Discriminating between anticipatory and visually triggered saccades:measuring minimal visual saccadic response time using luminance

We describe a novel behavioral method to accurately discriminate anticipatory (i.e., saccades not generated by visual input) from visually triggered saccades and to identify the minimal visual saccadic reaction time (SRT). This method can be used to calculate a feasible lower bound cutoff for latencies of visually triggered saccades within a certain experimental context or participant group. We apply this method to compute the minimal visual SRT for two different saccade target luminance levels. Three main findings are presented: 1) the minimal visual SRT for all participants was 46 ms shorter for bright targets than for dim targets, 2) the transition from non-visually triggered to visually triggered saccades occurred abruptly, independent of target luminance, and 3) although the absolute minimal visual SRTs varied between participants, the response pattern (response to bright targets being faster than to dim targets) was consistent across participants. These results are consistent with variability in saccadic and neural responses to luminance as has been reported in monkeys. On the basis of these results, we argue that differences in the minimal visual SRT can easily occur when stimuli vary in luminance or other saliency features. Applying an absolute cutoff (i.e., 70-90 ms) that approaches the minimal neuronal conduction delays, which is general practice in many laboratories, may result in the wrongful inclusion of saccades that are not visually triggered. It is suggested to assess the lower SRT bound for visually triggered saccades when piloting an experimental setup and before including saccades based on particular latency criteria. NEW & NOTEWORTHY We successfully developed an anticipation paradigm to discriminate between anticipatory and visually triggered saccades by measuring the minimal visual saccadic response time (SRT). We show that the 70- to 90-ms lower bound cutoff for visually triggered saccades should be applied in a flexible way and that the transitional interval is very short. The paradigm can be employed to investigate the effects of different stimulus features, experimental conditions, and participant groups on the minimal visual SRT in humans

Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease

PURPOSE: To investigate whether multivariate pattern recognition analysis of arterial spin labeling (ASL) perfusion maps can be used for classification and single-subject prediction of patients with Alzheimer disease (AD) and mild cognitive impairment (MCI) and subjects with subjective cognitive decline (SCD) after using the W score method to remove confounding effects of sex and age. MATERIALS AND METHODS: Pseudocontinuous 3.0-T ASL images were acquired in 100 patients with probable AD; 60 patients with MCI, of whom 12 remained stable, 12 were converted to a diagnosis of AD, and 36 had no follow-up; 100 subjects with SCD; and 26 healthy control subjects. The AD, MCI, and SCD groups were divided into a sex- and age-matched training set (n = 130) and an independent prediction set (n = 130). Standardized perfusion scores adjusted for age and sex (W scores) were computed per voxel for each participant. Training of a support vector machine classifier was performed with diagnostic status and perfusion maps. Discrimination maps were extracted and used for single-subject classification in the prediction set. Prediction performance was assessed with receiver operating characteristic (ROC) analysis to generate an area under the ROC curve (AUC) and sensitivity and specificity distribution. RESULTS: Single-subject diagnosis in the prediction set by using the discrimination maps yielded excellent performance for AD versus SCD (AUC, 0.96; P .05). CONCLUSION: With automated methods, age- and sex-adjusted ASL perfusion maps can be used to classify and predict diagnosis of AD, conversion of MCI to AD, stable MCI, and SCD with good to excellent accuracy and AUC values

Strategies to reduce sample sizes in Alzheimer’s disease primary and secondary prevention trials using longitudinal amyloid PET imaging

BACKGROUND: Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer's disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. METHODS: Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database ( www.oasis-brains.org ). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only. RESULTS: Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). CONCLUSION: Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development

Strategies to reduce sample sizes in Alzheimer’s disease primary and secondary prevention trials using longitudinal amyloid PET imaging

BACKGROUND: Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer's disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. METHODS: Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database ( www.oasis-brains.org ). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only. RESULTS: Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). CONCLUSION: Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development

New continuous wave infrared Ar‐Xe laser at intermediate gas pressures pumped by a transverse radio frequency discharge

An atomic Xe laser with a transverse rf excitation has been operated in a cw mode in the intermediate pressure regime. The laser output spectrum consisted of 5 Xe lines with wavelengths of 2.03, 2.63, 2.65, 3.37, and 3.51 μm. The unoptimized total output power of 330 mW was obtained for a gas mixture Ar:He:Xe=59:40:1 at a pressure of 85 Torr and a rf input power of 150 W and excitation frequency of 121 MHz

Multi-tracer model for staging cortical amyloid deposition using PET imaging

OBJECTIVE: To develop and evaluate a model for staging cortical amyloid deposition using PET with high generalizability. METHODS: 3027 subjects (1763 Cognitively Unimpaired (CU), 658 Impaired, 467 Alzheimer's disease (AD) dementia, 111 non-AD dementia, and 28 with missing diagnosis) from six cohorts (EMIF-AD, ALFA, ABIDE, ADC, OASIS-3, ADNI) who underwent amyloid PET were retrospectively included; 1049 subjects had follow-up scans. Applying dataset-specific cut-offs to global Standard Uptake Value ratio (SUVr) values from 27 regions, single-tracer and pooled multi-tracer regional rankings were constructed from the frequency of abnormality across 400 CU subjects (100 per tracer). The pooled multi-tracer ranking was used to create a staging model consisting of four clusters of regions as it displayed a high and consistent correlation with each single-tracer ranking. Relationships between amyloid stage, clinical variables and longitudinal cognitive decline were investigated. RESULTS: SUVr abnormality was most frequently observed in cingulate, followed by orbitofrontal, precuneal, and insular cortices, then the associative, temporal and occipital regions. Abnormal amyloid levels based on binary global SUVr classification were observed in 1.0%, 5.5%, 17.9%, 90.0%, and 100.0% of stage 0-4 subjects, respectively. Baseline stage predicted decline in MMSE (ADNI: N=867, F=67.37, p3000 subjects across cohorts and radiotracers, and detects pre-global amyloid burden and distinct risk profiles of cognitive decline within globally amyloid-positive subjects

Nonstrict hierarchical reinforcement learning for interactive systems and robots

Conversational systems and robots that use reinforcement learning for policy optimization in large domains often face the problem of limited scalability. This problem has been addressed either by using function approximation techniques that estimate the approximate true value function of a policy or by using a hierarchical decomposition of a learning task into subtasks. We present a novel approach for dialogue policy optimization that combines the benefits of both hierarchical control and function approximation and that allows flexible transitions between dialogue subtasks to give human users more control over the dialogue. To this end, each reinforcement learning agent in the hierarchy is extended with a subtask transition function and a dynamic state space to allow flexible switching between subdialogues. In addition, the subtask policies are represented with linear function approximation in order to generalize the decision making to situations unseen in training. Our proposed approach is evaluated in an interactive conversational robot that learns to play quiz games. Experimental results, using simulation and real users, provide evidence that our proposed approach can lead to more flexible (natural) interactions than strict hierarchical control and that it is preferred by human users

Loss of DPP6 in neurodegenerative dementia : a genetic player in the dysfunction of neuronal excitability

Emerging evidence suggested a converging mechanism in neurodegenerative brain diseases (NBD) involving early neuronal network dysfunctions and alterations in the homeostasis of neuronal firing as culprits of neurodegeneration. In this study, we used paired-end short-read and direct long-read whole genome sequencing to investigate an unresolved autosomal dominant dementia family significantly linked to 7q36. We identified and validated a chromosomal inversion of ca. 4Mb, segregating on the disease haplotype and disrupting the coding sequence of dipeptidyl-peptidase 6 gene (DPP6). DPP6 resequencing identified significantly more rare variants-nonsense, frame-shift, and missense-in early-onset Alzheimer's disease (EOAD, p value = 0.03, OR = 2.21 95% CI 1.05-4.82) and frontotemporal dementia (FTD, p = 0.006, OR = 2.59, 95% CI 1.28-5.49) patient cohorts. DPP6 is a type II transmembrane protein with a highly structured extracellular domain and is mainly expressed in brain, where it binds to the potassium channel K(v)4.2 enhancing its expression, regulating its gating properties and controlling the dendritic excitability of hippocampal neurons. Using in vitro modeling, we showed that the missense variants found in patients destabilize DPP6 and reduce its membrane expression (p < 0.001 and p < 0.0001) leading to a loss of protein. Reduced DPP6 and/or K(v)4.2 expression was also detected in brain tissue of missense variant carriers. Loss of DPP6 is known to cause neuronal hyperexcitability and behavioral alterations in Dpp6-KO mice. Taken together, the results of our genomic, genetic, expression and modeling analyses, provided direct evidence supporting the involvement of DPP6 loss in dementia. We propose that loss of function variants have a higher penetrance and disease impact, whereas the missense variants have a variable risk contribution to disease that can vary from high to low penetrance. Our findings of DPP6, as novel gene in dementia, strengthen the involvement of neuronal hyperexcitability and alteration in the homeostasis of neuronal firing as a disease mechanism to further investigate

LEDGF/p75-Independent HIV-1 Replication Demonstrates a Role for HRP-2 and Remains Sensitive to Inhibition by LEDGINs

Lens epithelium–derived growth factor (LEDGF/p75) is a cellular cofactor of HIV-1 integrase (IN) that interacts with IN through its IN binding domain (IBD) and tethers the viral pre-integration complex to the host cell chromatin. Here we report the generation of a human somatic LEDGF/p75 knockout cell line that allows the study of spreading HIV-1 infection in the absence of LEDGF/p75. By homologous recombination the exons encoding the LEDGF/p75 IBD (exons 11 to 14) were knocked out. In the absence of LEDGF/p75 replication of laboratory HIV-1 strains was severely delayed while clinical HIV-1 isolates were replication-defective. The residual replication was predominantly mediated by the Hepatoma-derived growth factor related protein 2 (HRP-2), the only cellular protein besides LEDGF/p75 that contains an IBD. Importantly, the recently described IN-LEDGF/p75 inhibitors (LEDGINs) remained active even in the absence of LEDGF/p75 by blocking the interaction with the IBD of HRP-2. These results further support the potential of LEDGINs as allosteric integrase inhibitors

TBK1 mutation spectrum in an extended European patient cohort with frontotemporal dementia and amyotrophic lateral sclerosis

We investigated the mutation spectrum of the TANK-Binding Kinase 1 (TBK1) gene and its associated phenotypic spectrum by exonic resequencing of TBK1 in a cohort of 2,538 patients with frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), or FTD plus ALS, ascertained within the European Early-Onset Dementia Consortium. We assessed pathogenicity of predicted protein-truncating mutations by measuring loss of RNA expression. Functional effect of in-frame amino acid deletions and missense mutations was further explored in vivo on protein level and in vitro by an NFB-induced luciferase reporter assay and measuring phosphorylated TBK1. The protein-truncating mutations led to the loss of transcript through nonsense-mediated mRNA decay. For the in-frame amino acid deletions, we demonstrated loss of TBK1 or phosphorylated TBK1 protein. An important fraction of the missense mutations compromised NFB activation indicating that at least some functions of TBK1 are lost. Although missense mutations were also present in controls, over three times more mutations affecting TBK1 functioning were found in the mutation fraction observed in patients only, suggesting high-risk alleles (P = 0.03). Total mutation frequency for confirmed TBK1 LoF mutations in the European cohort was 0.7%, with frequencies in the clinical subgroups of 0.4% in FTD, 1.3% in ALS, and 3.6% in FTD-ALS