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Quaresima, A., Fitz, H., Duarte, R., Van den Broek, D., Hagoort, P., & Petersson, K. M. (2023). The Tripod neuron: A minimal structural reduction of the dendritic tree. The Journal of Physiology, 601(15), 3007-3437. doi:10.1113/JP283399.
Abstract
Neuron models with explicit dendritic dynamics have shed light on mechanisms for coincidence detection, pathway selection and temporal filtering. However, it is still unclear which morphological and physiological features are required to capture these phenomena. In this work, we introduce the Tripod neuron model and propose a minimal structural reduction of the dendritic tree that is able to reproduce these computations. The Tripod is a three-compartment model consisting of two segregated passive dendrites and a somatic compartment modelled as an adaptive, exponential integrate-and-fire neuron. It incorporates dendritic geometry, membrane physiology and receptor dynamics as measured in human pyramidal cells. We characterize the response of the Tripod to glutamatergic and GABAergic inputs and identify parameters that support supra-linear integration, coincidence-detection and pathway-specific gating through shunting inhibition. Following NMDA spikes, the Tripod neuron generates plateau potentials whose duration depends on the dendritic length and the strength of synaptic input. When fitted with distal compartments, the Tripod encodes previous activity into a dendritic depolarized state. This dendritic memory allows the neuron to perform temporal binding, and we show that it solves transition and sequence detection tasks on which a single-compartment model fails. Thus, the Tripod can account for dendritic computations previously explained only with more detailed neuron models or neural networks. Due to its simplicity, the Tripod neuron can be used efficiently in simulations of larger cortical circuits. -
Fitz, H., & Chang, F. (2019). Language ERPs reflect learning through prediction error propagation. Cognitive Psychology, 111, 15-52. doi:10.1016/j.cogpsych.2019.03.002.
Abstract
Event-related potentials (ERPs) provide a window into how the brain is processing language. Here, we propose a theory that argues that ERPs such as the N400 and P600 arise as side effects of an error-based learning mechanism that explains linguistic adaptation and language learning. We instantiated this theory in a connectionist model that can simulate data from three studies on the N400 (amplitude modulation by expectancy, contextual constraint, and sentence position), five studies on the P600 (agreement, tense, word category, subcategorization and garden-path sentences), and a study on the semantic P600 in role reversal anomalies. Since ERPs are learning signals, this account explains adaptation of ERP amplitude to within-experiment frequency manipulations and the way ERP effects are shaped by word predictability in earlier sentences. Moreover, it predicts that ERPs can change over language development. The model provides an account of the sensitivity of ERPs to expectation mismatch, the relative timing of the N400 and P600, the semantic nature of the N400, the syntactic nature of the P600, and the fact that ERPs can change with experience. This approach suggests that comprehension ERPs are related to sentence production and language acquisition mechanisms -
Zuidema, W., & Fitz, H. (2019). Key issues and future directions: Models of human language and speech processing. In P. Hagoort (
Ed. ), Human language: From genes and brain to behavior (pp. 353-358). Cambridge, MA: MIT Press. -
Brouwer, H., Fitz, H., & Hoeks, J. C. (2010). Modeling the noun phrase versus sentence coordination ambiguity in Dutch: Evidence from Surprisal Theory. In Proceedings of the 2010 Workshop on Cognitive Modeling and Computational Linguistics, ACL 2010 (pp. 72-80). Association for Computational Linguistics.
Abstract
This paper investigates whether surprisal theory can account for differential processing difficulty in the NP-/S-coordination ambiguity in Dutch. Surprisal is estimated using a Probabilistic Context-Free Grammar (PCFG), which is induced from an automatically annotated corpus. We find that our lexicalized surprisal model can account for the reading time data from a classic experiment on this ambiguity by Frazier (1987). We argue that syntactic and lexical probabilities, as specified in a PCFG, are sufficient to account for what is commonly referred to as an NP-coordination preference. -
Fitz, H. (2010). Statistical learning of complex questions. In S. Ohlsson, & R. Catrambone (
Eds. ), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 2692-2698). Austin, TX: Cognitive Science Society.Abstract
The problem of auxiliary fronting in complex polar questions occupies a prominent position within the nature versus nurture controversy in language acquisition. We employ a model of statistical learning which uses sequential and semantic information to produce utterances from a bag of words. This linear learner is capable of generating grammatical questions without exposure to these structures in its training environment. We also demonstrate that the model performs superior to n-gram learners on this task. Implications for nativist theories of language acquisition are discussed.
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