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PubMed · 1504816

Neuronal multipotentiality: evidence for network representation of physiological function.

E B Montgomery·M H Clare·S Sahrmann·S R Buchholz·L S Hibbard·W M Landau
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Abstract

Extracellular action potentials of single neurons in motor cortex and rectified and integrated electromyographic activity (EMG) of gastrocnemius and anterior tibialis were recorded while a monkey performed isometric ankle plantar and dorsal flexion tasks. This study determined the consistency of neuronal behaviors across different tasks. Methods characterized neuronal behaviors by determining which behavioral event within a single task, such as the appearance of the 'go' signal, force onset, or agonist and antagonist EMG onset, was best related to changes in neuronal activity. Another method compared the temporal profiles of discharge modulation across different tasks. Of 220 neurons recorded, 44 were selected because they were consistently active in the tasks. Of these, 37 were in the precentral cortex and the remaining seven were in the postcentral cortex. Only 14 of the 33 in motor cortex were consistent in their behavioral correlations. Several had multiple changes in activity within a single task that were related to different behavioral events. Half were consistent for direction of force and a third were consistent for magnitude of force. Furthermore, there was little consistency in the temporal profiles of discharge activity for all 44 neurons across tasks. Similar modulations of discharge activity among neurons in one task were different in another task. Such inconsistencies are evidence against the cardinal cell hypothesis of physiological representation. We offer a new hypothesis analogous to connectionism in parallel distributed processing.

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Action PotentialsAnimalsElectric StimulationIsometric ContractionMacaca nemestrinaNeuronsComparative StudyJournal ArticleResearch Support, Non-U.S. Gov't

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E B Montgomery, M H Clare, S Sahrmann, S R Buchholz, L S Hibbard, W M Landau. 1992-05-15. Neuronal multipotentiality: evidence for network representation of physiological function.. https://doi.org/10.1016/0006-8993(92)90926-z

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