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Scientific conferences and meetings have an important role in research, but they also suffer from a number of disadvantages: in particular, they can have a massive carbon footprint, they are time-consuming, and the high costs involved in attending can exclude many potential participants. The COVID-19 pandemic has led to the cancellation of many conferences, forcing the scientific community to explore online alternatives. Here, we report on our experiences of organizing an online neuroscience conference, neuromatch, that attracted some 3000 participants and featured two days of talks, debates, panel discussions, and one-on-one meetings facilitated by a matching algorithm. By offering most of the benefits of traditional conferences, several clear advantages, and with fewer of the downsides, we feel that online conferences have the potential to replace many legacy conferences., Competing Interests: TA, TR, IB, SV, BW, DG, KK No competing interests declared, (© 2020, Achakulvisut et al.)

Brian 2 allows scientists to simply and efficiently simulate spiking neural network models. These models can feature novel dynamical equations, their interactions with the environment, and experimental protocols. To preserve high performance when defining new models, most simulators offer two options: low-level programming or description languages. The first option requires expertise, is prone to errors, and is problematic for reproducibility. The second option cannot describe all aspects of a computational experiment, such as the potentially complex logic of a stimulation protocol. Brian addresses these issues using runtime code generation. Scientists write code with simple and concise high-level descriptions, and Brian transforms them into efficient low-level code that can run interleaved with their code. We illustrate this with several challenging examples: a plastic model of the pyloric network, a closed-loop sensorimotor model, a programmatic exploration of a neuron model, and an auditory model with real-time input., Competing Interests: MS, RB, DG No competing interests declared, (© 2019, Stimberg et al.)

Cluster analysis faces two problems in high dimensions: the "curse of dimensionality" that can lead to overfitting and poor generalization performance and the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of spike sorting for next-generation, high-channel-count neural probes. In this problem, only a small subset of features provides information about the cluster membership of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a "masked EM" algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data and to real-world high-channel-count spike sorting data.

Simulating biological neuronal networks is a core method of research in computational neuroscience. A full specification of such a network model includes a description of the dynamics and state changes of neurons and synapses, as well as the synaptic connectivity patterns and the initial values of all parameters. A standard approach in neuronal modeling software is to build network models based on a library of pre-defined components and mechanisms; if a model component does not yet exist, it has to be defined in a special-purpose or general low-level language and potentially be compiled and linked with the simulator. Here we propose an alternative approach that allows flexible definition of models by writing textual descriptions based on mathematical notation. We demonstrate that this approach allows the definition of a wide range of models with minimal syntax. Furthermore, such explicit model descriptions allow the generation of executable code for various target languages and devices, since the description is not tied to an implementation. Finally, this approach also has advantages for readability and reproducibility, because the model description is fully explicit, and because it can be automatically parsed and transformed into formatted descriptions. The presented approach has been implemented in the Brian2 simulator.

The activity of sensory neural populations carries information about the environment. This may be extracted from neural activity using different strategies. In the auditory brainstem, a recent theory proposes that sound location in the horizontal plane is decoded from the relative summed activity of two populations in each hemisphere, whereas earlier theories hypothesized that the location was decoded from the identity of the most active cells. We tested the performance of various decoders of neural responses in increasingly complex acoustical situations, including spectrum variations, noise, and sound diffraction. We demonstrate that there is insufficient information in the pooled activity of each hemisphere to estimate sound direction in a reliable way consistent with behavior, whereas robust estimates can be obtained from neural activity by taking into account the heterogeneous tuning of cells. These estimates can still be obtained when only contralateral neural responses are used, consistently with unilateral lesion studies. DOI: http://dx.doi.org/10.7554/eLife.01312.001.

Modern graphics cards contain hundreds of cores that can be programmed for intensive calculations. They are beginning to be used for spiking neural network simulations. The goal is to make parallel simulation of spiking neural networks available to a large audience, without the requirements of a cluster. We review the ongoing efforts towards this goal, and we outline the main difficulties.

The human cochlea includes about 3000 inner hair cells which filter sounds at frequencies between 20 Hz and 20 kHz. This massively parallel frequency analysis is reflected in models of auditory processing, which are often based on banks of filters. However, existing implementations do not exploit this parallelism. Here we propose algorithms to simulate these models by vectorizing computation over frequency channels, which are implemented in "Brian Hears," a library for the spiking neural network simulator package "Brian." This approach allows us to use high-level programming languages such as Python, because with vectorized operations, the computational cost of interpretation represents a small fraction of the total cost. This makes it possible to define and simulate complex models in a simple way, while all previous implementations were model-specific. In addition, we show that these algorithms can be naturally parallelized using graphics processing units, yielding substantial speed improvements. We demonstrate these algorithms with several state-of-the-art cochlear models, and show that they compare favorably with existing, less flexible, implementations.

High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.

Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input-output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model.

Spike timing is precise in the auditory system and it has been argued that it conveys information about auditory stimuli, in particular about the location of a sound source. However, beyond simple time differences, the way in which neurons might extract this information is unclear and the potential computational advantages are unknown. The computational difficulty of this task for an animal is to locate the source of an unexpected sound from two monaural signals that are highly dependent on the unknown source signal. In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. The model was able to accurately estimate the location of previously unknown sounds in both azimuth and elevation (including front/back discrimination) in a known acoustic environment. We found that multiple representations of different acoustic environments could coexist as sets of overlapping neural assemblies which could be associated with spatial locations by Hebbian learning. The model demonstrates the computational relevance of relative spike timing to extract spatial information about sources independently of the source signal.

We demonstrate a technique for the design of neural network simulation software, runtime code generation. This technique can be used to give the user complete flexibility in specifying the mathematical model for their simulation in a high level way, along with the speed of code written in a low level language such as C+ +. It can also be used to write code only once but target different hardware platforms, including inexpensive high performance graphics processing units (GPUs). Code generation can be naturally combined with computer algebra systems to provide further simplification and optimisation of the generated code. The technique is quite general and could be applied to any simulation package. We demonstrate it with the 'Brian' simulator ( http://www.briansimulator.org ).

Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains) that can run in parallel on graphics processing units (GPUs). The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

"Brian" is a simulator for spiking neural networks (http://www.briansimulator.org). The focus is on making the writing of simulation code as quick and easy as possible for the user, and on flexibility: new and non-standard models are no more difficult to define than standard ones. This allows scientists to spend more time on the details of their models, and less on their implementation. Neuron models are defined by writing differential equations in standard mathematical notation, facilitating scientific communication. Brian is written in the Python programming language, and uses vector-based computation to allow for efficient simulations. It is particularly useful for neuroscientific modelling at the systems level, and for teaching computational neuroscience.

Objective: To report the results of penetrating keratoplasty performed by residents., Method: A retrospective medical record review of all patients undergoing penetrating keratoplasty performed by residents at our institution from April 1998 to April 2002., Results: Forty penetrating keratoplasty procedures were performed by 8 residents. The most common indication was keratoconus (17 eyes [43%]), followed by corneal scarring (14 eyes [35%]). Mean preoperative best-corrected visual acuity was 20/250. No intraoperative complications were reported. Mean follow-up time was 15 months. Postoperatively, mean best-corrected visual acuity was 20/40, mean postoperative astigmatism was 3.4 +/- 2.1 diopters, and graft survival was 92.5%. Postoperative complications included elevated intraocular pressure, wound dehiscence, and endophthalmitis., Main Outcome Measures: Best-corrected visual acuity, postoperative astigmatism, graft survival, and intraoperative and postoperative complications., Conclusion: Residents can be introduced to penetrating keratoplasty and achieve surgical success with intraoperative and postoperative complication rates similar to those previously published.

Objective: To describe the clinical, histopathologic, and hereditary features of a novel familial anterior segment dysgenesis., Design: Prospective, observational case series and interventional case report., Participants: Ten individuals from three generations of a single family with iris and corneal abnormalities associated with congenital cataracts., Main Outcome Measures: An ophthalmic evaluation including slit-lamp examination, corneal topography, pachymetry, and specular biomicroscopy of all family members, and histopathologic and ultrastructural evaluation of one excised corneal button., Results: The proband was an 81-year-old man with bilateral aphakia and diffuse corneal haze, and thinning associated with corneal guttae. His pupils were small, mildly eccentric, and difficult to dilate. Pachymeter readings were 335 microm (right eye) and 330 microm (left eye). Topography confirmed advanced steepening of both corneas. Light microscopic and transmission electron microscopic examinations of the corneal button revealed an attenuated endothelium with prominent intracellular random aggregates of small-diameter filaments staining positively for cytokeratin. Descemet's membrane was thickened and had marked posterior nodularity. Various-sized polymorphic vacuoles containing layered electron-dense material were present within and between collagen lamellae and within keratocytes throughout the stroma and Bowman's membrane. Secondary bullous changes of the epithelium with thickening of the basement membrane were also observed. The family pedigree demonstrated an autosomal dominant inheritance pattern., Conclusions: This constellation of autosomal dominantly inherited corneal endothelial and stromal disorder, with congenital cataracts and iris abnormalities, represents a novel anterior segment disorder. Its etiology may involve an abnormal migration of the secondary mesenchyme.

Purpose: To purify and characterize a cornea-associated antigen (CO-Ag) and to determine antibody levels to CO-Ag in patients with Mooren's ulcer., Method: Standard ion exchange and gel filtration chromatographies were used to isolate and purify CO-Ag from crude bovine stromal extracts. The serum of a patient with Mooren's ulcer, containing a high level of antibodies directed against CO-Ag, was used to monitor isolation procedures. Using this newly purified CO-Ag, an enzyme-linked immunoabsorbent assay was used to detect the presence of antibodies to CO-Ag in the sera of other patients with Mooren's ulcer., Results: CO-Ag was purified to apparent homogeneity from bovine corneal stromal extracts by a series of ion exchange chromatographies and gel filtration. Polyacrylamide gel electrophoresis showed that CO-Ag was a tetramer with a molecular weight of 30,000 d that may dissociate under denaturing conditions into a monomer of 7000 d. Strong indirect immunofluorescent staining was demonstrated of the stroma by guinea pig anti-CO-Ag antibody. A statistically significant difference in the level of specific antibodies to CO-Ag between patients with Mooren's ulcer and controls was found (P < 0.001). The antibody level was elevated in patients with Mooren's ulcer (mean antibody level, 0.58 +/- 0.13) compared with the controls (mean antibody level, 0.22 +/- 0.04)., Conclusion: These results suggest that an autoantigen exists in the corneal stroma that reacts with serum antibodies from patients with Mooren's ulcer. The availability of a purified corneal antigen could facilitate the diagnosis and define the pathogenetic mechanisms in Mooren's ulcer.

Little information on the natural course of corneal astigmatism following cataract surgery exists. We report a prospective, computerized analysis of postoperative astigmatism, based on keratometry measurements, of 137 cases of extracapsular cataract extraction with intraocular lens implantation performed by one surgeon. No sutures were cut postoperatively. Surgery induced 1.44 diopters (D) of with-the-rule astigmatism at one month, which declined at a rate of 0.77 D and 0.35 D per month for the next two months, respectively, with a more gradual decline thereafter. The mean surgically induced astigmatism at the last postoperative visit ranged from 0.29 D at six months (minimum follow-up) to 1.23 D at 48 months; both were against-the-rule. Mean follow-up was 28.92 months. These findings may be technique specific and suggest that (1) corneal curvature continues to change slowly even two to four years postoperatively; (2) most patients develop against-the-rule astigmatism, thus more with-the-rule astigmatism is desirable in the early postoperative period; (3) selective suture removal is necessary only when significantly more than 3.00 D of surgically induced with-the-rule astigmatism is present.

The 193-nm excimer laser was used to ablate experimental septate fungal (Fusarium) and an atypical mycobacterial (Mycobacterium fortuitum) keratitis in an animal model. The infections were allowed to proceed for 24 and 72 hours. After incubation, ablation with a 193-nm excimer laser with 5.0-mm treatment zones was performed until all suppurative areas were treated. The corneas were excised, halved, homogenized, and plated. All cultures were negative in the 24-hour group. However, in those corneas in which the infections were allowed to proceed to 72 hours, post-treatment cultures were positive for both organisms. Histopathologic examination confirmed that 24-hour infections had been eradicated and that 72-hour infections had organisms present. Three of the eight eyes in the M. fortuitum group perforated during treatment, even though the treatment depth by computer preselection was only 150 microns. Excimer laser photoablation may be a useful technique to eradicate early, localized microbial infections. However, it is apparent that advanced infections with deep stromal involvement and suppuration cannot be eradicated using this technique. Because corneas may be perforated inadvertently during treatment, excimer laser treatment of infectious keratitis should be approached with caution and used for superficial and well circumscribed lesions.

Due to continued improvement in lens design, lens manufacturing, and surgical technique, the incidence of complications of cataract surgery with intraocular lens (IOL) implantation have decreased in recent years. Complications may be categorized into operative and postoperative, both early and late onset. Operative complications include posterior capsule rupture with or without vitreous loss, loss of all or part of the lens nucleus, iris damage, and stripping of Descemet's membrane. Early postoperative complications include pupillary block, hyphema, elevation of the intraocular pressure associated with the use of viscoelastic substances, persistent uveitis with or without hypopyon, and endophthalmitis. Late postoperative complications include IOL malposition, secondary glaucoma, cystoid macular edema, retinal detachment, and pseudophakic bullous keratopathy.

Aneurysms of the intracavernous portion of the internal carotid artery may become very large, but they very rarely rupture. A case is described in which rupture of such a lesion resulted in a lethal massive subdural hematoma with transtentorial herniation. This is the second reported case of substantiated intracranial rupture from a wholly intracavernous carotid artery aneurysm.

We treated two sporadic cases of postoperative endophthalmitis caused by rapidly growing (Runyon's group IV) mycobacteria. Both involved intraocular lenses, one a secondary implant after intracapsular cataract extraction (Mycobacterium chelonae subspecies abscessus) and the other a primary posterior chamber lens implantation after extracapsular cataract extraction (pigment-producing member group IV). Signs of inflammation were judged severe enough to warrant diagnostic and therapeutic intervention during the fourth postoperative week in both cases. In both eyes the organism seemed to be eradicated by intravitreal amikacin in combination with vitrectomy, as well as topical, subconjunctival, and, in one case, systemic antibiotic therapy.

Although epikeratoplasty (epikeratophakia) for aphakia in children has achieved a high degree of success, there remains a significant incidence of complications, some of which may result in removal of the lenticule. We report a 2-year-old child in whom epikeratoplasty was followed by an acute suppurative keratitis, necessitating removal of the epikeratoplasty lenticule. The recipient bed remained scarred following removal of the lenticule with anterior stomal fibrosis, which precluded good vision. We were able to avoid a penetrating keratoplasty by performing a superficial lamellar keratoplasty with a repeat epikeratoplasty that has remained clear.

Staphylococcus epidermidis accounts for nearly one third of all cases of bacterial keratitis in certain geographic areas. Recently, the sensitivity of this organism has changed dramatically so that nearly half of nosocomially acquired systemic S epidermidis infections are resistant to methicillin sodium, cephalosporins, and aminoglycosides. Methicillin-resistant and gentamicin sulfate-resistant S epidermidis causing infectious blepharoconjunctivitis and endophthalmitis has previously been reported. Two cases of methicillin- and gentamicin-resistant S epidermidis keratitis occurred that were treated successfully with topical vancomycin hydrochloride.

To avoid the complications associated with anterior chamber intraocular lenses (IOLs), we have developed a technique for the implantation of a posterior chamber IOL in the absence of capsular support. The IOL is secured in the ciliary sulcus by suturing the haptics to the sclera at the ciliary sulcus inferiorly and to the sclera or iris superiorly. We have used this technique for secondary IOL implantation in 16 contact lens-intolerant patients with aphakia with a mean follow-up of 9 months (range, 5 to 20 months) and in eight eyes at the time of IOL removal. All eyes with secondary implants had equal or improved vision postoperatively; none developed persistent angiographic cystoid macular edema. In the 8 patients with IOL exchange, visual acuity improved in five eyes, remained the same in two, and decreased two lines in one. Suturing of an IOL in the ciliary sulcus has enabled us to use a posterior chamber IOL in eyes without a posterior capsule when secondary IOL implantation or IOL exchange is indicated. Secondary posterior chamber IOL implantation is recommended only when satisfactory vision cannot be achieved with glasses or contact lenses, and further follow-up is needed before this procedure can be widely recommended.

A 71-year-old man underwent enucleation because of intractable pain ten months after receiving helium ion therapy for a uveal melanoma. There was no clinical or ultrasonographic evidence of tumor regression but histologically the tumor appeared almost entirely necrotic.