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A Cerebellar Neuroprosthetic System: Computational Architecture and in vivo Test.

Herreros I, Giovannucci A, Taub AH, Hogri R, Magal A, Bamford S, Prueckl R, Verschure PF - Front Bioeng Biotechnol (2014)

Bottom Line: As a result, we show that the anesthetized rat, equipped with our neuroprosthetic system, can be classically conditioned to the acquisition of an eye-blink response.The resulting system represents an important step toward replacing lost functions of the central nervous system via neuroprosthetics, obtained by integrating a synthetic circuit with the afferent and efferent pathways of a damaged brain region.These results also embody an early example of science-based medicine, where on the one hand the neuroprosthetic system directly validates a theory of cerebellar learning that informed the design of the system, and on the other one it takes a step toward the development of neuro-prostheses that could recover lost learning functions in animals and, in the longer term, humans.

View Article: PubMed Central - PubMed

Affiliation: Synthetic Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra , Barcelona , Spain.

ABSTRACT
Emulating the input-output functions performed by a brain structure opens the possibility for developing neuroprosthetic systems that replace damaged neuronal circuits. Here, we demonstrate the feasibility of this approach by replacing the cerebellar circuit responsible for the acquisition and extinction of motor memories. Specifically, we show that a rat can undergo acquisition, retention, and extinction of the eye-blink reflex even though the biological circuit responsible for this task has been chemically inactivated via anesthesia. This is achieved by first developing a computational model of the cerebellar microcircuit involved in the acquisition of conditioned reflexes and training it with synthetic data generated based on physiological recordings. Secondly, the cerebellar model is interfaced with the brain of an anesthetized rat, connecting the model's inputs and outputs to afferent and efferent cerebellar structures. As a result, we show that the anesthetized rat, equipped with our neuroprosthetic system, can be classically conditioned to the acquisition of an eye-blink response. However, non-stationarities in the recorded biological signals limit the performance of the cerebellar model. Thus, we introduce an updated cerebellar model and validate it with physiological recordings showing that learning becomes stable and reliable. The resulting system represents an important step toward replacing lost functions of the central nervous system via neuroprosthetics, obtained by integrating a synthetic circuit with the afferent and efferent pathways of a damaged brain region. These results also embody an early example of science-based medicine, where on the one hand the neuroprosthetic system directly validates a theory of cerebellar learning that informed the design of the system, and on the other one it takes a step toward the development of neuro-prostheses that could recover lost learning functions in animals and, in the longer term, humans.

No MeSH data available.


Related in: MedlinePlus

Weight trajectory during the experiment. The dashed vertical line separates the acquisition and extinction phases.
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Figure 13: Weight trajectory during the experiment. The dashed vertical line separates the acquisition and extinction phases.

Mentions: The evolution of the synaptic efficacy w is displayed in Figure 13. We estimate that given our setup CRs follow a PN event whenever the value of w goes below 0.4. However, for such CRs to be anticipatory, w should settle at 0.28 or below. During the experiment, w decreased steadily during the first 60 trials, down to a value of 0.29. Afterward, the decrease decelerated. The dynamics of w suggest that learning has reached an asymptotic-level by the end of the acquisition stage (Figure 13). The mean value of w during well-timed CRs was 0.25, corresponding to CRs triggered on average 140 ms after the PN detection. Thus, for an ISI of 300 ms the model acquired an internal timing (tCR) of 140 ms.


A Cerebellar Neuroprosthetic System: Computational Architecture and in vivo Test.

Herreros I, Giovannucci A, Taub AH, Hogri R, Magal A, Bamford S, Prueckl R, Verschure PF - Front Bioeng Biotechnol (2014)

Weight trajectory during the experiment. The dashed vertical line separates the acquisition and extinction phases.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126458&req=5

Figure 13: Weight trajectory during the experiment. The dashed vertical line separates the acquisition and extinction phases.
Mentions: The evolution of the synaptic efficacy w is displayed in Figure 13. We estimate that given our setup CRs follow a PN event whenever the value of w goes below 0.4. However, for such CRs to be anticipatory, w should settle at 0.28 or below. During the experiment, w decreased steadily during the first 60 trials, down to a value of 0.29. Afterward, the decrease decelerated. The dynamics of w suggest that learning has reached an asymptotic-level by the end of the acquisition stage (Figure 13). The mean value of w during well-timed CRs was 0.25, corresponding to CRs triggered on average 140 ms after the PN detection. Thus, for an ISI of 300 ms the model acquired an internal timing (tCR) of 140 ms.

Bottom Line: As a result, we show that the anesthetized rat, equipped with our neuroprosthetic system, can be classically conditioned to the acquisition of an eye-blink response.The resulting system represents an important step toward replacing lost functions of the central nervous system via neuroprosthetics, obtained by integrating a synthetic circuit with the afferent and efferent pathways of a damaged brain region.These results also embody an early example of science-based medicine, where on the one hand the neuroprosthetic system directly validates a theory of cerebellar learning that informed the design of the system, and on the other one it takes a step toward the development of neuro-prostheses that could recover lost learning functions in animals and, in the longer term, humans.

View Article: PubMed Central - PubMed

Affiliation: Synthetic Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra , Barcelona , Spain.

ABSTRACT
Emulating the input-output functions performed by a brain structure opens the possibility for developing neuroprosthetic systems that replace damaged neuronal circuits. Here, we demonstrate the feasibility of this approach by replacing the cerebellar circuit responsible for the acquisition and extinction of motor memories. Specifically, we show that a rat can undergo acquisition, retention, and extinction of the eye-blink reflex even though the biological circuit responsible for this task has been chemically inactivated via anesthesia. This is achieved by first developing a computational model of the cerebellar microcircuit involved in the acquisition of conditioned reflexes and training it with synthetic data generated based on physiological recordings. Secondly, the cerebellar model is interfaced with the brain of an anesthetized rat, connecting the model's inputs and outputs to afferent and efferent cerebellar structures. As a result, we show that the anesthetized rat, equipped with our neuroprosthetic system, can be classically conditioned to the acquisition of an eye-blink response. However, non-stationarities in the recorded biological signals limit the performance of the cerebellar model. Thus, we introduce an updated cerebellar model and validate it with physiological recordings showing that learning becomes stable and reliable. The resulting system represents an important step toward replacing lost functions of the central nervous system via neuroprosthetics, obtained by integrating a synthetic circuit with the afferent and efferent pathways of a damaged brain region. These results also embody an early example of science-based medicine, where on the one hand the neuroprosthetic system directly validates a theory of cerebellar learning that informed the design of the system, and on the other one it takes a step toward the development of neuro-prostheses that could recover lost learning functions in animals and, in the longer term, humans.

No MeSH data available.


Related in: MedlinePlus