Tag Archives: synapse

An electronic synapse

It is a truism that simulation of the brain with ‘electronic neurons’ has been very approximate at best. One problem was simulating the behavior of synapses in software – and synapses are key to ‘biological neuron’ communication. But soon there may be a simulation of the synapse in hardware. This does not solve all the problems with simulating the brain but it will be a large step in that direction. This is somewhat like the brain’s architecture which is more physically based than algorithmically based. Of course, miniaturization is necessary as the number of synapses in any smallish part of the brain is astronomical.


The idea is to use a very thin sheet of samarium nickelate between two platinum terminals. The sheet can be changed from isolating to conducting by the concentration of oxygen ions in the sheet. The oxygen ions can be made to leak out or in - from a small reservoir of ionic liquid by applied voltages. The voltage is controlled by the strength and timing of spikes on the ‘dentrite’ and ‘axon’ terminals. The changes in conductivity are stable until forced to change by another voltage signal. The devices can therefore ‘learn’/’remember’.


They have the advantages that they: can be integrated into silicon-based circuits, are fast, can work at room temperature, are energy efficient, do not require continuous power to maintain their ‘learning’.


Here is the citation and abstract:


Jian Shi, Sieu D. Ha, You Zhou, Frank Schoofs, Shriram Ramanathan. A correlated nickelate synaptic transistor. Nature Communications, 2013


Inspired by biological neural systems, neuromorphic devices may open up new computing paradigms to explore cognition, learning and limits of parallel computation. Here we report the demonstration of a synaptic transistor with SmNiO3, a correlated electron system with insulator–metal transition temperature at 130°C in bulk form. Non-volatile resistance and synaptic multilevel analogue states are demonstrated by control over composition in ionic liquid-gated devices on silicon platforms. The extent of the resistance modulation can be dramatically controlled by the film microstructure. By simulating the time difference between postneuron and preneuron spikes as the input parameter of a gate bias voltage pulse, synaptic spike-timing-dependent plasticity learning behaviour is realized. The extreme sensitivity of electrical properties to defects in correlated oxides may make them a particularly suitable class of materials to realize artificial biological circuits that can be operated at and above room temperature and seamlessly integrated into conventional electronic circuits.



Watching memories form

ScienceDaily has an item on memory (here) on a paper:


K. E. Moczulska, J. Tinter-Thiede, M. Peter, L. Ushakova, T. Wernle, B. Bathellier, S. Rumpel. Dynamics of dendritic spines in the mouse auditory cortex during memory formation and memory recall. Proceedings of the National Academy of Sciences, 2013; DOI: 10.1073/pnas.1312508110



Here is the abstract:


Long-lasting changes in synaptic connections induced by relevant experiences are believed to represent the physical correlate of memories. Here, we combined chronic in vivo two-photon imaging of dendritic spines with auditory-cued classical conditioning to test if the formation of a fear memory is associated with structural changes of synapses in the mouse auditory cortex. We find that paired conditioning and unpaired conditioning induce a transient increase in spine formation or spine elimination, respectively. A fraction of spines formed during paired conditioning persists and leaves a long-lasting trace in the network. Memory recall triggered by the reexposure of mice to the sound cue did not lead to changes in spine dynamics. Our findings provide a synaptic mechanism for plasticity in sound responses of auditory cortex neurons induced by auditory-cued fear conditioning; they also show that retrieval of an auditory fear memory does not lead to a recapitulation of structural plasticity in the auditory cortex as observed during initial memory consolidation.



In effect the researchers made microscopic ‘photos’ of the formation of memories and the weakening of the them plus the retrieval of the memories. The idea that ‘neurons that fire together wire together’ was clearly illustrated. The repeated conditioning increased the strength of the memory, while disrupting the conditioning decreased it, but did not destroy the memory. Retrieval of the memory did not change its strength. The notion that recall recapitulated the original memory formation was not supported.