Higher-order nonlinear electron-acoustic solitary excitations in partially degenerate quantum electron-ion plasmas

Propagation of dressed solitary excitations are studied in a partially degenerate quantum plasma in the framework of quantum-hydrodynamics (QHD) model using multiple scales technique. The evolution equation together with a linear inhomogeneous differential equation is solved using Kodama-Taniuti renormalizing technique. It is shown that the type of solitary excitations (bright or dark) is defined by two critical plasma parameter values.Comment: To appear in Indian Journal of Physic

Converging Neuronal Activity in Inferior Temporal Cortex during the Classification of Morphed Stimuli

How does the brain dynamically convert incoming sensory data into a representation useful for classification? Neurons in inferior temporal (IT) cortex are selective for complex visual stimuli, but their response dynamics during perceptual classification is not well understood. We studied IT dynamics in monkeys performing a classification task. The monkeys were shown visual stimuli that were morphed (interpolated) between pairs of familiar images. Their ability to classify the morphed images depended systematically on the degree of morph. IT neurons were selected that responded more strongly to one of the 2 familiar images (the effective image). The responses tended to peak ∼120 ms following stimulus onset with an amplitude that depended almost linearly on the degree of morph. The responses then declined, but remained above baseline for several hundred ms. This sustained component remained linearly dependent on morph level for stimuli more similar to the ineffective image but progressively converged to a single response profile, independent of morph level, for stimuli more similar to the effective image. Thus, these neurons represented the dynamic conversion of graded sensory information into a task-relevant classification. Computational models suggest that these dynamics could be produced by attractor states and firing rate adaptation within the population of IT neurons

Dual component NMDA receptor currents at a single central synapse

Present thinking about the way that the NMDA (N-methyl-D-aspartate) class of glutamate receptor operates at central synapses relies mainly on information obtained from single-channel and whole-cell recordings from cultured neurons stimulated by exogenous NMDA receptor agonists. The mechanisms that operate in the postsynaptic membrane of a normal neuron following release of the natural transmitter are far less clear. An important problem is that most normal neurons receive many excitatory synapses (10(3)-10(5) per cell) and these synapses are located on slender dendritic elements far away from the somatic recording site, making the study of discrete synaptic events difficult. Typically, when populations of synapses are activated, NMDA receptor-mediated synaptic potentials appear as slowly rising, long-lasting waves superimposed on faster, non-NMDA-receptor potentials. Although believed to be critical for NMDA receptor function, this slow time-course would not be predicted from single-channel kinetics and its origin remains puzzling. We have now analysed the events occurring at the level of a single excitatory synapse using a simple, small, neuron--the cerebellar granule cell--which has an unusually simple glutamatergic input. By applying high-resolution whole-cell recording techniques to these cells in situ, we were able to study the nature of elementary NMDA receptor-mediated synaptic currents. Contrary to expectations, the prominent currents are fast but are followed by slow ones. Both types of current are strongly voltage-dependent but differ subtly in this respect. Furthermore, the currents are absent unless glycine is provided