Extracting non-linear integrate-and-fire models from experimental data using dynamic I–V curves

The dynamic I–V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current–voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models—of the refractory exponential integrate-and-fire type—provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons.     

Non-secretory solitary plasmacytoma of the spleen

A case of primary nonsecretory plasmacytoma of the spleen is reported. On laparotomy and splenectomy a 920 g spleen was removed, measuring 16×14×6 cm. The cut surface of the entire spleen showed that the tumour occupied most of the splenic tissue. A bone marrow aspirate and trephine, skeletal survey showed no signs of myeloma. Biopsy of the liver and regional lymph nodes was normal. Immunocytochemistry of the splenic tumour showed positivity for pan-B and plasma cell markers. After splenectomy the patient was treated with chemotherapy according to protocol VBCMP (M2).     

Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns

Hebbian learning allows a network of spiking neurons to store and retrieve spatio-temporal patterns with a time resolution of 1 ms, despite the long postsynaptic and dendritic integration times. To show this, we introduce and analyze a model of spiking neurons, the spike response model, with a realistic distribution of axonal delays and with realistic postsynaptic potentials. Learning is performed by a local Hebbian rule which is based on the synchronism of presynaptic neurotransmitter release and some short-acting postsynaptic process. The time window of this synchronism determines the temporal resolution of pattern retrieval, which can be initiated by applying a short external stimulus pattern. Furthermore, a rate quantization is found in dependence upon the threshold value of the neurons, i.e., in a given time a pattern runsn times as often as learned, wheren is a positive integer (n 0). We show that all information about the spike pattern is lost if only mean firing rates (temporal average) or ensemble activities (spatial average) are considered. An average over several retrieval runs in order to generate a post-stimulus time histogram may also deteriorate the signal. The full information on a pattern is contained in the spike raster of a single run. Our results stress the importance, and advantage, of coding by spatio-temporal spike patterns instead of firing rates and average ensemble activity. The implications regarding modelling and experimental data analysis are discussed.     

Analysis of ploidy in hypopharyngeal cancer by laser scanning cytometry on fine needle aspirate biopsies.

AIM: To test laser scanning cytometry (LSC) for the analysis of ploidy in squamous cell carcinoma of the hypopharynx (SCCH) and to develop a routine application for minimal samples such as fine needle aspirate biopsies (FNABs). METHODS: From 11 individuals 30 FNABs of primary tumors (n=11) and lymphatic metastases of SCCH (n=11) and non-metastatic lymph nodes (n=8) are analyzed by LSC. This microscope based instrument scans the cells after immobilization on a glass slide and after double staining of cytokeratin and DNA. The location of each cell is stored with the fluorescence data. Therefore the morphology of every cell can be documented by re-staining with H & E; and re-localization on the slide. Additionally, aliquots are Feulgen-stained for image cytometry in 8 specimens. RESULTS: The diploid reference peak is identified taking leukocytes as internal standard. The DNA-index of the carcinoma cells ranges from 0.4 to 3.8. Comparison with image cytometry shows good correlation (r=0.89). CONCLUSION: LSC provides a reliable and objective way to determine the ploidy of SCCH pre-operatively. Colour figures can be viewed on http://www.esacp.org/acp/2003/25-2/gerstner.htm.