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Nonlinear dynamics of spiking neural networks have recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective spiking dynamics of neurons, the fine control of spiking dynamics is desirable for neuromorphic devices. Here we show that photonic spiking neurons implemented with paired nonlinear optical oscillators can be controlled to generate two modes of bio-realistic spiking dynamics by changing optical-pump amplitude. When the photonic neurons are coupled in a network, the interaction between them induces an effective change in the pump amplitude depending on the order parameter that characterizes synchronization. The experimental results show that the effective change causes spontaneous modification of the spiking modes and firing rates of clustered neurons, and such collective dynamics can be utilized to realize efficient heuristics for solving NP-hard combinatorial optimization problems.

Reservoir computing (RC) is a machine learning algorithm that can learn complex time series from data very rapidly based on the use of high-dimensional dynamical systems, such as random networks of neurons, called "reservoirs." To implement RC in edge computing, it is highly important to reduce the amount of computational resources that RC requires. In this study, we propose methods that reduce the size of the reservoir by inputting the past or drifting states of the reservoir to the output layer at the current time step. To elucidate the mechanism of model-size reduction, the proposed methods are analyzed based on information processing capacity proposed by Dambre et al. (Sci Rep 2:514, 2012). In addition, we evaluate the effectiveness of the proposed methods on time-series prediction tasks: the generalized Hénon-map and NARMA. On these tasks, we found that the proposed methods were able to reduce the size of the reservoir up to one tenth without a substantial increase in regression error.

Minimal invasive surgery and reconstructive surgery tend to become the standard in France in the management of head and neck tumors. The use of endoscopic approaches (through endoscopic endonasal/transoral approaches±robot-assisted) instead of open surgery and the use of reconstructive surgery using autologous (flaps) or heterologous materials aim to reduce surgical morbidity by making-up for the loss of substance to restore the function. The impact of these substantial changes in surgical techniques has not been assessed with respect to postoperative radiotherapy practice. Endoscopic endonasal approaches result, however, in piecemeal resection, which, along the analysis of resection margins (a key prognostic factor), make the interpretation of the quality of resection more complex for radiation oncologists. The definition of tumour sub-volumes to be irradiated and doses to these sub-volumes then requires accurate histosurgical mapping and close multidisciplinary consultation between surgeons, pathologists, radiologists and radiation oncologists. Similarly, the increasing use of various types of flaps (of soft tissue or bone flaps), adapted to the patient and tumor anatomy, is associated with substantial modifications to the operating bed. The delineation of tumour volumes in postoperative radiotherapy is made more complex. Tremendous multidisciplinary efforts should now be initiated to fully take advantage of surgical advances and to further optimize the therapeutic index by making radiotherapy also less toxic, i.e. "mini-morbid"., (Copyright © 2020 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.)

The relaxation of binary spins to analog values has been the subject of much debate in the field of statistical physics, neural networks, and more recently quantum computing, notably because the benefits of using an analog state for finding lower energy spin configurations are usually offset by the negative impact of the improper mapping of the energy function that results from the relaxation. We show that it is possible to destabilize trapping sets of analog states that correspond to local minima of the binary spin Hamiltonian by extending the phase space to include error signals that correct amplitude inhomogeneity of the analog spin states and controlling the divergence of their velocity. Performance of the proposed analog spin system in finding lower energy states is competitive against state-of-the-art heuristics.

Recent experiments have shown that stereotypical spatiotemporal patterns occur during brief packets of spiking activity in the cortex, and it has been suggested that top-down inputs can modulate these patterns according to the context. We propose a simple model that may explain important features of these experimental observations and is analytically tractable. The key mechanism underlying this model is that context-dependent top-down inputs can modulate the effective connection strengths between neurons because of short-term synaptic depression. As a result, the degree of synchrony and, in turn, the spatiotemporal patterns of spiking activity that occur during packets are modulated by the top-down inputs. This is shown using an analytical framework, based on avalanche dynamics, that allows calculating the probability that a given neuron spikes during a packet and numerical simulations. Finally, we show that the spatiotemporal patterns that replay previously experienced sequential stimuli and their binding with their corresponding context can be learned because of spike-timing-dependent plasticity.

The dynamics of driven-dissipative systems is shown to be well-fitted for achieving efficient combinatorial optimization. The proposed method can be applied to solve any combinatorial optimization problem that is equivalent to minimizing an Ising Hamiltonian. Moreover, the dynamics considered can be implemented using various physical systems as it is based on generic dynamics-the normal form of the supercritical pitchfork bifurcation. The computational principle of the proposed method relies on an hybrid analog-digital representation of the binary Ising spins by considering the gradient descent of a Lyapunov function that is the sum of an analog Ising Hamiltonian and archetypal single or double-well potentials. By gradually changing the shape of the latter potentials from a single to double well shape, it can be shown that the first nonzero steady states to become stable are associated with global minima of the Ising Hamiltonian, under the approximation that all analog spins have the same amplitude. In the more general case, the heterogeneity in amplitude between analog spins induces the stabilization of local minima, which reduces the quality of solutions to combinatorial optimization problems. However, we show that the heterogeneity in amplitude can be reduced by setting the parameters of the driving signal near a regime, called the dynamic phase transition, where the analog spins' DC components map more accurately the global minima of the Ising Hamiltonian which, in turn, increases the quality of solutions found. Last, we discuss the possibility of a physical implementation of the proposed method using networks of degenerate optical parametric oscillators.

A robust method for inferring the structure of networks is presented based on the one-to-one correspondence between the expected composition of cascades of bursts of activity, called crackling noise or avalanches, and the weight matrix. Using a model of neuronal avalanches as a paradigmatic example, we derive this correspondence exactly by calculating the closed-form expression of the joint probability distribution of avalanche sizes obtained by counting separately the number of elements active in each subnetwork during avalanches.

We study a realistic model of a cortical column taking into account short-term plasticity between pyramidal cells and interneurons. The simulation of leaky integrate-and-fire neurons shows that low-frequency oscillations emerge spontaneously as a result of intrinsic network properties. These oscillations are composed of prolonged phases of high and low activity reminiscent of cortical up and down states, respectively. We simplify the description of the network activity by using a mean field approximation and reduce the system to two slow variables exhibiting some relaxation oscillations. We identify two types of slow oscillations. When the combination of dynamic synapses between pyramidal cells and those between interneurons accounts for the generation of these slow oscillations, the end of the up phase is characterized by asynchronous fluctuations of the membrane potentials. When the slow oscillations are mainly driven by the dynamic synapses between interneurons, the network exhibits fluctuations of membrane potentials, which are more synchronous at the end than at the beginning of the up phase. Additionally, finite size effect and slow synaptic currents can modify the irregularity and frequency, respectively, of these oscillations. Finally, we consider possible roles of a slow oscillatory input modeling long-range interactions in the brain. Spontaneous slow oscillations of local networks are modulated by the oscillatory input, which induces, notably, synchronization, subharmonic synchronization, and chaotic relaxation oscillations in the mean field approximation. In the case of forced oscillations, the slow population-averaged activity of leaky integrate-and-fire neurons can have both deterministic and stochastic temporal features. We discuss the possibility that long-range connectivity controls the emergence of slow sequential patterns in local populations due to the tendency of a cortical column to oscillate at low frequency.

In this article, we analyze combined effects of LTP/LTD and synaptic scaling and study the creation of persistent activity from a periodic or chaotic baseline attractor. The bifurcations leading to the creation of new attractors have been detailed; this was achieved using a mean field approximation. Attractors encoding persistent activity can notably appear via generalized period-doubling bifurcations, tangent bifurcations of the second iterates or boundary crises, after which the basins of attraction become irregular. Synaptic scaling is shown to maintain the coexistence of a state of persistent activity and the baseline. According to the rate of change of the external inputs, different types of attractors can be formed: line attractors for rapidly changing external inputs and discrete attractors for constant external inputs.

Introduction: Cutaneous location of multiple myeloma is rare, and generally develops as a consequence of direct spread from an underlying bony focus of the disease. Metastatic skin lesions without adjacent bone involvement are uncommon. The prognosis is very poor., Case Report: A 74-year-old man consulted for a hemorrhagic cutaneous nodule localized on the left inguinal area. This patient had been treated for five months for a stage I IgG lambda multiple myeloma. The histopathologic examination of the lesion showed a predominantly nodular configuration made up of masses of atypical cells with numerous hemorrhagic areas. The diagnosis of cutaneous metastasis of multiple myeloma was confirmed by the positivity of the cells for anti-IgG lambda antibodies., Discussion: Cutaneous involvement in multiple myeloma without extension from underlying bony focus is exceptional. The lesions generally consist of firm, erythematous nodules involving the neck and lower extremities. To our knowledge, we present here the first case mimicking clinically and histologically a malignant vascular proliferation.

Objectives: Denutrition is a frequent condition in elderly persons and may have major consequences. A noninvasive investigation, whole body dual energy X-ray absorptiometry, should allow, by direct measurement of body composition, early and reliable diagnosis of denutrition. This study was conducted to elaborate a diagnostic tool using this exam and to test its validity., Patients and Methods: A global index of denutrition was proposed combining anthropometric, biological criteria, and the Mini Nutritional Assessment scale. Two agreement analyses were made between classical diagnostic criteria of nutritional status and body fat and fat free mass assessed by anthropometry and absorptiometry. An association between nutritional status and body absorptiometric composition were studied with univariate analysis followed by a multivariate logistic regression model. This model allowed an elaboration of a nutritional absorptiometric index (NAI)., Results: One hundred one elderly subjects were included. Twenty-three were considered to be in a state of denutrition. Agreement was poor between anthropometric and biological diagnostic criteria of denutrition. It was good between the different masses assess by anthropometry and absorptiometry. Subjects in a state of denutrition had significantly lower body fat and lower fat free mass. The fat free mass index (fat free mass divided by the square height) and body fat were entered into a logistic model and composed the NAI, which showed good diagnostic validity in terms of specificity and sensitivity., Discussion: Absorptiometry appears to be a simple reliable diagnostic tool for assessing denutrition in elderly persons in routine practice. Further studies are required and should lead to a confirmation of the interest of these absorptiometric indexes.

We report 16 cases of epiphyseal metatarsal stress fractures in 11 patients. Four patients had osteoporosis and two of these four were under fluoride therapy. Three of the fractures occurred upon resumption of weight-bearing. The fractures were distributed over the five rays; seven fractures were located to the second metatarsal. Manifestations were acute focal metatarsal pain, diffuse edema of the forefoot and inflammatory metatarsophalangeal arthropathy. Delayed, transient visualization of a linear area of epiphyseal sclerosis occurred in 14 cases. Radionuclide bone scans consistently showed early accumulation of the tracer in the metatarsal head. The focus of increased activity extended to the shaft in three cases. The main differential diagnoses are second ray syndrome, metatarsophalangeal arthritis, focal radial reflex sympathetic dystrophy of the foot and osteonecrosis of the metatarsal heads. The clinical and roentgenographic outcome was consistently favorable after one month without weight-bearing. These fractures can simulate, complicate, induce (two cases), reflex sympathetic dystrophy of the foot or occur concomitantly with (two cases).

Diffuse uniform vertebral osteosclerosis in vertebra affected by osteoporotic crush fracture, without osteonecrosis is reported. Multiple fissure-fractures were seen upon magnetic resonance imaging.

Synthetic chromogenic substrates were adapted to KEM-O-MAT 2HP for an automated monitoring of anticoagulant treatments, determination of factor X (S 2337) in oral anticoagulation, anti-Xa (Hepachrom) and anti-lla (S 2238) activities of heparin in prophylactic and curative heparin therapies. In all cases, these methods revealed high sensitivity, reproducibility, and a good correlation of their results with those of classical clotting assays. The present cost of synthetic substrates seriously limits the potential value of chromogenic assays for routine controls. However, the development of automated amidolytic techniques should provide an easier standardization in the laboratory control of anticoagulant treatments.