Open science and data sharing in cognitive neuroscience with MouseBytes and MouseBytes.

Open access to rodent cognitive data has lagged behind the rapid generation of large open-access datasets in other areas of neuroscience, such as neuroimaging and genomics. One contributing factor has been the absence of uniform standardization in experiments and data output, an issue that has particularly plagued studies in animal models. Touchscreen-automated cognitive testing of animal models allows standardized outputs that are compatible with open-access sharing. Touchscreen datasets can be combined with different neuro-technologies such as fiber photometry, miniscopes, optogenetics, and MRI to evaluate the relationship between neural activity and behavior. Here we describe a platform that allows deposition of these data into an open-access repository. This platform, called MouseBytes, is a web-based repository that enables researchers to store, share, visualize, and analyze cognitive data. Here we present the architecture, structure, and the essential infrastructure behind MouseBytes. In addition, we describe MouseBytes+, a database that allows data from complementary neuro-technologies such as imaging and photometry to be easily integrated with behavioral data in MouseBytes to support multi-modal behavioral analysis.

Geographic distribution and time trends of water-pipe use among Iranian youth and teenage students: A meta-analysis and systematic review.

Water-pipe tobacco smoking is harmful to health, yet its rate of prevalence remains uncertain. Recent evidence has shown that the prevalence of water-pipe smoking among students is higher than in the general population. In this study, a systematic review of related literature on water-pipe use was conducted, and for this purpose, 76 articles were examined in the study. In this vein, geographic distribution and time trends of water-pipe consumption in Iran were considered. The results of this study showed that lifetime, last-year, and last-month prevalence of water-pipe smoking use among Iranian students were 28.78 (25.07-32.49), 20.84 (16.01-25.66), and 16.36 (11.86-20.85), respectively. The results also showed a wide variation by the region and sex in Iran. This study has shown the importance of addressing public prevention and alerting programs in schools and universities.

Continuous cholinergic-dopaminergic updating in the nucleus accumbens underlies approaches to reward-predicting cues.

The ability to learn Pavlovian associations from environmental cues predicting positive outcomes is critical for survival, motivating adaptive behaviours. This cued-motivated behaviour depends on the nucleus accumbens (NAc). NAc output activity mediated by spiny projecting neurons (SPNs) is regulated by dopamine, but also by cholinergic interneurons (CINs), which can release acetylcholine and glutamate via the activity of the vesicular acetylcholine transporter (VAChT) or the vesicular glutamate transporter (VGLUT3), respectively. Here we investigated behavioural and neurochemical changes in mice performing a touchscreen Pavlovian approach task by recording dopamine, acetylcholine, and calcium dynamics from D1- and D2-SPNs using fibre photometry in control, VAChT or VGLUT3 mutant mice to understand how these signals cooperate in the service of approach behaviours toward reward-predicting cues. We reveal that NAc acetylcholine-dopaminergic signalling is continuously updated to regulate striatal output underlying the acquisition of Pavlovian approach learning toward reward-predicting cues.

Functional dissociation of behavioral effects from acetylcholine and glutamate released from cholinergic striatal interneurons.

In the striatum, cholinergic interneurons (CINs) have the ability to release both acetylcholine and glutamate, due to the expression of the vesicular acetylcholine transporter (VAChT) and the vesicular glutamate transporter 3 (VGLUT3). However, the relationship these neurotransmitters have in the regulation of behavior is not fully understood. Here we used reward-based touchscreen tests in mice to assess the individual and combined contributions of acetylcholine/glutamate co-transmission in behavior. We found that reduced levels of the VAChT from CINs negatively impacted dopamine signalling in response to reward, and disrupted complex responses in a sequential chain of events. In contrast, diminished VGLUT3 levels had somewhat opposite effects. When mutant mice were treated with haloperidol in a cue-based task, the drug did not affect the performance of VAChT mutant mice, whereas VGLUT3 mutant mice were highly sensitive to haloperidol. In mice where both vesicular transporters were deleted from CINs, we observed altered reward-evoked dopaminergic signalling and behavioral deficits that resemble, but were worse, than those in mice with specific loss of VAChT alone. These results demonstrate that the ability to secrete two different neurotransmitters allows CINs to exert complex modulation of a wide range of behaviors.

Highlights from the Era of Open Source Web-Based Tools.

High digital connectivity and a focus on reproducibility are contributing to an open science revolution in neuroscience. Repositories and platforms have emerged across the whole spectrum of subdisciplines, paving the way for a paradigm shift in the way we share, analyze, and reuse vast amounts of data collected across many laboratories. Here, we describe how open access web-based tools are changing the landscape and culture of neuroscience, highlighting six free resources that span subdisciplines from behavior to whole-brain mapping, circuits, neurons, and gene variants.

New frontiers in translational research: Touchscreens, open science, and the mouse translational research accelerator platform.

Many neurodegenerative and neuropsychiatric diseases and other brain disorders are accompanied by impairments in high-level cognitive functions including memory, attention, motivation, and decision-making. Despite several decades of extensive research, neuroscience is little closer to discovering new treatments. Key impediments include the absence of validated and robust cognitive assessment tools for facilitating translation from animal models to humans. In this review, we describe a state-of-the-art platform poised to overcome these impediments and improve the success of translational research, the Mouse Translational Research Accelerator Platform (MouseTRAP), which is centered on the touchscreen cognitive testing system for rodents. It integrates touchscreen-based tests of high-level cognitive assessment with state-of-the art neurotechnology to record and manipulate molecular and circuit level activity in vivo in animal models during human-relevant cognitive performance. The platform also is integrated with two Open Science platforms designed to facilitate knowledge and data-sharing practices within the rodent touchscreen community, touchscreencognition.org and mousebytes.ca. Touchscreencognition.org includes the Wall, showcasing touchscreen news and publications, the Forum, for community discussion, and Training, which includes courses, videos, SOPs, and symposia. To get started, interested researchers simply create user accounts. We describe the origins of the touchscreen testing system, the novel lines of research it has facilitated, and its increasingly widespread use in translational research, which is attributable in part to knowledge-sharing efforts over the past decade. We then identify the unique features of MouseTRAP that stand to potentially revolutionize translational research, and describe new initiatives to partner with similar platforms such as McGill's M3 platform (m3platform.org).

MouseBytes, an open-access high-throughput pipeline and database for rodent touchscreen-based cognitive assessment.

Open Science has changed research by making data accessible and shareable, contributing to replicability to accelerate and disseminate knowledge. However, for rodent cognitive studies the availability of tools to share and disseminate data is scarce. Automated touchscreen-based tests enable systematic cognitive assessment with easily standardised outputs that can facilitate data dissemination. Here we present an integration of touchscreen cognitive testing with an open-access database public repository (mousebytes.ca), as well as a Web platform for knowledge dissemination (https://touchscreencognition.org). We complement these resources with the largest dataset of age-dependent high-level cognitive assessment of mouse models of Alzheimer's disease, expanding knowledge of affected cognitive domains from male and female mice of three strains. We envision that these new platforms will enhance sharing of protocols, data availability and transparency, allowing meta-analysis and reuse of mouse cognitive data to increase the replicability/reproducibility of datasets.

Quantification of whole-body bradykinesia in Parkinson's disease participants using multiple inertial sensors.

Bradykinesia (slowness of movement) is a common motor symptom of Parkinson's disease (PD) that can severely affect quality of life for those living with the disease. Assessment and treatment of PD motor symptoms largely depends on clinical scales such as the Unified Parkinson's Disease Rating Scale (UPDRS). However, such clinical scales rely on the visual assessment by a human observer, naturally resulting in inter-rater variability. Although previous studies have developed objective means for measuring bradykinesia in PD patients, their evaluation was restricted by the type of movement and number of joints assessed. These studies failed to provide a more comprehensive, whole-body evaluation capable of measuring multiple joints simultaneously. This study utilizes wearable inertial measurement units (IMUs) to quantify whole-body movements, providing novel bradykinesia indices for walking (WBI) and standing up from a chair (sit-to-stand; SBI). The proposed bradykinesia indices include the joint angles at both upper and lower limbs and trunk motion to compute a complete, objective score for whole body bradykinesia. Thirty PD and 11 age-matched healthy control participants were recruited for the study. The participants performed two standard walking tasks that involved multiple body joints in the upper and lower limbs. The WBI and SBI successfully identified differences between control and PD participants. The indices also effectively identified differences within the PD population, distinguishing participants assessed with (ON) and without (OFF) levodopa; the gold-standard of treatment for PD. The goal of this study is to provide health professionals with an objective score for whole body bradykinesia by simultaneously measuring the upper and lower extremities along with truncal movement. This method demonstrates potential to be used in conjunction with current clinical standards for motor symptom assessment, and may also be promising for the remote assessment of PD patients and in cases where experienced clinicians may not be available. In conclusion, the intelligent use of this technology for the measurement of bradykinesia (among other symptoms) has vast implications for optimizing treatment in Parkinson's disease, ultimately leading to an improvement in quality of life.

Towards remote monitoring of Parkinson's disease tremor using wearable motion capture systems.

The management of movement disorders is shifting from a centralized-clinical assessment towards remote monitoring and individualized therapy. While a variety of treatment options are available, ranging from pharmaceutical drugs to invasive neuromodulation, the clinical effects are inconsistent and often poorly measured. For instance, the lack of remote monitoring has been a major limitation to optimize therapeutic interventions for patients with Parkinson's Disease (PD). In this work, we focus on the assessment of full-body tremor as the most recognized PD symptom. Forty PD and twenty two healthy participants were recruited. The main assessment tool was an inertial measurement unit (IMU)-based motion capture system to quantify full-body tremor and to separate tremor-dominant from non-tremor-dominant PD patients as well as from healthy controls. We developed a new measure and evaluated its clinical utility by correlating the results with the Unified Parkinson's Disease Rating Scale (UPDRS) scores as the gold standard. Significant correlation was observed between the UPDRS and the tremor severity scores for the selected tasks. The results suggest that it is feasible and clinically meaningful to utilize the suggested objective tremor score for the assessment of PD patients. Furthermore, this portable assessment tool could potentially be used in the home environment to monitor PD tremor and facilitate optimizing therapeutic interventions.

Feature-based active contour model and occluding object detection.

This paper presents a method for image segmentation and object detection. The proposed strategy consists of two major stages. The first one corresponds to image segmentation, which is based on the active contour model (ACM) algorithm, using an automatic selection of the best candidate features among gradient, polarity, and depth, coupled with a combination of them by the kernel support vector machine (KSVM). Although existing techniques, such as the ones based on ACM, perform well in the single-object case and non-noisy environments, these techniques fail when the scene consists of multiple occluding objects, with possibly similar colors. Thus, the second stage corresponds to the identification of salient and occluded objects based on the fuzzy C-mean algorithm (FCM). In this stage, the depth is included as another clue that allows us to estimate the cluster number and to make the clustering process more robust. In particular, complex occlusions can be handled this way, and the objects can be properly segmented and identified. Experimental results on real images and on several standard datasets have shown the success and effectiveness of the proposed method.