Synaptic potentiation facilitates memory-like attractor dynamics in cultured in vitro hippocampal networks

Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological perturbation on in vitro networks of hippocampal neurons that has been shown to increase synaptic strength follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more "errant" spikes into bursts. Lastly, phase plots indicate a conserved activity pattern suggesting that the network is operating in a stable dynamical state

Adaptation through minimization of the phase lag in coupled nonidentical systems

We show that the internal control of adaptation can be obtained from the properties of the phase lag that results from phase synchronization of two nonidentical chaotic oscillators. The direction and magnitude of the phase lag depend upon the relative internal properties of the coupled units, and they can be used as indicators during the adjustment of dynamics, i.e., adaptation of the target unit to match that of the control. The properties of the phase lag are obtained using a method based on the estimation of properties of the distributions of relative event times of both (target and control) units. The phase lag dependent mechanism to control the adaptation process was applied to a system of nonidentical Rössler oscillators and a system of nonidentical Lorenz oscillators. We also elucidate its importance as a control mechanism of the changes of neuronal activity showing its application to neural adaptation. © 2004 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70311/2/CHAOEH-14-3-583-1.pd

Conditional entropies, phase synchronization and changes in the directionality of information flow in neural systems

We devised a novel measure that dynamically evaluates temporal interdependences between two coupled units based on the properties of the distributions of their relative interevent intervals. We investigate its properties on the system of two coupled non-identical Rössler oscillators and a system of non-identical Hindmarsh–Rose models of thalamocortical neurons and show that the measure highlights the properties of phase synchronization observed in those two systems. We postulate that the observed properties of the phase lag, in conjunction with the experimentally observed activity-dependent synaptic modification in the neural systems, may drive the changes of the direction of information flow in a neural network, and thus the measure can play an important role in assessing those changes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48841/2/a4_12_007.pd

Adaptation of nonlinear systems through dynamic entropy estimation

We show that adaptation and control of the target system can be achieved by linking the modification of its dynamical properties to the estimated difference of the distribution of the dynamical characteristics of the control and target signals. Subsequently the target system, which has initially different dynamical properties adjusts its dynamics via changes of its control parameters and synchronizes with the control one. The differences in the evolving probability distributions are evaluated through entropy estimation, causing the adaptation to be based solely on the statistical properties of the control and target signals without explicit knowledge of the underlying equations of the system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48843/2/a4_6_018.pd

EphA4 expression promotes network activity and spine maturation in cortical neuronal cultures

<p>Abstract</p> <p>Background</p> <p>Neurons form specific connections with targets via synapses and patterns of synaptic connectivity dictate neural function. During development, intrinsic neuronal specification and environmental factors guide both initial formation of synapses and strength of resulting connections. Once synapses form, non-evoked, spontaneous activity serves to modulate connections, strengthening some and eliminating others. Molecules that mediate intercellular communication are particularly important in synaptic refinement. Here, we characterize the influences of EphA4, a transmembrane signaling molecule, on neural connectivity.</p> <p>Results</p> <p>Using multi-electrode array analysis on <it>in vitro </it>cultures, we confirmed that cortical neurons mature and generate spontaneous circuit activity as cells differentiate, with activity growing both stronger and more patterned over time. When EphA4 was over-expressed in a subset of neurons in these cultures, network activity was enhanced: bursts were longer and were composed of more spikes than in control-transfected cultures. To characterize the cellular basis of this effect, dendritic spines, the major excitatory input site on neurons, were examined on transfected neurons <it>in vitro</it>. Strikingly, while spine number and density were similar between conditions, cortical neurons with elevated levels of EphA4 had significantly more mature spines, fewer immature spines, and elevated colocalization with a mature synaptic marker.</p> <p>Conclusions</p> <p>These results demonstrate that experimental elevation of EphA4 promotes network activity <it>in vitro</it>, supporting spine maturation, producing more functional synaptic pairings, and promoting more active circuitry.</p

Measuring asymmetric temporal interdependencies in simulated and biological networks

We use a newly developed metric to characterize asymmetric temporal interdependencies in networks of coupled dynamical elements. We studied the formation of temporal ordering in a system of coupled Rössler oscillators for different connectivity ratios and network topologies and also applied the metric to investigate the functional structure of a biological network (cerebral ganglia of Helix snail). In the former example we show how the local ordering evolves to the global one as a function of structural parameters of the network, while in the latter we show spontaneous emergence of functional interdependence between two groups of electrodes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87883/2/043121_1.pd

Functional clustering in hippocampal cultures: relating network structure and dynamics

In this work we investigate the relationship between gross anatomic structural network properties, neuronal dynamics and the resultant functional structure in dissociated rat hippocampal cultures. Specifically, we studied cultures as they developed under two conditions: the first supporting glial cell growth (high glial group), and the second one inhibiting it (low glial group). We then compared structural network properties and the spatio-temporal activity patterns of the neurons. Differences in dynamics between the two groups could be linked to the impact of the glial network on the neuronal network as the cultures developed. We also implemented a recently developed algorithm called the functional clustering algorithm (FCA) to obtain the resulting functional network structure. We show that this new algorithm is useful for capturing changes in functional network structure as the networks evolve over time. The FCA detects changes in functional structure that are consistent with expected dynamical differences due to the impact of the glial network. Cultures in the high glial group show an increase in global synchronization as the cultures age, while those in the low glial group remain locally synchronized. We additionally use the FCA to quantify the amount of synchronization present in the cultures and show that the total level of synchronization in the high glial group is stronger than in the low glial group. These results indicate an interdependence between the glial and neuronal networks present in dissociated cultures.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85417/1/ph10_4_046004.pd