Publications by authors named "Eleftheria K Pissadaki"

This review addresses the present state of single-cell models of the firing pattern of midbrain dopamine neurons and the insights that can be gained from these models into the underlying mechanisms for diseases such as Parkinson's, addiction, and schizophrenia. We will explain the analytical technique of separation of time scales and show how it can produce insights into mechanisms using simplified single-compartment models. We also use morphologically realistic multicompartmental models to address spatially heterogeneous aspects of neural signaling and neural metabolism.

View Article and Find Full Text PDF

Hippocampal CA3 area generates temporally structured network activity such as sharp waves and gamma and theta oscillations. Parvalbumin-expressing basket cells, making GABAergic synapses onto cell bodies and proximal dendrites of pyramidal cells, control pyramidal cell activity and participate in network oscillations in slice preparations, but their roles in vivo remain to be tested. We have recorded the spike timing of parvalbumin-expressing basket cells in areas CA2/3 of anesthetized rats in relation to CA3 putative pyramidal cell firing and activity locally and in area CA1.

View Article and Find Full Text PDF

Dopamine neurons of the substantia nigra pars compacta (SNc) are uniquely sensitive to degeneration in Parkinson's disease (PD) and its models. Although a variety of molecular characteristics have been proposed to underlie this sensitivity, one possible contributory factor is their massive, unmyelinated axonal arbor that is orders of magnitude larger than other neuronal types. We suggest that this puts them under such a high energy demand that any stressor that perturbs energy production leads to energy demand exceeding supply and subsequent cell death.

View Article and Find Full Text PDF

Although genes, protein aggregates, environmental toxins, and other factors associated with Parkinson's disease (PD) are widely distributed in the nervous system and affect many classes of neurons, a consistent feature of PD is the exceptional and selective vulnerability of dopamine (DA) neurons of the SNc. What is it about these neurons, among all other neurons in the brain, that makes them so susceptible in PD? We hypothesize that a major contributory factor is the unique cellular architecture of SNc DA neuron axons. Their large, complex axonal arbour puts them under such a tight energy budget that it makes them particularly susceptible to factors that contribute to cell death, including unique molecular characteristics associated with SNc DA neurons and nonspecific, nervous-system-wide factors.

View Article and Find Full Text PDF

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing.

View Article and Find Full Text PDF

For many decades, neurons were considered to be the elementary computational units of the brain and were assumed to summate incoming signals and elicit action potentials only in response to suprathreshold stimuli. Although modelling studies predicted that single neurons constitute a much more powerful computational entity, able to perform an array of nonlinear calculations, this possibility was not explored experimentally until the discovery of active mechanisms in the dendrites of most neuron types. Here, we review several modelling studies that have addressed information processing in single neurons, starting with those characterizing the arithmetic of different dendritic components, to those tackling neuronal integration at the cell body and, finally, those analysing the computational abilities of the axon.

View Article and Find Full Text PDF