By Péter Érdi, János Tóth (auth.), Massimo De Gregorio, Vito Di Maio, Maria Frucci, Carlo Musio (eds.)
This publication constitutes the refereed lawsuits of the 1st overseas Symposium on mind, imaginative and prescient and synthetic Intelligence, BVAI 2005, held in Naples, Italy in October 2005.
The forty eight revised papers offered including 6 invited lectures have been rigorously reviewed and chosen from greater than eighty submissions for inclusion within the ebook. The papers are addressed to the subsequent major issues and sub-topics: mind fundamentals - neuroanatomy and body structure, improvement, plasticity and studying, synaptic, neuronic and neural community modelling; traditional imaginative and prescient - visible neurosciences, mechanisms and version structures, visible conception, visible cognition; synthetic imaginative and prescient - form notion, form research and popularity, form realizing; man made inteligence - hybrid clever structures, brokers, and cognitive models.
Read Online or Download Brain, Vision, and Artificial Intelligence: First International Symposium, BVAI 2005, Naples, Italy, October 19 – 21, 2005. Proceedings PDF
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Extra resources for Brain, Vision, and Artificial Intelligence: First International Symposium, BVAI 2005, Naples, Italy, October 19 – 21, 2005. Proceedings
Takahashi S, Anzai Y, Sakurai Y. A new approach to spike sorting for multi-neuronal activities recorded with a tetrode – how ICA can be practical. Neuroscience Research (2003) 46: 265–272. 7. Villa AEP, Tetko IV, Hyland B, Najem A. Spatiotemporal activity patterns of rat cortical neurons predict responses in a conditioned task. Proc. Natl. Acad. Sci. USA (1999) 96: 1006–1011. 8. Zhang PM, Wu JY, Zhoub Y, Liang PJ, Yuan JQ. Spike sorting; Template-matching; χ2 -Test; Overlapping; Principal component analysis; Subtractive clustering.
P. org 6 Institute for Scientiﬁc Interchange Foundation, Villa Gualino, Torino Abstract. , recordings from large microelectrode arrays in behaving animals). We present an algorithm that can recognize the waveform of neural traces corresponding to extracellular action potentials. Spike shapes are expressed in a phase space spanned by the ﬁrst and second derivatives of the raw signal trace. The performance of the algorithm is tested against artiﬁcially generated noisy data sets. We present the main features of the algorithm aimed to on-line real-time operations.
For the analysis of a signal recorded with the data acquisition board. Users can easily shift from one mode to the other without restarting the application. In each operation mode, the application provides three utilities: a signal viewer showing only the event detection, the template learning utility including the template-to-all error distributions and the spike sorting utility. The application with GUI can be operated by users intuitively. The main window of the application (Fig. 1) shows the waveform of the raw signal.