying neural mechanisms of the event segmentation process. Recent work has suggested that event segmentation can be linked to regional changes in neural activity patterns. Accurate methods for identifying such activity changes are important to allow further investigation of the neural basis of event segmentation and its link to the temporal processing hierarchy of the brain. In this study, we introduce a new set of elegant and simple methods to study these mechanisms. We introduce a method for identifying the boundaries between neural states in a brain area and a complementary one for identifying the number of neural states. Furthermore, we present the results of a comprehensive set of simulations and analyses of empirical fMRI data to provide guidelines for reliable estimation of neural states and show that our proposed methods outperform the current state-of-the-art in the literature. This methodological innovation will allow researchers to make headway in investigating the neural basis of event segmentation and information processing during naturalistic stimulation.HighlightsBoundaries between meaningful events are related to neural state transitions.Neural states are temporarily stable regional brain activity patterns.We introduce novel methods for data-driven detection of neural state boundaries.These methods can identify the location and the number of neural state boundaries.Simulations and empirical data support the reliability and validity of our methods.

Naturalistic stimuli (e.g., movies) provide the opportunity to study lifelike experiences in the lab. While young adults respond to these stimuli in a highly synchronized manner (as indexed by intersubject correlations [ISC] in their neural activity), older adults respond more idiosyncratically. Here, we examine whether eye movement synchrony (eye-ISC) also declines with age during movie-watching and whether it relates to memory for the movie. Our results show no age-related decline in eye-ISC, suggesting that age differences in neural ISC are not caused by differences in viewing patterns. Both age groups recalled the same number of episodic details from the movie, however, older adults recalled more semantic and false information. In both age groups, more recall of false information related to lower eye-ISC. Finally, older adults showed better cued-recall than younger adults across event boundaries, suggesting that older adults may form broader associations across events when encoding everyday experiences.

Cardiovascular health declines with age, increasing the risk of hypertension and elevated heart rate in middle and old age. Here, we used multivariate techniques to investigate the associations between cardiovascular health (diastolic blood pressure, systolic blood pressure, and heart rate) and white matter macrostructure (lesion volume and number) and microstructure (as measured by diffusion-weighted imaging) in the cross-sectional, population-based Cam-CAN cohort (N = 667, aged 18–88). We found that cardiovascular health and age made approximately similar contributions to white matter health and explained up to 56% of variance therein. Lower diastolic blood pressure, higher systolic blood pressure, and higher heart rate were each strongly, and independently, associated with white matter abnormalities on all indices. Body mass and exercise were associated with white matter health, both directly and indirectly via cardiovascular health. These results highlight the importance of cardiovascular risk factors for white matter health across the adult lifespan and suggest that systolic blood pressure, diastolic blood pressure, and heart rate affect white matter health via separate mechanisms., Highlights • Cardiovascular health is related to white matter lesion burden and diffusivity. • Low diastolic pressure, high systolic pressure, and higher heart rate contribute independently. • Cardiovascular health and age explain up to 56% of variance in white matter health. • The uncinate fasciculus, inferior fronto-occipital fasciculus, and forceps minor show most sensitivity. • Lower BMI and more exercise may have protective effects.

Contains fulltext : 195401.pdf (Author’s version postprint ) (Open Access) We know how age affects the brain during lab-based tasks, but what about situations truer to everyday life, such as watching movies? We measured fMRI activity while participants (N=577) from the Cambridge Centre for Ageing and Neuroscience (www.cam-can.com) watched a movie. Watching the same movie induces significant inter-subject synchronization of brain activity across participants. These cross-subject correlations suggest that viewers are processing incoming information in a similar (or shared) way. We show that with advancing age, synchrony is preserved in some areas, including the language network, but decreased in others, including the medial prefrontal cortex, medial temporal lobe and fronto-parietal network. Synchrony declines were driven by more idiosyncratic responding in older adults and were associated with regionally-distinct temporal profiles and functional connectivity patterns, as well as declines in white matter integrity. These findings suggest that areas involved in language processing remain intact with age, while regions involved in attentional control and memory may show age-related declines, even in situations similar to daily life. 15 p.

Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brain's functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured dFC may be caused by other sources of heterogeneity between people. For example, the shape of the haemodynamic response function (HRF) and levels of measurement noise have been found to vary with age. We use a generic simulation framework for fMRI data to investigate the effect of such heterogeneity on estimates of dFC. Our findings show that, despite no differences in true dFC, individual differences in measured dFC can result from other (non-dynamic) features of the data, such as differences in neural autocorrelation, HRF shape, connectivity strength and measurement noise. We also find that common dFC methods such as k-means and multilayer modularity approaches can detect spurious group differences in dynamic connectivity due to inappropriate setting of their hyperparameters. fMRI studies therefore need to consider alternative sources of heterogeneity across individuals before concluding differences in dFC., Graphical abstract fx1, Highlights • Estimates of dFC may be affected by various sources of between-people heterogeneity. • We simulated fMRI data to investigate the effect of such heterogeneity on dFC. • Differences in estimated dFC resulted from non-dynamic features of the data. • Choice of parameters in common methods produced spurious group differences in dFC.

Many studies report individual differences in functional connectivity, such as those related to age. However, estimates of connectivity from fMRI are confounded by other factors, such as vascular health, head motion and changes in the location of functional regions. Here, we investigate the impact of these confounds, and pre-processing strategies that can mitigate them, using data from the Cambridge Centre for Ageing & Neuroscience (www.cam-can.com). This dataset contained two sessions of resting-state fMRI from 214 adults aged 18–88. Functional connectivity between all regions was strongly related to vascular health, most likely reflecting respiratory and cardiac signals. These variations in mean connectivity limit the validity of between-participant comparisons of connectivity estimates, and were best mitigated by regression of mean connectivity over participants. We also showed that high-pass filtering, instead of band-pass filtering, produced stronger and more reliable age-effects. Head motion was correlated with gray-matter volume in selected brain regions, and with various cognitive measures, suggesting that it has a biological (trait) component, and warning against regressing out motion over participants. Finally, we showed that the location of functional regions was more variable in older adults, which was alleviated by smoothing the data, or using a multivariate measure of connectivity. These results demonstrate that analysis choices have a dramatic impact on connectivity differences between individuals, ultimately affecting the associations found between connectivity and cognition. It is important that fMRI connectivity studies address these issues, and we suggest a number of ways to optimize analysis choices. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

Because of the high dimensionality of neuroimaging data, identifying a statistical test that is both valid and maximally sensitive is an important challenge. Here, we present a combination of two approaches for functional magnetic resonance imaging (fMRI) data analysis that together result in substantial improvements of the sensitivity of cluster-based statistics. The first approach is to create novel cluster definitions that optimize sensitivity to plausible effect patterns. The second is to adopt a new approach to combine test statistics with different sensitivity profiles, which we call the min(p) method. These innovations are made possible by using the randomization inference framework. In this article, we report on a set of simulations and analyses of real task fMRI data that demonstrate (a) that the proposed methods control the false-alarm rate, (b) that the sensitivity profiles of cluster-based test statistics vary depending on the cluster defining thresholds and cluster definitions, and (c) that the min(p) method for combining these test statistics results in a drastic increase of sensitivity (up to fivefold), compared to existing fMRI analysis methods. This increase in sensitivity is not at the expense of the spatial specificity of the inference.

The adaption of movement to changes in the environment varies across life span. Recent evidence has linked motor adaptation and its reduction with age to differences in “explicit” learning processes. We examine differences in brain structure and cognition underlying motor adaptation in a population-based cohort (n = 322, aged 18–89 years) using a visuomotor learning task and structural magnetic resonance imaging. Reduced motor adaptation with age was associated with reduced volume in striatum, prefrontal, and sensorimotor cortical regions, but not cerebellum. Medial temporal lobe volume, including the hippocampus, became a stronger determinant of motor adaptation with age. Consistent with the role of the medial temporal lobes, declarative long-term memory showed a similar interaction, whereby memory was more positively correlated with motor adaptation with increasing age. By contrast, visual short-term memory was related to motor adaptation, independently of age. These results support the hypothesis that cerebellar learning is largely unaffected in old age, and the reduction in motor adaptation with age is driven by a decline in explicit memory systems., Highlights • Reduced motor adaptation with age relates to less graey matter in motor regions. • These regions are striatum, premotor and prefrontal cortex, but not the cerebellum. • With age, motor adaptation is more positively related to medial temporal lobe areas. • Motor adaptation relates to short-term memory measures regardless of age. • With age, motor adaptation is more positively related to long-term memory scores.

The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical phenotype such as age-group, disease condition or mental state. To do so reliably, it is necessary to determine the features of the connectivity structure that are common across a group of brain scans. Given the complex interdependencies inherent in network data, this is not a straightforward task. Some studies construct a group-representative network (GRN), ignoring individual differences, while other studies analyse networks for each individual independently, ignoring information that is shared across individuals. We propose a Bayesian framework based on exponential random graph models (ERGM) extended to multiple networks to characterise the distribution of a entire population of networks. Using resting-state fMRI data from the Cam-CAN project, a study on healthy ageing, we demonstrate how our method can be used to characterise and compare the brain's functional connectivity structure across a group of young individuals and a group of old individuals.

A large body of research shows that aging is accompanied by localized changes in brain structure and function. However, over the past decade the neuroimaging community has begun to recognize the importance of investigating the brain as a network. Brain regions don’t function independently, rather they form an expansive network that allows for communication between distant areas and enables complex cognitive functioning. Hence, age-related changes in the network structure might explain changes in cognitive functioning.Characterizing this network by investigating the brain’s functional connectivity has enabled new insights into brain organization. In this chapter, we will outline how the brain’s functional connectivity is affected by aging and how changes in functional connectivity relate to changes in cognitive functioning. We will address how neurodegenerative pathology influences functional connectivity and how, based on these measurements, biomarkers for clinical outcome might be developed in the future.

Item does not contain fulltext This is a commentary on Campbell and Schacter (2016), "Ageing and the resting state: Is cognition obsolete?" (Journal Language, Cognition and Neuroscience, Advance online publication. http://doi.org/10.1080/23273798.2016.1227858). Campbell and Schacter argue that resting state data have a limited ability to contribute to the study of neurocognitive ageing and that the field should focus more on results from carefully controlled experimental designs. In this commentary, we argue for a different perspective on future research directions in neurocognitive ageing. Specifically for the need to use a more integrative approach; combining rest and task data as well as information from different modalities to obtain a better understanding of the neural mechanisms that underlie healthy cognitive ageing. Potential benefits of this integrative approach are illustrated with a number of examples. In addition, we discuss some of the advantages of using resting state data as part of this integrative approach. 8 p.

Neuroticism and genetic variation in the serotonin-transporter (SLC6A4) and catechol-O-methyltransferase (COMT) gene are risk factors for psychopathology. Alterations in the functional integration and segregation of neural circuits have recently been found in individuals scoring higher on neuroticism. The aim of the current study was to investigate how genetic risk factors impact functional network organization and whether genetic risk factors moderate the association between neuroticism and functional network organization. We applied graph theory analysis on resting-state fMRI data in a sample of 120 women selected based on their neuroticism score, and genotyped two polymorphisms: 5-HTTLPR (S-carriers and L-homozygotes) and COMT (rs4680-rs165599; COMT risk group and COMT non-risk group). For the 5-HTTLPR polymorphism, we found that subnetworks related to cognitive control show less connections with other subnetworks in S-carriers compared to L-homozygotes. The COMT polymorphism moderated the association between neuroticism and functional network organization. We found that neuroticism was associated with lower efficiency coefficients in visual and somatosensory-motor subnetworks in the COMT risk group compared to the COMT non-risk group. The findings of altered topology of specific subnetworks point to different cognitive-emotional processes that may be affected in relation to the genetic risk factors, concerning emotion regulation in S-carriers (5-HTTLPR) and emotional salience processing in COMT risk carriers. Electronic supplementary material The online version of this article (doi:10.1007/s11682-016-9626-2) contains supplementary material, which is available to authorized users.

Focal lesions can affect connectivity between distal brain regions (connectional diaschisis) and impact the graph-theoretic properties of major brain networks (connectomic diaschisis). Given its unique anatomy and diverse range of functions, the hippocampus has been claimed to be a critical "hub" in brain networks. We investigated the effects of hippocampal lesions on structural and functional connectivity in six patients with amnesia, using a range of magnetic resonance imaging (MRI) analyses. Neuropsychological assessment revealed marked episodic memory impairment and generally intact performance across other cognitive domains. The hippocampus was the only brain structure exhibiting reduced grey-matter volume that was consistent across patients, and the fornix was the only major white-matter tract to show altered structural connectivity according to both diffusion metrics. Nonetheless, functional MRI revealed both increases and decreases in functional connectivity. Analysis at the level of regions within the default-mode network revealed reduced functional connectivity, including between nonhippocampal regions (connectional diaschisis). Analysis at the level of functional networks revealed reduced connectivity between thalamic and precuneus networks, but increased connectivity between the default-mode network and frontal executive network. The overall functional connectome showed evidence of increased functional segregation in patients (connectomic diaschisis). Together, these results point to dynamic reorganization following hippocampal lesions, with both decreased and increased functional connectivity involving limbic-diencephalic structures and larger-scale networks. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.

Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on “distance correlation”; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across sessions, 2) more similar across participants, and 3) more robust to different sets of ROIs. Moreover, we found that the similarity between functional connectivity and structural covariance estimates was higher for distance correlation compared to Pearson correlation. We also explored the relative effects of different preprocessing options and motion artefacts on functional connectivity. Because distance correlation is easy to implement and fast to compute, it is a promising alternative to Pearson correlations for investigating ROI-based brain-wide connectivity patterns, for functional as well as structural data., Highlights • We introduce distance correlation as a new measure of ROI-based connectivity. • It can be used for functional connectivity and structural covariance analyses. • Simulations show that distance correlation copes with inhomogeneous ROIs. • In real data, distance correlation is more reliable and robust than Pearson correlation. • Distance correlation improves correspondence between different ROI definitions.

The personality trait neuroticism is a potent risk marker for psychopathology. Although the neurobiological basis remains unclear, studies have suggested that alterations in connectivity may underlie it. Therefore, the aim of the current study was to shed more light on the functional network organization in neuroticism. To this end, we applied graph theory on resting-state functional magnetic resonance imaging (fMRI) data in 120 women selected based on their neuroticism score. Binary and weighted brain-wide graphs were constructed to examine changes in the functional network structure and functional connectivity strength. Furthermore, graphs were partitioned into modules to specifically investigate connectivity within and between functional subnetworks related to emotion processing and cognitive control. Subsequently, complex network measures (ie, efficiency and modularity) were calculated on the brain-wide graphs and modules, and correlated with neuroticism scores. Compared with low neurotic individuals, high neurotic individuals exhibited a whole-brain network structure resembling more that of a random network and had overall weaker functional connections. Furthermore, in these high neurotic individuals, functional subnetworks could be delineated less clearly and the majority of these subnetworks showed lower efficiency, while the affective subnetwork showed higher efficiency. In addition, the cingulo-operculum subnetwork demonstrated more ties with other functional subnetworks in association with neuroticism. In conclusion, the 'neurotic brain' has a less than optimal functional network organization and shows signs of functional disconnectivity. Moreover, in high compared with low neurotic individuals, emotion and salience subnetworks have a more prominent role in the information exchange, while sensory(-motor) and cognitive control subnetworks have a less prominent role.

Slowing is a common feature of ageing, yet a direct relationship between neural slowing and brain atrophy is yet to be established in healthy humans. We combine magnetoencephalographic (MEG) measures of neural processing speed with magnetic resonance imaging (MRI) measures of white and grey matter in a large population-derived cohort to investigate the relationship between age-related structural differences and visual evoked field (VEF) and auditory evoked field (AEF) delay across two different tasks. Here we use a novel technique to show that VEFs exhibit a constant delay, whereas AEFs exhibit delay that accumulates over time. White-matter (WM) microstructure in the optic radiation partially mediates visual delay, suggesting increased transmission time, whereas grey matter (GM) in auditory cortex partially mediates auditory delay, suggesting less efficient local processing. Our results demonstrate that age has dissociable effects on neural processing speed, and that these effects relate to different types of brain atrophy., Neural processing speed slows with age, but the relationship between this slowing and brain atrophy is unknown. Here, authors show that age-related functional brain differences in auditory and visual processing are partly due to structural differences in the distinct brain regions underlying these processes.

Aging affects functional connectivity between brain areas, however, a complete picture of how aging affects integration of information within and between functional networks is missing. We used complex network measures, derived from a brain-wide graph, to provide a comprehensive overview of age-related changes in functional connectivity. Functional connectivity in young and older participants was assessed during resting-state fMRI. The results show that aging has a large impact, not only on connectivity within functional networks but also on connectivity between the different functional networks in the brain. Brain networks in the elderly showed decreased modularity (less distinct functional networks) and decreased local efficiency. Connectivity decreased with age within networks supporting higher level cognitive functions, that is, within the default mode, cingulo-opercular and fronto-parietal control networks. Conversely, no changes in connectivity within the somatomotor and visual networks, networks implicated in primary information processing, were observed. Connectivity between these networks even increased with age. A brain-wide analysis approach of functional connectivity in the aging brain thus seems fundamental in understanding how age affects integration of information.

Item does not contain fulltext Remitted patients with major depressive disorder (rMDD) often report more fluctuations in mood as residual symptomatology. It is unclear how this affective instability is associated with information processing related to the default mode (DMS), salience/reward (SRS) and fronto-parietal (FPS) subnetworks in rMDD patients at high risk of recurrence (rrMDD). Sixty-two unipolar, drug-free rrMDD patients ([ges]2 MDD-episodes) and 41 HC (HC) were recruited. We used Experience Sampling Methodology (ESM) to monitor mood/cognitions (10 times a day for 6 days) and calculated affective instability using the mean adjusted absolute successive difference. Subsequently, we collected resting-state functional Magnetic Resonance Imaging data and performed graph theory to obtain network metrics of integration within (local efficiency) the DMS, SRS and FPS, and between (participation coefficient) these subnetworks and others. In rrMDD patients compared to HC, we found that affective instability was increased in most negative mood/cognition variables and that the DMS had less connections with other subnetworks. Furthermore, we found that rrMDD patients, who showed more instability in feeling down and irritated, had less connections between the SRS and other subnetworks and higher local efficiency coefficients in the FPS, respectively. In conclusion, rrMDD patients, compared to HC, are less stable in their negative mood and these dynamics are related to differences in information processing within and between specific functional subnetworks. These results are a first step to gain a better understanding of how mood fluctuations in real-life are represented in the brain and provide insights in the vulnerability profile of MDD. 10 p.

Many studies report individual differences in functional connectivity, such as those related to age. However, estimates of connectivity from fMRI are confounded by other factors, such as vascular health, head motion and changes in the location of functional regions. Here, we investigate the impact of these confounds, and pre‐processing strategies that can mitigate them, using data from the Cambridge Centre for Ageing & Neuroscience (www.cam-can.com). This dataset contained two sessions of resting‐state fMRI from 214 adults aged 18–88. Functional connectivity between all regions was strongly related to vascular health, most likely reflecting respiratory and cardiac signals. These variations in mean connectivity limit the validity of between‐participant comparisons of connectivity estimates, and were best mitigated by regression of mean connectivity over participants. We also showed that high‐pass filtering, instead of band‐pass filtering, produced stronger and more reliable age‐effects. Head motion was correlated with gray‐matter volume in selected brain regions, and with various cognitive measures, suggesting that it has a biological (trait) component, and warning against regressing out motion over participants. Finally, we showed that the location of functional regions was more variable in older adults, which was alleviated by smoothing the data, or using a multivariate measure of connectivity. These results demonstrate that analysis choices have a dramatic impact on connectivity differences between individuals, ultimately affecting the associations found between connectivity and cognition. It is important that fMRI connectivity studies address these issues, and we suggest a number of ways to optimize analysis choices. Hum Brain Mapp 38:4125–4156, 2017. © 2017 Wiley Periodicals, Inc.

There are errors in the fourth and fifth sentences of the Abstract. The correct sentences are: Our results indicated that a higher BOLD response in the VLPFC was associated with increased performance accuracy in older adults, in the more complex task condition. This ‘BOLD-performance’ relationship suggests that the neural correlates linked with successful performance in the older adults are related to specific working memory processes present in the complex but not in the baseline task condition.There are errors in the second and third sentences of the second paragraph of the “Independent component analysis (ICA)” portion of the “fMRI image analysis” subsection of the Materials and Methods. The correct sentences are: The GLM design matrix was based on the task events (onsets), as well as the movement parameters derived from the realignment step and their first derivatives and a high pass filter of 230 seconds, implemented using a discrete cosine transform (DCT) set. The task events were convolved with three basis functions of the hemodynamic response function (HRF): the canonical HRF, its time derivative and its dispersion derivative.There are multiple errors throughout the “Performance and age” section of the Results. The correct text is: Older adults had a mean accuracy cost of.23 (SD = .12) and a mean speed cost of.47 (.19). Younger adults had a mean accuracy cost of.08 (.04) and a mean speed cost of.31 (.18). Coefficients for the main effects of age on accuracy and speed cost were based on the regression model assessing the effects of age and/or BOLD load effect in the VLPFC component. Older adults had a higher accuracy cost (β age = .147, t(74) = 7.08, p < .0005; R2 = .419, F(3,74) = 18.8, p < .0005) and speed cost (β age = .167, t(74) = 4.01, p < .0005; R2 = .215, F(3,74) = 6.5, p < .0005) than younger adults. Additional regression models, performed in each load condition, revealed that older adults had lower accuracy scores in the 2-back load than younger adults (β age = −.129, t(74) = −6.47, p < .0005; R2 = .414, F(3,74) = 16.7, p < .0005). Furthermore, older adults were slower than younger adults in both load conditions (0-back: β age = 115.32, t(74) = 9.83, p < .0005; R2 = .581, F(3,74) = 32.9, p < .0005 and 2-back: β age = 249.01, t(74) = 9.61, p < .0005; R2 = .569, F(3,74) = 31.3, p < .0005; see Table 2).There are multiple errors throughout the “Components of interest: Age and BOLD load effect” section of the Results. The correct text is: The main repeated measure ANOVA on the BOLD load effects observed in the eight ICs associated with working memory processes, showed a general interaction between age and BOLD load effect (F(7,511) = 3.1, p = .007). To identify which of these 8 ICs showed an age-related BOLD load effect, additional post-hoc two sample t-tests were performed. These tests revealed that the difference in BOLD activation between the 2-back and the 0-back load condition was larger for older than younger adults in 3 ICs. Namely, the ICs containing mainly the VLPFC (t(73) = 1.9, p = .061), the right FPN (t(73) = 2.2, p = .035) and the left FPN (t(73) = 4, p < .0005).After identifying these 3 ICs, we subsequently performed a one-sample t-test in younger and older adults, separately. The purpose of these tests was to investigate whether the BOLD activation in each of the 3 selected ICs differed significantly between the 0-back and the 2-back load condition within each age-group. The one-sample t-test was significant in all 3 ICs, for younger (VLPFC: t(37) = 6.5, p< .0005; right FPN: t(37) = 3, p = .005 and left FPN: t(37) = -4.1, p< .0005) and older adults (VLPFC (t(36) = 9.8, p< .0005), the right FPN (t(36) = 6, p< .0005 and the left FPN (t(36) = -1.7, p = .093). For all participants, the BOLD activation in the right FPN and the VLPFC increased with task load. However, the BOLD activation of the left FPN was negatively modulated by the task, as revealed by the negative beta-weights and the positive spatial map of this component (see Fig 2B and Fig 3). In young adults, the BOLD activation in the left FPN became more negative with increasing task demands. To determine whether age modulated the BOLD signal in these 3 ICs of interest in the 0-back, in the 2-back or in both load conditions, subsequent post-hoc independent two sample t-tests were performed. These tests showed that compared to younger adults, older adults had a higher BOLD activation in the VLPFC (t(73) = 3, p = .006) and the right FPN (t(73) = 2.4, p = .020), in the 2-back load condition. In the 0-back load condition, younger and older adults showed similar BOLD activation in the VLPFC and the right FPN. On the other hand, older adults had a more negative BOLD response in the left FPN than younger adults, in the 0-back load condition (t(73) = 4.5, p < .0005). Younger and older adults had comparable BOLD load effect in the other working memory related ICs.

Temporal integration was examined using a missing element task, in which task performance depends on the ability to integrate brief successive stimulus displays. Previous studies have suggested that temporal integration is under endogenous control and that integration is more likely when stimuli match the observer’s temporal expectancies. Beta oscillations have previously been related to such cognitive (and attentional) control, as well as to audiovisual integration. We thus hypothesized that prestimulus power in the beta frequency band might reflect “integration readiness” and distinguish trials in which stimuli were successfully integrated from unsuccessful ones. The results showed increased upper beta power (21–30 Hz) prior to successful integration over central and parietal electrodes. This finding supported the idea that increased prestimulus beta power might reflect general control processes that can facilitate integration. Descriptors: Temporal integration, EEG, Beta frequency band, Prestimulus activity

The importance of studying connectivity in the aging brain is increasingly recognized. Recent studies have shown that connectivity within the default mode network is reduced with age and have demonstrated a clear relation of these changes with cognitive functioning. However, research on age-related changes in other functional networks is sparse and mainly focused on prespecified functional networks. Using functional magnetic resonance imaging, we investigated age-related changes in functional connectivity during a visual oddball task in a range of functional networks. It was found that compared with young participants, elderly showed a decrease in connectivity between areas belonging to the same functional network. This was found in the default mode network and the somatomotor network. Moreover, in all identified networks, elderly showed increased connectivity between areas within these networks and areas belonging to different functional networks. Decreased connectivity within functional networks was related to poorer cognitive functioning in elderly. The results were interpreted as a decrease in the specificity of functional networks in older participants. Hum Brain Mapp 35:319-330, 2014. (c) 2012 Wiley Periodicals, Inc.

Brain function is thought to become less specialized with age. However, this view is largely based on findings of increased activation during tasks that fail to separate task-related processes (e.g., attention, decision making) from the cognitive process under examination. Here we take a systems-level approach to separate processes specific to language comprehension from those related to general task demands and to examine age differences in functional connectivity both within and between those systems. A large population-based sample (N= 111; 22–87 years) from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) was scanned using functional MRI during two versions of an experiment: a natural listening version in which participants simply listened to spoken sentences and an explicit task version in which they rated the acceptability of the same sentences. Independent components analysis across the combined data from both versions showed that although task-free language comprehension activates only the auditory and frontotemporal (FTN) syntax networks, performing a simple task with the same sentences recruits several additional networks. Remarkably, functionality of the critical FTN is maintained across age groups, showing no difference in within-network connectivity or responsivity to syntactic processing demands despite gray matter loss and reduced connectivity to task-related networks. We found no evidence for reduced specialization or compensation with age. Overt task performance was maintained across the lifespan and performance in older, but not younger, adults related to crystallized knowledge, suggesting that decreased between-network connectivity may be compensated for by older adults' richer knowledge base.SIGNIFICANCE STATEMENTUnderstanding spoken language requires the rapid integration of information at many different levels of analysis. Given the complexity and speed of this process, it is remarkably well preserved with age. Although previous work claims that this preserved functionality is due to compensatory activation of regions outside the frontotemporal language network, we use a novel systems-level approach to show that these “compensatory” activations simply reflect age differences in response to experimental task demands. Natural, task-free language comprehension solely recruits auditory and frontotemporal networks, the latter of which is similarly responsive to language-processing demands across the lifespan. These findings challenge the conventional approach to neurocognitive aging by showing that the neural underpinnings of a given cognitive function depend on how you test it.

The control of voluntary movement changes markedly with age. A critical component of motor control is the integration of sensory information with predictions of the consequences of action, arising from internal models of movement. This leads to sensorimotor attenuation—a reduction in the perceived intensity of sensations from self-generated compared with external actions. Here we show that sensorimotor attenuation occurs in 98% of adults in a population-based cohort (n=325; 18–88 years; the Cambridge Centre for Ageing and Neuroscience). Importantly, attenuation increases with age, in proportion to reduced sensory sensitivity. This effect is associated with differences in the structure and functional connectivity of the pre-supplementary motor area (pre-SMA), assessed with magnetic resonance imaging. The results suggest that ageing alters the balance between the sensorium and predictive models, mediated by the pre-SMA and its connectivity in frontostriatal circuits. This shift may contribute to the motor and cognitive changes observed with age., Decline in sensorimotor skills with age may be due to an overreliance on the prediction of the sensory consequences of one's actions. Here the authors show that sensorimotor attenuation increases with age, and that this is associated with structural and functional changes in frontostriatal circuits.

Much is known about how age affects the brain during tightly controlled, though largely contrived, experiments, but do these effects extrapolate to everyday life? Naturalistic stimuli, such as movies, closely mimic the real world and provide a window onto the brain's ability to respond in a timely and measured fashion to complex, everyday events. Young adults respond to these stimuli in a highly synchronized fashion, but it remains to be seen how age affects neural responsiveness during naturalistic viewing. To this end, we scanned a large (N = 218), population-based sample from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) during movie-watching. Intersubject synchronization declined with age, such that older adults' response to the movie was more idiosyncratic. This decreased synchrony related to cognitive measures sensitive to attentional control. Our findings suggest that neural responsivity changes with age, which likely has important implications for real-world event comprehension and memory.

To investigate which neural correlates are associated with successful working memory performance, fMRI was recorded in healthy younger and older adults during performance on an n-back task with varying task demands. To identify functional networks supporting working memory processes, we used independent component analysis (ICA) decomposition of the fMRI data. Compared to younger adults, older adults showed a larger neural (BOLD) response in the more complex (2-back) than in the baseline (0-back) task condition, in the ventral lateral prefrontal cortex (VLPFC) and in the right fronto-parietal network (FPN). Our results indicated that a higher BOLD response in the VLPFC was associated with increased performance accuracy in older adults, in both the baseline and the more complex task condition. This 'BOLD-performance' relationship suggests that the neural correlates linked with successful performance in the older adults are not uniquely related to specific working memory processes present in the complex but not in the baseline task condition. Furthermore, the selective presence of this relationship in older but not in younger adults suggests that increased neural activity in the VLPFC serves a compensatory role in the aging brain which benefits task performance in the elderly.

Visual hallucinations (VHs) often occur in patients with advanced Parkinson disease (PD). Overstimulation of dopamine receptors has been considered as one of the causes for VHs in PD. However, several clinical studies suggested that apomorphine infusion did not worsen existing VHs in PD, but could even improve VHs in some PD patients. This pilot study included 4 PD patients with VHs, who were examined before, during, and after an intravenous infusion with apomorphine. The examinations included tests for lower- and higher-order visual functions, attention, and motor functions. Apomorphine had a significantly positive effect on contrast sensitivity and showed a significantly negative effect on attention. These results may explain why apomorphine is able to improve VHs in PD in some patients with mainly visual perceptive problems, but may also worsen VHs in other patients because of impaired attention.

The ability to suppress irrelevant information declines with age, while the ability to enhance relevant information remains largely intact. We examined mechanisms behind this dissociation in an fMRI study, using a selective attention task in which relevant and irrelevant information appeared simultaneously. Slowing of response times due to distraction by irrelevant targets was larger in older than younger participants. Increased distraction was related to larger increases in activity and connectivity in areas of the dorsal attention network, indicating a more pronounced (re-)orientation of attention. The decreases in accuracy in target compared to nontarget trials were smaller in older compared to younger participants. In older adults we found increased recruitment of areas in the fronto-parietal control network (FPCN) during target detection. Moreover, older adults showed increased connectivity between the FPCN, supporting cognitive control, and somatomotor areas implicated in response selection and execution. This connectivity increase was related to improved target detection, suggesting that older adults engage additional cognitive control, which might enable the observed intact performance in detecting and responding to target stimuli.

Recent studies have shown that aging has a large impact on connectivity within and between functional networks. An open question is whether elderly still have the flexibility to adapt functional network connectivity (FNC) to the demands of the task at hand. To study this, we collected fMRI data in younger and older participants during resting state, a selective attention (SA) task and an n‐back working memory task with varying levels of difficulty. Spatial independent component (IC) analysis was used to identify functional networks over all participants and all conditions. Dual regression was used to obtain participant and task specific time‐courses per IC. Subsequently, functional connectivity was computed between all ICs in each of the tasks. Based on these functional connectivity matrices, a scaled version of the eigenvector centrality (SEC) was used to measure the total influence of each IC in the complete graph of ICs. The results demonstrated that elderly remain able to adapt FNC to task demands. However, there was an age‐related shift in the impetus for FNC change. Older participants showed the maximal change in SEC patterns between resting state and the SA task. Young participants, showed the largest shift in SEC patterns between the less demanding SA task and the more demanding 2‐back task. Our results suggest that increased FNC changes from resting state to low demanding tasks in elderly reflect recruitment of additional resources, compared with young adults. The lack of change between the low and high demanding tasks suggests that elderly reach a resource ceiling. Hum Brain Mapp 35:3788–3804, 2014. © 2013 Wiley Periodicals, Inc.

While some elderly show deteriorations in cognitive performance, others achieve performance levels comparable to young adults. To examine whether age-related changes in brain activity varied with working memory performance efficiency, we recorded electroencephalography (EEG) from young and older healthy adults during performance on an n-back task with two loads (0- and 1-back) and two versions (identity and integrated). Young adults showed a typical P3 amplitude pattern with a parietal-maximum. Compared to young adults, the P3 amplitude of older adults was characterized by frontal hyperactivity coupled with posterior hypoactivity. Moreover, P3 amplitude in young and older adults varied with working memory performance efficiency. Among young adults, more efficient performance correlated with a larger P3 amplitude at parietal sites. In contrast, a higher P3 amplitude at midline electrode sites in older adults correlated with less efficient performance. Particularly, the enhanced frontal midline EEG activity in older adults during working memory performance seems to reflect inefficient use of neural resources due to frontal lobe dysfunction.

With increasing age, people experience more difficulties with suppressing irrelevant information, which may have a major impact on cognitive functioning. The extent of decline of inhibitory functions with age is highly variable between individuals. In this study, we used ERPs and phase locking analyses to investigate neural correlates of this variability in inhibition between individuals. Older and younger participants performed a selective attention task in which relevant and irrelevant information was presented simultaneously. The participants were split into high and low performers based on their level of inhibition inefficiency, that is, the slowing of RTs induced by information that participants were instructed to ignore. P1 peak amplitudes were larger in low performers than in high performers, indicating that low performers were less able to suppress the processing of irrelevant stimuli. Phase locking analyses were used as a measure of functional connectivity. Efficient inhibition in both age groups was related to the increased functional connectivity in the alpha band between frontal and occipito-parietal ROIs in the prestimulus interval. In addition, increased power in the alpha band in occipito-parietal ROIs was related to better inhibition both before and after stimulus onset. Phase locking in the upper beta band before and during stimulus presentation between frontal and occipito-parietal ROIs was related to a better performance in older participants only, suggesting that this is an active compensation mechanism employed to maintain adequate performance. In addition, increased top–down modulation and increased power in the alpha band appears to be a general mechanism facilitating inhibition in both age groups.