Gender and other potential biases in peer review: cross-sectional analysis of 38 250 external peer review reports.

OBJECTIVES: To examine whether the gender of applicants and peer reviewers and other factors influence peer review of grant proposals submitted to a national funding agency. SETTING: Swiss National Science Foundation (SNSF). DESIGN: Cross-sectional analysis of peer review reports submitted from 2009 to 2016 using linear mixed effects regression models adjusted for research topic, applicant's age, nationality, affiliation and calendar period. PARTICIPANTS: External peer reviewers. PRIMARY OUTCOME MEASURE: Overall score on a scale from 1 (worst) to 6 (best). RESULTS: Analyses included 38 250 reports on 12 294 grant applications from medicine, architecture, biology, chemistry, economics, engineering, geology, history, linguistics, mathematics, physics, psychology and sociology submitted by 26 829 unique peer reviewers. In univariable analysis, male applicants received more favourable evaluation scores than female applicants (+0.18 points; 95% CI 0.14 to 0.23), and male reviewers awarded higher scores than female reviewers (+0.11; 95% CI 0.08 to 0.15). Applicant-nominated reviewers awarded higher scores than reviewers nominated by the SNSF (+0.53; 95% CI 0.50 to 0.56), and reviewers from outside of Switzerland more favourable scores than reviewers affiliated with Swiss institutions (+0.53; 95% CI 0.49 to 0.56). In multivariable analysis, differences between male and female applicants were attenuated (+0.08; 95% CI 0.04 to 0.13) whereas results changed little for source of nomination and affiliation of reviewers. The gender difference increased after September 2011, when new evaluation forms were introduced (p=0.033 from test of interaction). CONCLUSIONS: Peer review of grant applications at SNSF might be prone to biases stemming from different applicant and reviewer characteristics. The SNSF abandoned the nomination of peer reviewers by applicants. The new form introduced in 2011 may inadvertently have given more emphasis to the applicant's track record. We encourage other funders to conduct similar studies, in order to improve the evidence base for rational and fair research funding.

NeuroMorph: A Software Toolset for 3D Analysis of Neurite Morphology and Connectivity.

The geometries of axons, dendrites and their synaptic connections provide important information about their functional properties. These can be collected directly from measurements made on serial electron microscopy images. However, manual and automated segmentation methods can also yield large and accurate models of neuronal architecture from which morphometric data can be gathered in 3D space. This technical paper presents a series of software tools, operating in the Blender open source software, for the quantitative analysis of axons and their synaptic connections. These allow the user to annotate serial EM images to generate models of different cellular structures, or to make measurements of models generated in other software. The paper explains how the tools can measure the cross-sectional surface area at regular intervals along the length of an axon, and the amount of contact with other cellular elements in the surrounding neuropil, as well as the density of organelles, such as vesicles and mitochondria, that it contains. Nearest distance measurements, in 3D space, can also be made between any features. This provides many capabilities such as the detection of boutons and the evaluation of different vesicle pool sizes, allowing users to comprehensively describe many aspects of axonal morphology and connectivity.

The effects of aging on neuropil structure in mouse somatosensory cortex-A 3D electron microscopy analysis of layer 1.

This study has used dense reconstructions from serial EM images to compare the neuropil ultrastructure and connectivity of aged and adult mice. The analysis used models of axons, dendrites, and their synaptic connections, reconstructed from volumes of neuropil imaged in layer 1 of the somatosensory cortex. This shows the changes to neuropil structure that accompany a general loss of synapses in a well-defined brain region. The loss of excitatory synapses was balanced by an increase in their size such that the total amount of synaptic surface, per unit length of axon, and per unit volume of neuropil, stayed the same. There was also a greater reduction of inhibitory synapses than excitatory, particularly those found on dendritic spines, resulting in an increase in the excitatory/inhibitory balance. The close correlations, that exist in young and adult neurons, between spine volume, bouton volume, synaptic size, and docked vesicle numbers are all preserved during aging. These comparisons display features that indicate a reduced plasticity of cortical circuits, with fewer, more transient, connections, but nevertheless an enhancement of the remaining connectivity that compensates for a generalized synapse loss.

Computer assisted detection of axonal bouton structural plasticity in in vivo time-lapse images.

The ability to measure minute structural changes in neural circuits is essential for long-term in vivo imaging studies. Here, we propose a methodology for detection and measurement of structural changes in axonal boutons imaged with time-lapse two-photon laser scanning microscopy (2PLSM). Correlative 2PLSM and 3D electron microscopy (EM) analysis, performed in mouse barrel cortex, showed that the proposed method has low fractions of false positive/negative bouton detections (2/0 out of 18), and that 2PLSM-based bouton weights are correlated with their volumes measured in EM (r = 0.93). Next, the method was applied to a set of axons imaged in quick succession to characterize measurement uncertainty. The results were used to construct a statistical model in which bouton addition, elimination, and size changes are described probabilistically, rather than being treated as deterministic events. Finally, we demonstrate that the model can be used to quantify significant structural changes in boutons in long-term imaging experiments.

Delayed and Temporally Imprecise Neurotransmission in Reorganizing Cortical Microcircuits.

Synaptic neurotransmission is modified at cortical connections throughout life. Varying the amplitude of the postsynaptic response is one mechanism that generates flexible signaling in neural circuits. The timing of the synaptic response may also play a role. Here, we investigated whether weakening and loss of an entire connection between excitatory cortical neurons was foreshadowed in the timing of the postsynaptic response. We made electrophysiological recordings in rat primary somatosensory cortex that was undergoing experience-dependent loss of complete local excitatory connections. The synaptic latency of pyramid-pyramid connections, which typically comprise multiple synapses, was longer and more variable. Connection strength and latency were not correlated. Instead, prolonged latency was more closely related to progression of connection loss. The action potential waveform and axonal conduction velocity were unaffected, suggesting that the altered timing of neurotransmission was attributable to a synaptic mechanism. Modeling studies indicated that increasing the latency and jitter at a subset of synapses reduced the number of action potentials fired by a postsynaptic neuron. We propose that prolonged synaptic latency and diminished temporal precision of neurotransmission are hallmarks of impending loss of a cortical connection.

NeuroMorph: a toolset for the morphometric analysis and visualization of 3D models derived from electron microscopy image stacks.

Serialelectron microscopy imaging is crucial for exploring the structure of cells and tissues. The development of block face scanning electron microscopy methods and their ability to capture large image stacks, some with near isotropic voxels, is proving particularly useful for the exploration of brain tissue. This has led to the creation of numerous algorithms and software for segmenting out different features from the image stacks. However, there are few tools available to view these results and make detailed morphometric analyses on all, or part, of these 3D models. We have addressed this issue by constructing a collection of software tools, called NeuroMorph, with which users can view the segmentation results, in conjunction with the original image stack, manipulate these objects in 3D, and make measurements of any region. This approach to collecting morphometric data provides a faster means of analysing the geometry of structures, such as dendritic spines and axonal boutons. This bridges the gap that currently exists between rapid reconstruction techniques, offered by computer vision research, and the need to collect measurements of shape and form from segmented structures that is currently done using manual segmentation methods.

Correlative in vivo 2-photon imaging and focused ion beam scanning electron microscopy: 3D analysis of neuronal ultrastructure.

This protocol describes how dendrites and axons, imaged in vivo, can subsequently be analyzed in 3D using focused ion beam scanning electron microscopy (FIBSEM). The fluorescent structures are identified after chemical fixation and their position highlighted using the 2-photon laser to burn fiducial marks around the region. Once the section has been stained and resin embedded, a small block is trimmed close to these marks. Serially aligned EM images are acquired through this region, using FIBSEM, and the neurites of interest then reconstructed semi-automatically using the Ilastik software (ilastik.org). This fast and reliable imaging and reconstruction technique avoids the use of specific labels to identify the features of interest in the electron microscope and optimizes their preservation for high-quality imaging and 3D analysis.

Distributed consensus on camera pose.

Our work addresses pose estimation in a distributed camera framework. We examine how processing cameras can best reach a consensus about the pose of an object when they are each given a model of the object, defined by a set of point coordinates in the object frame of reference. The cameras can only see a subset of the object feature points in the midst of background clutter points, not knowing which image points match with which object points, nor which points are object points or background points. The cameras individually recover a prediction of the object's pose using their knowledge of the model, and then exchange information with their neighbors, performing consensus updates locally to obtain a single estimate consistent across all cameras, without requiring a common centralized processor. Our main contributions are: 1) we present a novel algorithm performing consensus updates in 3-D world coordinates penalized by a 3-D model, and 2) we perform a thorough comparison of our method with other current consensus methods. Our method is consistently the most accurate, and we confirm that the existing consensus method based upon calculating the Karcher mean of rotations is also reliable and fast. Experiments on simulated and real imagery are reported.