Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers

Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.

Matrix metalloproteinases are associated with brain atrophy in cognitively unimpaired individuals

Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) have been linked to age-related neurodegeneration and Alzheimer's disease (AD), but their role in normal aging is poorly understood. We used linear mixed models to determine if baseline or rate of yearly change in cerebrospinal fluid (CSF) levels of MMP-2; MMP-3; MMP-10; TIMP-123 (composite of TIMP-1, TIMP-2, and TIMP-3); or TIMP-4 predicted changes in bilateral entorhinal cortex thickness, hippocampal volume, or lateral ventricle volume in cognitively unimpaired individuals. We also assessed effects on the CSF AD biomarkers amyloid-β42 and phosphorylated tau181. Low baseline levels of MMP-3 predicted larger ventricle volumes and more entorhinal cortex thinning. Increased CSF MMP-2 levels over time predicted more entorhinal thinning, hippocampal atrophy, and ventricular expansion, while increased TIMP-123 over time predicted ventricular expansion. No MMP/TIMPs predicted changes in CSF AD biomarkers. Notably, we show for the first time that longitudinal increases in MMP-2 and TIMP-123 levels may predict age-associated brain atrophy. In conclusion, MMPs and TIMPs may play a role in brain atrophy in cognitively unimpaired aging.

Associations of neuroinflammatory IL-6 and IL-8 with brain atrophy, memory decline, and core AD biomarkers - in cognitively unimpaired older adults

Concentrations of pro-inflammatory cytokines -interleukin-6 (IL-6) and interleukin-8 (IL-8) - are increased with age and in Alzheimer's disease (AD). It is not clear whether concentrations of IL-6 and IL-8 in the central nervous system predict later brain and cognitive changes over time nor whether this relationship is mediated by core AD biomarkers. Here, 219 cognitively healthy older adults (62-91 years), with baseline cerebrospinal fluid (CSF) measures of IL-6 and IL-8 were followed over time - up to 9 years - with assessments that included cognitive function, structural magnetic resonance imaging, and CSF measurements of phosphorylated tau (p-tau) and amyloid-β (Aβ-42) concentrations (for a subsample). Higher baseline CSF IL-8 was associated with better memory performance over time in the context of lower levels of CSF p-tau and p-tau/Aβ-42 ratio. Higher CSF IL-6 was related to less CSF p-tau changes over time. The results are in line with the hypothesis suggesting that an up-regulation of IL-6 and IL-8 in the brain may play a neuroprotective role in cognitively healthy older adults with lower load of AD pathology.

Individual variations in 'brain age' relate to early-life factors more than to longitudinal brain change

Brain age is a widely used index for quantifying individuals’ brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging.

Scientists who study the brain and aging are keen to find an effective way to measure brain health, which could help identify people at risk for dementia or memory problems. One popular marker is ‘brain age’. This measurement uses a brain scan to estimate a person’s chronological age, then compares the estimated brain age to the person’s actual age to determine whether their brain is aging faster or slower than expected for their age.

However, since brain age relies on one brain scan taken at one point in time, it is not clear whether it really measures brain aging or if it might capture brain differences that have been present throughout the individual’s life. Studies comparing individual brain scans over several years would be necessary to know for sure.

Now, Vidal-Piñeiro et al. show that the brain-age measurement does not reflect faster brain aging. In the experiments, the researchers compared repeated brain scans of thousands of individuals over 40 years of age. The experiments showed that deviations from normative brain age detected in a single scan reflected early life differences more than changes in the brain over time. For example, people with older-looking brains were more likely to have had a low birth weight or to have a combination of genes associated with having an older looking brain.

Vidal-Piñeiro et al. show that brain age mostly reflects a pre-existing brain condition rather than brain aging. The experiments also suggest that genetics and early brain development likely have a strong impact on brain health throughout life. Future studies trying to test or develop brain-aging measurements should use serial measurements to track brain changes over time.

The genetic organization of longitudinal subcortical volumetric change is stable throughout the lifespan

Development and aging of the cerebral cortex show similar topographic organization and are governed by the same genes. It is unclear whether the same is true for subcortical regions, which follow fundamentally different ontogenetic and phylogenetic principles. We tested the hypothesis that genetically governed neurodevelopmental processes can be traced throughout life by assessing to which degree brain regions that develop together continue to change together through life. Analyzing over 6000 longitudinal MRIs of the brain, we used graph theory to identify five clusters of coordinated development, indexed as patterns of correlated volumetric change in brain structures. The clusters tended to follow placement along the cranial axis in embryonic brain development, suggesting continuity from prenatal stages, and correlated with cognition. Across independent longitudinal datasets, we demonstrated that developmental clusters were conserved through life. Twin-based genetic correlations revealed distinct sets of genes governing change in each cluster. Single-nucleotide polymorphisms-based analyses of 38,127 cross-sectional MRIs showed a similar pattern of genetic volume–volume correlations. In conclusion, coordination of subcortical change adheres to fundamental principles of lifespan continuity and genetic organization.

Methylphenidate Effects on Cortical Thickness in Children and Adults with Attention-Deficit/Hyperactivity Disorder: A Randomized Clinical Trial

BACKGROUND AND PURPOSE

Although methylphenidate is frequently used to treat children with attention-deficit/hyperactivity disorder, it is currently unknown how methylphenidate affects brain development. In a randomized controlled trial, we investigated whether the cortical effects of methylphenidate are modulated by age.

MATERIALS AND METHODS

Between June 1, 2011, and June 15, 2015, we conducted a randomized, double-blind, placebo-controlled trial (Effects of Psychotropic Drugs on Developing Brain-Methylphenidate) in 99 males with attention-deficit/hyperactivity disorder (according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, criteria) from referral centers in the greater Amsterdam area in the Netherlands. The trial was registered on March 24, 2011 (identifier NL34509.000.10) and subsequently at the Netherlands National Trial Register (identifier NTR3103). Participants (first enrolled October 13, 2011) were 10-12 years or 23-40 years of age and randomized to treatment with either methylphenidate or a placebo for 16 weeks. Our main outcome was a change in cortical thickness in predefined ROIs as measured by MR imaging pre- and posttreatment.

RESULTS

We observed a time × medication × age interaction (F[1,88.825] = 4.316, P < .05) for the right medial cortex ROI, where methylphenidate treatment yielded less cortical thinning in children, but not in adults or the placebo groups.

CONCLUSIONS

Our finding that the effects of methylphenidate on right medial cortical thickness differ between children and adults infers that the drug affects gray matter development in this brain region. This warrants replication in larger groups with longer follow-up to determine whether this effect can also be observed in other cortical brain regions and whether it may have long-term consequences.

Lifespan trajectories of relative corpus callosum thickness: Regional differences and cognitive relevance

The cerebral hemispheres are specialized for different cognitive functions and receive divergent information from the sensory organs, so that the interaction between the hemispheres is a crucial aspect of perception and cognition. At the same time, the major fiber tract responsible for this interaction, the corpus callosum, shows a structural development across the lifespan which is over-proportional. That is, compared to changes in overall forebrain volume, the corpus callosum shows an accentuated growth during childhood, adolescence, and early adulthood, as well as pronounced decline in older age. However, this over-proportionality of growth and decline along with potential consequences for cognition, have been largely overlooked in empirical research. In the present study we systematically address the proportionality of callosal development in a large mixed cross-sectional and longitudinal sample (1867 datasets from 1014 unique participants), covering the human lifespan (age range 4-93 years), and examine the cognitive consequences of the observed changes. Relative corpus callosum thickness was measured at 60 segments along the midsagittal surface, and lifespan trajectories were clustered to identify callosal subsections of comparable lifespan development. While confirming the expected inverted u-shaped lifespan trajectories, we also found substantial regional variation. Compared with anterior clusters, the most posterior sections exhibited an accentuated growth during development which extends well into the third decade of life, and a protracted decline in older age which is delayed by about 10 years (starting mid to late 50s). We further showed that the observed longitudinal changes in relative thickness of the mid splenium significantly mediates age-related changes in tests assessing verbal knowledge and non-verbal visual-spatial abilities across the lifespan. In summary, we demonstrate that analyzing the proportionality of callosal growth and decline offers valuable insight into lifespan development of structural connectivity between the hemispheres, and suggests consequences for the cognitive development of perception and cognition.

Healthy minds from 0-100 years: Optimising the use of European brain imaging cohorts ("Lifebrain")

The main objective of "Lifebrain" is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5,000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.

CSF neurofilament light levels predict hippocampal atrophy in cognitively healthy older adults

Cerebrospinal fluid (CSF) neurofilament light (NFL) is a marker of axonal degeneration. We tested whether CSF NFL levels predict hippocampal atrophy rate in cognitively healthy older adults independently of the established CSF Alzheimer's disease (AD) biomarkers, β-amyloid 1-42, and phosphorylated tau (P-tau). We included 144 participants in a 2-year longitudinal study with baseline CSF measures and 2 magnetic resonance images. Eighty-eight participants had full data available. A subgroup of 36 participants with very low AD risk was also studied. NFL predicted hippocampal atrophy rate independently of age, β-amyloid 1-42, and P-tau. Including NFL, P-tau, and age in the same model, higher NFL and lower P-tau predicted higher hippocampal atrophy (R² = 0.20, NFL: β = -0.34; p = 0.003; P-tau: β = 0.27; p = 0.009). The results were upheld in the participants with very low AD risk. NFL predicted neurodegeneration in older adults with very low AD probability. We suggest that factors previously shown to be important for brain degeneration in mild cognitive impairment may also impact changes in normal aging, demonstrating that NFL is likely to indicate AD-independent, age-expected neurodegeneration.

White matter characteristics and cognition in prenatally opiate- and polysubstance-exposed children: a diffusion tensor imaging study

BACKGROUND AND PURPOSE

Prenatal drug exposure may influence the developing brain. Our aim was to study WM characteristics with DTI in children with prenatal opiate and polysubstance exposure and in controls. We assessed whether group differences in FA, DA, and DR could be found and related to cognitive function.

MATERIALS AND METHODS

The study was approved by a committee for medical research ethics. Parents signed an informed consent; children gave spoken consent. Our sample included 14 prenatally substance-exposed adopted children (5 girls; age range, 8.6-13.9 years; mean, 11.3 +/- 1.7 years) and 14 control children (7 girls; age range, 9.0-10.2 years; mean, 9.8 +/- 0.3 years). Tract-based spatial statistics were used to define a common WM skeleton for the sample, and FA was compared between groups throughout the skeleton, controlling for age and sex. Clusters of significant group differences >or=100 voxels (P <. 05) were identified. FA, DA, and DR within clusters were correlated with cognitive function.

RESULTS

Ten clusters of FA group differences, mostly in central, posterior, and inferior parts of the brain, were identified (P <. 05), showing lower FA in substance-exposed children. FA and DA correlated positively and DR, negatively with cognitive function across groups.

CONCLUSIONS

Prenatally substance-exposed children exhibited lower FA in restricted areas of WM, mostly relatively central, inferior, and posterior, where myelination occurs early in development. Myelin in these areas may be particularly vulnerable to prenatal substance exposure. FA and DR related moderately to cognitive function. Potential confounding factors existed and were considered.

Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease

BACKGROUND AND PURPOSE

Different biomarkers for AD may potentially be complementary in diagnosis and prognosis of AD. Our aim was to combine MR imaging, FDG-PET, and CSF biomarkers in the diagnostic classification and 2-year prognosis of MCI and AD, by examining the following: 1) which measures are most sensitive to diagnostic status, 2) to what extent the methods provide unique information in diagnostic classification, and 3) which measures are most predictive of clinical decline.

MATERIALS AND METHODS

ADNI baseline MR imaging, FDG-PET, and CSF data from 42 controls, 73 patients with MCI, and 38 patients with AD; and 2-year clinical follow-up data for 36 controls, 51 patients with MCI, and 25 patients with AD were analyzed. The hippocampus and entorhinal, parahippocampal, retrosplenial, precuneus, inferior parietal, supramarginal, middle temporal, lateral, and medial orbitofrontal cortices were used as regions of interest. CSF variables included Abeta42, t-tau, p-tau, and ratios of t-tau/Abeta42 and p-tau/Abeta42. Regression analyses were performed to determine the sensitivity of measures to diagnostic status as well as 2-year change in CDR-SB, MMSE, and delayed logical memory in MCI.

RESULTS

Hippocampal volume, retrosplenial thickness, and t-tau/Abeta42 uniquely predicted diagnostic group. Change in CDR-SB was best predicted by retrosplenial thickness; MMSE, by retrosplenial metabolism and thickness; and delayed logical memory, by hippocampal volume.

CONCLUSIONS

All biomarkers were sensitive to the diagnostic group. Combining MR imaging morphometry and CSF biomarkers improved diagnostic classification (controls versus AD). MR imaging morphometry and PET were largely overlapping in value for discrimination. Baseline MR imaging and PET measures were more predictive of clinical change in MCI than were CSF measures.

Mini-mental state examination is sensitive to brain atrophy in Alzheimer's disease

BACKGROUND/AIMS

Screening instruments such as the Mini-Mental State Examination (MMSE) are useful for the early identification of Alzheimer's disease (AD). We tested whether macrostructural differences in brain volume are related to the MMSE.

METHODS

The MMSE was related to cortical thickness and the volume of 19 brain structures in 96 patients with mild to moderate AD. In addition, the patients were compared to 93 healthy elderly controls.

RESULTS

The MMSE was related to the volume of the total brain, cerebral cortex, accumbens, cerebral white matter, inferior lateral ventricles and hippocampus. Positive correlations with cortical thickness were found for 41% of the brain surface, and 58% of this area was significantly thinner in AD.

CONCLUSION

The MMSE is sensitive to macrostructural brain atrophy in AD, but also to morphometric variation not specifically related to AD.

Multimodal imaging in mild cognitive impairment: Metabolism, morphometry and diffusion of the temporal-parietal memory network

This study compared sensitivity of FDG-PET, MR morphometry, and diffusion tensor imaging (DTI) derived fractional anisotropy (FA) measures to diagnosis and memory function in mild cognitive impairment (MCI). Patients (n=44) and normal controls (NC, n=22) underwent FDG-PET and MRI scanning yielding measures of metabolism, morphometry and FA in nine temporal and parietal areas affected by Alzheimer's disease and involved in the episodic memory network. Patients also underwent memory testing (RAVLT). Logistic regression analysis yielded 100% diagnostic accuracy when all methods and ROIs were combined, but none of the variables then served as unique predictors. Within separate ROIs, diagnostic accuracy for the methods combined ranged from 65.6% (parahippocampal gyrus) to 73.4 (inferior parietal cortex). Morphometry predicted diagnostic group for most ROIs. PET and FA did not uniquely predict group, but a trend was seen for the precuneus metabolism. For the MCI group, stepwise regression analyses predicting memory scores were performed with the same methods and ROIs. Hippocampal volume and FA of the retrosplenial WM predicted learning, and hippocampal metabolism and parahippocampal cortical thickness predicted 5 minute recall. No variable predicted 30 minute recall independently of learning. In conclusion, higher diagnostic accuracy was achieved when multiple methods and ROIs were combined, but morphometry showed superior diagnostic sensitivity. Metabolism, morphometry and FA all uniquely explained memory performance, making a multi-modal approach superior. Memory variation in MCI is likely related to conversion risk, and the results indicate potential for improved predictive power by the use of multimodal imaging.

Multi-modal imaging predicts memory performance in normal aging and cognitive decline

This study (n=161) related morphometric MR imaging, FDG-PET and APOE genotype to memory scores in normal controls (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD). Stepwise regression analyses focused on morphometric and metabolic characteristics of the episodic memory network: hippocampus, entorhinal, parahippocampal, retrosplenial, posterior cingulate, precuneus, inferior parietal, and lateral orbitofrontal cortices. In NC, hippocampal metabolism predicted learning; entorhinal metabolism predicted recognition; and hippocampal metabolism predicted recall. In MCI, thickness of the entorhinal and precuneus cortices predicted learning, while parahippocampal metabolism predicted recognition. In AD, posterior cingulate cortical thickness predicted learning, while APOE genotype predicted recognition. In the total sample, hippocampal volume and metabolism, cortical thickness of the precuneus, and inferior parietal metabolism predicted learning; hippocampal volume and metabolism, parahippocampal thickness and APOE genotype predicted recognition. Imaging methods appear complementary and differentially sensitive to memory in health and disease. Medial temporal and parietal metabolism and morphometry best explained memory variance. Medial temporal characteristics were related to learning, recall and recognition, while parietal structures only predicted learning.

Morphometric changes in the episodic memory network and tau pathologic features correlate with memory performance in patients with mild cognitive impairment

BACKGROUND AND PURPOSE

Mild cognitive impairment (MCI) may affect several cognitive domains, including attention and reasoning, but is often first characterized by memory deficits. The purpose of this study was to ask these 2 questions: 1) Can levels of CSF tau proteins and amyloid beta 42 peptide explain thinning of the cerebral cortex in patients with MCI? 2) How are brain morphometry, CSF biomarkers, and apolipoprotein E (APOE) allelic variation related to episodic memory function in MCI?

MATERIALS AND METHODS

Hippocampal volume and cortical thickness were estimated by MR imaging and compared for patients with MCI (n = 18) and healthy controls (n = 18). In addition, regions of interest (ROIs) were selected in areas where the MCI group had atrophy and which overlapped with the episodic memory network (temporal, entorhinal, inferior parietal, precuneus/posterior cingulate, and frontal). Relationships among morphometry, CSF biomarkers, APOE, and memory were tested. The analyses were repeated with an independent sample of patients with MCI (n = 19).

RESULTS

Patients with MCI and pathologic CSF values had hippocampal atrophy. However, both patients with pathologic and patients with nonpathologic CSF had a thinner cortex outside the hippocampal area. CSF pathology was related to hippocampal volume, whereas relationships with cortical thickness were found mainly in one of the samples. Morphometry correlated robustly with memory performance across MCI samples, whereas less stable results were found for tau protein.

CONCLUSION

The differences in hippocampal volume between the MCI and the healthy control groups were only found in patients with pathologic CSF biomarkers, whereas differences in cortical thickness were also found for patients without such pathologic features. Morphometry in areas in the episodic memory network was robustly correlated with memory performance. It is speculated that atrophy in these areas may be associated with the memory problems seen in MCI.

Volumetric cerebral characteristics of children exposed to opiates and other substances in utero

Morphometric cerebral characteristics were studied in children with prenatal poly-substance exposure (n=14) compared to controls (n=14) without such exposure. Ten of the substance-exposed children were born to mothers who used opiates (heroin) throughout the pregnancy. Groups were compared across 16 brain measures: cortical gray matter, cerebral white matter, hippocampus, amygdala, thalamus, accumbens area, caudate, putamen, pallidum, brainstem, cerebellar cortex, cerebellar white matter, lateral ventricles, inferior lateral ventricles, and the 3rd and 4th ventricles. In addition, continuous measurement of thickness across the entire cortical mantle was performed. Volumetric characteristics were correlated with ability and questionnaire assessments 2 years prior to scan. Compared to controls, the substance-exposed children had smaller intracranial and brain volumes, including smaller cerebral cortex, amygdala, accumbens area, putamen, pallidum, brainstem, cerebellar cortex, cerebellar white matter, and inferior lateral ventricles, and thinner cortex of the right anterior cingulate and lateral orbitofrontal cortex. Pallidum and putamen appeared especially reduced in the subgroup exposed to opiates. Only volumes of the right anterior cingulate, the right lateral orbitofrontal cortex and the accumbens area, showed some association with ability and questionnaire measures. The sample studied is rare and hence small, so conclusions cannot be drawn with certainty. Morphometric group differences were observed, but associations with previous behavioral assessment were generally weak. Some of the volumetric differences, particularly thinner cortex in part of the right lateral orbitofrontal cortex, may be moderately involved in cognitive and behavioral difficulties more frequently experienced by opiate and poly-substance-exposed children.

Size does matter in the long run: hippocampal and cortical volume predict recall across weeks

OBJECTIVE

To study the morphometric determinants of recall of verbal material for an extended period in an adult lifespan sample.

METHODS

Healthy adults of varying ages were studied using automated segmentation of MRI scans with volumes of hippocampus, cortex, and white matter, and verbal memory tests assessing recall after 5 minutes, 30 minutes, and a mean period of 11 weeks. Stepwise regression analyses were performed with 5 minutes, 30 minutes, and 11-week recall as the dependent variables. Hippocampal, cortical, and white matter volumes were included in the initial set of predictor variables in each case, and the analyses were repeated with age as an additional predictor variable.

RESULTS

When age was not included, cortical volume was the only variable predicting recall after 5 and 30 minutes, whereas hippocampal and cortical volumes predicted recall after 11 weeks. When age was included in the model, this was the only variable predicting recall after 5 and 30 minutes, whereas age and hippocampus gave contributions in prediction of recall after several weeks.

CONCLUSION

This study supports a critical role of cortical and hippocampal size in recall. Hippocampal size seems more important in recall after 11 weeks than after a shorter time interval.

P300 and neuropsychological tests as measures of aging: scalp topography and cognitive changes

The rationale for the present study was to investigate several aspects of P300 topography in relation to aging and neuropsychological measures. We administered an auditory oddball ERP task to 72 participants aged 21.8 to 94.7 years, 36 males and 36 females, in addition to the Wechsler Abbreviated Scales of Intelligence (WASI) and digit span from the Wechsler Adult Intelligence Scales--Revised (WAIS-R). The relationship between age and P300 latency and amplitude at different electrodes was investigated, as well as the changes in the correlational pattern between P300 latency and amplitude with increasing age. A formal test of curvilinear relationships for P300 latency/amplitude and age was performed. Principal component factor analyses were performed for P300 latency and amplitude separately in order to check for possible superordinate structures in the distribution of the electrical activity measured at the scalp. In addition, each of the electrodes and each of the factors were correlated with the different neuropsychological measures, and the contribution of age to the observed relationships is discussed. The main conclusion drawn is that the activity generated from different brain areas change at different rates with age. While the posterior area shows a clear reduction of P300 amplitude and a delay of P300 latency with age, the amplitude does not decrease at the same rate in the fronto-central areas, and there is at the same time a marked hemispheric asymmetry in the age dependent change of activation. Based on our data, it may be concluded that a curvilinear expression generally does not explain the aging effect on the ERP component P300. Correlations between neuropsychological measures and P300 did, as expected, vary with area of activation, and the strongest correlations were generally found between matrices, block design and digit span, and the midline and left fronto-temporal electrodes. These relationships were in turn mediated by age. Implications of the findings are discussed.

Two- and three-stimuli auditory oddball ERP tasks and neuropsychological measures in aging

The purpose of this study was to decide whether the P300 from an auditory three-stimuli oddball task is more sensitive to aging than the P300 from a two-stimuli task, and to investigate the relationship between neuropsychological tests and the different ways of eliciting the P300. Thirty-one adults (21.8-94.7 years) completed five neuropsychological tests and two ERP tasks. The way P300 was elicited did not influence its relationship to aging or neuropsychological scores, and the correlations between the two paradigms were strong for amplitude, but rather weak for latency. The main conclusion is that the P300 from an auditory three-stimulus paradigm is sensitive to aging and neuropsychologically valid.