Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing.

Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neural dynamics, there exists numerous software and hardware solutions and stacks whose variability makes it difficult to reproduce findings. Here, we establish a common reference frame for computations in digital neuromorphic systems, titled Neuromorphic Intermediate Representation (NIR).

EXODUS: Stable and efficient training of spiking neural networks.

Introduction: Spiking Neural Networks (SNNs) are gaining significant traction in machine learning tasks where energy-efficiency is of utmost importance. Training such networks using the state-of-the-art back-propagation through time (BPTT) is, however, very time-consuming. Previous work employs an efficient GPU-accelerated backpropagation algorithm called SLAYER, which speeds up training considerably.

Adversarial attacks on spiking convolutional neural networks for event-based vision.

Event-based dynamic vision sensors provide very sparse output in the form of spikes, which makes them suitable for low-power applications. Convolutional spiking neural networks model such event-based data and develop their full energy-saving potential when deployed on asynchronous neuromorphic hardware. Event-based vision being a nascent field, the sensitivity of spiking neural networks to potentially malicious adversarial attacks has received little attention so far.

The Developing Human Connectome Project Neonatal Data Release.

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods.

Event-Based Face Detection and Tracking Using the Dynamics of Eye Blinks.

We present the first purely event-based method for face detection using the high temporal resolution properties of an event-based camera to detect the presence of a face in a scene using eye blinks. Eye blinks are a unique and stable natural dynamic temporal signature of human faces across population that can be fully captured by event-based sensors. We show that eye blinks have a unique temporal signature over time that can be easily detected by correlating the acquired local activity with a generic temporal model of eye blinks that has been generated from a wide population of users.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction.

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines.

LUMOR: an app for standardized control and monitoring of a porcine lung and its nutrient cycle.

The outcome of the EU-funded project ElBik has been the lung simulator 'iLung', which imitates an actively breathing human lung with a porcine lung. In order to keep the explanted lung in a nearly physiological state during transportation from the slaughterhouse to the ventilation laboratory the tissue needs to be nourished and temperature controlled. The Project AlveoPic designs a mobile transport vehicle implementing an ISO/IEEE 11073-20601 compliant communication interface for the exchange of the physical parameters, alert messages and setpoint-values.