Abstract
Purkinje neurons (PN) in the cerebellum have over 100,000 inputs organized in an orthogonal geometry, and a single output channel. As the sole output of the cerebellar cortex layer, their complex firing pattern has been associated with motor control and learning. As such they have been extensively modeled and measured using tools ranging from electrophysiology and neuroanatomy, to dynamic systems and artificial intelligence methods. However, there is an alternative approach to analyze and describe the neuronal output of these cells using concepts from electrical engineering, particularly signal processing and digital/analog circuits. By viewing the PN as an unknown circuit to be reverse-engineered, we can use the tools that provide the foundations of today’s integrated circuits and communication systems to analyze the Purkinje system at the circuit level. We use Fourier transforms to analyze and isolate the inherent frequency modes in the PN and define three unique frequency ranges associated with the cells’ output. Comparing the PN to a signal generator that can be externally modulated adds an entire level of complexity to the functional role of these neurons both in terms of data analysis and information processing, relying on Fourier analysis methods in place of statistical ones. We also re-describe some of the recent literature in the field, using the nomenclature of signal processing. Furthermore, by comparing the experimental data of the past decade with basic electronic circuitry, we can resolve the outstanding controversy in the field, by recognizing that the PN can act as a multivibrator circuit.
Highlights
Reviewed by: Audrey Mercer, University of London, UK Michael Nitabach, Yale University School of Medicine, USA
Using tools from EE to understand the fundamental processes occurring at the cellular circuit level are essential if we are to understand the ultimate functionality of the cerebellum
Despite input–output relations such as the linear algorithm shown in Figure 3A (Walter and Khodakhah, 2006), the mixed analog signal of the Purkinje neurons (PN) would appear to function beyond the complexity of a basic multiplexor or comparator (Hendry, 2004)
Summary
Reviewed by: Audrey Mercer, University of London, UK Michael Nitabach, Yale University School of Medicine, USA. The most elementary methodology to reverse engineer the PN, whose functions are unknown, is to treat it as a “black box,” and measure the response of the cell (via the axon) as a function of its inputs In this sense, the input signal must be subdivided into a zero input response – the natural firing pattern of the PN in the absence of inputs; the first-order input response – considering the output response to a variety of external sources; and higher-order responses including feedback and feedforward control mechanisms, where the inputs signals are re-fed into the cell. Comparisons of in vitro and in vivo analyses must take into account the different circuits involved, with most zero- and first-order results
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