A reaction diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality

Self-organized structures in networks with spike-timing dependent plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic feed-forward networks of nonlinear rate neurons with a correlation sensitive learning rule inspired by and being qualitatively similar to STDP. After obtaining equations that describe the change of the spatial shape of the signal from layer to layer, we derive a criterion for the non-linearity necessary to obtain stable dynamics for arbitrary input. We classify the possible scenarios of signal evolution and find that close to the transition to the unstable regime meta-stable solutions appear. The form of these dissipative solitons is determined analytically and the evolution and interaction of several such coexistent objects is investigated

Patient-Reported Outcomes Measurement Information System physical function correlates with Toronto Extremity Salvage Score in an orthopaedic oncology population

Background: The National Institute of Health\u27s Patient-Reported Outcomes Measurement Information System (PROMIS) uses computerised-adaptive testing to reduce survey burden and improve sensitivity. PROMIS is being used across medical and surgical disciplines but has not been studied in orthopaedic oncology. Questions/purposes: The aim of the study was to compare PROMIS measures with upper extremity (UE) and lower extremity (LE) Toronto Extremity Salvage Score (TESS) by assessing the following: (1) responder burden, (2) correlation between scores and (3) floor/ceiling effects. Patients and methods: This cross-sectional trial analysed all 97 adult patients treated surgically for a bone or soft tissue tumour at a tertiary institution between November 2015 and March 2016. TESS (UE or LE) and PROMIS (Physical Function, Pain Interference and Depression) surveys were administered preoperatively. Pearson correlations between each PROMIS domain and TESS were calculated, as were floor/ceiling effects of each outcome measure. Results: (1) Completion of three PROMIS questionnaires required a mean total of 16.8 (+/- 5.8 standard deviation) questions, compared with 31 and 32 questions for the LE and UE TESS questionnaires, respectively. (2) The PROMIS Physical Function scores demonstrated a strong positive correlation with the LE TESS (r = 0.84; 95% confidence interval [CI], 0.72-0.91; p \u3c 0.001) and moderate positive correlation with the UE TESS (r = 0.64; 95% CI, 0.34-0.83; p = 0.055). The PROMIS Depression scores demonstrated a weak negative correlation with both the LE TESS (r = -0.38; 95% CI, -0.61 to -0.10; p = 0.010) and with UE TESS (r = -0.38; 95% CI, -0.67 to -0.01; p = 0.055). The PROMIS Pain Interference scores demonstrated a strong negative correlation with the LE TESS (r = -0.71; 95% CI, -0.83 to -0.52; p \u3c 0.001) and a moderate negative correlation with the UE TESS (r = -0.62; 95% CI, -0.81 to -0.30; p = 0.001). (3) The UE TESS had a range of scores from 16 to 100 with a 27% ceiling effect and no floor effect, and the LE TESS had a range from 10 to 98 with no floor or ceiling effect. There was no floor or ceiling effect for any PROMIS measures. Conclusions: In an orthopaedic oncology population, the PROMIS Physical Function and Pain Interference scores correlate with the TESS and have the benefit of reduced survey burden and ceiling effect. The PROMIS Depression scores may provide additional information regarding patient outcomes not captured by the TESS. Level of Evidence: Level III. The translational potential of this article: Patient reported outcome measures asses patients\u27 symptoms, function and health-related quality of life and are designed to capture more clinical information than can be gathered by objective medial testing alone. As reimbursements and the understanding of patient outcomes are becoming tied to performance on PROMIS measures, it is an important step to establish how PROMIS measures correlate and compare to traditional legacy measures

Shearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting

High-resolution three-dimensional (3D) cardiovascular magnetic resonance (CMR) is a valuable medical imaging technique, but its widespread application in clinical practice is hampered by long acquisition times. Here we present a novel compressed sensing (CS) reconstruction approach using shearlets as a sparsifying transform allowing for fast 3D CMR (3DShearCS). Shearlets are mathematically optimal for a simplified model of natural images and have been proven to be more efficient than classical systems such as wavelets. Data is acquired with a 3D Radial Phase Encoding (RPE) trajectory and an iterative reweighting scheme is used during image reconstruction to ensure fast convergence and high image quality. In our in-vivo cardiac MRI experiments we show that the proposed method 3DShearCS has lower relative errors and higher structural similarity compared to the other reconstruction techniques especially for high undersampling factors, i.e. short scan times. In this paper, we further show that 3DShearCS provides improved depiction of cardiac anatomy (measured by assessing the sharpness of coronary arteries) and two clinical experts qualitatively analyzed the image quality

The cellular and synaptic architecture of the mechanosensory dorsal horn

The deep dorsal horn is a poorly characterized spinal cord region implicated in processing low-threshold mechanoreceptor (LTMR) information. We report an array of mouse genetic tools for defining neuronal components and functions of the dorsal horn LTMR-recipient zone (LTMR-RZ), a role for LTMR-RZ processing in tactile perception, and the basic logic of LTMR-RZ organization. We found an unexpectedly high degree of neuronal diversity in the LTMR-RZ: seven excitatory and four inhibitory subtypes of interneurons exhibiting unique morphological, physiological, and synaptic properties. Remarkably, LTMRs form synapses on between four and 11 LTMR-RZ interneuron subtypes, while each LTMR-RZ interneuron subtype samples inputs from at least one to three LTMR classes, as well as spinal cord interneurons and corticospinal neurons. Thus, the LTMR-RZ is a somatosensory processing region endowed with a neuronal complexity that rivals the retina and functions to pattern the activity of ascending touch pathways that underlie tactile perception

Random projection to preserve patient privacy

With the availability of accessible and widely used cloud services, it is natural that large components of healthcare systems migrate to them; for example, patient databases can be stored and processed in the cloud. Such cloud services provide enhanced flexibility and additional gains, such as availability, ease of data share, and so on. This trend poses serious threats regarding the privacy of the patients and the trust that an individual must put into the healthcare system itself. Thus, there is a strong need of privacy preservation, achieved through a variety of different approaches. In this paper, we study the application of a random projection-based approach to patient data as a means to achieve two goals: (1) provably mask the identity of users under some adversarial-attack settings, (2) preserve enough information to allow for aggregate data analysis and application of machine-learning techniques. As far as we know, such approaches have not been applied and tested on medical data. We analyze the tradeoff between the loss of accuracy on the outcome of machine-learning algorithms and the resilience against an adversary. We show that random projections proved to be strong against known input/output attacks while offering high quality data, as long as the projected space is smaller than the original space, and as long as the amount of leaked data available to the adversary is limited

Non-Markovian dynamics of a damped driven two-state system

We study a driven two-state system interacting with a structured environment. We introduce the non-Markovian master equation ruling the system dynamics, and we derive its analytic solution for general reservoir spectra. We compare the non-Markovian dynamics of the Bloch vector for two classes of reservoir spectra: the Ohmic and the Lorentzian reservoir. Finally, we derive the analytic conditions for complete positivity with and without the secular approximation. Interestingly, the complete positivity conditions have a transparent physical interpretation in terms of the characteristic timescales of phase diffusion and relaxation processes.Comment: 12 pages, 5 figures, final versio

Orientational correlations in confined DNA

We study how the orientational correlations of DNA confined to nanochannels depend on the channel diameter D by means of Monte Carlo simulations and a mean-field theory. This theory describes DNA conformations in the experimentally relevant regime where the Flory-de Gennes theory does not apply. We show how local correlations determine the dependence of the end-to-end distance of the DNA molecule upon D. Tapered nanochannels provide the necessary resolution in D to study experimentally how the extension of confined DNA molecules depends upon D. Our experimental and theoretical results are in qualitative agreement.Comment: Revised version including supplemental material, 7 pages, 8 figure