The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech Production
Background: The computer-based simulation of the whole processing route for speech production and speech perception in a neurobiologically inspired way remains a challenge. Only a few neural based models of speech production exist, and these models either concentrate on the cognitive-linguistic comp...
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| Format: | Article |
| Language: | English |
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IMR Press
2023-08-01
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| Series: | Journal of Integrative Neuroscience |
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| Online Access: | https://www.imrpress.com/journal/JIN/22/5/10.31083/j.jin2205124 |
| _version_ | 1827810386541281280 |
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| author | Bernd J. Kröger |
| author_facet | Bernd J. Kröger |
| author_sort | Bernd J. Kröger |
| collection | DOAJ |
| description | Background: The computer-based simulation of the whole processing route for speech production and speech perception in a neurobiologically inspired way remains a challenge. Only a few neural based models of speech production exist, and these models either concentrate on the cognitive-linguistic component or the lower-level sensorimotor component of speech production and speech perception. Moreover, these existing models are second-generation neural network models using rate-based neuron approaches. The aim of this paper is to describe recent work developing a third-generation spiking-neuron neural network capable of modeling the whole process of speech production, including cognitive and sensorimotor components. Methods: Our neural model of speech production was developed within the Neural Engineering Framework (NEF), incorporating the concept of Semantic Pointer Architecture (SPA), which allows the construction of large-scale neural models of the functioning brain based on only a few essential and neurobiologically well-grounded modeling or construction elements (i.e., single spiking neuron elements, neural connections, neuron ensembles, state buffers, associative memories, modules for binding and unbinding of states, modules for time scale generation (oscillators) and ramp signal generation (integrators), modules for input signal processing, modules for action selection, etc.). Results: We demonstrated that this modeling approach is capable of constructing a fully functional model of speech production based on these modeling elements (i.e., biologically motivated spiking neuron micro-circuits or micro-networks). The model is capable of (i) modeling the whole processing chain of speech production and, in part, for speech perception based on leaky-integrate-and-fire spiking neurons and (ii) simulating (macroscopic) speaking behavior in a realistic way, by using neurobiologically plausible (microscopic) neural construction elements. Conclusions: The model presented here is a promising approach for describing speech processing in a bottom-up manner based on a set of micro-circuit neural network elements for generating a large-scale neural network. In addition, the model conforms to a top-down design, as it is available in a condensed form in box-and-arrow models based on functional imaging and electrophysiological data recruited from speech processing tasks. |
| first_indexed | 2024-03-11T22:51:49Z |
| format | Article |
| id | doaj.art-8c67c54df4d241a9bbee646a5e37b837 |
| institution | Directory Open Access Journal |
| issn | 0219-6352 |
| language | English |
| last_indexed | 2024-03-11T22:51:49Z |
| publishDate | 2023-08-01 |
| publisher | IMR Press |
| record_format | Article |
| series | Journal of Integrative Neuroscience |
| spelling | doaj.art-8c67c54df4d241a9bbee646a5e37b8372023-09-22T02:49:15ZengIMR PressJournal of Integrative Neuroscience0219-63522023-08-0122512410.31083/j.jin2205124S0219-6352(23)00594-6The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech ProductionBernd J. Kröger0Department of Phoniatrics, Pedaudiology, and Communication Disorders, Medical School, RWTH Aachen University, 52074 Aachen, GermanyBackground: The computer-based simulation of the whole processing route for speech production and speech perception in a neurobiologically inspired way remains a challenge. Only a few neural based models of speech production exist, and these models either concentrate on the cognitive-linguistic component or the lower-level sensorimotor component of speech production and speech perception. Moreover, these existing models are second-generation neural network models using rate-based neuron approaches. The aim of this paper is to describe recent work developing a third-generation spiking-neuron neural network capable of modeling the whole process of speech production, including cognitive and sensorimotor components. Methods: Our neural model of speech production was developed within the Neural Engineering Framework (NEF), incorporating the concept of Semantic Pointer Architecture (SPA), which allows the construction of large-scale neural models of the functioning brain based on only a few essential and neurobiologically well-grounded modeling or construction elements (i.e., single spiking neuron elements, neural connections, neuron ensembles, state buffers, associative memories, modules for binding and unbinding of states, modules for time scale generation (oscillators) and ramp signal generation (integrators), modules for input signal processing, modules for action selection, etc.). Results: We demonstrated that this modeling approach is capable of constructing a fully functional model of speech production based on these modeling elements (i.e., biologically motivated spiking neuron micro-circuits or micro-networks). The model is capable of (i) modeling the whole processing chain of speech production and, in part, for speech perception based on leaky-integrate-and-fire spiking neurons and (ii) simulating (macroscopic) speaking behavior in a realistic way, by using neurobiologically plausible (microscopic) neural construction elements. Conclusions: The model presented here is a promising approach for describing speech processing in a bottom-up manner based on a set of micro-circuit neural network elements for generating a large-scale neural network. In addition, the model conforms to a top-down design, as it is available in a condensed form in box-and-arrow models based on functional imaging and electrophysiological data recruited from speech processing tasks.https://www.imrpress.com/journal/JIN/22/5/10.31083/j.jin2205124speech productionspeech processingneural network modelleaky-integrate-and-fire-neuronsspiking neuron model |
| spellingShingle | Bernd J. Kröger The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech Production Journal of Integrative Neuroscience speech production speech processing neural network model leaky-integrate-and-fire-neurons spiking neuron model |
| title | The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech Production |
| title_full | The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech Production |
| title_fullStr | The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech Production |
| title_full_unstemmed | The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech Production |
| title_short | The NEF-SPA Approach as a Framework for Developing a Neurobiologically Inspired Spiking Neural Network Model for Speech Production |
| title_sort | nef spa approach as a framework for developing a neurobiologically inspired spiking neural network model for speech production |
| topic | speech production speech processing neural network model leaky-integrate-and-fire-neurons spiking neuron model |
| url | https://www.imrpress.com/journal/JIN/22/5/10.31083/j.jin2205124 |
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