Biomedical subjects

Mikhail I Rabinovich

Publications and source records attributed to Mikhail I Rabinovich.

10 recordsLinked to original sources

PubMed2006

Generation and reshaping of sequences in neural systems.

The generation of informational sequences and their reorganization or reshaping is one of the most intriguing subjects for both neuroscience and the theory of autonomous intelligent systems. In spite of the diversity of sequential activities of sensory, motor, and cognitive neural systems, they have many similarities from the dynamical point of view. In this review we discus the ideas, models, and mathematical image of sequence generation and reshaping on different levels of the neural hierarchy, i.e., the role of a sensory network dynamics in the generation of a motor program (hunting swimming of marine mollusk Clione), olfactory dynamical coding, and sequential learning and decision making. Analysis of these phenomena is based on the winnerless competition principle. The considered models can be a basis for the design of biologically inspired autonomous intelligent systems.

Animals↗

PubMed2006

Dynamics of sequential decision making.

We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.

Animals↗

PubMed2006

Heteroclinic synchronization: ultrasubharmonic locking.

According to the traditional view of synchronization, a weak periodic input is able to lock a nonlinear oscillator at a frequency close to that of the input (1:1 zone). If the forcing increases, it is possible to achieve synchronization at subharmonic bands also. Using a competitive dynamical system we show the inverse phenomenon: with a weak signal the 1:1 zone is narrow, but the synchronization of ultrasubharmonics is dominant. In the system's phase space, there exists a heteroclinic contour in the autonomous regime, which is the image of sequential dynamics. Under the action of a weak periodic forcing, in the vicinity of the contour a stable limit cycle with long period appears. This results in the locking of very low-frequency oscillations with the finite frequency of the forcing. We hypothesize that this phenomenon can be the origin for the synchronization of slow and fast brain rhythms.

Animals↗

PubMed2005

Self-organization in the olfactory system: one shot odor recognition in insects.

We show in a model of spiking neurons that synaptic plasticity in the mushroom bodies in combination with the general fan-in, fan-out properties of the early processing layers of the olfactory system might be sufficient to account for its efficient recognition of odors. For a large variety of initial conditions the model system consistently finds a working solution without any fine-tuning, and is, therefore, inherently robust. We demonstrate that gain control through the known feedforward inhibition of lateral horn interneurons increases the capacity of the system but is not essential for its general function. We also predict an upper limit for the number of odor classes Drosophila can discriminate based on the number and connectivity of its olfactory neurons.

Animals↗

PubMed2005

The role of sensory network dynamics in generating a motor program.

Sensory input plays a major role in controlling motor responses during most behavioral tasks. The vestibular organs in the marine mollusk Clione, the statocysts, react to the external environment and continuously adjust the tail and wing motor neurons to keep the animal oriented vertically. However, we suggested previously that during hunting behavior, the intrinsic dynamics of the statocyst network produce a spatiotemporal pattern that may control the motor system independently of environmental cues. Once the response is triggered externally, the collective activation of the statocyst neurons produces a complex sequential signal. In the behavioral context of hunting, such network dynamics may be the main determinant of an intricate spatial behavior. Here, we show that (1) during fictive hunting, the population activity of the statocyst receptors is correlated positively with wing and tail motor output suggesting causality, (2) that fictive hunting can be evoked by electrical stimulation of the statocyst network, and (3) that removal of even a few individual statocyst receptors critically changes the fictive hunting motor pattern. These results indicate that the intrinsic dynamics of a sensory network, even without its normal cues, can organize a motor program vital for the survival of the animal.

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PubMed2005

Synchronization and coordination of sequences in two neural ensembles.

There are many types of neural networks involved in the sequential motor behavior of animals. For high species, the control and coordination of the network dynamics is a function of the higher levels of the central nervous system, in particular the cerebellum. However, in many cases, especially for invertebrates, such coordination is the result of direct synaptic connections between small circuits. We show here that even the chaotic sequential activity of small model networks can be coordinated by electrotonic synapses connecting one or several pairs of neurons that belong to two different networks. As an example, we analyzed the coordination and synchronization of the sequential activity of two statocyst model networks of the marine mollusk Clione. The statocysts are gravity sensory organs that play a key role in postural control of the animal and the generation of a complex hunting motor program. Each statocyst network was modeled by a small ensemble of neurons with Lotka-Volterra type dynamics and nonsymmetric inhibitory interactions. We studied how two such networks were synchronized by electrical coupling in the presence of an external signal which lead to winnerless competition among the neurons. We found that as a function of the number and the strength of connections between the two networks, it is possible to coordinate and synchronize the sequences that each network generates with its own chaotic dynamics. In spite of the chaoticity, the coordination of the signals is established through an activation sequence lock for those neurons that are active at a particular instant of time.

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PubMed2003

Enhancement of synchronization in a hybrid neural circuit by spike-timing dependent plasticity.

Synchronization of neural activity is fundamental for many functions of the brain. We demonstrate that spike-timing dependent plasticity (STDP) enhances synchronization (entrainment) in a hybrid circuit composed of a spike generator, a dynamic clamp emulating an excitatory plastic synapse, and a chemically isolated neuron from the Aplysia abdominal ganglion. Fixed-phase entrainment of the Aplysia neuron to the spike generator is possible for a much wider range of frequency ratios and is more precise and more robust with the plastic synapse than with a nonplastic synapse of comparable strength. Further analysis in a computational model of Hodgkin-Huxley-type neurons reveals the mechanism behind this significant enhancement in synchronization. The experimentally observed STDP plasticity curve appears to be designed to adjust synaptic strength to a value suitable for stable entrainment of the postsynaptic neuron. One functional role of STDP might therefore be to facilitate synchronization or entrainment of nonidentical neurons.

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PubMed2003

Dynamics-based sequential memory: winnerless competition of patterns.

We introduce a biologically motivated dynamical principle of sequential memory which is based on winnerless competition (WLC) of event images. This mechanism is implemented in a two-layer neural model of sequential spatial memory. We present the learning dynamics which leads to the formation of a WLC network. After learning, the system is capable of associative retrieval of prerecorded sequences of patterns.

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PubMed2002

Inhibitory synchronization of bursting in biological neurons: dependence on synaptic time constant.

Using the dynamic clamp technique, we investigated the effects of varying the time constant of mutual synaptic inhibition on the synchronization of bursting biological neurons. For this purpose, we constructed artificial half-center circuits by inserting simulated reciprocal inhibitory synapses between identified neurons of the pyloric circuit in the lobster stomatogastric ganglion. With natural synaptic interactions blocked (but modulatory inputs retained), these neurons generated independent, repetitive bursts of spikes with cycle period durations of approximately 1 s. After coupling the neurons with simulated reciprocal inhibition, we selectively varied the time constant governing the rate of synaptic activation and deactivation. At time constants 400 ms), bursts became phase-locked in a fully overlapping pattern with little or no phase lag and a shorter period. During the in-phase bursting, the higher-frequency spiking activity was not synchronized. If the circuit lacked a robust periodic burster, increasing the time constant evoked a sharp transition from out-of-phase oscillations to in-phase oscillations with associated intermittent phase-jumping. When a coupled periodic burster neuron was present (on one side of the half-center circuit), the transition was more gradual. We conclude that the magnitude and stability of phase differences between mutually inhibitory neurons varies with the ratio of burst cycle period duration to synaptic time constant and that cellular bursting (whether periodic or irregular) can adopt in-phase coordination when inhibitory synaptic currents are sufficiently slow.

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PubMedDate not supplied

Decoding temporal information through slow lateral excitation in the olfactory system of insects.

Sensory information is represented in a spatio-temporal code in the antennal lobe, the first processing stage of the olfactory system of insects. We propose a novel mechanism for decoding this information in the next processing stage, the mushroom body. The Kenyon cells in the mushroom body of insects exhibit lateral excitatory connections at their axons. We demonstrate that slow lateral excitation between Kenyon cells allows one to decode sequences of activity in the antennal lobe. We are thus able to clarify the role of the existing connections as well as to demonstrate a novel mechanism for decoding temporal information in neuronal systems. This mechanism complements the variety of existing temporal decoding schemes. It seems that neuronal systems not only have a rich variety of code types but also quite a diversity of algorithms for transforming different codes into each other.

Animals↗