A computational model for identifying behavioral patterns in people with neuropsychiatric disorders

Abstract Cross-linguistic influence (CLI) is one of the key phenomena in bilingual and second language learning. We propose a method for quantifying CLI in the use of linguistic constructions with the help of a computational model, which acquires constructions in two languages from bilingual input. We focus on the acquisition of case-marking cues in Russian and German and simulate two experiments that employ a picture-choice task tapping into the mechanisms of sentence interpretation. Our model yields behavioral patterns similar to human, and these patterns can be explained by the amount of CLI: the negative CLI in high amounts leads to the misinterpretation of participant roles in Russian and German object-verb-subject sentences. Finally, we make two novel predictions about the acquisition of case-marking cues in Russian and German. Most importantly, our simulations suggest that the high degree of positive CLI may facilitate the interpretation of object-verb-subject sentences.

Download Full-text

From Occasional Choices to Inevitable Musts: A Computational Model of Nicotine Addiction

Computational Intelligence and Neuroscience ◽

10.1155/2012/817485 ◽

2012 ◽

Vol 2012 ◽

pp. 1-14 ◽

Cited By ~ 3

Author(s):

Selin Metin ◽

N. Serap Sengor

Keyword(s):

Computational Model ◽

Computational Models ◽

Nonlinear Dynamical Systems ◽

Dynamical Behavior ◽

Nicotine Addiction ◽

Behavioral Patterns ◽

Nonlinear Dynamical ◽

Proposed Model ◽

Neurophysiological Basis ◽

Different Levels

Although, there are considerable works on the neural mechanisms of reward-based learning and decision making, and most of them mention that addiction can be explained by malfunctioning in these cognitive processes, there are very few computational models. This paper focuses on nicotine addiction, and a computational model for nicotine addiction is proposed based on the neurophysiological basis of addiction. The model compromises different levels ranging from molecular basis to systems level, and it demonstrates three different possible behavioral patterns which are addict, nonaddict, and indecisive. The dynamical behavior of the proposed model is investigated with tools used in analyzing nonlinear dynamical systems, and the relation between the behavioral patterns and the dynamics of the system is discussed.

Download Full-text

Reductionist thinking and animal models in neuropsychiatric research

Behavioral and Brain Sciences ◽

10.1017/s0140525x18001231 ◽

2019 ◽

Vol 42 ◽

Cited By ~ 1

Author(s):

Nicole M. Baran

Keyword(s):

Animal Models ◽

Mental Disorders ◽

Environmental Factors ◽

Neuropsychiatric Disorders ◽

Model Organisms ◽

Developmental Genetic ◽

Term Study ◽

Genetic And Environmental Factors ◽

Mechanisms Of Plasticity

AbstractReductionist thinking in neuroscience is manifest in the widespread use of animal models of neuropsychiatric disorders. Broader investigations of diverse behaviors in non-model organisms and longer-term study of the mechanisms of plasticity will yield fundamental insights into the neurobiological, developmental, genetic, and environmental factors contributing to the “massively multifactorial system networks” which go awry in mental disorders.

Download Full-text