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Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery.

The presents study examined patterns of cerebral activation during a working memory (WM) rehearsal task in individuals diagnosed with multiple sclerosis (MS) and in healthy adults. BOLD functional magnetic resonance imaging (IMRI) was performed using a 1.5 TGE scanner to asses activation during a WM task adapted from the sternberg paradigm (Sternberg, 1969).Participants included 8 individuals diagnosed with MS, and 5 healthy controls (HCs) matched for age and educating. Task difficulty was manipulated by increasing the length of time that strings of letters were to be rehearsed. Findings revealed increased right prefrontal cortex activation and increased right temporal lobe activation in individuals diagnosed with MS compared to HCs. The potential explanations for increased right hemisphere activation in persons with MS are discussed. [ABSTRACT FROM AUTHOR]

Semantic memory representations are generally well maintained in aging, whereas semantic control is thought to be more affected. To explain this phenomenon, this study tested the predictions of the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), focusing on task demands in aging as a possible framework. The CRUNCH effect would manifest itself in semantic tasks through a compensatory increase in neural activation in semantic control network regions but only up to a certain threshold of task demands. This study compares 39 younger (20-35 years old) with 39 older participants (60-75 years old) in a triad-based semantic judgment task performed in an fMRI scanner while manipulating task demand levels (low versus high) through semantic distance. In line with the CRUNCH predictions, differences in neurofunctional activation and behavioral performance (accuracy and response times) were expected in younger versus older participants in the low- versus high-demand conditions, which should be manifested in semantic control Regions of Interest (ROIs). Our older participants had intact behavioral performance, as proposed in the literature for semantic memory tasks (maintained accuracy and slower response times (RTs)). Age-invariant behavioral performance in the older group compared to the younger one is necessary to test the CRUNCH predictions. The older adults were also characterized by high cognitive reserve, as our neuropsychological tests showed. Our behavioral results confirmed that our task successfully manipulated task demands: error rates, RTs and perceived difficulty increased with increasing task demands in both age groups. We did not find an interaction between age group and task demand, or a statistically significant difference in activation between the low- and high-demand conditions for either RTs or accuracy. As for brain activation, we did not find the expected age group by task demand interaction, or a significant main effect of task demand. Overall, our results are compatible with some neural activation in the semantic network and the semantic control network, largely in frontotemporoparietal regions. ROI analyses demonstrated significant effects (but no interactions) of task demand in the left and right inferior frontal gyrus, the left posterior middle temporal gyrus, the posterior inferior temporal gyrus and the prefrontal gyrus. Overall, our test did not confirm the CRUNCH predictions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Haitas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study tested the hypothesis that within older Barbadian adults, sex, education, and occupation type lessen age-related cognitive decline. The analyses used a cross-sectional data set from 1325 people collected in the 2006 SABE Study (Health, Well-being, and Aging). Cognition was assessed as scores in each subdomain of the Mini-Mental State Exam. The loss of a single point in each subdomain was predicted by sex, years of education, job type, and their interactions with age. Results demonstrated that age and protective factors affect each cognitive domain differently. High education combined with mentally complex employment helped maintain cognitive performance in later life. Beneficial lifetime exposures are additive, providing combined benefits. Findings provide insight into public policy aiming to minimize the number of adults with cognitive decline and dementia in Barbados and the Caribbean.

Working memory (WM) describes the dynamic process of maintenance and manipulation of information over a certain time delay. Neuronally, WM recruits a distributed network of cortical regions like the visual and dorsolateral prefrontal cortex as well as the subcortical hippocampus. How the input dynamics and subsequent neural dynamics impact WM remains unclear though. To answer this question, we combined the analysis of behavioral WM capacity with measuring neural dynamics through task-related power spectrum changes, e.g., median frequency (MF) in functional magnetic resonance imaging (fMRI). We show that the processing of the input dynamics, e.g., the task structure's specific timescale, leads to changes in the unimodal visual cortex's corresponding timescale which also relates to working memory capacity. While the more transmodal hippocampus relates to working memory capacity through its balance across multiple timescales or frequencies. In conclusion, we here show the relevance of both input dynamics and different neural timescales for WM capacity in uni - and transmodal regions like visual cortex and hippocampus for the subject's WM performance., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Psychological resilience may play an important role in protecting multiple sclerosis care-partners from the negative effects of their support role. However, predictors of resilience in this population have yet to be identified., Objectives: To identify characteristics predictive of psychological resilience in multiple sclerosis care-partners as informed by the Ecological Model of Resilience., Methods: Informal multiple sclerosis care-partners ( n  = 540) completed an online survey. Psychological resilience was measured using the 25-item Connor-Davidson Resilience Scale. Sociodemographic and care-context predictors of resilience were analyzed using hierarchical regression., Results: The mean resilience score was 59.0 ( SD  = 7.6) out of a possible 100. Sociodemographic variables accounted for 31% of the variance in resilience scores in multiple sclerosis care-partners. When care-context variables were incorporated into the model, 55% of variance was explained ( F [7,320] = 26.824, p  < 0.001). Each group of variables remained significant in both low disability and high disability models. Social support was the only individual variable that remained significant across all models ( p  < 0.05)., Conclusions: Multiple sclerosis care-partners differ strikingly from other caregiving populations. Both sociodemographic and care-context variables were found to promote or hinder resilience in multiple sclerosis care-partners. Social support, in particular, may be an important target for promoting resilience in multiple sclerosis care-partners and could be leveraged in future initiatives., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s), 2022.)

The vast majority of fMRI studies of task-related brain activity utilize common levels of task demands and analyses that rely on the central tendencies of the data. This approach does not take into account perceived difficulty nor regional variations in brain activity between people. The results are findings of brain-behavior relationships that weaken as sample sizes increase. Participants of the current study included twenty-six healthy young adults evenly split between the sexes. The current work utilizes five parametrically modulated levels of memory load centered around each individual's predetermined working memory cognitive capacity. Principal components analyses (PCA) identified the group-level central tendency of the data. After removing the group effect from the data, PCA identified individual-level patterns of brain activity across the five levels of task demands. Expression of the group effect significantly differed between the sexes across all load levels. Expression of the individual level patterns demonstrated a significant load by sex interaction. Furthermore, expressions of the individual maps make better predictors of response time behavior than group-derived maps. We demonstrated that utilization of an individual's unique pattern of brain activity in response to increasing a task's perceived difficulty is a better predictor of brain-behavior relationships than study designs and analyses focused on identification of group effects. Furthermore, these methods facilitate exploration into how individual differences in patterns of brain activity relate to individual differences in behavior and cognition., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to declare., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Task-based functional magnetic resonance imaging (MRI) neuroimaging for the study of cognitive neuroscience provides insight into how the brain responds to increasing cognitive demands. Theoretical models of neural-cognitive relationships define neural efficiency and neural capacity as two parameters to describe the rate of gain of brain activity and the upper limits of the increases, respectively. Although qualitatively well described, there are limited discussions and demonstrations of estimating these parameters from data. The current work presents a method using a quadratic equation model of cognitive demands. The methods were applied to 21 healthy young adults while engaging in four levels of the verbal n-back working memory task (0, 1, 2 and 3-back). Measures of the area under the curve captured both linear and curvilinear responses to quantify the locations and amounts of task-related increases in brain activity. In addition, we calculated voxel-wise maps of neural efficiency and neural capacity. Results showed increases in brain activation in regions typically involved in working memory. The relationships between increasing cognitive demands and brain activity also differed across the brain within and between individuals, as indicated by differential neural efficiency and neural capacity values. This approach provides tools for evaluating current theories about the relationships between brain activity and cognition. Neural efficiency and neural capacity provide physiological measures of brain activity, which will help evaluate how age, disease and intervention processes affect brain activity. Finally, all presented methods are readily applicable using standard current software packages for neuroimaging., (© 2021 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

In this study, Artificial Intelligence was used to analyze a dataset containing the cortical thickness from 1,100 healthy individuals. This dataset had the cortical thickness from 31 regions in the left hemisphere of the brain as well as from 31 regions in the right hemisphere. Then, 62 artificial neural networks were trained and validated to estimate the number of neurons in the hidden layer. These neural networks were used to create a model for the cortical thickness through age for each region in the brain. Using the artificial neural networks and kernels with seven points, numerical differentiation was used to compute the derivative of the cortical thickness with respect to age. The derivative was computed to estimate the cortical thickness speed. Finally, color bands were created for each region in the brain to identify a positive derivative, that is, a part of life with an increase in cortical thickness. Likewise, the color bands were used to identify a negative derivative, that is, a lifetime period with a cortical thickness reduction. Regions of the brain with similar derivatives were organized and displayed in clusters. Computer simulations showed that some regions exhibit abrupt changes in cortical thickness at specific periods of life. The simulations also illustrated that some regions in the left hemisphere do not follow the pattern of the same region in the right hemisphere. Finally, it was concluded that each region in the brain must be dynamically modeled. One advantage of using artificial neural networks is that they can learn and model non-linear and complex relationships. Also, artificial neural networks are immune to noise in the samples and can handle unseen data. That is, the models based on artificial neural networks can predict the behavior of samples that were not used for training. Furthermore, several studies have shown that artificial neural networks are capable of deriving information from imprecise data. Because of these advantages, the results obtained in this study by the artificial neural networks provide valuable information to analyze and model the cortical thickness., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Ledesma, Ibarra-Manzano, Almanza-Ojeda, Fallavollita and Steffener.)

Semantic memory representations are overall well-maintained in aging whereas semantic control is thought to be more affected. To explain this phenomenon, this study aims to test the predictions of the Compensation Related Utilization of Neural Circuits Hypothesis (CRUNCH) focusing on task demands in aging as a possible framework. The CRUNCH effect would manifest itself in semantic tasks through a compensatory increase in neural activation in semantic control network regions but only up to a certain threshold of task demands. This study will compare 40 young (20-35 years old) with 40 older participants (60-75 years old) in a triad-based semantic judgment task performed in an fMRI scanner while manipulating levels of task demands (low vs. high) through semantic distance. In line with the CRUNCH predictions, differences in neurofunctional activation and behavioral performance (accuracy and response times) are expected in young vs. old participants in the low- vs. high-demand conditions manifested in semantic control Regions of Interest., Competing Interests: The authors have declared that no competing interests exist.

This study investigated whether relationships between age and measures of gray matter in the brain differed across the lifespan and by years of education. The hypothesis is that year to year differences in brain measures vary across the lifespan and are affected by the years of education someone has. Cortical thickness and subcortical volume were measured from 391 healthy adults (age range: 19-80 years). Brain measures were predicted using a quadratic age effect and moderating effects of education using linear regression. Results demonstrate that 12 brain regions had significant moderating effects of age and education on brain measures. These are brain regions where the effect of age on gray matter varied across the lifespan and across levels of education. The results highlighted that when the moderating effects of education are absent from the model, age and brain measures were linearly related. The moderating effects reveal complex age-brain dynamics and support theories of brain maintenance, suggesting that lifestyle factors limit the negative effects of advancing age. Greater education was related to maintained gray matter until later ages. This protection came at a cost, which indicated that year to year decline in gray matter was larger in late life in those with greater levels of education. Improving our understanding of how age and individual differences affect gray matter measures is an important step toward improving the clinical utility of cortical thickness and volume. This article is part of the Virtual Special Issue titled "COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING". The full issue can be found on ScienceDirect at https://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Olfactory dysfunction consistently occurs in patients with Alzheimer's disease (AD), beyond the mild and gradual decline in olfactory ability found in normal aging. This dysfunction begins early in the disease course, typically before clinical diagnosis, and progresses with disease severity. While odor identification and detection deficits clearly differentiate AD from controls, there remains uncertainty as to whether these are determined by olfactory threshold. The purpose of the current preliminary fMRI study was to examine the neural correlates of olfactory processing in healthy young and old adults and compare them with AD patients. We also explored the interplay between age and disease-related psychophysical olfactory declines and odorant-induced brain activation. Results indicated AD patients had decreased odor detection task-related signal in all regions of the primary olfactory cortex, with activity in the entorhinal cortex best differentiating the groups. Moderated-mediation analyses on neuro-psychophysical relationships found that increased brain activation in the entorhinal cortex moderated the negative effect of disease-related threshold changes on olfactory detection. Therefore, even in the face of higher (worse) olfactory thresholds, older adults and AD patients compensated for this effect with increased brain activation in a primary olfactory brain region. This was the case for odor detection but not odor identification. fMRI activation induced by an olfactory detection task may eventually be useful in improving early discovery of AD and may, eventually, facilitate early treatment interventions in subjects at risk for AD., (Copyright © 2020. Published by Elsevier B.V.)

Advancing age affects the recruitment of task related neural resources thereby changing the efficiency, capacity and use of compensatory processes. With advancing age, brain activity may therefore increase within a region or be reorganized to utilize different brain regions. The different brain regions may be exclusive to old adults or accessible to young and old alike, but non-optimal. Interference during verbal working memory information retention recruits parahippocampal brain regions in young adults similar to brain activity recruited by old adults in the absence of external interference. The current work tests the hypothesis that old adults recruit neural resources to combat increases in age-related intrinsic noise that young adults recruit during high levels of interference during information retention. This experiment administered a verbal delayed item recognition task with low and high levels of an interfering addition task during information maintenance. Despite strong age-related behavioral effects, brain imaging results demonstrated no significant interaction effects between age group and the interference or memory tasks. Significant effects were only found for the interaction between interference level and memory load within the inferior frontal cortex, supplementary motor cortex and posterior supramarginal regions. Results demonstrate that neural resources were shared when facing increasing memory load and interference. The combined cognitive demands resulted in brain activity reaching a neural capacity limit which was similar for both age groups and which brain activation did not increase above. Despite significant behavioral differences the neural capacity limited the detection of age group differences in brain activity., Competing Interests: The authors have declared that no competing interests exist.

Studies of working memory have used immediate and delayed recall of lists of items. Serial position effects are the phenomena where items at the beginning and end of a studied list are recalled differentially from items in the middle of the list. In matching versions of the task, study items may be presented serially or simultaneously in a grid. After a delay a single probe item is presented for which the participant determines whether or not it was in the study set. The effects of the position of an item when studied on a screen are currently not well understood and are the focus of the current work. Findings from a delayed match to sample task in 49 healthy young adults with 1 to 9 items presented in a 3 by 3 grid, demonstrate that the column of the studied items affect response time and accuracy. The effects of position on accuracy also significantly interact with task demands. The importance of screen position effects is demonstrated with simulations using the mean accuracies split by task demands and screen locations. Simulations demonstrate the possible range of accuracies based on screen effects when the number of trials presented to an individual is less than 20 for each task demand. This has important implications when a small number of trials are administered using randomly generated stimuli which is often the case in neuroimaging studies where tasks are delivered under constrained time limits., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Chronic pain affects both adolescent and adult Canadians. To study the effect of social rejection on pain management in adolescents with chronic pain, an algometer can be used in conjunction with functional Magnetic Resonance Imaging (fMRI) to measure brain activity in real time. The algometer uses an automated pneumatic control system that follows a customizable pain schedule, controlling the amount of airflow in and out of a pressure cuff wrapped around a human participant's thigh. Plastic components allow compatibility with an fMRI environment. Measurable pain stimuli allow repeatable pressure schedules to be administered with a standard deviation between trials of 300 Pa (2.25 mmHg). A Failure Mode Effects Analysis was used to reduce participant, researcher and facility harm, with multiple safety features incorporated into the design. Through the analysis of medical standards and studies, the algometer is shown to be biologically safe to use on research subjects within the suggested usage parameters of a maximum pressure of 42.6 kPa (320 mmHg) and a pressure application period of up to one hour. This makes it feasible for research studies using fMRI machines.

Objective : We examined the extent to which loss of consciousness (LOC) following mild traumatic brain injury (mTBI) may be associated with impairments in executive functions and declarative memory more than a year after brain injury. Method : Analyses were run on 548 participants who had self-reported LOC of <1 min, 441 with LOC of 1-20 min, and 13,609 no brain injury comparison participants, taken from the Canadian Longitudinal Study on Aging (CLSA), a nationwide study on health and aging. Results : Those that had mTBI with LOC of 1-20 min were more likely than no head injury comparisons to be impaired on measures of executive functioning and declarative memory. Impairments were evident when examining for single- and two-test impairment rates on measures of executive functioning and declarative memory. Conclusions : A subset of people that had reported a single mTBI with LOC more than 12 months ago may experience impairments in executive functioning and declarative memory, particularly those who spent more time unconscious.

Background: Olfactory dysfunction (OD) is a frequent symptom of Parkinson's disease (PD) that appears years prior to diagnosis. Previous studies suggest that PD-related OD is different from non-parkinsonian forms of olfactory dysfunction (NPOD) as PD patients maintain trigeminal sensitivity as opposed to patients with NPOD who typically exhibit reduced trigeminal sensitivity. We hypothesize the presence of a specific alteration of functional connectivity between trigeminal and olfactory processing areas in PD., Objective: We aimed to assess potential differences in functional connectivity within the chemosensory network in 15 PD patients and compared them to 15 NPOD patients, and to 15 controls., Methods: Functional MRI scanning session included resting-state and task-related scans where participants carried out an olfactory and a trigeminal task. We compared functional connectivity, using a seed-based correlation approach, and brain network modularity of the chemosensory network., Results: PD patients had impaired functional connectivity within the chemosensory network while no such changes were observed for NPOD patients. No group differences we found in modularity of the identified networks. Both patient groups exhibited impaired connectivity when executing an olfactory task, while network modularity was significantly weaker for PD patients than both other groups. When performing a trigeminal task, no changes were found for PD patients, but NPOD patients exhibited impaired connectivity. Conversely, PD patients exhibited a significantly higher network modularity than both other groups., Conclusion: In summary, the specific pattern of functional connectivity and chemosensory network recruitment in PD-related OD may explain distinct behavioral chemosensory features in PD when compared to NPOD patients and healthy controls.

Idiopathic hypersomnia (IH) is characterized by excessive daytime sleepiness but, in contrast to narcolepsy, does not involve cataplexy, sleep-onset REM periods, or any consistent hypocretin-1 deficiency. The pathophysiological mechanisms of IH remain unclear. Because of the involvement of the default-mode network (DMN) in alertness and sleep, our aim was to investigate the structural and functional modifications of the DMN in IH. We conducted multimodal magnetic resonance imaging (MRI) in 12 participants with IH and 15 good sleeper controls (mean age ± SD: 32 ± 9.6 years, range 22-53 years, nine males). Self-reported as well as objective measures of daytime sleepiness were collected. Gray matter volume and cortical thickness were analyzed to investigate brain structural differences between good sleepers and IH. Structural covariance and resting-state functional connectivity were analyzed to investigate changes in the DMN. Participants with IH had greater volume and cortical thickness in the precuneus, a posterior hub of the DMN. Cortical thickness in the left medial prefrontal cortex was positively correlated with thickness of the precuneus, and the strength of this correlation was greater in IH. In contrast, functional connectivity at rest was lower within the anterior DMN (medial prefrontal cortex) in IH, and correlated with self-reported daytime sleepiness. The present results show that IH is associated with structural and functional differences in the DMN, in proportion to the severity of daytime sleepiness, suggesting that a disruption of the DMN contributes to the clinical features of IH. Larger volume and thickness in this network might reflect compensatory changes to lower functional connectivity in IH., (© Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Training and repeated exposure to odorants leads to enhanced olfactory sensitivity. So far, the efficacy of intensive olfactory training on olfactory function in a healthy population and its underlying neurobiological basis remain poorly known. This study investigated the effects of a 6-week intensive and well-controlled olfactory training on olfactory function and brain structure/neuroplasticity. Thirty-six healthy young individuals were recruited and randomly distributed in three groups: (1) 12 participants underwent daily intensive olfactory training of at least 20 min that included an (a) odor intensity classification task, an (b) odor quality classification task and an (c) target odor detection task, (2) 12 participants underwent an equivalent visual control training, and (3) 12 control individuals did not participate in any training. Before and after the training period, all participants performed a series of olfactory tests and those from groups 1 and 2 underwent structural magnetic resonance (MR) imaging, from which we obtained measures such as cortical thickness and tissue density. Participants improved in the respectively trained tasks throughout the 6-weeks training period. Those who underwent olfactory training improved general olfactory function compared to control participants, especially in odor identification, thus showing intramodal transfer. Further, MR imaging analysis revealed that olfactory training led to increased cortical thickness in the right inferior frontal gyrus, the bilateral fusiform gyrus and the right entorhinal cortex. This research shows that intensive olfactory training can generally improve olfactory function and that this improvement is associated with changes in the structure of olfactory processing areas of the brain., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Most of the current knowledge about age-related differences in brain neurofunctional organization stems from neuroimaging studies using either a "resting state" paradigm, or cognitive tasks for which performance decreases with age. However, it remains to be known if comparable age-related differences are found when participants engage in cognitive activities for which performance is maintained with age, such as vocabulary knowledge tasks. A functional connectivity analysis was performed on 286 adults ranging from 18 to 80 years old, based either on a resting state paradigm or when engaged in vocabulary tasks. Notable increases in connectivity of regions of the language network were observed during task completion. Conversely, only age-related decreases were observed across the whole connectome during resting-state. While vocabulary accuracy increased with age, no interaction was found between functional connectivity, age and task accuracy or proxies of cognitive reserve, suggesting that older individuals typically benefits from semantic knowledge accumulated throughout one's life trajectory, without the need for compensatory mechanisms.

In Figure 3b of the originally published article, the colours of the bars were incorrectly reversed. The bars shown in green should have been shown in blue to represent the findings from older adults, whereas the bars shown in blue should have been shown in green to represent the findings from young adults. This has been corrected in the HTML and PDF versions of the article. Images of the original figure are shown in the correction notice.

Cognitive ageing research examines the cognitive abilities that are preserved and/or those that decline with advanced age. There is great individual variability in cognitive ageing trajectories. Some older adults show little decline in cognitive ability compared with young adults and are thus termed 'optimally ageing'. By contrast, others exhibit substantial cognitive decline and may develop dementia. Human neuroimaging research has led to a number of important advances in our understanding of the neural mechanisms underlying these two outcomes. However, interpreting the age-related changes and differences in brain structure, activation and functional connectivity that this research reveals is an ongoing challenge. Ambiguous terminology is a major source of difficulty in this venture. Three terms in particular - compensation, maintenance and reserve - have been used in a number of different ways, and researchers continue to disagree about the kinds of evidence or patterns of results that are required to interpret findings related to these concepts. As such inconsistencies can impede progress in both theoretical and empirical research, here, we aim to clarify and propose consensual definitions of these terms.

The concept of cognitive reserve (CR) can explain individual differences in susceptibility to cognitive or functional impairment in the presence of age or disease-related brain changes. Epidemiologic evidence indicates that CR helps maintain performance in the face of pathology across multiple cognitive domains. We therefore tried to identify a single, "task-invariant" CR network that is active during the performance of many disparate tasks. In imaging data acquired from 255 individuals age 20-80 while performing 12 different cognitive tasks, we used an iterative approach to derive a multivariate network that was expressed during the performance of all tasks, and whose degree of expression correlated with IQ, a proxy for CR. When applied to held out data or forward applied to fMRI data from an entirely different activation task, network expression correlated with IQ. Expression of the CR pattern accounted for additional variance in fluid reasoning performance over and above the influence of cortical thickness, and also moderated between cortical thickness and reasoning performance, consistent with the behavior of a CR network. The identification of a task-invariant CR network supports the idea that life experiences may result in brain processing differences that might provide reserve against age- or disease-related changes across multiple tasks., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: We aimed to examine the extent to which loss of consciousness (LOC) following mild traumatic brain injury (mTBI) may be associated with impairments in time- and event-based prospective memory (PM). PM is thought to involve executive processes and be subserved by prefrontal regions. Neuroimaging research suggests alterations to these areas of the brain several years after mTBI, particularly if LOC was experienced. However, it remains unclear whether impairments in time- or event-based functioning may persist more than a year after mTBI, and what the link with duration of LOC may be., Method: Analyses were run on data from the Canadian Longitudinal Study on Aging, a nationwide study on health and aging involving individuals between the ages of 45-85. The present study consisted of 1937 participants who experienced mTBI more than 12 months prior, of whom 1146 reported spending less than 1 min unconscious, and 791 had LOC between 1 and 20 min, and 13,525 cognitively healthy adults. Participants were administered the Miami Prospective Memory Test, and tests of retrospective memory and executive functioning., Results: Both mTBI groups were impaired in time-based PM relative to people with no history of TBI. Time- and event-based impairments were predicted by older age, and executive dysfunction among those who spent more time unconscious., Conclusions: Those with mTBI with LOC may experience impairments in PM, particularly in conditions of high demand on executive processes (time-based PM). Implications for interventions aimed at ameliorating PM among those who have experienced mTBI are discussed.

Two independent lines of research provide evidence that speaking more than one language may 1) contribute to increased grey matter in healthy younger and older adults and 2) delay cognitive symptoms in mild cognitive impairment (MCI) or Alzheimer disease (AD). We examined cortical thickness and tissue density in monolingual and multilingual MCI and AD patients matched (within Diagnosis Groups) on demographic and cognitive variables. In medial temporal disease-related (DR) areas, we found higher tissue density in multilingual MCIs versus monolingual MCIs, but similar or lower tissue density in multilingual AD versus monolingual AD, a pattern consistent with cognitive reserve in AD. In areas related to language and cognitive control (LCC), both multilingual MCI and AD patients had thicker cortex than the monolinguals. Results were largely replicated in our native-born Canadian MCI participants, ruling out immigration as a potential confound. Finally, multilingual patients showed a correlation between cortical thickness in LCC regions and performance on episodic memory tasks. Given that multilinguals and monolinguals were matched on memory functioning, this suggests that increased gray matter in these regions may provide support to memory functioning. Our results suggest that being multilingual may contribute to increased gray matter in LCC areas and may also delay the cognitive effects of disease-related atrophy., (Copyright © 2017 Elsevier Ltd. All rights reserved.)