Rhonda Dzakpasu

MMPs and soluble ICAM-5 increase neuronal excitability within in vitro networks of hippocampal neurons.

Matrix metalloproteinases (MMPs) are zinc-dependent endopeptidases that are released from neurons in an activity dependent manner. Published studies suggest their activity is important to varied forms of learning and memory. At least one MMP can stimulate an increase in the size of dendritic spines, structures which represent the post synaptic component for a large number of glutamatergic synapses. This change may be associated with increased synaptic glutamate receptor incorporation, and an increased amplitude and/or frequency of α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate (AMPA) mini excitatory post-synaptic currents (EPSCs). An associated increase in the probability of action potential occurrence would be expected. While the mechanism(s) by which MMPs may influence synaptic structure and function are not completely understood, MMP dependent shedding of specific cell adhesion molecules (CAMs) could play an important role. CAMs are ideally positioned to be cleaved by synaptically released MMPs, and shed N terminal domains could potentially interact with previously unengaged integrins to stimulate dendritic actin polymerization with spine expansion. In the present study, we have used multielectrode arrays (MEAs) to investigate MMP and soluble CAM dependent changes in neuronal activity recorded from hippocampal cultures. We have focused on intercellular adhesion molecule-5 (ICAM-5) in particular, as this CAM is expressed on glutamatergic dendrites and shed in an MMP dependent manner. We show that chemical long-term potentiation (cLTP) evoked changes in recorded activity, and the dynamics of action potential bursts in particular, are altered by MMP inhibition. A blocking antibody to β1 integrins has a similar effect. We also show that the ectodomain of ICAM-5 can stimulate β1 integrin dependent increases in spike counts and burst number. These results support a growing body of literature suggesting that MMPs have important effects on neuronal excitability. They also support the possibility that MMP dependent shedding of specific synaptic CAMs can contribute to these effects.

Cellular Mechanisms of Desynchronizing Effects of Hypothermia in an In Vitro Epilepsy Model

Hypothermia can terminate epileptiform discharges in vitro and in vivo epilepsy models. Hypothermia is becoming a standard treatment for brain injury in infants with perinatal hypoxic ischemic encephalopathy, and it is gaining ground as a potential treatment in patients with drug resistant epilepsy. However, the exact mechanism of action of cooling the brain tissue is unclear. We have studied the 4-aminopyridine model of epilepsy in mice using single- and dual-patch clamp and perforated multi-electrode array recordings from the hippocampus and cortex. Cooling consistently terminated 4-aminopyridine induced epileptiform-like discharges in hippocampal neurons and increased input resistance that was not mimicked by transient receptor potential channel antagonists. Dual-patch clamp recordings showed significant synchrony between distant CA1 and CA3 pyramidal neurons, but less so between the pyramidal neurons and interneurons. In CA1 and CA3 neurons, hypothermia blocked rhythmic action potential discharges and disrupted their synchrony; however, in interneurons, hypothermia blocked rhythmic discharges without abolishing action potentials. In parallel, multi-electrode array recordings showed that synchronized discharges were disrupted by hypothermia, whereas multi-unit activity was unaffected. The differential effect of cooling on transmitting or secreting γ-aminobutyric acid interneurons might disrupt normal network synchrony, aborting the epileptiform discharges. Moreover, the persistence of action potential firing in interneurons would have additional antiepileptic effects through tonic γ-aminobutyric acid release.

Hippocampal neuron firing and local field potentials in the in vitro 4-aminopyridine epilepsy model.

Excessive synchronous neuronal activity is a defining feature of epileptic activity. We previously characterized the properties of distinct glutamatergic and GABAergic transmission-dependent synchronous epileptiform discharges in mouse hippocampal slices using the 4-aminopyridine model of epilepsy. In the present study, we sought to identify the specific hippocampal neuronal populations that initiate and underlie these local field potentials (LFPs). A perforated multielectrode array was used to simultaneously record multiunit action potential firing and LFPs during spontaneous epileptiform activity. LFPs had distinct components based on the initiation site, extent of propagation, and pharmacological sensitivity. Individual units, located in different hippocampal subregions, fired action potentials during these LFPs. A specific neuron subgroup generated sustained action potential firing throughout the various components of the LFPs. The activity of this subgroup preceded the LFPs observed in the presence of antagonists of ionotropic glutamatergic synaptic transmission. In the absence of ionotropic glutamatergic and GABAergic transmission, LFPs disappeared, but units with shorter spike duration and high basal firing rates were still active. These spontaneously active units had an increased level of activity during LFPs and consistently preceded all LFPs recorded before blockade of synaptic transmission. Our findings reveal that neuronal subpopulations with interneuron properties are likely responsible for initiating synchronous activity in an in vitro model of epileptiform discharges.

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

BackgroundNeurons 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.ResultsUsing multi-electrode array analysis on in vitro 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 in vitro. 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.ConclusionsThese results demonstrate that experimental elevation of EphA4 promotes network activity in vitro, supporting spine maturation, producing more functional synaptic pairings, and promoting more active circuitry.

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 computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, 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 treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons 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. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network.

Long-Term Dynamical Constraints on Pharmacologically Evoked Potentiation Imply Activity Conservation within In Vitro Hippocampal Networks

This paper describes a long-term study of network dynamics from in vitro, cultured hippocampal neurons after a pharmacological induction of synaptic potentiation. We plate a suspension of hippocampal neurons on an array of extracellular electrodes and record electrical activity in the absence of the drugs several days after treatment. While previous studies have reported on potentiation lasting up to a few hours after treatment, to the best of our knowledge, this is the first report to characterize the network effects of a potentiating mechanism several days after treatment. Using this reduced, two-dimensional in vitro network of hippocampal neurons, we show that the effects of potentiation are persistent over time but are modulated under a conservation of spike principle. We suggest that this conservation principle might be mediated by the appearance of a resonant inter-spike interval that prevents the network from advancing towards a state of hyperexcitability.

Dopamine-dependent effects on basal and glutamate stimulated network dynamics in cultured hippocampal neurons

Oscillatory activity occurs in cortical and hippocampal networks with specific frequency ranges thought to be critical to working memory, attention, differentiation of neuronal precursors, and memory trace replay. Synchronized activity within relatively large neuronal populations is influenced by firing and bursting frequency within individual cells, and the latter is modulated by changes in intrinsic membrane excitability and synaptic transmission. Published work suggests that dopamine, a potent modulator of learning and memory, acts on dopamine receptor 1‐like dopamine receptors to influence the phosphorylation and trafficking of glutamate receptor subunits, along with long‐term potentiation of excitatory synaptic transmission in striatum and prefrontal cortex. Prior studies also suggest that dopamine can influence voltage gated ion channel function and membrane excitability in these regions. Fewer studies have examined dopamines effect on related endpoints in hippocampus, or potential consequences in terms of network burst dynamics. In this study, we record action potential activity using a microelectrode array system to examine the ability of dopamine to modulate baseline and glutamate‐stimulated bursting activity in an in vitro network of cultured murine hippocampal neurons. We show that dopamine stimulates a dopamine type‐1 receptor‐dependent increase in number of overall bursts within minutes of its application. Notably, however, at the concentration used herein, dopamine did not increase the overall synchrony of bursts between electrodes. Although the number of bursts normalizes by 40 min, bursting in response to a subsequent glutamate challenge is enhanced by dopamine pretreatment. Dopamine‐dependent potentiation of glutamate‐stimulated bursting was not observed when the two modulators were administered concurrently. In parallel, pretreatment of murine hippocampal cultures with dopamine stimulated lasting increases in the phosphorylation of the glutamate receptor subunit GluA1 at serine 845. This effect is consistent with the possibility that enhanced membrane insertion of GluAs may contribute to a more slowly evolving dopamine‐dependent potentiation of glutamate‐stimulated bursting. Together, these results are consistent with the possibility that dopamine can influence hippocampal bursting by at least two temporally distinct mechanisms, contributing to an emerging appreciation of dopamine‐dependent effects on network activity in the hippocampus.

Functional Reconstruction of Dyadic and Triadic Subgraphs in Spiking Neural Networks

Neural networks reconstructed from measurement data are known to exhibit various forms of nonrandom structures, including subgraph motifs and smallworldedness. It has been suggested such nonrandom structures are critical for neural information-processing; however, it is unclear how the topological structure of anatomical networks influences the reconstruction of functional networks. To better understand the importance of such nonrandom structures, we study how dyadic and triadic subgraphs are preserved during the reconstruction. We use a model-free information-theoretic measure, transfer entropy, to quantify the directional associations of pairwise neuronal activity. We employ multiplex networks to compare how dyadic and triadic subgraphs differ from structural to functional networks, with particular attention to recurrent connections. We find that certain structural subgraphs have more influence on the topology of the functional network than others.

Graph theoretical comparison of functional connectivity between cLTP treated and untreated microelectrode arrays

Analyzing graph properties of neural networks has recently gained much attention in attempts to understand how information is processed in the brain. Using in-vitro techniques to form neural networks has increased in popularity as it allows one to develop small, easy to record networks that maintain many of the graph properties of larger brain networks [1]. One widely recognized tool for studying in vitro networks is the Microelectrode Array (MEAs) on which neurons can be cultured and recorded simultaneously. MEAs can be used to grow neural networks from disassociated cells to understand how neurons spontaneously connect to create networks and how these networks then evolve over time. In addition, these cultures can be treated with pharmacological agents to study how these agents affect the networks as a whole [2,3]. To understand the network formation of MEA cultured neurons, we study the graph theoretical properties of two MEAs networks, the control MEA network and the MEA network treated with chemical Long Term Potentiation (cLTP). The data sets for each MEA network consists of recording from three days: baseline, 2 days past baseline and 5 days past baseline. Based on these data sets and the assumption that each electrode on the MEA records one neuron, we construct functional connectivity graphs of MEA networks for different days. Nodes in such a connectivity graph represent the electrodes (also neurons). To determine whether there is a connection (an edge on the graph) between two nodes, we carry out several steps of computations. We first filter the recorded spike trains with a Gaussian kernel, and perform cross-correlation analysis using the Pearson product moment correlation coefficient [4]. We set a correlation threshold by applying a shuffling method to the inter-spike intervals of a spike train. Using thresholded correlations, unweighted, undirected adjacency matrices, we create corresponding graphs for untreated (not shown) and treated MEA networks (shown baseline and 5 days past baseline in Figure 1). We find that the synchronization and average node degree increase dramatically for the cLTP treated networks while the untreated network shows no obvious change. Figure 1 Graph models. (a) cLTP treated MEA network at baseline; (b) cLTP treated MEA network at 5 days past baseline. To better understand the treated and untreated MEA network, we will evaluate the graph theoretic properties, such as degree distribution and clustering coefficient. We will determine how cLTP affects these properties. The graphical analysis will enable us to identify what type of network each is (such as a small-world or a scale free network) and determine whether cLTP has an effect on the network development or merely on the strength of connectivity. We conjecture that cLTP treated networks have more efficient and quicker communication between nodes. Therefore, the cLTP treated networks show greater clustering as well as shorter path length than the untreated networks. Information flow is another important aspect of such graph model. We intend to develop directed graphs using transfer entropy to study how information flow of the network may change during its development.