A proteome is defined as a comprehensive protein set either of an organ or an organism at a given time and under specific physiological conditions. Accordingly, the study of the nervous system's proteomes is called neuroproteomics. In the neuroproteomics process, various pieces of the nervous system are "fragmented" to understand the dynamics of each given sub-proteome in a much better way. Functional proteomics addresses the organisation of proteins into complexes and the formation of organelles from these multiprotein complexes that control various physiological processes. Current functional studies of neuroproteomics mainly talk about the synapse structure and its organisation, the major building site of the neuronal communication channel. The proteomes of synaptic vesicle, presynaptic terminal, and postsynaptic density, have been examined by various proteomics techniques. The objectives of functional neuroproteomics are: to solve the proteome of single neurons or astrocytes grown in cell cultures or from the primary brain cells isolated from tissues under various conditions, to identify the set of proteins that characterize specific pathogenesis, or to determine the group of proteins making up postsynaptic or presynaptic densities. It is usual to solve a particular sub-proteome like the heat-shock response proteome or the proteome responding to inflammation. Post-translational protein modifications alter their functions and interactions. The techniques to detect synapse phosphoproteome are available. However, techniques for the analysis of ubiquitination and sumoylation are under development.
In earlier models, synaptic plasticity forms the basis for cellular signaling underlying learning and memory. However, synaptic computation of learning and memory in the brain remains controversial. In this paper, we discuss ways in which synaptic plasticity remodels subcellular networks by deflecting trajectories in neuronal state-space as regulating patterns for the synthesis of dynamic continuity that form cognitive networks of associable representations through endogenous dendritic coding to consolidate memory.
Ultra-slow cortical oscillatory activity of 1-100 mHz has been recorded in human by electroencephalography and in dissociated cultures of cortical rat neurons, but the underlying mechanisms remain to be elucidated. This study presents a computational model of ultra-slow oscillatory activity based on the interaction between neurons and astrocytes. We predict that the frequency of these oscillations closely depends on activation of astrocytes in the network, which is reflected by oscillations of their intracellular calcium concentrations with periods between tens of seconds and minutes. An increase of intracellular calcium in astrocytes triggers the release of adenosine triphosphate from these cells which may alter transmission at nearby synapses by increasing or decreasing neurotransmitter release. These results provide theoretical support for the emerging awareness of astrocytes as active players in the regulation of neural activity and identify neuron-astrocyte interactions as a potential primary mechanism for the emergence of ultra-slow cortical oscillations.