Linda K. McEvoy

Monitoring Working Memory Load during Computer-Based Tasks with EEG Pattern Recognition Methods:

We assessed working memory load during computer use with neural network pattern recognition applied to EEG spectral features. Eight participants performed high-, moderate-, and low-load working memory tasks. Frontal theta EEG activity increased and alpha activity decreased with increasing load. These changes probably reflect task difficulty-related increases in mental effort and the proportion of cortical resources allocated to task performance. In network analyses, test data segments from high and low load levels were discriminated with better than 95% accuracy. More than 80% of test data segments associated with a moderate load could be discriminated from high- or low-load data segments. Statistically significant classification was also achieved when applying networks trained with data from one day to data from another day, when applying networks trained with data from one task to data from another task, and when applying networks trained with data from a group of participants to data from new participants. These results support the feasibility of using EEG-based methods for monitoring cognitive load during human-computer interaction.

One year brain atrophy evident in healthy aging

An accurate description of changes in the brain in healthy aging is needed to understand the basis of age-related changes in cognitive function. Cross-sectional magnetic resonance imaging (MRI) studies suggest thinning of the cerebral cortex, volumetric reductions of most subcortical structures, and ventricular expansion. However, there is a paucity of detailed longitudinal studies to support the cross-sectional findings. In the present study, 142 healthy elderly participants (60–91 years of age) were followed with repeated MRI, and were compared with 122 patients with mild to moderate Alzheimers disease (AD). Volume changes were measured across the entire cortex and in 48 regions of interest. Cortical reductions in the healthy elderly were extensive after only 1 year, especially evident in temporal and prefrontal cortices, where annual decline was ∼0.5%. All subcortical and ventricular regions except caudate nucleus and the fourth ventricle changed significantly over 1 year. Some of the atrophy occurred in areas vulnerable to AD, while other changes were observed in areas less characteristic of the disease in early stages. This suggests that the changes are not primarily driven by degenerative processes associated with AD, although it is likely that preclinical changes associated with AD are superposed on changes due to normal aging in some subjects, especially in the temporal lobes. Finally, atrophy was found to accelerate with increasing age, and this was especially prominent in areas vulnerable to AD. Thus, it is possible that the accelerating atrophy with increasing age is due to preclinical AD.

Intracranial EEG Reveals a Time- and Frequency-Specific Role for the Right Inferior Frontal Gyrus and Primary Motor Cortex in Stopping Initiated Responses

Inappropriate response tendencies may be stopped via a specific fronto/basal ganglia/primary motor cortical network. We sought to characterize the functional role of two regions in this putative stopping network, the right inferior frontal gyrus (IFG) and the primary motor cortex (M1), using electocorticography from subdural electrodes in four patients while they performed a stop-signal task. On each trial, a motor response was initiated, and on a minority of trials a stop signal instructed the patient to try to stop the response. For each patient, there was a greater right IFG response in the beta frequency band (∼16 Hz) for successful versus unsuccessful stop trials. This finding adds to evidence for a functional network for stopping because changes in beta frequency activity have also been observed in the basal ganglia in association with behavioral stopping. In addition, the right IFG response occurred 100–250 ms after the stop signal, a time range consistent with a putative inhibitory control process rather than with stop-signal processing or feedback regarding success. A downstream target of inhibitory control is M1. In each patient, there was alpha/beta band desynchronization in M1 for stop trials. However, the degree of desynchronization in M1 was less for successfully than unsuccessfully stopped trials. This reduced desynchronization on successful stop trials could relate to increased GABA inhibition in M1. Together with other findings, the results suggest that behavioral stopping is implemented via synchronized activity in the beta frequency band in a right IFG/basal ganglia network, with downstream effects on M1.

Alzheimer Disease: Quantitative Structural Neuroimaging for Detection and Prediction of Clinical and Structural Changes in Mild Cognitive Impairment

PURPOSE To use structural magnetic resonance (MR) images to identify a pattern of regional atrophy characteristic of mild Alzheimer disease (AD) and to investigate whether presence of this pattern prospectively can aid prediction of 1-year clinical decline and increased structural loss in mild cognitive impairment (MCI). MATERIALS AND METHODS The study was conducted with institutional review board approval and compliance with HIPAA regulations. Written informed consent was obtained from each participant. High-throughput volumetric segmentation and cortical surface reconstruction methods were applied to MR images from 84 subjects with mild AD, 175 with MCI, and 139 healthy control (HC) subjects. Stepwise linear discriminant analysis was used to identify regions that best can aid discrimination of HC subjects from subjects with AD. A classifier trained on data from HC subjects and those with AD was applied to data from subjects with MCI to determine whether presence of phenotypic AD atrophy at baseline was predictive of clinical decline and structural loss. RESULTS Atrophy in mesial and lateral temporal, isthmus cingulate, and orbitofrontal areas aided discrimination of HC subjects from subjects with AD, with fully cross-validated sensitivity of 83% and specificity of 93%. Subjects with MCI who had phenotypic AD atrophy showed significantly greater 1-year clinical decline and structural loss than those who did not and were more likely to have progression to probable AD (annual progression rate of 29% for subjects with MCI who had AD atrophy vs 8% for those who did not). CONCLUSION Semiautomated, individually specific quantitative MR imaging methods can be used to identify a pattern of regional atrophy in MCI that is predictive of clinical decline. Such information may aid in prediction of patient prognosis and increase the efficiency of clinical trials.

Neurophysiological indices of strategy development and skill acquisition

In order to examine neurophysiological changes associated with the development of cognitive and visuomotor strategies and skills, spectral features of the EEG were measured as participants learned to perform new tasks. In one experiment eight individuals practiced working memory tasks that required development of either spatial or verbal rehearsal and updating strategies. In a second experiment six individuals practiced a video game with a difficult visuomotor tracking component. The alpha rhythm, which is attenuated by functional cortical activation, was affected by task practice. In both experiments, a lower-frequency, centrally distributed alpha component increased between practice sessions in a task-independent fashion, reflecting an overall decrease in the extent of cortical activation after practice. A second, higher-frequency, posterior component of the alpha rhythm displayed task-specific practice effects. Practice in the verbal working memory task resulted in an increase of this signal over right posterior regions, an effect not seen after practice with the spatial working memory task or with the video game. This between-task difference presumably reflects a continued involvement of the posterior region of the right hemisphere in tasks that invoke visuospatial processes. This finding thus provides neurophysiological evidence for the formation of a task-specific neurocognitive strategy. In the second experiment a third component of the alpha rhythm, localized over somatomotor cortex, was enhanced in conjunction with acquisition of tracking skill. These alpha band results suggest that cortical regions not necessary for task performance become less active as skills develop. In both experiments the frontal midline (Fm) theta rhythm also displayed increases over the course of test sessions. This signal is associated with states of focused concentration, and its enhancement might reflect the conscious control over attention associated with maintenance of a task-appropriate mental set. Overall, the results suggest that the EEG can be used to monitor practice-related changes in the patterns of cortical activity that are associated with task processing. Additionally, these results highlight the importance of ensuring that subjects have developed stable strategies for performance before drawing inferences about the functional architecture underlying specific cognitive processes.

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 Aβ42, t-tau, p-tau, and ratios of t-tau/Aβ42 and p-tau/Aβ42. 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/Aβ42 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.

Neurophysiological signals of working memory in normal aging.

To examine how neurophysiological signals of working memory (WM) change with normal aging, we recorded EEGs from healthy groups (n=10 each) of young (mean age=21 years), middle-aged (mean=47 years), and older (mean=69 years) adults. EEGs were recorded while subjects performed easy and difficult versions of a spatial WM task. Groups were matched for IQ (mean=123; WAIS-R) and practiced in task performance. Responses slowed with age, particularly in the more difficult task. Advanced age was associated with decreased amplitude and increased latency of the parietal P300 component of the event-related potential and an increase in the amplitude of a frontal P200 component. Spectral features of the EEG also differed between groups. Younger subjects displayed an increase in the frontal midline θ rhythm with increased task difficulty, a result not observed in older subjects. Age-related changes were also observed in the task-related alpha signal, the amplitude of which decreases as more neurons become involved in task-related processing. Young adults showed a decrease in alpha power with increased task difficulty over parietal regions but not over frontal regions. Middle-aged and older adults showed decreased alpha power with increased task difficulty over both frontal and parietal regions. This suggests that normal aging may be associated with changes in the fronto-parietal networks involved with spatial WM processes. Younger subjects appear to use a strategy that relies on parietal areas involved with spatial processing, whereas older subjects appear to use a strategy that relies more on frontal areas.

High resolution evoked potential imaging of the cortical dynamics of human working memory

High resolution evoked potentials (EPs), sampled from 115 channels and spatially sharpened with the finite element deblurring method, were recorded from 8 subjects during working memory (WM) and control tasks. The tasks required matching each stimulus with a preceding stimulus on either verbal or spatial attributes. All stimuli elicited a central P200 potential that was larger in the spatial tasks than in the verbal tasks, and larger in the WM tasks than in the control tasks. Frequent, non-matching stimuli elicited a frontal, positive peak at 305 msec that was larger in the spatial WM task relative to the other tasks. Irrespective of whether subjects attended to verbal or spatial stimulus attributes, non-matching stimuli in the WM tasks also elicited an enhanced P450 potential over the left frontal cortex, followed by a sustained potential over the superior parietal cortex. A posterior P390 potential elicited by infrequent, matching stimuli was smaller in amplitude for both spatial and verbal WM tasks compared to control tasks, as was a central prestimulus CNV. These results indicate that WM is a function of a distributed system with both task-specific and task-independent components. Lesion studies and course temporal resolution functional imaging methods, such as PET and fMRI, tend to paint a fairly static picture of the cortical regions which participate in the performance of WM tasks. In contrast, the fine-grain time resolution provided by imaging brain function with EP methods provides a dynamic picture of subsecond changes in the spatial distribution of WM effects over the course of individual trials, as well as evidence for differences in the activity elicited by matching and non-matching stimuli within sequences of trials. This information about the temporal dynamics of WM provides a critical complement to the fine-grain spatial resolution provided by other imaging modalities.

What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

What can be expected in normal aging, and where does normal aging stop and pathological neurodegeneration begin? With the slow progression of age-related dementias such as Alzheimers disease (AD), it is difficult to distinguish age-related changes from effects of undetected disease. We review recent research on changes of the cerebral cortex and the hippocampus in aging and the borders between normal aging and AD. We argue that prominent cortical reductions are evident in fronto-temporal regions in elderly even with low probability of AD, including regions overlapping the default mode network. Importantly, these regions show high levels of amyloid deposition in AD, and are both structurally and functionally vulnerable early in the disease. This normalcy-pathology homology is critical to understand, since aging itself is the major risk factor for sporadic AD. Thus, rather than necessarily reflecting early signs of disease, these changes may be part of normal aging, and may inform on why the aging brain is so much more susceptible to AD than is the younger brain. We suggest that regions characterized by a high degree of life-long plasticity are vulnerable to detrimental effects of normal aging, and that this age-vulnerability renders them more susceptible to additional, pathological AD-related changes. We conclude that it will be difficult to understand AD without understanding why it preferably affects older brains, and that we need a model that accounts for age-related changes in AD-vulnerable regions independently of AD-pathology.

Regional rates of neocortical atrophy from normal aging to early Alzheimer disease

Objective: To evaluate the spatial pattern and regional rates of neocortical atrophy from normal aging to early Alzheimer disease (AD). Methods: Longitudinal MRI data were analyzed using high-throughput image analysis procedures for 472 individuals diagnosed as normal, mild cognitive impairment (MCI), or AD. Participants were divided into 4 groups based on Clinical Dementia Rating Sum of Boxes score (CDR-SB). Annual atrophy rates were derived by calculating percent cortical volume loss between baseline and 12-month scans. Repeated-measures analyses of covariance were used to evaluate group differences in atrophy rates across regions as a function of impairment. Planned comparisons were used to evaluate the change in atrophy rates across levels of disease severity. Results: In patients with MCI–CDR-SB 0.5–1, annual atrophy rates were greatest in medial temporal, middle and inferior lateral temporal, inferior parietal, and posterior cingulate. With increased impairment (MCI–CDR-SB 1.5–2.5), atrophy spread to parietal, frontal, and lateral occipital cortex, followed by anterior cingulate cortex. Analysis of regional trajectories revealed increasing rates of atrophy across all neocortical regions with clinical impairment. However, increases in atrophy rates were greater in early disease within medial temporal cortex, whereas increases in atrophy rates were greater at later stages in prefrontal, parietal, posterior temporal, parietal, and cingulate cortex. Conclusions: Atrophy is not uniform across regions, nor does it follow a linear trajectory. Knowledge of the spatial pattern and rate of decline across the spectrum from normal aging to Alzheimer disease can provide valuable information for detecting early disease and monitoring treatment effects at different stages of disease progression.