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Updated: May 13, 2026
03:14
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
A modular approach to language production: models and facts
Juan C Valle-Lisboa1, Andrés Pomi1, Álvaro Cabana1
1Group of Cognitive Systems Modeling, Biophysics Section, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.
Summary
This study introduces a neurocomputational model to analyze language disorders by visualizing discourse as trajectories. It links neural networks, functional neuroimaging, and Latent Semantic Analysis to understand speech organization and potential links to schizophrenia.
Area of Science:
- Neuroscience
- Computational Linguistics
- Cognitive Science
Background:
- Cortical disorders frequently impact language functions.
- Understanding the neural basis of language is crucial for treating related disorders.
- Existing methods lack a unified framework to connect language behavior with neural substrates.
Purpose of the Study:
- To develop a neurocomputational approach linking observed language behavior to underlying neural mechanisms.
- To create a graphical representation of discourse to quantify order and disorder.
- To explore the potential of synaptic disconnection in schizophrenia-related discourse alterations.
Main Methods:
- Designed a graphical trajectory representation for discourse analysis.
- Integrated neural models of associative memory with Latent Semantic Analysis (LSA).
- Utilized mathematical principles of functional neuroimaging within the neurocomputational framework.
Main Results:
- Demonstrated how neurocomputational models, LSA, and functional neuroimaging mathematics interconnect.
- Developed a context-dependent neural model for goal-oriented linguistic behavior.
- Generated "functional brain images" from the model for transparent analysis.
Conclusions:
- The neurocomputational framework provides a "transparent box" to analyze statistical imaging implications.
- Functional synaptic disconnection may increase concept connectivity, potentially explaining discourse alterations in schizophrenia.
- This approach offers novel insights into the dynamics of language production and comprehension.
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