High-yield methods for accurate two-alternative visual psychophysics in head-fixed mice

Research in neuroscience increasingly relies on the mouse, a mammalian species that affords unparalleled genetic tractability and brain atlases. Here, we introduce high-yield methods for probing mouse visual decisions. Mice are head-fixed, facilitating repeatable visual stimulation, eye tracking, and brain access. They turn a steering wheel to make two alternative choices, forced or unforced. Learning is rapid thanks to intuitive coupling of stimuli to wheel position. The mouse decisions deliver high-quality psychometric curves for detection and discrimination and conform to the predictions of a simple probabilistic observer model. The task is readily paired with two-photon imaging of cortical activity. Optogenetic inactivation reveals that the task requires mice to use their visual cortex. Mice are motivated to perform the task by fluid reward or optogenetic stimulation of dopamine neurons. This stimulation elicits a larger number of trials and faster learning. These methods provide a platform to accurately probe mouse vision and its neural basis

A standardized and reproducible method to measure decision-making in mice.

Abstract Progress in neuroscience is hindered by poor reproducibility of mouse behavior. Here we show that in a visual decision making task, reproducibility can be achieved by automating the training protocol and by standardizing experimental hardware, software, and procedures. We trained 101 mice in this task across seven laboratories at six different research institutions in three countries, and obtained 3 million mouse choices. In trained mice, variability in behavior between labs was indistinguishable from variability within labs. Psychometric curves showed no significant differences in visual threshold, bias, or lapse rates across labs. Moreover, mice across laboratories adopted similar strategies when stimulus location had asymmetrical probability that changed over time. We provide detailed instructions and open-source tools to set up and implement our method in other laboratories. These results establish a new standard for reproducibility of rodent behavior and provide accessible tools for the study of decision making in mice

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

kdharris101/toupee: Paper version

Release of Lauren Wool's toupee repository to accompany the paper "Mouse frontal cortex nonlinearly encodes sensory, choice and outcome signals

Reporting checklist for the paper "Mouse frontal cortex nonlinearly encodes sensory, choice and outcome signals"

ARRIVE Essential 10 checklist for the paper "Mouse frontal cortex nonlinearly encodes sensory, choice and outcome signals"   Frontal area MOs (secondary motor area) is a key brain structure in rodents for making decisions based on sensory evidence and on reward value. In behavioral tasks, its neurons can encode sensory stimuli, upcoming choices, expected rewards, ongoing actions, and recent outcomes. However, the information encoded, and the nature of the resulting code, may depend on the task being performed. We recorded MOs population activity using two-photon calcium imaging, in a task requiring mice to integrate sensory evidence with reward value. Mice turned a wheel to report the location of a visual stimulus following a delay period, to receive a reward whose size varied over trial blocks. MOs neurons encoded multiple task variables, but not all of those seen in other tasks. In the delay period, the MOs population strongly encoded the stimulus side but did not significantly encode the reward-size block. A correlation of MOs activity with upcoming choice could be explained by a common effect of stimulus on those two correlates. After the wheel turn and the feedback, the MOs population encoded choice side and choice outcome jointly and nonlinearly according to an exclusive-or (XOR) operation. This nonlinear operation would allow a downstream linear decoder to infer the correct choice side (i.e., the side that would have been rewarded) even on zero contrast trials, when there had been no visible stimulus. These results indicate that MOs neurons flexibly encode some but not all variables that determine behavior, depending on task. Moreover, they reveal that MOs activity can reflect a nonlinear combination of these behavioral variables, allowing simple linear inference of task events that would not have been directly observable.</p

Knowledge across networks: how to build a global neuroscience collaboration

The International Brain Laboratory (IBL) is a collaboration of ~20 laboratories dedicated to developing a standardized mouse decision-making behavior, coordinating measurements of neural activity across the mouse brain, and utilizing theoretical approaches to formalize the neural computations that support decision-making. In contrast to traditional neuroscientific practice, in which individual laboratories each probe different behaviors and record from a few select brain areas, IBL aims to deliver a standardized, high-density approach to behavioral and neural assays. This approach relies on a highly distributed, collaborative network of ~50 researchers—postdocs, graduate students, and scientific staff—who coordinate the intellectual, administrative, and sociological aspects of the project. In this article, we examine this network, extract some lessons learned, and consider how IBL may represent a template for other team-based approaches in neuroscience, and beyond

Data files for the paper "Mouse frontal cortex nonlinearly encodes sensory, choice and outcome signals"

Contains raw and processed calcium fluorescence traces for cells recorded with 2-photon microscopy from mice performing a choice task.   Frontal area MOs (secondary motor area) is a key brain structure in rodents for making decisions based on sensory evidence and on reward value. In behavioral tasks, its neurons can encode sensory stimuli, upcoming choices, expected rewards, ongoing actions, and recent outcomes. However, the information encoded, and the nature of the resulting code, may depend on the task being performed. We recorded MOs population activity using two-photon calcium imaging, in a task requiring mice to integrate sensory evidence with reward value. Mice turned a wheel to report the location of a visual stimulus following a delay period, to receive a reward whose size varied over trial blocks. MOs neurons encoded multiple task variables, but not all of those seen in other tasks. In the delay period, the MOs population strongly encoded the stimulus side but did not significantly encode the reward-size block. A correlation of MOs activity with upcoming choice could be explained by a common effect of stimulus on those two correlates. After the wheel turn and the feedback, the MOs population encoded choice side and choice outcome jointly and nonlinearly according to an exclusive-or (XOR) operation. This nonlinear operation would allow a downstream linear decoder to infer the correct choice side (i.e., the side that would have been rewarded) even on zero contrast trials, when there had been no visible stimulus. These results indicate that MOs neurons flexibly encode some but not all variables that determine behavior, depending on task. Moreover, they reveal that MOs activity can reflect a nonlinear combination of these behavioral variables, allowing simple linear inference of task events that would not have been directly observable. </p

Standardized and reproducible measurement of decision-making in mice.

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches

Genetic Control of Human Brain Transcript Expression in Alzheimer Disease

We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We have now analyzed additional samples with a confirmed pathologic diagnosis of late-onset Alzheimer disease (LOAD; final n = 188 controls, 176 cases). Nine percent of the cortical transcripts that we analyzed had expression profiles correlated with their genotypes in the combined cohort, and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate-gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power for discovering risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease