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Updating the prepost plane in monetdbxquery

The versatile Hebbian synapse device is applicable to a variety of neuroprosthesis, brain-machine interface, neurorobotics, neuromimetic computation, machine learning, and neural-inspired adaptive control problems.

The XIME-P workshop will take place in Baltimore, Maryland (the same place as SIGMOD/PODS).

Authors are invited to submit original papers relevant to one or several broad XIME-P topics: implementation, experience, or perspectives.

Papers should adhere to the ACM formatting guidelines.

Please submit your papers at: https://msrcmt.research.microsoft.com/XIMEP2005 paper submission, of up to 6 pages length.

Currently, there is general agreement that LTP can result from both SRDP and STDP learning rules via postsynaptic NMDAR-mediated coincidence detection of prepostynaptic activities.

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These protocols are consistent with the theoretical learning rule (BCM rule) proposed by Bienenstock, Cooper, and Munro (9), in which the sign and magnitude of synaptic plasticity are controlled solely by postsynaptic activity as determined by presynaptic firing rate: low postsynaptic activity weakens synaptic efficacy and high postsynaptic activity strengthens it.

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Furthermore, the workshop proceedings will appear on the XIME CD and on Website Pavel Hlousek (Charles University) Na XDB - Realizing Pipelined XQuery Processing in a Native XML Database System Jens HŸndling (University of Potsdam), Jan Sievers (University of Potsdam), Mathias Weske (University of Potsdam) Deep Set Operators for XQuery Bo Luo (School of Information Sciences and Technology), Dongwon Lee (The Pennsylvania State University), Wang-Chien Lee (The Pennsylvania State University), Peng Liu (The Pennsylvania State University) - Coffee break/demos - Invited speaker: Michael Kay, Saxonica: XQuery: how will the users react? Fernandez) - XQuery and Information Retrieval-- Jayavel Shanmugasundaram, Cornell univ.Compared to conventional software-based computer modeling and simulation approaches, these neuromorphic electronic circuits have extremely small size (micro- to nanoscale) and low power requirements (μA to p A current per unit device with 0.5–5 V power supply) for large scale neural modeling and high speed simulation purposes.These capabilities are critical for many real-time, portable/implantable neural computing applications such as neuroprosthesis, brain-machine interface, neurorobotics, neuromimetic computation, machine learning, or neural-inspired adaptive control (44).Here, we propose a CMOS circuit implementation of a biophysically grounded neuromorphic (iono-neuromorphic) model of synaptic plasticity that is capable of capturing both the spike rate-dependent plasticity (SRDP, of the Bienenstock-Cooper-Munro or BCM type) and STDP rules.The iono-neuromorphic model reproduces bidirectional synaptic changes with NMDA receptor-dependent and intracellular calcium-mediated long-term potentiation or long-term depression assuming retrograde endocannabinoid signaling as a second coincidence detector.Changes in excitatory or inhibitory synaptic weights are registered and stored in a nonvolatile and compact digital format analogous to the discrete insertion and removal of AMPA or GABA receptor channels.