A central goal of systems neuroscience is to simultaneously measure the activities of all achievable neurons in the brain at millisecond resolution in freely moving animals. This paper describes a protocol converter which is part of a measurement acquisition system for multichannel real time recording of brain signals. In practice, in such techniques, a primary consideration of reliability leads to great necessity towards increasing the sampling rate of these signals while simultaneously increasing the resolution of A/D conversion to 24 bits or even to the unprecedented 32 bits per sample. In fact, this was the guiding principle for our team in the present study. By increasing the temporal and amplitude resolution, it is supposed that we get enabled to discover or recognize and identify new signal components which have previously been masked at a "low" temporal and amplitude resolution, and these new signal components, in the future, are likely to contribute to a deeper understanding of the workings of the brain.
In computer networks data flows can often reach transfer rates of several Gigabits per second. On the other hand most embedded systems have additional criteria -power consumption, size, low cost, generated heat -which usually means that even a flow rate of several Megabits per second is difficult to reach. This paper reports on the development of an automated embedded system for data transfers of up to 47Mib/s using two customized embedded 68k/Coldfire RISC microprocessors.
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