Recent advancements in connectome analyses have enabled more precise measurements of brain network integrity. Identifying neural measures that can operate as mechanisms of cognitive reserve is integral for the study of individual variability in age-related cognitive changes. In the present study, we tested the hypothesis that network resilience, or the network's ability to maintain functionality when facing internal or external perturbations that cause damage or error, can function as a cognitive reserve (CR) candidate, modifying the relationship between cognitive and brain changes in a lifespan cohort of cognitively healthy adults. One hundred cognitively healthy older adults from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (50-80 years) underwent resting-state fMRI and neuropsychological testing at baseline and 5-year follow-up. Using undirected weighted adjacency matrices created from the Schaefer et al. (2018) 400-parcellation atlas and 19 additional subcortical regions (419 nodes in total), whole-brain network resilience was assessed through a targeted attack approach, where nodes were sequentially removed by nodal strength and resilience defined as the iteration of the steepest slope in the largest connected component (LCC) decay. We observed that network resilience moderated the effect of cortical thickness (CT) changes on longitudinal changes in Fluid Reasoning performance, even after adjusting for baseline differences, demographic factors, and the initial LCC of the unlesioned matrix, indicating that individuals with greater resilience were less sensitive to the effect of cortical thickness changes on changes in cognition. These findings support the use of targeted attack as a measure of cognitive reserve, suggesting that higher network resilience may allow individuals with reduced brain integrity to better cope with structural loss and maintain cognitive function.

Recent advancements in connectome analyses allow for more fine-grained measurements of brain network integrity. One measure of integrity is resilience, or the capacity of the network to retain functionality when confronted with endogenous or exogenous perturbations that result in damage or error. We assessed the impact of individual differences in the resilience of resting BOLD connectivity on the relationship between cognitive and brain changes in a lifespan cohort of cognitively healthy adults over a 5-year period. One hundred twenty-six cognitively healthy participants from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (age 20-80 years) underwent resting-state fMRI to measure functional connectivity and an out-of-scanner neuropsychological battery at baseline and five-year follow-up. Undirected weighted adjacency matrices were generated from Schaefer et al. (2018) 400 parcellation atlas. As a measure of whole-brain network resilience, we adopted a targeted attack approach, whereby nodes are sequentially removed from the connectome in order of nodal strength. At each iteration of attack, nodal strength is recalculated based on the effect of prior lesioning and the largest connected component (LCC) is measured. We inferred that more resilient individuals will sustain larger LCCs over longer iterations of lesioning before decay in LCC becomes evident, with resilience operationalized as the iteration of steepest slope in LCC. We tested whether our operationalization of brain resilience (BR) moderated the effect of brain integrity (i.e., cortical thickness; CT) on out-of-scanner neuropsychological test performance across four domains of cognition in the context of longitudinal change (∆) over time. After accounting for baseline differences in change variables and adjusting for the demographic factors of Age, Sex, NART IQ, and Education, we observed a significant negative interaction between ∆CT and ∆BR on ΔCognition for the Fluid Reasoning domain. That is, individuals with increased brain resilience over time were less sensitive to the effect of changes in cortical thickness on changes in cognition. Our finding supports evidence for targeted attack as a measure of cognitive reserve, where higher brain network resilience may have permitted individuals with reduced brain integrity to better cope with structural loss and enhance preservation of cognitive function.

Some theories of aging have linked age-related cognitive decline to a reduction in distinctiveness of neural processing. Observed age-related correlation increases among disparate cognitive tasks have supported the dedifferentiation hypothesis. We previously showed cross-sectional evidence for age-related correlation decreases instead, supporting an alternative disintegration hypothesis. In the current study, we extended our previous research to a longitudinal sample. We tested 135 participants (20-80 years) at two time points-baseline and 5-year follow-up-on a battery of 12 in-scanner tests, each tapping one of four reference abilities. We performed between-tasks correlations within domain (convergent) and between domain (discriminant) at both the behavioral and neural level, calculating a single measure of construct validity (convergent - discriminant). Cross-sectionally, behavioral construct validity was significantly different from chance at each time point, but longitudinal change was not significant. Analysis by median age split revealed that older adults showed higher behavioral validity, driven by higher discriminant validity (lower between-tasks correlations). Participant-level neural validity decreased over time, with convergent validity consistently greater than discriminant validity; this finding was also observed at the cross-sectional level. In addition, a disproportionate decrease in neural validity with age remained significant after controlling for demographic factors. Factors predicting longitudinal changes in global cognition (mean performance across all 12 tasks) included age, change in neural validity, education, and National Adult Reading Test (premorbid intelligence). Change in neural validity partially mediated the effect of age on change in global cognition. Our findings support the theory of age-related disintegration, linking cognitive decline to changes in neural representations over time.

Cerebrospinal fluid (CSF) biomarkers of synaptic dysfunction, neuroinflammation, and glial response, complementing Alzheimer’s disease (AD) core biomarkers, have improved the pathophysiological characterization of the disease. Here, we tested the hypothesis that the co-expression of multiple CSF biomarkers will help the identification of AD-like phenotypes when biomarker positivity thresholds are not met yet. Two hundred and seventy cognitively unimpaired adults with family history (FH) of sporadic AD (mean age = 60.6 ± 4.85 years, 64.8

Sex-specific vulnerability and resilience along the amyloid cascade may be partly explained by neuroinflammatory processes. Microglial activation may play a more important role in the development of Alzheimer’s disease (AD) in women than in men. We investigated the effect of sex and biomarkers of microglia and astrocytic activation on amyloid (A) and tau (T) burden, and neurodegeneration (N) in cognitively unimpaired (CU) older adults at increased AD risk. We included 397 CU participants (49-73 years, 61.5% women) with the following available CSF biomarker data: Aβ 42/40 , p-tau 181 , sTREM2, GFAP, and YKL40 measured with Roche NeuroToolKit or Elecsys ® immunoassays. A subsample (n = 299) also had MRI-based hippocampal volume data (ASHS segmentation). The outcomes of interest were A: Aβ 42/40 , T: p-tau 181 , and N: hippocampal volume. Predictors included demographics and neuroinflammation markers. First, we tested the effect of sex and neuroinflammation markers on A, T, and N in the whole sample. Then, we tested the neuroinflammation*Aβ 42/40 and neuroinflammation*p-tau interactions on p-tau and hippocampal volume, respectively. Finally, we looked at sex-stratified models. Men were older, more often APOE - ε4 carriers and showed higher GFAP levels (men>women). In the whole sample, neither sex nor neuroinflammation markers were associated with Aβ 42/40 . However, sex (women>men), higher sTREM2 and higher YKL40 were associated with higher p-tau 181 levels, and sex (women<men), lower sTREM2, and higher YKL40 were associated with lower hippocampal volume. Models including interaction terms showed a sex-independent interaction of GFAP with Aβ 42/40 and p-tau 181 on p-tau 181 and hippocampal volume, respectively, suggesting a role of astrocytic activation along the ATN pathway. Sex-stratified analyses showed (1) in women only , a YKL40*Aβ 42/40 interaction on p-tau 181 and an association of higher sTREM2 levels with greater hippocampal volume ( p = .030), suggesting a protective effect, and (2) in men only , a p-tau 181 *sTREM2 and p-tau 181 *YKL40 interaction on hippocampal volume. Statistics are provided in Table 1. Pending replication with longitudinal measurements, our results suggest that microglial and astrocytic activation may play a sex-specific role in downstream amyloid. While astrocytic activation moderates the associations between A, T and N in men and women, microglial activation might provide resilience to neurodegeneration only in women (Figure 1).

Cognitively unimpaired (CU) adults with Alzheimer’s disease (AD) pathologic change may be more vulnerable to developing neuropsychiatric symptoms. We reported an association of higher β-amyloid (Aβ) and increased anxiety/depression during the COVID-19 lockdown in CU adults (Akinci et al., 2022). Here, we investigated whether changes in Aβ 1−42 predict post-traumatic stress disorder (PTSD) symptomatology following COVID-19 lockdown in CU adults at risk for AD. We included 128 CU participants who underwent lumbar puncture 2.3±0.6 years before and 1.1±0.4 years after the lockdown. The outcome of interest was self-reported PTSD symptomatology (Impact of Event Scale Revised) measured 1.7±0.1 years after the lockdown. The main predictor was annual rate of change in cerebrospinal fluid (CSF) Aβ 1−42 measured with the NeuroToolKit panel of robust prototype assays (Roche Diagnostics International Ltd, Rotkreuz, Switzerland). Other predictors included sex, age, years of education, stressors during COVID-19, and anxiety/depression (Hospital Anxiety and Depression Scale, HADS) and perceived stress (Perceived Stress Scale, PSS) measured during lockdown. We performed regression analyses to explore the association between annual rate of change in Aβ 1-42 with PTSD scores adjusting for demographic and stressor variables, and further adjusting for HADS and PSS scores. We then explored the mediating effect of HADS and PSS on the association between change in Aβ 1-42 and PTSD scores. Participant age ranged from 53−72 and 59% were women (Table 1). Independent of demographic variables and stressors experienced during COVID-19, the rate of annual change in Aβ 1-42 predicted PTSD scores (p = .008; Table 2). This association attenuated after introducing HADS and PSS scores into the model (p = .066). We found full mediation effects of HADS and PSS scores, explaining 46% and 40% of the effect of annual change in Aβ 1-42 on PTSD scores, respectively (Figure 1). CU older adults with longitudinal CSF Aβ 1−42 increases are more vulnerable to developing PTSD symptomatology after a stressful event, such as the pandemic. Anxiety/depression is one plausible mechanism through which increases in Aβ might exacerbate PTSD symptomatology. The results suggest a window for stress regulation during stressful events to prevent further mental health worsening in people at risk for AD.

Recent attention has been given to topological data analysis (TDA), and more specifically persistent homology (PH), to identify the underlying shape of brain network connectivity beyond simple edge pairings by computing connective components across different connectivity thresholds (see Sizemore et al., 2019 ). In the present study, we applied PH to task-based functional connectivity, computing 0-dimension Betti (B 0 ) curves and calculating the area under these curves (AUC); AUC indicates how quickly a single connected component is formed across correlation filtration thresholds, with lower values interpreted as potentially analogous to lower whole-brain system segregation (e.g., Gracia-Tabuenca et al., 2020 ). One hundred sixty-three participants from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (age 20-80 years) were tested in-scanner at baseline and five-year follow-up on a battery of tests comprising four domains of cognition (i.e., Stern et al., 2014 ). We tested for 1.) age-related change in the AUC of the B 0 curve over time, 2.) the predictive utility of AUC in accounting for longitudinal change in behavioral performance and 3.) compared system segregation to the PH approach. Results demonstrated longitudinal age-related decreases in AUC for Fluid Reasoning, with these decreases predicting longitudinal declines in cognition, even after controlling for demographic and brain integrity factors; moreover, change in AUC partially mediated the effect of age on change in cognitive performance. System segregation also significantly decreased with age in three of the four cognitive domains but did not predict change in cognition. These results argue for greater application of TDA to the study of aging.

We investigated factors that influence the maintenance of youthful functional activation for a working memory task in healthy older adults. While task-related functional activation has been found to increase in extent and intensity in aging, there have been few investigations into the factors that enable more youthful-appearing activation patterns. Similarity to young-like templates underlying more successful cognitive aging is an attractive idea and has been operationalized in a variety of different data domains in neuroscience. We applied an operationalization of such template similarity in a well-understood verbal working-memory task examined in 135 older adults (age=64.9 ± 3.17 years) using 44 younger adults (age=26.0 ± 2.9 years) as the reference group. Topographic similarity to the young-reference pattern was computed as spatial correlation across voxels between a young- and an older-group pattern. Similarity to the young-reference pattern was evaluated via two approaches: group-wise and at the individual level. In group-wise similarity, moderating factors were dichotomized, splitting older adults into two group. Examining the similarity between these group patterns and the young-reference pattern, we observed more youthful-appearing activation patterns for females than males, participants with thicker than thinner cortex, less white matter hyperintensity than more, and better performance in vocabulary, processing speed, memory, and reasoning. No difference in similarity was observed for high vs. low education groups. Individual-level similarity was quantified between the young-reference pattern template and each older adult’s pattern, for which linear regression showed that the degree of similarity to the young pattern was associated with more accurate performance on the working-memory task, even after covarying out age, sex, education, and three brain structural measures. Overall, using a novel approach to quantify topographic similarity between younger and older adults, we provided evidence that older adults with better overall cognition recruit more youthful-appearing activation patterns during working-memory rehearsal, and we discussed its relevance to resilience mechanisms in aging.### Competing Interest StatementThe authors have declared no competing interest.### Funding StatementWe wish to gratefully acknowledge support from the grant NIH/NIA R01AG038465-06.### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Ethics committee/Internal Review Board of the College of Physicians and Surgeons of Columbia University gave ethical approval for this work.I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesAll deidentified neuropsychological and behavioral data, and neuroimaging summary measures, along with analytical scripts used to produce the results presented in the manuscript will be uploaded to Dryad ([datadryad.org][1]). [1]: http://datadryad.org

Previous studies reported sleep alterations during the COVID-19 lockdown. Disrupted sleep may influence and promote Alzheimer’s disease (AD) pathologies. In cognitively unimpaired adults at AD risk, we investigated the association of sleep duration changes during lockdown in relation to pre- and post-lockdown AD-related CSF biomarkers. We included 118 adults (52-71 years, 61.9% women) with self-reported data on sleep duration before and during the lockdown (May–July 2020). Participants completed a questionnaire on hours of sleep per night (<7h vs . ≥7h) at both timepoints and were classified into three groups: “No change (<7h or ≥7h before and during lockdown)”, “Increased (from <7h to ≥7h during lockdown)” or “Decreased (from ≥7h to <7h during lockdown)”. All had CSF biomarkers measured with Roche NeuroToolKit or Elecsys ® immunoassays before (pre-lockdown) and after (post-lockdown) completing the questionnaire (average time lapse: 3.4±0.4 years). During the lockdown, 117 (99.1%) participants completed an anxiety/depression assessment (Hospital Anxiety and Depression Scale). ANCOVA models adjusted by pre-lockdown biomarker values were run to investigate differences among the three groups in post-lockdown AD pathology (Aβ42/40 and p-tau), neuroinflammation (sTREM2), and neuronal injury (NfL) biomarkers. Covariates included age, sex, education (years), APOE -ε4 status, anxiety/depression levels, and time variability between the biomarker assessments. We then performed sensitivity analyses to adjust the models by pre-lockdown Aβ42/40 levels and sleep quality (Pittsburgh Sleep Quality Index, n = 90). Ninety-four participants (79.7%) reported “No change (stable)”, 10 (8.5%) “Increased” and 14 (11.5%) “Decreased” sleep duration during lockdown. Irrespective of pre-lockdown p-tau and NfL levels, participants transitioning to decreased sleep showed higher p-tau and NfL post-lockdown compared with the increased sleep group. Further, those with stable sleep duration showed higher post-lockdown p-tau and NfL compared with the increased group (Table 1). Results were independent of pre-lockdown Aβ42/40 levels (Table 2) and sleep quality (Table 3). Transitioning to fewer hours of sleep during the lockdown was associated with greater tau pathology and neuronal injury levels post-lockdown. Consequently, alterations in sleep duration during the pandemic may hasten pathological processes downstream amyloid pathology. These findings suggest that pandemic-induced lifestyle changes may increase AD prevalence in the long term.

COVID-19-related SARS-CoV-2 infection has been linked with brain abnormalities and cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD), neuroinflammation, and neuronal injury. Whether COVID-19 increases the brain’s vulnerability to the development of AD is unclear. In participants at an increased risk of AD, we investigated the association of COVID-19 with pre- and post-pandemic AD biomarkers. We included 132 cognitively unimpaired adults from the ALFA+ cohort (52-71 years, 61.4% women) who provided retrospective self-reported data on SARS-CoV-2 infection (with COVID-19 vs . without COVID-19). As of February 2022, 125 (94.7%) participants had available CSF biomarkers (measured with exploratory Roche NeuroToolKit or Elecsys ® immunoassays, Roche Diagnostics International Ltd, Rotkreuz, Switzerland) and 76 (57.6%) had [ 18 F]flutemetamol-PET data acquired before (pre-pandemic) and after (post-pandemic) the beginning of the COVID-19 pandemic (average time lapse between the assessments: 3.5±0.6 years). [ 18 F]flutemetamol PET SUVR maps were obtained using the whole cerebellum as the reference region. First, we performed ANCOVA models to investigate whether COVID-19 was associated with post-pandemic CSF biomarkers of core AD pathology (Aβ42/40 and p-tau), neuronal injury (NfL), and neuroinflammation (sTREM2, GFAP, and IL-6), while controlling for pre-pandemic biomarker levels. Covariates were age, sex, years of education, APOE -ε4 status, and time lapse between the biomarker assessments. Second, we performed a voxel-wise analysis in SPM-12 using a matched-group comparison design (with COVID-19 vs . without COVID-19 matched by pre-pandemic Centiloid values, age, and APOE -ε4 status) with the post-pandemic amyloid-PET scans as the outcome of interest. Fifteen (12%) participants included in ANCOVA reported COVID-19. Eleven (14.5%) with amyloid-PET scans reported COVID-19 and were matched with 11 participants without COVID-19 for voxel-wise analysis. In ANCOVA models, no significant association between COVID-19 and post-pandemic CSF biomarkers was found (Table 1). Results from the t-test voxel-wise analysis also did not show any differences between participants with vs . without COVID-19 on [ 18 F]flutemetamol-PET uptake after correction with false discovery rate. Our interim analyses did not show any association between self-reported COVID-19 and post-pandemic biomarkers of AD pathology, neuronal injury, and neuroinflammation. The results are pending confirmation of COVID-19 status using serology data (n = 181) and complete sample size.

The aging process is characterized by change across several measures that index cognitive status and brain integrity. In the present study, 54 cognitively-healthy younger and older adults, were analyzed, longitudinally, on a verbal working memory task to investigate the effect of brain maintenance (i.e., cortical thickness) and cognitive reserve (i.e., NART IQ as proxy) factors on a derived measure of neural efficiency. Participants were scanned using fMRI while presented with the Letter Sternberg task, a verbal working memory task consisting of encoding, maintenance and retrieval phases, where cognitive load is manipulated by varying the number of presented items (i.e., between one and six letters). Via correlation analysis, we looked at region-level and whole-brain relationships between load levels within each phase and then computed a global task measure, what we term phase specificity , to analyze how similar neural responses were across load levels within each phase compared to between each phase. We found that longitudinal change in phase specificity was positively related to longitudinal change in cortical thickness, at both the whole-brain and regional level. Additionally, baseline NART IQ was positively related to longitudinal change in phase specificity over time. Furthermore, we found a longitudinal effect of sex on change in phase specificity, such that females displayed higher phase specificity over time. Cross-sectional findings aligned with longitudinal findings, with the notable exception of behavioral performance being positively linked to phase specificity cross-sectionally at baseline. Taken together, our findings suggest that phase specificity positively relates to brain maintenance and reserve factors and should be better investigated as a measure of neural efficiency.

Aging is typically marked by a decline in some domains of cognition. Some theories have linked this decline to a reduction in distinctiveness of processing at the neural level that in turn leads to cognitive decline. Increasing correlations with age among tasks formerly considered independent have been posited, supporting dedifferentiation, although results have been mixed. An alternative view is that tasks become more, and not less, independent of one another with increasing age, suggesting age-related differentiation, or what has also been termed disintegration. In the current study, we investigated if the aging process leads to a loss of behavioral and neural specificity within latent cognitive abilities. To this end, we tested 287 participants (20-80 years) on a battery of 12 in-scanner tests, three each tapping one of four reference abilities. We performed between-task correlations within domain (pertaining to convergent validity), and between domain (pertaining to discriminant validity) at both the behavioral and neural level and found that neural convergent validity was positively associated with behavioral convergent validity. In examining neural validity across the lifespan, we found significant reductions in both within- and between-domain task correlations, with a significant decrease in construct validity (convergent or discriminant) with age. Furthermore, the effect of age on total cognition was significantly mediated by neural construct validity. Taken together, contrary to a hypothesis of dedifferentiation, these correlation reductions suggest that tasks indeed become more independent with advancing age, favoring a differentiation/disintegration hypothesis of aging.

Category-specific impairments witnessed in patients with semantic deficits have broadly dissociated into natural and artificial kinds. However, how the category of food (more specifically, fruits and vegetables) fits into this distinction has been difficult to interpret, given a pattern of deficit that has inconsistently mapped onto either kind, despite its intuitive membership to the natural domain. The present study explores the effects of a manipulation of a visual sensory (i.e., color) or functional (i.e., orientation) feature on the consequential semantic processing of fruits and vegetables (and tools, by comparison), first at the behavioral and then at the neural level. The categorization of natural (i.e., fruits/vegetables) and artificial (i.e., utensils) entities was investigated via cross–modal priming. Reaction time analysis indicated a reduction in priming for color-modified natural entities and orientation-modified artificial entities. Standard event-related potentials (ERP) analysis was performed, in addition to linear classification. For natural entities, a N400 effect at central channel sites was observed for the color-modified condition compared relative to normal and orientation conditions, with this difference confirmed by classification analysis. Conversely, there was no significant difference between conditions for the artificial category in either analysis. These findings provide strong evidence that color is an integral property to the categorization of fruits/vegetables, thus substantiating the claim that feature-based processing guides as a function of semantic category.

Cross-sectional versus longitudinal comparisons of age-related change have often revealed differing results. In the current study, we used within-subject task-based fMRI to investigate changes in voxel-based activations and behavioral performance across the life span in the Reference Ability Neural Network cohort, at both baseline and 5 year follow-up. We analyzed fMRI data from between 127 and 159 participants (20-80 years) on a battery of tests relating to each of four cognitive reference abilities. We applied a Gaussian age kernel to capture continuous change across the life span using a 5 year sliding window centered on each age in our participant sample, with a subsequent division into young, middle, and old age brackets. This method was applied separately to both cross-sectional approximations of change and real longitudinal changes adopting a comparative approach. We then focused on longitudinal measurements of neural change to identify regions expressing peak changes and fluctuations of sign change across our sample. Our results revealed several regions expressing divergence between cross-sectional and longitudinal measurements in each domain and age bracket; behavioral comparisons between measurements showed differences in change curves for all four domains, with processing speed displaying the steepest declines. In the longitudinal change measurement, we found lack of support for age-related frontal increases across analysis types, instead finding more posterior regions displaying peak increases in activation, particularly in the old age bracket. Our findings encourage greater focus on longitudinal measurements of age-related changes, which display appreciable differences from cross-sectional approximations.

Although studies report age-related declines on tests of executive function, not all executive tests show age differences, including the dual-task paradigm. As processing speed is known to decline with age, it is possible that changes in speed contribute to the variation in age-related decline found on different tests of executive function. In this study, the effects of age and processing speed on different executive tests in the same group of younger and older adults were investigated. Fifty-nine (n = 28 males & n = 31 females) younger adults ( M age = 21.49; SD = 2.54) and N = 52 (n = 22 males & n = 30 females) older adults ( M age = 72.04; SD = 4.99) were assessed on the following battery of measures: processing speed and the executive functions of dual-tasking, inhibition, set-shifting, and updating. Older adults performed significantly worse than younger adults on all executive function tests except dual-tasking. In addition, age, rather than processing speed, predicted executive function performance on executive tests of inhibition, set-shifting and updating tests. These findings confirm that dual-tasking does not decline with age and the age differences found on tests of inhibition, set-shifting and updating are not simply explained by processing speed.

Cognitive functions and their underlying neural substrates change across the lifespan (for a review, see Grady et al., 2012). In an attempt to capture these changes, most prior work utilizing a cross‐sectional approach have investigated age‐group differences in behavioral performance or neural activations related to particular functions. In the present study, we aimed to quantify neural changes in the brain associated with four principal cognitive domains by considering age as a continuous factor and linking regions displaying the greatest change in each domain with behavioral performance.

Previous studies have demonstrated that four latent variables, or reference abilities (RAs), can account for the majority of age-related changes in cognition: these being episodic memory, fluid reasoning, speed of processing, and vocabulary. In the current study, we focused on RA-selective functional connectivity patterns that vary with both age and behavior. We analyzed fMRI data from 287 community-dwelling adults (20-80 years) on a battery of tests relating to the four RAs (three tests per RA = 12 tests). Functional connectivity values were calculated between a pre-defined set of 264 ROIs (nodes). Across all participants, we (a) identified connections (edges) that correlated with an RA-specific indicator variable and, indexing only these edges; (b) performed linear regression analysis per edge, regressing indicator correlations (Model 1) and connectivity values (Model 2) on Age, Behavioral Performance, and the Interaction term; and (c) took the conjunction of significant edges between models. Results revealed a different subset of edges for each RA whose connectivity strength and domain-selectivity varied with age and behavior. Strikingly, the fluid reasoning RA was particularly vulnerable to the effects of age and displayed the most extensive connectivity and selectivity "footprint" for behavior. These findings indicate that different functional networks are recruited across RA, with fluid reasoning displaying a special status among them.

There is ongoing debate regarding the role that sensorimotor regions play in conceptual processing, with embodied theories supporting their direct involvement in processing verbs describing body part movements. Patient lesion studies examining a causal role for sensorimotor activation in conceptual task performance have suffered the caveat of lesions being largely diffuse and extensive beyond sensorimotor cortices. The current study addresses this limitation in reporting on 20 pre-operative neurosurgical patients with focal lesion to the pre- and post-central area corresponding to somatotopic representations. Patients were presented with a battery of neuropsychological tests and experimental tasks tapping into motor imagery and verbal conceptual verb processing in addition to neurophysiological measures including DTI, fMRI, and MEP being measured. Results indicated that left tumor patients who presented with a lesion at or near somatotopic hand representations performed significantly worse on the mental rotation hand task and that performance correlated with MEP amplitudes in the upper limb motor region. Furthermore, performance on tasks of verbal processing was within the normal range. Taken together, while our results evidence the involvement of the motor system in motor imagery processes, they do not support the embodied view that sensorimotor regions are necessary to tasks of action verb processing.

Visual recognition of objects may rely on different features depending on the category to which they belong. Recognizing natural objects, such as fruits and plants, weighs more on their perceptual attributes, whereas recognizing man-made objects, such as tools or vehicles, weighs more upon the functions and actions they enable. Edible objects are perceptually rich but also prepared for specific functions, therefore it is unclear how perceptual and functional attributes affect their recognition. Two event-related potentials experiments investigated: (i) whether food categorization in the brain is differentially modulated by sensory and functional attributes, depending on whether the food is natural or transformed; (ii) whether these processes are modulated by participants' body mass index. In experiment 1, healthy normal-weight participants were presented with a sentence (prime) and a photograph of a food. Primes described either a sensory feature ('It tastes sweet') or a functional feature ('It is suitable for a wedding party') of the food, while photographs depicted either a natural (e.g., cherry) or a transformed food (e.g., pizza). Prime-feature pairs were either congruent or incongruent. This design aimed at modulating N400-like components elicited by semantic processing. In experiment 1, N400-like amplitude was significantly larger for transformed food than for natural food with sensory primes, and vice versa with functional primes. In experiment 2, underweight and obese women performed the same semantic task. We found that, while the N400-like component in obese participants was modulated by sensory-functional primes only for transformed food, the same modulation was found in underweight participants only for natural food. These findings suggest that the level of food transformation interacts with participants' body mass index in modulating food perception and the underlying brain processing.

In recent years we have witnessed an increasing interest in food processing and eating behaviors. This is probably due to several reasons. The biological relevance of food choices, the complexity of the food-rich environment in which we presently live (making food-intake regulation difficult), and the increasing health care cost due to illness associated with food (food hazards, food contamination, and aberrant food-intake). Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for non-commercial purposes to independent researchers who aim at developing their own research program. The FoodCast Research Image Database (FRIDa) we present here includes 877 images belonging to eight different categories: natural-food (e.g., strawberry), transformed-food (e.g., french fries), rotten-food (e.g., moldy banana), natural-non-food items (e.g., pinecone), artificial food-related objects (e.g., teacup), artificial objects (e.g., guitar), animals (e.g., camel), and scenes (e.g., airport). FRIDa has been validated on a sample of healthy participants (N = 73) on standard variables (e.g., valence, familiarity, etc.) as well as on other variables specifically related to food items (e.g., perceived calorie content); it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power, etc.). FRIDa is a well-controlled, flexible, validated, and freely available (http://foodcast.sissa.it/neuroscience/) tool for researchers in a wide range of academic fields and industry.