Theta-mediated dynamics of spatial information in hippocampus.

In rodent hippocampus, neuronal activity is organized by a 6-10 Hz theta oscillation. The spike timing of hippocampal pyramidal cells with respect to the theta rhythm correlates with an animal's position in space. This correlation has been suggested to indicate an explicit temporal code for position. Alternatively, it may be interpreted as a byproduct of theta-dependent dynamics of spatial information flow in hippocampus. Here we show that place cell activity on different phases of theta reflects positions shifted into the future or past along the animal's trajectory in a two-dimensional environment. The phases encoding future and past positions are consistent across recorded CA1 place cells, indicating a coherent representation at the network level. Consistent theta-dependent time offsets are not simply a consequence of phase-position correlation (phase precession), because they are no longer seen after data randomization that preserves the phase-position relationship. The scale of these time offsets, 100-300 ms, is similar to the latencies of hippocampal activity after sensory input and before motor output, suggesting that offset activity may maintain coherent brain activity in the face of information processing delays

Experience in Building Infectious Hospital for Treatment of Particularly Dangerous Infectious Diseases in the Republic of Guinea

Ebola treatment hospital was constructed within the frames of the West Africa support infinitive of the Russian Federation, in cooperation with the United Company “RUSAL”. Permanent building with bed capacity rated 60 and strict separation of clean area from hazard zone set this medical facility apart from tent camps, which are used by international organizations. For the first time ever, in West Africa, deployed was a strategy of waste decontamination using caustic. It is of note that due to biological safety procedure compliance, no case of nosocomial infection was registered during the whole time of operation. Commissioning of this hospital is an effective mechanism for Ebola virus disease control

Epidemiological Peculiarities and Clinical Features of Ebola Virus Disease in the Republic of Guinea

The current outbreak of the Ebola fever in West Africa is unprecedented in terms of its scale. As of today, 27550 suspected cases and 11235 deaths have been reported. The outbreak differs from previous epidemics in terms of epidemiological and clinical progression of the disease. The article covers several epidemiological issues related to Ebola virus disease by the example of the Guinean outbreak, which has been plaguing the country since 2014. Given is the preliminary clinical analysis of the medical observations, performed in the Research and Diagnostic Centre of Epidemiology and Microbiology built by RUSAL. Regarded are epidemiological and clinical features of the Ebola virus disease (EVD) in 83 patients, who were admitted to RUSAL Treatment Center since March 6th till June 30th, 2015. In 28 of the patients, EVD diagnosis was laboratory confirmed. The principle assessment criteria are: morbidity rate, lethality index, gender, age, occupation, time since the onset of the disease until hospitalization, an average duration of the stay at the hospital, complaints, symptoms, complications, and the therapy provided

Learning to Learn: Theta Oscillations Predict New Learning, which Enhances Related Learning and Neurogenesis

Animals in the natural world continuously encounter learning experiences of varying degrees of novelty. New neurons in the hippocampus are especially responsive to learning associations between novel events and more cells survive if a novel and challenging task is learned. One might wonder whether new neurons would be rescued from death upon each new learning experience or whether there is an internal control system that limits the number of cells that are retained as a function of learning. In this experiment, it was hypothesized that learning a task that was similar in content to one already learned previously would not increase cell survival. We further hypothesized that in situations in which the cells are rescued hippocampal theta oscillations (3–12 Hz) would be involved and perhaps necessary for increasing cell survival. Both hypotheses were disproved. Adult male Sprague-Dawley rats were trained on two similar hippocampus-dependent tasks, trace and very-long delay eyeblink conditioning, while recording hippocampal local-field potentials. Cells that were generated after training on the first task were labeled with bromodeoxyuridine and quantified after training on both tasks had ceased. Spontaneous theta activity predicted performance on the first task and the conditioned stimulus induced a theta-band response early in learning the first task. As expected, performance on the first task correlated with performance on the second task. However, theta activity did not increase during training on the second task, even though more cells were present in animals that had learned. Therefore, as long as learning occurs, relatively small changes in the environment are sufficient to increase the number of surviving neurons in the adult hippocampus and they can do so in the absence of an increase in theta activity. In conclusion, these data argue against an upper limit on the number of neurons that can be rescued from death by learning

Energy efficient sparse connectivity from imbalanced synaptic plasticity rules

It is believed that energy efficiency is an important constraint in brain evolution. As synaptic transmission dominates energy consumption, energy can be saved by ensuring that only a few synapses are active. It is therefore likely that the formation of sparse codes and sparse connectivity are fundamental objectives of synaptic plasticity. In this work we study how sparse connectivity can result from a synaptic learning rule of excitatory synapses. Information is maximised when potentiation and depression are balanced according to the mean presynaptic activity level and the resulting fraction of zero-weight synapses is around 50%. However, an imbalance towards depression increases the fraction of zero-weight synapses without significantly affecting performance. We show that imbalanced plasticity corresponds to imposing a regularising constraint on the L1-norm of the synaptic weight vector, a procedure that is well-known to induce sparseness. Imbalanced plasticity is biophysically plausible and leads to more efficient synaptic configurations than a previously suggested approach that prunes synapses after learning. Our framework gives a novel interpretation to the high fraction of silent synapses found in brain regions like the cerebellum

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison

Coherent transform, quantization, and Poisson geometry

This volume contains three extensive articles written by Karasev and his pupils. Topics covered include the following: coherent states and irreducible representations for algebras with non-Lie permutation relations, Hamilton dynamics and quantization over stable isotropic submanifolds, and infinitesimal tensor complexes over degenerate symplectic leaves in Poisson manifolds. The articles contain many examples (including from physics) and complete proofs

Creation and Support of Operation of a Hospital Net to Treat COVID-19 Patients in Guinea

The paper provides information on the construction, development and functioning of a hospital network for the detection and treatment of patients with dangerous infectious diseases in the Republic of Guinea. With the support of UC RUSAL and with the assistance of the Ministry of Health of Guinea, hospitals have been established to provide medical care to patients suspected of COVID-19. Sick persons are admitted from regional hospitals from all over country. The majority of the hospitalized persons are patients with mild and moderate forms of the disease. Diagnostic studies using RT-PCR to detect SARS-CoV-2 virus RNA are carried out at the premises of stationary (Kindia) and mobile (Fria) laboratories. Testing of the received samples is carried out using diagnostic preparations of domestic and foreign production. This stage of work is performed by employees of the Rospotrebnadzor institutions (the Russian Federation) working on the territory of the Republic of Guinea. In total, since the beginning of the epidemic, more than 630 patients have received treatment in the stated hospitals; more than 20 thousand tests of clinical material samples have been conducted to detect the RNA of the SARS-CoV-2 virus. In addition to residents of Guinea, medical assistance was provided to citizens of Russia, Ukraine, Belarus, Kazakhstan, China, India, Sierra Leone, and the Comoros. The organization of the network of hospitals and their inclusion into the national system for counteracting the spread of new coronavirus infection allowed us to begin active work on the identifcation and treatment of COVID-19 patients in the territory of the Republic of Guinea and make a signifcant contribution to the fght against the epidemic

Active Ultra Wideband Wireless Networks Usage for Modelling Ensembles of Nonlinear Continuous Time Dynamical Systems

The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. In the modelling process each dynamical system is associated with a node of the active network. A computing device (microcontroller) placed on this node integrates equations of the dynamical system. Interaction between the dynamical systems is achieved by means of transmitting information on the state of the system via radio channels between active network nodes. The platform capabilities are demonstrated on example of an ensemble of Kuramoto oscillators. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed