Simulation-based Inference for Model Parameterization on Analog Neuromorphic Hardware

The BrainScaleS-2 (BSS-2) system implements physical models of neurons as well as synapses and aims for an energy-efficient and fast emulation of biological neurons. When replicating neuroscientific experiment results, a major challenge is finding suitable model parameters. This study investigates the suitability of the sequential neural posterior estimation (SNPE) algorithm for parameterizing a multi-compartmental neuron model emulated on the BSS-2 analog neuromorphic hardware system. In contrast to other optimization methods such as genetic algorithms or stochastic searches, the SNPE algorithms belongs to the class of approximate Bayesian computing (ABC) methods and estimates the posterior distribution of the model parameters; access to the posterior allows classifying the confidence in parameter estimations and unveiling correlation between model parameters. In previous applications, the SNPE algorithm showed a higher computational efficiency than traditional ABC methods. For our multi-compartmental model, we show that the approximated posterior is in agreement with experimental observations and that the identified correlation between parameters is in agreement with theoretical expectations. Furthermore, we show that the algorithm can deal with high-dimensional observations and parameter spaces. These results suggest that the SNPE algorithm is a promising approach for automating the parameterization of complex models, especially when dealing with characteristic properties of analog neuromorphic substrates, such as trial-to-trial variations or limited parameter ranges

Muscle fiber diameter assessment in cleft lip using image processing

OBJECTIVE: To pilot investigation of muscle fiber diameter (MFD) on medial and lateral sides of the cleft in 18 infants with cleft lip with or without cleft palate (CL/P) using image processing. MATERIAL AND METHODS: Formalin-fixed paraffin-embedded (FFPE) tissue samples from the medial and lateral sides of the cleft were analyzed for MFD using an image-processing program (ImageJ). For within-case comparison, a paired Student's t test was performed. For comparisons between classes, an unpaired t test was used. RESULTS: Image processing enabled rapid measurement of MFD with majority of fibers showing diameter between 6 and 11 μm. There was no significant difference in mean MFD between the medial and lateral sides, or between CL and CLP. However, we found a significant difference on the medial side (p = .032) between males and females. CONCLUSION: The image processing on FFPE tissues resulted in easy quantification of MFD with finding of a smaller MFD on the medial side in males suggesting possible differences in orbicularis oris (OO) muscle between the two sexes in CL that warrants replication using larger number of cases. Moreover, this finding can aid subclinical phenotyping and potentially in the restoration of the anatomy and function of the upper lip

Fast neutron production at the LNL Tandem from the 7^7Li(14^{14}N,xn)X reaction

Fast neutron beams are of relevance for many scientific and industrial applications. This paper explores fast neutron production using a TANDEM accelerator at the Legnaro National Laboratories, via an energetic ion beam (90 MeV $^{14}N$) onto a lithium target. The high energy models for nuclear collision of FLUKA foresee large neutron yields for reactions of this kind. The experiment aimed at validating the expected neutron yields from FLUKA simulations, using two separate and independent set-ups: one based on the multi-foil activation technique, and the other on the time of flight technique, by using liquid scintillator detectors. The results of the experiment show clear agreement of the measured spectra with the FLUKA simulations, both in the shape and the magnitude of the neutron flux at the measured positions. The neutron spectrum is centered around the 8 MeV range with mild tails, and a maximum neutron energy spanning up to 50 MeV. These advantageous results provide a starting point in the development of fast neutron beams based on high energy ion beams from medium-sized accelerator facilities

The BrainScaleS-2 Neuromorphic Platform — A Report on the Integration and Operation of an Open Science Hardware Platform within EBRAINS

This report presents the challenges encountered and the solutions created for the operation of the BrainScaleS neuromorphic platform, and the overall progress leading to this state at the end of the Human Brain Project (HBP)

A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware.

Neuromorphic systems open up opportunities to enlarge the explorative space for computational research. However, it is often challenging to unite efficiency and usability. This work presents the software aspects of this endeavor for the BrainScaleS-2 system, a hybrid accelerated neuromorphic hardware architecture based on physical modeling. We introduce key aspects of the BrainScaleS-2 Operating System: experiment workflow, API layering, software design, and platform operation. We present use cases to discuss and derive requirements for the software and showcase the implementation. The focus lies on novel system and software features such as multi-compartmental neurons, fast re-configuration for hardware-in-the-loop training, applications for the embedded processors, the non-spiking operation mode, interactive platform access, and sustainable hardware/software co-development. Finally, we discuss further developments in terms of hardware scale-up, system usability, and efficiency

How Do I Look? Body Image Perceptions among University Students from England and Denmark

This study examined differences in body image perception between university students in two European countries, United Kingdom and Denmark. A total of 816 British and 548 Danish university students participated in a cross-sectional survey. A self-administered questionnaire assessed socio-demographic information, body image perception (as “too thin”, “just right” or “too fat”), and the association of related factors with body image perception (nutrition behaviour, social support, perceived stressors and quality of life). The proportions of students who perceived themselves as “too thin”, “just right”, or “too fat” were 8.6%, 37.7%, and 53.7% respectively. Multi-factorial logistic regression analysis showed that students who perceived themselves as “too fat” were more likely to be from the British university, to be females, to be older than 30 years, to report stress due to their financial situation and were less likely to have a high quality of life. The findings highlight the need for interventions with focus on healthy food choices whilst acknowledging financial stressors and quality of life

In Support of a Patient-Driven Initiative and Petition to Lower the High Price of Cancer Drugs

Comment in Lowering the High Cost of Cancer Drugs--III. [Mayo Clin Proc. 2016] Lowering the High Cost of Cancer Drugs--I. [Mayo Clin Proc. 2016] Lowering the High Cost of Cancer Drugs--IV. [Mayo Clin Proc. 2016] In Reply--Lowering the High Cost of Cancer Drugs. [Mayo Clin Proc. 2016] US oncologists call for government regulation to curb drug price rises. [BMJ. 2015

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO