The computational power of astrocyte mediated synaptic plasticity

Modeling the formation process of grouping stimuli sets through cortical columns and microcircuits to feature neurons

A computational model of a self-structuring neuronal net is presented in which repetitively applied pattern sets induce the formation of cortical columns and microcircuits which decode distinct patterns after a learning phase. In a case study, it is demonstrated how specific neurons in a feature classifier layer become orientation selective if they receive bar patterns of different slopes from an input layer. The input layer is mapped and intertwined by self-evolving neuronal microcircuits to the feature classifier layer. In this topical overview, several models are discussed which indicate that the net formation converges in its functionality to a mathematical transform which maps the input pattern space to a feature representing output space. The self-learning of the mathematical transform is discussed and its implications are interpreted. Model assumptions are deduced which serve as a guide to apply model derived repetitive stimuli pattern sets to in vitro cultures of neuron ensembles to condition them to learn and execute a mathematical transform.

Mechanisms of heterosynaptic metaplasticity

Synaptic plasticity is fundamental to the neural processes underlying learning and memory. Interestingly, synaptic plasticity itself can be dynamically regulated by prior activity, in a process termed 'metaplasticity', which can be expressed both homosynaptically and heterosynaptically. Here, we focus on heterosynaptic metaplasticity, particularly long-range interactions between synapses spread across dendritic compartments, and review evidence for intracellular versus intercellular signalling pathways leading to this effect. Of particular interest is our previously reported finding that priming stimulation in stratum oriens of area CA1 in the hippocampal slice heterosynaptically inhibits subsequent long-term potentiation and facilitates long-term depression in stratum radiatum. As we have excluded the most likely intracellular signalling pathways that might mediate this long-range heterosynaptic effect, we consider the hypothesis that intercellular communication may be critically involved. This hypothesis is supported by the finding that extracellular ATP hydrolysis, and activation of adenosine A2 receptors are required to induce the metaplastic state. Moreover, delivery of the priming stimulation in stratum oriens elicited astrocytic calcium responses in stratum radiatum. Both the astrocytic responses and the metaplasticity were blocked by gap junction inhibitors. Taken together, these findings support a novel intercellular communication system, possibly involving astrocytes, being required for this type of heterosynaptic metaplasticity.

Synaptic behavior and STDP of asymmetric nanoscale memristors in biohybrid systems

We fabricate and characterize asymmetric memristors which show a very strong single-sided hysteresis. When biased in one direction there is hysteresis and in the opposite direction there is a lack of hysteresis. We demonstrate that this apparent lack is actually hysteresis on a much faster time-scale. We further demonstrate that this form of asymmetric behavior correlates very well to the asymmetric structure and function of an actual synapse. The asymmetric memristor device presented here is necessary to correctly implement spike-timing-dependent-plasticity STDP in mixed memristor/neuron hybrid systems as an artificial synapse. These devices show the required characteristics for implementing the asymmetric form of long-term potentiation (LTP) and long-term depression (LTD) of a synapse between two neurons, where symmetric memristor devices do not. Signals from a presynaptic neuron are sent via its axon across the synapse to the dendrite of a postsynaptic neuron. Postsynaptic neuron signals sent to subsequent neurons have an influence on the strength of any further presynaptic neuron signals received by the postsynaptic neuron across the synapse. These signals are grouped into spike triplets within the framework of STDP and, as we experimentally show here, can be implemented with asymmetric memristors, not standard symmetric memristors.

A phase plane analysis of neuron-astrocyte interactions

Intensive experimental studies have shown that astrocytes are active partners in modulation of synaptic transmission. In the present research, we study neuron-astrocyte signaling using a biologically inspired model of one neuron synapsing one astrocyte. In this model, the firing dynamics of the neuron is described by the Morris-Lecar model and the Ca(2+) dynamics of a single astrocyte explained by a functional model introduced by Postnov and colleagues. Using the coupled neuron-astrocyte model and based on the results of the phase plane analyses, it is demonstrated that the astrocyte is able to activate the silent neuron or change the neuron spiking frequency through bidirectional communication. This suggests that astrocyte feedback signaling is capable of modulating spike transmission frequency by changing neuron spiking frequency. This effect is described by a saddle-node on invariant circle bifurcation in the coupled neuron-astrocyte model. In this way, our results suggest that the neuron-astrocyte crosstalk has a fundamental role in producing diverse neuronal activities and therefore enhances the information processing capabilities of the brain.

A behavioral neuroenergetics theory of ADHD

Energetic insufficiency in neurons due to inadequate lactate supply is implicated in several neuropathologies, including attention-deficit/hyperactivity disorder (ADHD). By formalizing the mechanism and implications of such constraints on function, the behavioral Neuroenergetics Theory (NeT) predicts the results of many neuropsychological tasks involving individuals with ADHD and kindred dysfunctions, and entails many novel predictions. The associated diffusion model predicts that response times will follow a mixture of Wald distributions from the attentive state, and ex-Wald distributions after attentional lapses. It is inferred from the model that ADHD participants can bring only 75-85% of the neurocognitive energy to bear on tasks, and allocate only about 85% of the cognitive resources of comparison groups. Parameters derived from the model in specific tasks predict performance in other tasks, and in clinical conditions often associated with ADHD. The primary action of therapeutic stimulants is to increase norepinephrine in active regions of the brain. This activates glial adrenoceptors, increasing the release of lactate from astrocytes to fuel depleted neurons. The theory is aligned with other approaches and integrated with more general theories of ADHD. Therapeutic implications are explored.