Despite the intuition that strongly held beliefs are particularly difficult to change, the data on error correction indicate that general information errors that people commit with a high degree of belief are especially easy to correct. This finding is called the hypercorrection effect. The hypothesis was tested that the reason for hypercorrection stems from enhanced attention and encoding that results from a metacognitive mismatch between the person’s confidence in their responses and the true answer. This experiment, which is the first to use imaging to investigate the hyper-correction effect, provided support for this hypothesis, showing that both metacognitive mismatch conditions—that in which high confidence accompanies a wrong answer and that in which low confidence accompanies a correct answer—revealed anterior cingulate and medial frontal gyrus activations. Only in the high confidence error condition, however, was an error that conflicted with the true answer mentally present. And only the high confidence error condition yielded activations in the right TPJ and the right dorsolateral pFC. These activations suggested that, during the correction process after error commission, people (1) were entertaining both the false belief as well as the true belief (as in theory of mind tasks, which also manifest the right TPJ activation) and (2) may have been suppressing the unwanted, incorrect information that they had, themselves, produced (as in think/no-think tasks, which also manifest dorsolateral pFC activation). These error-specific processes as well as enhanced attention because of metacognitive mismatch appear to be implicated.
Resting-state functional connectivity between neuroanatomical regions has attracted significant attention in recent years. In the process of obtaining the resting-state functional connectivity map of the human brain from blood-oxygen-level-dependent fMRI signals, it is common to average the signals from left and right hemispheres. This averaging can introduce unappreciated complexities and unintended consequences not related to the research question of interest. In this paper, we mathematically demonstrate that measures of functional connectivity obtained by averaging homologous regions from the both hemispheres become undesirably dependent on four inter-hemispheric connectivity measures. We explore this finding in real-world fMRI data from 25 healthy young participants. We show that inter-hemispheric averaging has a mixed effect on the results and may introduce correlation artifacts to the connectivity map. Furthermore, we show mathematically and demonstrate with Monte Carlo simulations of null data that inter-hemispheric averaging will not alter human brain connectivity map at rest only and if only there are no inter-hemispheric correlations.
fMRI; Resting BOLD; Brain; Functional Connectivity
Evidence suggests that individual variability in lifetime exposures influences how cognitive performance changes with advancing age. Brain maintenance and cognitive reserve are theories meant to account for preserved performance despite advancing age. These theories differ in their causal mechanisms. Brain maintenance predicts more advantageous lifetime exposures will reduce age-related neural differences. Cognitive reserve predicts that lifetime exposures will not directly reduce these differences but minimize their impact on cognitive performance. The present work used moderated-mediation modeling to investigate the contributions of these mechanisms at explaining variability in cognitive performance among a group of 39 healthy younger (mean age (standard deviation) 25.9 (2.92) and 45 healthy older adults (65.2 (2.79)). Cognitive scores were computed using composite measures from three separate domains (speed of processing, fluid reasoning, and memory), while their lifetime exposures were estimated using education and verbal IQ measures. T1-weighted MR images were used to measure cortical thickness and subcortical volumes. Results suggest a stronger role for cognitive reserve mechanisms in explaining age-related cognitive variability: even with age-related reduced gray matter, individuals with greater lifetime exposures could perform better given their quantity of brain measures.
Disruption of the default-mode network (DMN) in healthy elders has been reported in many studies.
In a group of 51 participants (25 young, 26 elder) we examined DMN connectivity in subjects' native space. In the native space method, subject-specific regional masks (obtained independently for each subject) are used to extract regional fMRI times series. This approach substitutes the spatial normalization and subsequent smoothing used in prevailing methods, affords more accurate spatial localization, and provides the power to examine connectivity separately in the two hemispheres instead of averaging regions across hemispheres.
The native space method yielded new findings which were not detectable by the prevailing methods. The most reliable and robust disruption in elders' DMN connectivity were found between supramarginal gyrus and superior-frontal cortex in the right hemisphere only. The mean correlation between these two regions in young participants was about 0.5, and dropped significantly to 0.04 in elders (P = 2.1 × 10−5). In addition, the magnitude of functional connectivity between these regions in the right hemisphere correlated with memory (P = 0.05) and general fluid ability (P = 0.01) in elder participants and with speed of processing in young participants (P = 0.008). These relationships were not observed in the left hemisphere.
These findings suggest that analysis of DMN connectivity in subjects' native space can improve localization and power and that it is important to examine connectivity separately in each hemisphere.
Age-related brain change; cognitive performance; fMRI analysis; interhemispheric averaging; resting-state BOLD fMRI; spatial normalization; SPM
Advancing age affects both cognitive performance and functional brain activity and interpretation of these effects has led to a variety of conceptual research models without always explicitly linking the two effects. However, to best understand the multifaceted effects of advancing age, age differences in functional brain activity need to be explicitly tied to the cognitive task performance. This work hypothesized that age-related differences in task performance are partially explained by age-related differences in functional brain activity and formally tested these causal relationships. Functional MRI data was from groups of young and old adults engaged in an executive task-switching experiment. Analyses were voxel-wise testing of moderated-mediation and simple mediation statistical path models to determine whether age group, brain activity and their interaction explained task performance in regions demonstrating an effect of age group. Results identified brain regions whose age-related differences in functional brain activity significantly explained age-related differences in task performance. In all identified locations, significant moderated-mediation relationships resulted from increasing brain activity predicting worse (slower) task performance in older but not younger adults. Findings suggest that advancing age links task performance to the level of brain activity. The overall message of this work is that in order to understand the role of functional brain activity on cognitive performance, analysis methods should respect theoretical relationships. Namely, that age affects brain activity and brain activity is related to task performance.
functional brain activity; cognitive aging; path analysis; moderated-mediation; mediation; task-switching
The effect of aging on functional network activation associated with task-switching was examined in 24 young (age = 25.2 ± 2.73 years) and 23 older adults (age = 65.2 ± 2.65 years) using functional Magnetic Resonance Imaging (fMRI). The study goals were to (1) identify a network shared by both young and older adults, (2) identify additional networks in each age group, and (3) examine the relationship between the networks identified and behavioral performance in task-switching. Ordinal Trend Covariance Analysis was used to identify the networks, which takes advantage of increasing activation with greater task demand to isolate the network of regions recruited by task-switching. Two task-related networks were found: a shared network that was strongly expressed by both young and older adults and a second network identified in the young data that was residualized from the shared network. Both networks consisted of regions associated with task-switching in previous studies including the middle frontal gyrus, the precentral gyrus, the anterior cingulate, and the superior parietal lobule. Not only was pattern expression of the shared network associated with reaction time in both age groups, the difference in the pattern expression across task conditions (task-switch minus single-task) was also correlated with the difference in RT across task conditions. On the contrary, expression of the young residual network showed a large age effect such that older adults do not increase expression of the network with greater task demand as young adults do and correlation between expression and accuracy was significant only for young adults. Thus, while a network related to RT is preserved in older adults, a different network related to accuracy is disrupted.
brain behavior correlation; fMRI; multivariate analysis; executive control; aging; dual-task
Mild cognitive impairment (MCI) and Alzheimer’s disease (AD) are associated with a progressive loss of cognitive abilities. In the present report, we assessed the relationship of memory and executive function with brain structure in a sample of 810 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants, including 188 AD, 396 MCI, and 226 healthy older adults (HC). Composite scores of memory (ADNI-Mem) and executive function (ADNI-Exec) were generated by applying modern psychometric theory to item-level data from ADNI’s neuropsychological battery. We used voxel-based morphometry (VBM) and surface-based association (SurfStat) analyses to evaluate relationships of ADNI-Mem and ADNI-Exec with grey matter (GM) density and cortical thickness across the whole brain in the combined sample and within diagnostic groups. We observed strong associations between ADNI-Mem and medial and lateral temporal lobe atrophy. Lower ADNI-Exec scores were associated with advanced GM and cortical atrophy across broadly distributed regions, most impressively in the bilateral parietal and temporal lobes. We also evaluated ADNI-Exec adjusted for ADNI-Mem, and found associations with GM density and cortical thickness primarily in the bilateral parietal, temporal, and frontal lobes. Within-group analyses suggest these associations are strongest in patients with MCI and AD. The present study provides insight into the spatially unbiased associations between brain atrophy and memory and executive function, and underscores the importance of structural brain changes in early cognitive decline.
Voxel-based morphometry (VBM); Surface-based Analysis; Memory; Executive Function; Alzheimer’s disease; Mild Cognitive Impairment
Differences in brain metabolism as measured by FDG-PET in prodromal and early Alzheimer's disease (AD) have been consistently observed, with a characteristic parietotemporal hypometabolic pattern. However, exploration of brain metabolic correlates of more nuanced measures of cognitive function has been rare, particularly in larger samples. We analyzed the relationship between resting brain metabolism and memory and executive functioning within diagnostic group on a voxel-wise basis in 86 people with AD, 185 people with mild cognitive impairment (MCI), and 86 healthy controls (HC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We found positive associations within AD and MCI but not in HC. For MCI and AD, impaired executive functioning was associated with reduced parietotemporal metabolism, suggesting a pattern consistent with known AD-related hypometabolism. These associations suggest that decreased metabolic activity in the parietal and temporal lobes may underlie the executive function deficits in AD and MCI. For memory, hypometabolism in similar regions of the parietal and temporal lobes were significantly associated with reduced performance in the MCI group. However, for the AD group, memory performance was significantly associated with metabolism in frontal and orbitofrontal areas, suggesting the possibility of compensatory metabolic activity in these areas. Overall, the associations between brain metabolism and cognition in this study suggest the importance of parietal and temporal lobar regions in memory and executive function in the early stages of disease and an increased importance of frontal regions for memory with increasing impairment.
mild cognitive impairment (MCI); Alzheimer's disease (AD); FDG PET; memory; executive function
The genetic basis of resilience, defined as better cognitive functioning than predicted based on neuroimaging or neuropathology, is not well understood. Our objective was to identify genetic variation associated with executive functioning resilience. We computed residuals from regression models of executive functioning, adjusting for age, sex, education, Hachinski score, and MRI findings (lacunes, cortical thickness, volumes of white matter hyperintensities and hippocampus). We estimated heritability and analyzed these residuals in models for each SNP. We further evaluated our most promising SNP result by evaluating cis-associations with brain levels of nearby (±100 kb) genes from a companion data set, and comparing expression levels in cortex and cerebellum from decedents with AD with those from other non-AD diseases. Complete data were available for 750 ADNI participants of European descent. Executive functioning resilience was highly heritable (H2=0.76; S.E. = 0.44). rs3748348 on chromosome 14 in the region of RNASE13 was associated with executive functioning resilience (p-value=4.31×10−7). rs3748348 is in strong linkage disequilibrium (D′ of 1.00 and 0.96) with SNPs that map to TPPP2, a member of the α-synuclein family of proteins. We identified nominally significant associations between rs3748348 and expression levels of three genes (FLJ10357, RNASE2, and NDRG2). The strongest association was for FLJ10357 in cortex, which also had the most significant difference in expression between AD and non-AD brains, with greater expression in cortex of decedents with AD (p-value=7×10−7). Further research is warranted to determine whether this signal can be replicated and whether other loci may be associated with cognitive resilience.
Memory; Executive functioning; Alzheimer’s disease; Psychometrics; Resilience; GWAS
Background. The evaluation of effective disease-modifying therapies for neurodegenerative disorders relies on objective and accurate measures of progression in at-risk individuals. Here we used a computational approach to identify a functional brain network associated with the progression of preclinical Huntington’s disease (HD).
Methods. Twelve premanifest HD mutation carriers were scanned with [18F]-fluorodeoxyglucose PET to measure cerebral metabolic activity at baseline and again at 1.5, 4, and 7 years. At each time point, the subjects were also scanned with [11C]-raclopride PET and structural MRI to measure concurrent declines in caudate/putamen D2 neuroreceptor binding and tissue volume. The rate of metabolic network progression in this cohort was compared with the corresponding estimate obtained in a separate group of 21 premanifest HD carriers who were scanned twice over a 2-year period.
Results. In the original premanifest cohort, network analysis disclosed a significant spatial covariance pattern characterized by progressive changes in striato-thalamic and cortical metabolic activity. In these subjects, network activity increased linearly over 7 years and was not influenced by intercurrent phenoconversion. The rate of network progression was nearly identical when measured in the validation sample. Network activity progressed at approximately twice the rate of single region measurements from the same subjects.
Conclusion. Metabolic network measurements provide a sensitive means of quantitatively evaluating disease progression in premanifest individuals. This approach may be incorporated into clinical trials to assess disease-modifying agents.
Trial registration. Registration is not required for observational studies.
Funding. NIH (National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering) and CHDI Foundation Inc.
The default-mode network (DMN) has become a well accepted concept in cognitive and clinical neuroscience over the last decade, and perusal of the recent literature attests to a stimulating research field of cognitive and diagnostic applications (for example, (Andrews-Hanna, Reidler, Huang, & Buckner, 2010; Koch et al., 2010; Sheline, Barch et al., 2009; Sheline, Raichle et al., 2009; Uddin et al., 2008; Uddin, Kelly, Biswal, Castellanos, & Milham, 2009; Weng et al., 2009; Yan et al., 2009)). However, a formal definition of what exactly constitutes a functional brain network is difficult to come by. In recent contributions, some researchers argue that the DMN is best understood as multiple interacting subsystems (Buckner, Andrews-Hanna, & Schacter, 2008) and have explored modular components of the DMN that have different functional specialization and could to some extent be identified separately (Fox et al., 2005; Harrison et al., 2008; Uddin et al., 2009). Such conception of modularity seems to imply an opposite construct of a ‘unified whole’, but it is difficult to locate proponents of the idea of a DMN who are supplying constraints that can be brought to bear on data in rigorous tests. Our aim in this paper is to present a principled way of deriving a single covariance pattern as the neural substrate of the DMN, test to what extent its behavior tracks the coupling strength between critical seed regions, and investigate to what extent our stricter concept of a network is consistent with the already established findings about the DMN in the literature. We show that our approach leads to a functional covariance pattern whose pattern scores are a good proxy for the integrity of the connections between a medioprefrontal, posterior cingulate and parietal seed regions. Our derived DMN network thus has potential for diagnostic applications that are simpler to perform than computation of pairwise correlational strengths or seed maps.
Default-mode network; resting fMRI; spatial covariance analysis; Principal Components Analysis
We performed a delayed-item-recognition task to investigate the neural substrates of non-verbal visual working memory with event-related fMRI (‘Shape task’). 25 young subjects (mean age: 24.0 years; STD=3.8 years) were instructed to study a list of either 1,2 or 3 unnamable nonsense line drawings for 3 seconds (‘stimulus phase’ or STIM). Subsequently, the screen went blank for 7 seconds (‘retention phase’ or RET), and then displayed a probe stimulus for 3 seconds in which subject indicated with a differential button press whether the probe was contained in the studied shape-array or not (‘probe phase’ or PROBE). Ordinal Trend Canonical Variates Analysis (Habeck et al., 2005a) was performed to identify spatial covariance patterns that showed a monotonic increase in expression with memory load during all task phases. Reliable load-related patterns were identified in the stimulus and retention phase (p<0.01), while no significant pattern could be discerned during the probe phase. Spatial covariance patterns that were obtained from an earlier version of this task (Habeck et al., 2005b) using 1, 3, or 6 letters (‘Letter task’) were also prospectively applied to their corresponding task phases in the current non-verbal task version. Interestingly, subject expression of covariance patterns from both verbal and non-verbal retention phases correlated positively in the non-verbal task for all memory loads (p<0.0001). Both patterns also involved similar frontoparietal brain regions that were increasing in activity with memory load, and mediofrontal and temporal regions that were decreasing. Mean subject expression of both patterns across memory load during retention also correlated positively with recognition accuracy (dL) in the Shape task (p<0.005). These findings point to similarities in the neural substrates of verbal and non-verbal rehearsal processes. Encoding processes, on the other hand, are critically dependent on the to-be-remembered material, and seem to necessitate material-specific neural substrates.
multivariate analysis; visual working memory; encoding; maintenance
Effects of dual-responding on tracking performance after 49-hr of sleep deprivation (SD) were evaluated behaviorally and with functional magnetic resonance imaging (fMRI). Continuous visuomotor tracking was performed simultaneously with an intermittent color-matching visual detection task in which a pair of color-matched stimuli constituted a target and non-matches were non-targets. Tracking error means were binned time-locked to stimulus onset of the detection task in order to observe changes associated with dual-responding by comparing the error during targets and non-targets. Similar comparison was made with fMRI data. Our result showed that despite a significant increase in the overall tracking error post SD, from 20 pixels pre SD to 45 pixels post SD, error decreased to a minimum of about 25 pixels 0 to 6 s after dual-response. Despite an overall reduced activation post SD, greater activation difference between targets and non-targets was found post SD in task-related regions, such as the left cerebellum, the left somatosensory cortex, the left extrastriate cortex, bilateral precuneus, the left middle frontal gyrus, and the left motor cortex. Our results suggest that dual-response helps to alleviate performance impairment usually associated with SD. The duration of the alleviation effect was on the order of seconds after dual-responding.
Visuomotor tracking; Visual detection; Continuous wakefulness; Dual responses; Dual tasks; Prefrontal cortex
The extent of task-related fMRI activation can vary as a function of task difficulty. Also the efficiency or capacity of the brain networks underlying task performance can change with aging. We asked whether the expression of a network underlying task performance would differ as a function of task demand in old and young individuals. 26 younger and 23 older healthy adults performed a delayed item recognition task that used the response signal method to parametrically manipulate the extrinsic difficulty of the task by imposing five different deadlines for recognition response. Both age groups showed a speed accuracy trade-off, but the younger group achieved greater discriminability at the longer deadlines. We identified a spatial pattern of fMRI activation during the probe phase whose expression increased as the response deadline shortened and the task became more difficult. This pattern was expressed to a greater degree by the old group at the long deadlines, when the task was easiest. By contrast, this pattern was expressed to greater degree by the younger group at the short deadlines, when the task was hardest. This suggests reduced efficiency and capacity of this network in older subjects. These findings suggest that neuroimaging studies comparing task-related activation across groups with different cognitive abilities must be interpreted in light of the relative difficulty of the task for each group.
fMRI; aging; working memory; speed-accuracy tradeoff
Subjects performed a continuous tracking concurrently with an intermittent visual detection task to investigate the existence of competition for a capacity-limited stage (a bottleneck stage). Both perceptual and response-related processes between the two tasks were examined behaviorally and the changes in brain activity during dual-tasking relative to single-task were also assessed. Tracking error and joystick speed were analyzed for changes that were time-locked to visual detection stimuli. The associated brain activations were examined with functional magnetic resonance imaging (fMRI). These were analyzed using mixed block and event-related models to tease apart sustained neural activity and activations associated with individual events. Increased tracking error and decreased joystick speed were observed relative to the target stimuli in the dual-task condition only, which supports the existence of a bottleneck stage in response-related processes. Neuroimaging data show decreased activation to target relative to non-target stimuli in the dual-task condition in the left primary motor and somatosensory cortices controlling right-hand tracking, consistent with the tracking interference observed in behavioral data. Furthermore, the ventral attention system, rather than the dorsal attention system, was found to mediate task coordination between tracking and visual detection.
fMRI; Compensatory tracking; Visual detection; Bottom-up attention system; Psychological refractory period; Dual-task interference
This functional neuroimaging (fMRI) study examined the neural networks (spatial patterns of covarying neural activity) associated with the speed-accuracy tradeoff (SAT) in younger adults. The response signal method was used to systematically increase probe duration (125, 250, 500, 1,000 2,000 ms) in a nonverbal delayed-item recognition task. A covariance-based multivariate approach identified three networks that varied with probe duration – indicating that the SAT is driven by three distributed neural networks.
Aging has a multi-faceted impact on brain structure, brain function and cognitive task performance, but the interaction of these different age-related changes is largely unexplored. We hypothesize that age-related structural changes alter the functional connectivity within the brain, resulting in altered task performance during cognitive challenges. In this neuroimaging study, we used independent components analysis to identify spatial patterns of coordinated functional activity involved in the performance of a verbal delayed item recognition task from 75 healthy young and 37 healthy old adults. Strength of functional connectivity between spatial components was assessed for age group differences and related to speeded task performance. We then assessed whether age-related differences in global brain volume were associated with age-related differences in functional network connectivity. Both age groups used a series of spatial components during the verbal working memory task and the strength and distribution of functional network connectivity between these components differed across the age groups. Poorer task performance, i.e. slower speed with increasing memory load, in the old adults was associated with decreases in functional network connectivity between components comprised of the supplementary motor area and the middle cingulate and between the precuneus and the middle/superior frontal cortex. Advancing age also led to decreased brain volume; however, there was no evidence to support the hypothesis that age-related alterations in functional network connectivity were the result of global brain volume changes. These results suggest that age-related differences in the coordination of neural activity between brain regions partially underlie differences in cognitive performance.
Resting-state functional connectivity has become a topic of enormous interest in the Neuroscience community in the last decade. Because resting-state data (1) harbor important information that often is diagnostically relevant and (2) are easy to acquire, there has been a rapid increase in the development of a variety of network analytic techniques for diagnostic applications, stimulating methodological research in general. While we are among those who welcome the increased interest in the resting state and multivariate analytic tools, we would like to draw attention to some entrenched practices that undermine the scientific quality of diagnostic functional-connectivity research, but whose correction is relatively easy to accomplish. With the current commentary we also hope to benefit the field at large and contribute to a healthy debate about research goals and best practices.
brain networks; correlation matrix; default mode network; independent component analysis (ICA); principal component analysis (PCA)
Spatiotemporal and recognition memory are affected by aging in humans and macaque monkeys. To investigate whether these deficits are coupled with atrophy of memory-related brain regions, T1-weighted magnetic resonance images were acquired and volumes of the cerebrum, ventricles, prefrontal cortex (PFC), calcarine cortex, hippocampus, and striatum were quantified in young and aged rhesus monkeys. Subjects were tested on a spatiotemporal memory procedure (delayed response [DR]) that requires the integrity of the PFC and a medial temporal lobe-dependent recognition memory task (delayed nonmatching to sample [DNMS]). Region of interest analyses revealed that age inversely correlated with striatal, dorsolateral prefrontal cortex (dlPFC), and anterior cingulate cortex volumes. Hippocampal volume predicted acquisition of the DR task. Striatal volume correlated with DNMS acquisition, whereas total prefrontal gray matter, prefrontal white matter, and dlPFC volumes each predicted DNMS accuracy. A regional covariance analysis revealed that age-related volumetric changes could be captured in a distributed network that was coupled with declining performance across delays on the DNMS task. This volumetric analysis adds to growing evidence that cognitive aging in primates arises from region-specific morphometric alterations distributed across multiple memory-related brain systems, including subdivisions of the PFC.
age-related memory impairment; medial temporal lobe; MRI; prefrontal cortex; rhesus monkey
By comparing hemodynamic signals acquired immediately before and during activation, functional magnetic resonance imaging (fMRI) is well suited for mapping acute changes in brain function. However, it remains unclear whether fMRI can map functional changes over longer periods. Here, we address this issue by empirically testing the feasibility of arterial spin labeling (ASL) fMRI to detect changes in cerebral blood flow (CBF) with baseline and task separated by 1 month. To increase the sensitivity of the method, we applied an algorithm that yielded flow density (CBFd) images that were independent of tissue content. To increase the accuracy, we developed a technique that generated arterial transit time at each voxel, independently. Results showed that activation changes in CBFd during the same session were statistically the same as across 30 days. The activation CBFd on day-30 was 34% (motor) and 25% (visual) higher than the respective baselines of 83 and 107 mL/100 g/min obtained on day-1. Furthermore, the signal-to-noise ratio of the CBFd measurement was 2.1 and 2.9 times higher than that of the conventional CBF for within-subject and across-subjects comparisons, respectively (n=9 healthy young subjects). Taken together, these results indicate that CBFd measure could be better suited than net CBF to map long-term changes in brain function.
ASL; arterial transit time; baseline drift; CBF; fMRI; 1/f noise; PVE
Functional magnetic resonance imaging (fMRI) studies have shown that repetition priming of visual objects is typically accompanied by a reduction in activity for repeated compared to new stimuli (repetition suppression). However, the spatial distribution and direction (suppression vs. enhancement) of neural repetition effects can depend on the pre-experimental familiarity of stimuli. The first goal of this study was to further probe the link between repetition priming and repetition suppression/enhancement for visual objects and how this link is affected by stimulus familiarity. A second goal was to examine whether priming of familiar and unfamiliar objects following a single stimulus repetition is supported by the same processes as priming following multiple repetitions within the same task. In this endeavor, we examined both between and within subjects correlations between priming and fMRI repetition effects for familiar and globally unfamiliar visual objects during the first and third repetition of the stimuli. We included reaction time of individual trials as a linear regressor to identify brain regions whose repetition effects varied with response facilitation on a trial-by-trial basis. The results showed that repetition suppression in bilateral fusiform gyrus, was selectively correlated with priming of familiar objects that had been repeated once, likely reflecting facilitated perceptual processing or the sharpening of perceptual representations. Priming during the third repetition was correlated with repetition suppression in prefrontal and parietal areas for both familiar and unfamiliar stimuli, possibly reflecting a shift from top-down controlled to more automatic processing that occurs for both item types.
priming; neural repetition suppression; neural repetition enhancement; fMRI; stimulus familiarity
Neurophysiological studies have provided evidence of primary motor cortex hyperexcitability in primary dystonia, but several functional imaging studies suggest otherwise. To address this issue, we measured sensorimotor activation at both the regional and network levels in carriers of the DYT1 dystonia mutation and in control subjects. We used 15Oxygen-labelled water and positron emission tomography to scan nine manifesting DYT1 carriers, 10 non-manifesting DYT1 carriers and 12 age-matched controls while they performed a kinematically controlled motor task; they were also scanned in a non-motor audio-visual control condition. Within- and between-group contrasts were analysed with statistical parametric mapping. For network analysis, we first identified a normal motor-related activation pattern in a set of 39 motor and audio-visual scans acquired in an independent cohort of 18 healthy volunteer subjects. The expression of this pattern was prospectively quantified in the motor and control scans acquired in each of the gene carriers and controls. Network values for the three groups were compared with ANOVA and post hoc contrasts. Voxel-wise comparison of DYT1 carriers and controls revealed abnormally increased motor activation responses in the former group (P < 0.05, corrected; statistical parametric mapping), localized to the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and the inferior parietal cortex. Network analysis of the normative derivation cohort revealed a significant normal motor-related activation pattern topography (P < 0.0001) characterized by covarying neural activity in the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and cerebellum. In the study cohort, normal motor-related activation pattern expression measured during movement was abnormally elevated in the manifesting gene carriers (P < 0.001) but not in their non-manifesting counterparts. In contrast, in the non-motor control condition, abnormal increases in network activity were present in both groups of gene carriers (P < 0.001). In this condition, normal motor-related activation pattern expression in non-manifesting carriers was greater than in controls, but lower than in affected carriers. In the latter group, measures of normal motor-related activation pattern expression in the audio-visual condition correlated with independent dystonia clinical ratings (r = 0.70, P = 0.04). These findings confirm that overexcitability of the sensorimotor system is a robust feature of dystonia. The presence of elevated normal motor-related activation pattern expression in the non-motor condition suggests that abnormal integration of audio-visual input with sensorimotor network activity is an important trait feature of this disorder. Lastly, quantification of normal motor-related activation pattern expression in individual cases may have utility as an objective descriptor of therapeutic response in trials of new treatments for dystonia and related disorders.
DYT1 dystonia; imaging marker; positron emission tomography; motor activation
Regional cerebral blood flow (CBF), a good indirect index of cerebral pathologic changes in Alzheimer disease (AD), is more severely reduced in patients with higher educational attainment and IQ when controlling for clinical severity. This has been interpreted as suggesting that cognitive reserve allows these patients to cope better with the pathologic changes in AD.
To evaluate whether premorbid engagement in various activities may also provide cognitive reserve.
We evaluated intellectual, social, and physical activities in 9 patients with early AD and 16 healthy elderly controls who underwent brain H215O positron emission tomography. In voxelwise multiple regression analyses that controlled for age and clinical severity, we investigated the association between education, estimated premorbid IQ, and activities, and CBF.
In accordance with previous findings, we replicated an inverse association between education and CBF and IQ and CBF in patients with AD. In addition, there was a negative correlation between previous reported activity score and CBF in patients with AD. When both education and IQ were added as covariates in the same model, a higher activity score was still associated with more prominent CBF deficits. No significant associations were detected in the controls.
At any given level of clinical disease severity, there is a greater degree of brain pathologic involvement in patients with AD who have more engagement in activities, even when education and IQ are taken into account. This may suggest that interindividual differences in lifestyle may affect cognitive reserve by partially mediating the relationship between brain damage and the clinical manifestation of AD.
Although multivariate analytic techniques might identify diagnostic patterns that are not captured by univariate methods, they have rarely been used to study the neural correlates of Alzheimer's disease (AD) or cognitive impairment. Nonquantitative
H215O PET scans were acquired during rest in 17 probable AD subjects selected for mild severity [mean-modified Mini Mental Status Examination (mMMS) 46/57; SD 5.1], 16 control subjects (mMMS 54; SD 2.5) and 23 subjects with minimal to mild cognitive impairment but no dementia (mMMS 53; SD 2.8). Expert clinical reading had low success in discriminating AD and controls. There were no significant mean flow differences among groups in traditional univariate SPM Voxel-wise analyses or region of interest (ROI) analyses. A covariance pattern was identified whose mean expression was significantly higher in the AD as compared to controls (P = 0.03; sensitivity 76–94%; specificity 63–81%). Sites of increased concomitant flow included insula, cuneus, pulvinar, lingual, fusiform, superior occipital and parahippocampal gyri, whereas decreased concomitant flow was found in cingulate, inferior parietal lobule, middle and inferior frontal, supramarginal and precentral gyri. The covariance analysis-derived pattern was then prospectively applied to the cognitively impaired subjects: as compared to subjects with Clinical Dementia Rating (CDR) = 0, subjects with CDR = 0.5 had significantly higher mean covariance pattern expression (P = 0.009). Expression of this pattern correlated inversely with Selective Reminding Test total recall (r = −0.401, P = 0.002), delayed recall (r = −0.351, P = 0.008) and mMMS scores (r = −0.401, P = 0.002) in all three groups combined. We conclude that patients with AD may differentially express resting cerebral blood flow covariance patterns even at very early disease stages. Significant alterations in expression of resting flow covariance patterns occur even for subjects with cognitive impairment. Expression of covariance patterns correlates with cognitive and functional performance measures, holding promise for meaningful associations with underlying biopathological processes.
Cognitive; Alzheimer's disease; Covariance; MCI; PET; CBF; diagnosis