Effects of ionizing radiation on charge-coupled imagers

The effects of ionizing radiation on three different charge coupled imagers have been investigated. Device performance was evaluated as a function of total gamma ray dose. The principal failure mechanisms have been identified for each particular device structure. The clock and bias voltages required for high total dose operation of the devices are presented

Increased Action Potential Firing Rates of Layer 2/3 Pyramidal Cells in the Prefrontal Cortex are Significantly Related to Cognitive Performance in Aged Monkeys

The neurobiological substrates of significant age-related deficits in higher cognitive abilities mediated by the prefrontal cortex (PFC) are unknown. To address this issue, whole-cell current-clamp recordings were used to compare the intrinsic membrane and action potential (AP) firing properties of layer 2/3 pyramidal cells in PFC slices from young and aged behaviorally characterized rhesus monkeys. Most aged subjects demonstrated impaired performance in Delayed Non-Match to Sample (DNMS) task acquisition, DNMS 2 min delay and the Delayed Recognition Span task. Resting membrane potential and membrane time constant did not differ in aged relative to young cells, but input resistance was significantly greater in aged cells. Single APs did not differ in terms of threshold, duration or rise time, but their amplitude and fall time were significantly decreased in aged cells. Repetitive AP firing rates were significantly increased in aged cells. Within the aged group, there was a U-shaped quadratic relationship between firing rate and performance on each behavioral task. Subjects who displayed either low or very high firing rates exhibited poor performance, while those who displayed intermediate firing rates exhibited relatively good performance. These data indicate that an increase in AP firing rate may be responsible, in part, for age-related PFC dysfunction

Association of Carotid Intima Media Thickening with Future Brain Region Specific Amyloid-β Burden.

BACKGROUND: Carotid atherosclerosis is associated with cognitive impairment and dementia, though there is limited evidence of a direct link between carotid disease and amyloid-β (Aβ) burden. OBJECTIVE: We studied the association of baseline and progressive carotid intima media thickness (CIMT) with Aβ on 11C-Pittsburgh Compound B (PiB) to determine if those with carotid atherosclerosis would have higher Aβ burden. METHODS: We studied 47 participants from the Framingham Offspring cohort with carotid ultrasounds measuring CIMT at their 6th clinic examination (aged 49.5±5.7 years) and an average of 9.6 years later, and PiB imaging measuring Aβ on average 22.1 years post baseline. We used multivariate linear regression analyses to relate baseline, follow-up, mean, and progression of internal carotid artery (ICA) and common carotid artery (CCA) CIMT to Aβ in brain regions associated with Alzheimers disease (AD) and related dementias (ADRD), adjusting for age, sex, and other vascular risk factors. RESULTS: Participants with higher mean ICA IMT had more Aβ in the precuneus (beta±standard error [β±SE]: 0.466±0.171 mm, p = 0.01) and the frontal, lateral, and retrosplenial regions (β±SE: 0.392±0.164 mm, p = 0.022) after adjusting for age, sex, vascular risk factors, and medication use. We did not find an association between any CCA IMT measures and Aβ or progression of ICA or CCA IMT and Aβ. CONCLUSION: Carotid atherosclerosis, as measured by ICA IMT, is associated with increased Aβ burden later in life. These findings support a link between vascular disease and AD/ADRD pathophysiology

Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer’s Disease

Whole-brain networks derived from diffusion tensor imaging (DTI) data require the identification of seed and target regions of interest (ROIs) to assess connectivity patterns. This study investigated how initiating tracts from gray matter (GM) or white matter (WM) seed ROIs impacts (1) structural networks constructed from DTI data from healthy elderly (control) and individuals with Alzheimer’s disease (AD) and (2) between-group comparisons using these networks. DTI datasets were obtained from the Alzheimer’s disease Neuroimaging Initiative database. Deterministic tractography was used to build two whole-brain networks for each subject; one in which tracts were initiated from WM ROIs and another in which they were initiated from GM ROIs. With respect to the first goal, in both groups, WM-seeded networks had approximately 400 more connections and stronger connections (as measured by number of streamlines per connection) than GM-seeded networks, but shared 94% of the connections found in the GM-seed networks. With respect to the second goal, between-group comparisons revealed a stronger subnetwork (as measured by number of streamlines per connection) in controls compared to AD using both WM-seeded and GM-seeded networks. The comparison using WM-seeded networks produced a larger (i.e., a greater number of connections) and more significant subnetwork in controls versus AD. Global, local, and nodal efficiency were greater in controls compared to AD, and between-group comparisons of these measures using WM-seeded networks had larger effect sizes than those using GM-seeded networks. These findings affirm that seed location significantly affects the ability to detect between-group differences in structural networks

A non-human primate test of abstraction and set shifting: an automated adaptation of the Wisconsin Card Sorting Test

Abstract Functional assessment of the prefrontal cortices in the non-human primate began with the seminal work of Jacobsen in the 1930s. However, despite nearly 70 years of research, the precise nature of the cognitive function of this region remains unclear. One factor that has limited progress in this endeavor has been the lack of behavioral tasks that parallel most closely those used with humans. In the present study, we describe a test for the non-human primate that was adapted from the Wisconsin Card Sorting Task (WCST), perhaps the most widely used test of prefrontal cognitive function in humans. Our adaptation of this task, the Conceptual Set-Shifting Task (CSST), uses learning criteria and stimuli nearly identical to those of the WCST. The CSST requires the animal to initially form a concept by establishing a pattern of responding to a given stimulus class, maintain responding to that stimulus class, and then shift to a different stimulus class when the reward contingency changes. The data presented here establishes baseline performance on the CSST for young adult rhesus monkeys and demonstrates that components of prefrontal cognitive function can be effectively assessed in the non-human primate in a manner that parallels the clinical assessment of humans

A longitudinal examination of plasma neurofilament light and total tau for the clinical detection and monitoring of Alzheimer's disease

We examined baseline and longitudinal associations between plasma neurofilament light (NfL) and total tau (t-tau), and the clinical presentation of Alzheimer's disease (AD). A total of 579 participants (238, normal cognition [NC]; 185, mild cognitive impairment [MCI]; 156, AD dementia) had baseline blood draws; 82% had follow-up evaluations. Plasma samples were analyzed for NfL and t-tau using Simoa technology. Baseline plasma NfL was higher in AD dementia than MCI (standardized mean difference = 0.55, 95% CI: 0.37–0.73) and NC (standardized mean difference = 0.68, 95% CI: 0.49–0.88), corresponded to Clinical Dementia Rating scores (OR = 1.94, 95% CI: 1.35–2.79]), and correlated with all neuropsychological tests (r's = 0.13–0.42). Longitudinally, NfL did not predict diagnostic conversion but predicted decline on 3/10 neuropsychological tests. Baseline plasma t-tau was higher in AD dementia than NC with a small effect (standardized mean difference = 0.33, 95% CI: 0.10–0.57) but not MCI. t-tau did not statistically significant predict any longitudinal outcomes. Plasma NfL may be useful for the detection of AD dementia and monitoring of disease progression. In contrast, there was minimal evidence in support of plasma t-tau

Human-to-monkey transfer learning identifies the frontal white matter as a key determinant for predicting monkey brain age

The application of artificial intelligence (AI) to summarize a whole-brain magnetic resonance image (MRI) into an effective “brain age” metric can provide a holistic, individualized, and objective view of how the brain interacts with various factors (e.g., genetics and lifestyle) during aging. Brain age predictions using deep learning (DL) have been widely used to quantify the developmental status of human brains, but their wider application to serve biomedical purposes is under criticism for requiring large samples and complicated interpretability. Animal models, i.e., rhesus monkeys, have offered a unique lens to understand the human brain - being a species in which aging patterns are similar, for which environmental and lifestyle factors are more readily controlled. However, applying DL methods in animal models suffers from data insufficiency as the availability of animal brain MRIs is limited compared to many thousands of human MRIs. We showed that transfer learning can mitigate the sample size problem, where transferring the pre-trained AI models from 8,859 human brain MRIs improved monkey brain age estimation accuracy and stability. The highest accuracy and stability occurred when transferring the 3D ResNet [mean absolute error (MAE) = 1.83 years] and the 2D global-local transformer (MAE = 1.92 years) models. Our models identified the frontal white matter as the most important feature for monkey brain age predictions, which is consistent with previous histological findings. This first DL-based, anatomically interpretable, and adaptive brain age estimator could broaden the application of AI techniques to various animal or disease samples and widen opportunities for research in non-human primate brains across the lifespan