# Computational Modeling of Semantic Decline in Bilingual Individuals with Mild Cognitive Impairment and Primary Progressive Aphasia

> **NIH NIH U01** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2020 · $437,924

## Abstract

Project Abstract
 The combination of an aging bilingual population combined with a projected increase in individuals with
dementia increases the urgency to understand the interaction between bilingualism and neurodegenerative
disorders. There are a cluster of neurodegenerative disorders lead to cognitive decline and dementia, such as
Alzheimer’s disease [1] and fronto-temporal dementia spectrum disorders [2, 3], including primary progressive
aphasia (PPA) [4, 5] and posterior cortical atrophy [6] and are all characterized by language deficits. It is
therefore, important to understand mechanisms of language decline in these individuals in order to improve
assessments or develop any restorative or facilitative approaches to help these individuals lead fulfilling lives.
Further, given the complex multitude of factors such as the age of acquisition of the second language, the relative
language exposure/proficiency in the two languages, the pathophysiology of the neurodegeneration, it is virtually
impossible if not impractical to obtain a clear understanding of the nature of bilingual language decline in
neurodegenerative disorders.
 As a novel alternative, in a previously funded project (NIH/NIDCD R21DC009446) and current project
(U01DC014922), we have developed BILEX, a computational model that can accurately simulate lexical access
in healthy bilinguals while accounting for individual differences in the age of acquisition of the second language,
and the relative amounts of lifetime use and exposure to each language. The model also accounts for the effects
of these factors on the representational organization of the bilingual mental lexicon at the individual level. In this
supplement, we aim to extend this model to simulate bilingual language impairment in individuals with
neurodegenerative disorders (specifically PPA and AD/MCI). In Aim 1, we will simulate semantic decline in the
BILEX model by damaging the semantic map. Performance on measures of object knowledge and lexical access
in the model will be validated against human data collected from 20 bilingual individuals with semantic dementia.
We expect to demonstrate that after appropriate damage to the semantic representation maps, BILEX can
accurately simulate deficits of object knowledge and lexical access deficits in bilingual dementia. In Aim 2, we
will evaluate this model’s ability to predict decline in naming and object knowledge, by comparing longitudinal
data (three time points) in bilingual individuals’ with dementia with the model’s prediction of decline based on
data from two time points. We expect to demonstrate that progressively increasing damage to the semantic
representation maps will accurately simulate and predict performance decline in bilingual individuals.

## Key facts

- **NIH application ID:** 10123256
- **Project number:** 3U01DC014922-05S1
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Swathi Kiran
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $437,924
- **Award type:** 3
- **Project period:** 2016-07-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10123256

## Citation

> US National Institutes of Health, RePORTER application 10123256, Computational Modeling of Semantic Decline in Bilingual Individuals with Mild Cognitive Impairment and Primary Progressive Aphasia (3U01DC014922-05S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10123256. Licensed CC0.

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