Determining Learning Ability in People With Aphasia

Summary

Aphasia is an impairment in the expression or comprehension of language that results from stroke, traumatic brain injury or progressive neurological disease. Approximately two million people in the United States suffer from aphasia, which has profound impacts on quality of life, the ability to return to work and participation in life activities. Research has shown that speech-language therapy, the treatment for aphasia, can significantly improve people's ability to communicate. However, a major limitation in the field of aphasia rehabilitation is the lack of predictability in patients' response to therapy and the inability to tailor treatment to individuals. Currently, aphasia treatments are selected largely based on patient's language abilities and language deficits with little consideration of learning ability, which this study refers to as learning phenotype. Learning phenotype has been used to inform rehabilitation approaches in other domains but is not currently considered in aphasia. The overarching hypothesis of this work is that poor alignment of learning ability and language therapy limits progress for patients and presents a barrier to individualizing treatment.

The objectives of the proposed study are to (1) determine the learning phenotype of individuals with aphasia, and (2) examine how lesion characteristics (size and location of damage to the brain), language ability and cognitive ability relate to learning ability. To accomplish objectives, investigators propose to measure implicit (observational) and explicit (rule-based) learning ability in people with aphasia via computer-based tasks. Regression models will be used to examine brain and behavioral factors that relate to learning ability.

Conditions

• Aphasia

Interventions

BEHAVIORAL

SRT Observational Learning

All participants completed a computer-based serial response time (SRT) task intended to measure observational (implicit) learning ability. The SRT Observational learning task is a classic paradigm, which has been integral to the understanding of implicit learning (see Schwarb \& Schumacher, 2012). The current task is a replication of classic SRT tasks first described by Nissen and Bullemer (1987), adapted for eye-tracking by Kinder et al. (2008). In this task, participants look at a dot move from one of 4 positions on a computer screen. Unbeknownst to participants, dot movement followed a 12-movement pattern for most experimental blocks. Eye-tracking data is collected and eye fixations within regions of interest trigger trial advancement. Learning ability is evaluated as a comparison of saccadic response times during sequenced trials relative to pseudorandomized trials.

BEHAVIORAL

AGL Observational Learning

All participants completed a computer-based observational artificial grammar learning (AGL) task. The AGL Observational learning task is another classic test of implicit learning involving learning of ordered items through exposure (Schuchard \& Thompson, 2017). Artificial grammars contain hierarchal dependencies, similar to the rules that govern word-order and syntax in natural language. In this task, participants look at sequences of geometric shapes on a computer screen. Participants judged if two sequences matched or did not match. After training, participants are shown sequences and must judge if sequences adhere to the pattern or not.

BEHAVIORAL

AGL Rule-based Learning

All participants completed a computer-based rule-based learning task intended to measure rule-based (explicit) learning ability of an artificial grammar expressed in nonlinguistic form (sequences of shapes). In this task, participants look at sequences of geometric shapes on a computer screen. Through visuals and verbal instruction, they are taught 5 rules that govern sequences. After learning rules, participants are asked to judge via button press whether novel sequences adhere to rules or not.

BEHAVIORAL

Standardized cognitive-linguistic assessment

Participants completed standardized cognitive-linguistic assessments that evaluate their ability to produce and understand language and evaluate cognitive skills of attention, executive function and working memory important for learning. Tests involve paper and pencil, looking at pictures, listening to words, indicating responses on a keyboard and talking.

OTHER

Brain imaging

Enrolled participants who were safe to scan via magnetic resonance imaging (MRI) completed a structural MRI scan between one-month and five months from behavioral testing of learning.

Sponsors & Collaborators

• National Institute on Deafness and Other Communication Disorders (NIDCD)

  collaborator NIH

• MGH Institute of Health Professions

  lead OTHER

Principal Investigators

• Sofia Vallila-Rohter, PhD · MGH Institute of Health Professions

Study Design

Allocation

NA

Purpose

DIAGNOSTIC

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

18 Years

Max Age

80 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2022-06-06

Primary Completion

2023-09-01

Completion

2023-09-01

Countries

• United States

Study Locations