Rosangela Follmann

• Ph.D in Applied Computing
• Illinois State University

We present a computational model of networked neurons developed to study the effect of temperature on neuronal synchronization in the brain in association with seizures. The network consists of a set of chaotic bursting neurons surrounding a core tonic neuron in a square lattice with periodic boundary conditions. Each neuron is reciprocally coupled...

In this work, we study the interplay between chaos and noise in neuronal state transitions involving period doubling cascades. Our approach involves the implementation of a neuronal mathematical model under the action of neuromodulatory input, with and without noise, as well as equivalent experimental work on a biological neuron in the stomatogastr...

The dynamical mechanisms underlying thermoreception in the nematode C. elegans are studied with a mathematical model for the amphid finger-like ciliated (AFD) neurons. The equations, equipped with Arrhenius temperature factors, account for the worm’s thermotaxis when seeking environments at its cultivation temperature, and for the AFD’s calcium dyn...

The coronavirus disease (COVID-19) continues to have devastating effects across the globe. No nation has been free from the uncertainty brought by this pandemic. The health, social and economic tolls associated with it are causing strong emotions and spreading fear in people of all ages, genders and races. Since the beginning of the COVID-19 pandem...

We construct an electronic circuit for mimicking a single neuron's behavior in connection with the dynamics of the Hodgkin–Huxley mathematical model. Our results show that the electronic neuron, even though it contains binary-state circuitry components, displays a timing interplay between the ion channels, which is consistent with the corresponding...

In this work, we employ reservoir computing, a recently developed machine learning technique, to predict the time evolution of neuronal activity produced by the Hindmarsh-Rose neuronal model. Our results show accurate short- and long-term predictions for periodic (tonic and bursting) neuronal behaviors, but only short-term accurate predictions for...

A ubiquitous feature of the nervous system is the processing of simultaneously arriving sensory inputs from different modalities. Yet, because of the difficulties of monitoring large populations of neurons with the single resolution required to determine their sensory responses, the cellular mechanisms of how populations of neurons encode different...

We study a heterogeneous neuronal network motif where a central node (hub neuron) is connected via electrical synapses to other nodes (peripheral neurons). Our numerical simulations show that the networked neurons synchronize in three different states: (i) robust tonic, (ii) robust bursting, and (iii) tonic initially evolving to bursting through a...

Phase synchronization may emerge from mutually interacting non-linear oscillators, even under weak coupling, when phase differences are bounded, while amplitudes remain uncorrelated. However, the detection of this phenomenon can be a challenging problem to tackle. In this work, we apply the Discrete Complex Wavelet Approach (DCWA) for phase assignm...

A transition between tonic and bursting neuronal behaviors is studied using a linear chain of three electrically coupled model neurons. Numerical simulations show that, depending on their individual dynamical states, the neurons first synchronize either in a tonic or in a bursting regime. Additionally, a characteristic firing rate, mediating tonic-...

Projection neurons play a key role in carrying long-distance information between spatially distant areas of the nervous system and in controlling motor circuits. Little is known about how projection neurons with distinct anatomical targets are organized, and few studies have addressed their spatial organization at the level of individual cells. In...

Here we investigate transitions occurring in the dynamical states of pairs of distinct neurons electrically coupled, with one neuron tonic and the other bursting. Depending on the dynamics of the individual neurons, and for strong enough coupling, they synchronize either in a tonic or a bursting regime, or initially tonic transitioning to bursting...

Most motor systems can generate a variety of behaviors, including categorically different behaviors and variants of a single motor act within the same behavioral category. In many cases this multifunctionality results from dynamic adaptations of existing, highly interconnected neural circuits. This temporary restructuring of the motor circuits is c...

Long-range communication in the nervous system is usually carried out with the propagation of action potentials along the axon of nerve cells. While typically thought of as being unidirectional, it is not uncommon for axonal propagation of action potentials to happen in both directions. This is the case because action potentials can be initiated at...

In this work we present and discuss a method for measuring the phase of chaotic systems. This method has as input a scalar time series and operates by estimating a fundamental frequency for short segments, or windows, along the whole extension of the signal. It minimizes the mean square error of fitting a sinusoidal function to the series segment....

We explore a properly interconnected set of Kuramoto type oscillators that results in a new associative-memory network configuration, which includes second- and third-order additional terms in the Fourier expansion of the network's coupling. Investigation of the response of the network to different external stimuli indicates an increase in the netw...

This work discusses the applicability of a method for phase determination of scalar time series from nonlinear systems. We apply the method to detect phase synchronization in different scenarios, and use the phase diffusion coefficient, the Lyapunov spectrum, and the similarity function to characterize synchronization transition in nonidentical cou...

A technique, first introduced in the context of pseudoperiodic sound waves, is here applied to the problem of detecting the phase of phase coherent and also phase noncoherent chaotic oscillators. The approach is based on finding sinusoidal fits to segments of the signal, therefore obtaining, for each segment, an appropriate frequency from which a p...

Pages: 2146-2153