To Protect and Collect: A Nationwide Study of Profit-motivated Police Crime

This study is part of a larger research project on police crime in the United States. Police crimes are those criminal offenses committed by sworn law enforcement officers who have the general powers of arrest. Profit-motivated police crime involves officers who use their authority of position to engage in crime for personal gain. This study reports the findings on 1,591 cases where a law enforcement officer was arrested for one or more profit-motivated crimes during the seven-year period 2005-2011. The profit-motivated arrest cases involved 1,396 individual officers employed by 782 state, local, special, constable, and tribal law enforcement agencies located in 531 counties and independent cities in 47 states and the District of Columbia. Our data is the first systematic study of profit-motivated police crime. The study describes the nature of this form of police misconduct in terms of several dimensions, including the characteristics of police who perpetrate these crimes, where it occurs, the specific criminal charges, and the contexts within which profit-motivated police crime is punished through police agencies and the criminal courts

Spatial Noise-Field Control With Online Secondary Path Modeling: A Wave-Domain Approach

Due to strong interchannel interference in multichannel active noise control (ANC), there are fundamental problems associated with the filter adaptation and online secondary path modeling remains a major challenge. This paper proposes a wave-domain adaptation algorithm for multichannel ANC with online secondary path modelling to cancel tonal noise over an extended region of two-dimensional plane in a reverberant room. The design is based on exploiting the diagonal-dominance property of the secondary path in the wave domain. The proposed wave-domain secondary path model is applicable to both concentric and nonconcentric circular loudspeakers and microphone array placement, and is also robust against array positioning errors. Normalized least mean squares-type algorithms are adopted for adaptive feedback control. Computational complexity is analyzed and compared with the conventional time-domain and frequency-domain multichannel ANCs. Through simulation-based verification in comparison with existing methods, the proposed algorithm demonstrates more efficient adaptation with low-level auxiliary noise.DP14010341

Cognitive Reserve Moderates the Association between Functional Network Anti-Correlations and Memory in MCI

Cognitive reserve (CR) shows protective effects on cognitive function in older adults. Here, we focused on the effects of CR at the functional network level. We assessed in patients with amnestic mild cognitive impairment (aMCI) whether higher CR moderates the association between low internetwork cross-talk on memory performance. In 2 independent aMCI samples (n = 76 and 93) and healthy controls (HC, n = 36), CR was assessed via years of education and intelligence (IQ). We focused on the anti-correlation between the dorsal attention network (DAN) and an anterior and posterior default mode network (DMN), assessed via sliding time window analysis of resting-state functional magnetic resonance imaging (fMRI). The DMN-DAN anti-correlation was numerically but not significantly lower in aMCI compared to HC. However, in aMCI, lower anterior DMN-DAN anti-correlation was associated with lower memory performance. This association was moderated by CR proxies, where the association between the internetwork anti-correlation and memory performance was alleviated at higher levels of education or IQ. In conclusion, lower DAN-DMN cross-talk is associated with lower memory in aMCI, where such effects are buffered by higher CR

Correspondence Between Resting-State and Episodic Memory-Task Related Networks in Elderly Subjects

Resting-state fMRI studies demonstrated temporally synchronous fluctuations in brain activity among ensembles of brain regions, suggesting the existence of intrinsic functional networks. A spatial match between some of the resting-state networks and regional brain activation during cognitive tasks has been noted, suggesting that resting-state networks support particular cognitive abilities. However, the spatial match and predictive value of any resting-state network and regional brain activation during episodic memory is only poorly understood. In order to address this research gap, we obtained fMRI acquired both during rest and a face-name association task in 38 healthy elderly subjects. In separate independent component analyses, networks of correlated brain activity during rest or the episodic memory task were identified. For the independent components identified for task-based fMRI, the design matrix of successful encoding or retrieval trials was regressed against the time course of each of the component to identify significantly activated networks. Spatial regression was used to assess the match of resting-state networks against those related to successful memory encoding or retrieval. We found that resting-state networks covering the medial temporal, middle temporal, and frontal areas showed increased activity during successful encoding. Resting-state networks located within posterior brain regions showed increased activity during successful recognition. However, the level of resting-state network connectivity was not predictive of the task-related activity in these networks. These results suggest that a circumscribed number of functional networks detectable during rest become engaged during successful episodic memory. However, higher intrinsic connectivity at rest may not translate into higher network expression during episodic memory

Rehabilitation robotics: pilot trial of a spatial extension for MIT-Manus

BACKGROUND: Previous results with the planar robot MIT-MANUS demonstrated positive benefits in trials with over 250 stroke patients. Consistent with motor learning, the positive effects did not generalize to other muscle groups or limb segments. Therefore we are designing a new class of robots to exercise other muscle groups or limb segments. This paper presents basic engineering aspects of a novel robotic module that extends our approach to anti-gravity movements out of the horizontal plane and a pilot study with 10 outpatients. Patients were trained during the initial six-weeks with the planar module (i.e., performance-based training limited to horizontal movements with gravity compensation). This training was followed by six-weeks of robotic therapy that focused on performing vertical arm movements against gravity. The 12-week protocol includes three one-hour robot therapy sessions per week (total 36 robot treatment sessions). RESULTS: Pilot study demonstrated that the protocol was safe and well tolerated with no patient presenting any adverse effect. Consistent with our past experience with persons with chronic strokes, there was a statistically significant reduction in tone measurement from admission to discharge of performance-based planar robot therapy and we have not observed increases in muscle tone or spasticity during the anti-gravity training protocol. Pilot results showed also a reduction in shoulder-elbow impairment following planar horizontal training. Furthermore, it suggested an additional reduction in shoulder-elbow impairment following the anti-gravity training. CONCLUSION: Our clinical experiments have focused on a fundamental question of whether task specific robotic training influences brain recovery. To date several studies demonstrate that in mature and damaged nervous systems, nurture indeed has an effect on nature. The improved recovery is most pronounced in the trained limb segments. We have now embarked on experiments that test whether we can continue to influence recovery, long after the acute insult, with a novel class of spatial robotic devices. This pilot results support the pursuit of further clinical trials to test efficacy and the pursuit of optimal therapy following brain injury

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

INTRODUCTION: We investigated the association of inflammatory mechanisms with markers of Alzheimer's disease (AD) pathology and rates of cognitive decline in the AD spectrum.METHODS: We studied 296 cases from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study (DELCODE) cohort, and an extension cohort of 276 cases of the Alzheimer's Disease Neuroimaging Initiative study. Using Bayesian confirmatory factor analysis, we constructed latent factors for synaptic integrity, microglia, cerebrovascular endothelial function, cytokine/chemokine, and complement components of the inflammatory response using a set of inflammatory markers in cerebrospinal fluid.RESULTS: We found strong evidence for an association of synaptic integrity, microglia response, and cerebrovascular endothelial function with a latent factor of AD pathology and with rates of cognitive decline. We found evidence against an association of complement and cytokine/chemokine factors with AD pathology and rates of cognitive decline.DISCUSSION: Latent factors provided access to directly unobservable components of the neuroinflammatory response and their association with AD pathology and cognitive decline.</p

Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy:A Bayesian Approach

Background: Cognitive decline is a key outcome of clinical studies in Alzheimer’s disease (AD). Objective: To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts. Methods: We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis. Results: We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases. Conclusions: We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid

Relevance of Minor Neuropsychological Deficits in Patients With Subjective Cognitive Decline

peer reviewed[en] BACKGROUND AND OBJECTIVES: To determine the relevance of minor neuropsychological deficits (MNPD) in patients with subjective cognitive decline (SCD) with regard to CSF levels of Alzheimer disease (AD) biomarkers, cognitive decline, and clinical progression to mild cognitive impairment (MCI). METHODS: This study included patients with clinical SCD and SCD-free, healthy control (HC) participants with available baseline CSF and/or longitudinal cognitive data from the observational DZNE Longitudinal Cognitive Impairment and Dementia study. We defined MNPD as a performance of at least 0.5SD below the mean on a demographically adjusted total score derived from the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological assessment battery. We compared SCD patients with MNPD and those without MNPD with regard to CSF amyloid-β (Aβ)42/Aβ40, phosphorylated tau (p-tau181), total tau and Aβ42/p-tau181 levels, longitudinal cognitive composite trajectories, and risk of clinical progression to incident MCI (follow-up M ± SD: 40.6 ± 23.7 months). In addition, we explored group differences between SCD and HC in those without MNPD. RESULTS: In our sample (N = 672, mean age: 70.7 ± 5.9 years, 50% female), SCD patients with MNPD (n = 55, 12.5% of SCD group) showed significantly more abnormal CSF biomarker levels, increased cognitive decline, and a higher risk of progression to incident MCI (HR: 4.07, 95% CI 2.46-6.74) compared with SCD patients without MNPD (n = 384). MNPD had a positive predictive value of 57.0% (95% CI 38.5-75.4) and a negative predictive value of 86.0% (95% CI 81.9-90.1) for the progression of SCD to MCI within 3 years. SCD patients without MNPD showed increased cognitive decline and a higher risk of incident MCI compared with HC participants without MNPD (n = 215; HR: 4.09, 95% CI 2.07-8.09), while AD biomarker levels did not differ significantly between these groups. DISCUSSION: Our results suggest that MNPD are a risk factor for AD-related clinical progression in cognitively normal patients seeking medical counseling because of SCD. As such, the assessment of MNPD could be useful for individual clinical prediction and for AD risk stratification in clinical trials. However, SCD remains a risk factor for future cognitive decline even in the absence of MNPD