Future Research Ideas in Neurocognitive Communication

By CSAND Lab Staff | September 20, 2024

As a researcher in the field of neurocognitive communication, I’m constantly exploring new avenues for investigation. Below, I’ve compiled a list of potential research or related ideas that I’m considering for future projects. While I can’t pursue all of these simultaneously, I’m sharing them in hopes of inspiring collaboration or sparking interest in these areas—if not me, at least someone will see to the work!

Assessment and Diagnostic Tools

  • Align MIR with CSA measures: Investigate how the Multidomain Impairment Rating (MIR) system for neurocognitive conditions aligns with Communication Sciences and Disorders Assessment (CSA) measures. For example, how good are we at predicting individual domains on the MIR, not just an overall score?
  • Gamify the Northwestern Anagram Test (NAT): Develop an iPad version of the NAT to improve grammar assessment and intervention in neurolinguistic conditions. Grammatical therapies could be gamified, and improvement quantified in this manner.
  • Semantic Object Retrieval Test (SORT): Investigate the potential applications of SORT in neurocognitive assessments. In a gamification manner similar to the above, we could also selectively focus on semantic retrieval. Furthermore, integration of AI generative models could begin to tailor therapeutic stimuli to the individual patient.
  • Behavioral analysis in dementia care: Explore the potential for Board Certified Behavior Analysts (BCBAs) to implement Applied Behavior Analysis (ABA) techniques in the homes of people with dementia.
  • Social cognition assessment integration: Further integrate and analyze the ability of AI to approximate various social cognition assessments, including:
  • Thematic Apperception Task development: Create a new Thematic Apperception Task for assessing narrative abilities in neurocognitive conditions. This could be done on multiple levels, from simple to complex themes. It could be helpful in those with “Weak Central Coherence.”

Advanced Technology and Healthcare

  • Innovating care and research through AI:
    • Conduct analyses focusing on reproducibility and replicability across different AI/ML approaches to communication analysis in neurocognitive disorders.
    • Create an AI-powered chatbot to assist people with disabilities in navigating various aspects of care, including form completion and resource access.
    • Develop a chatbot or AI system to automate the MIR severity assessment for neurocognitive conditions.
  • Bridging tech and medicine: Discuss strategies to bridge the cultural gap between technology and medicine in healthcare innovation.

Conversational and Communicative Analysis

  • Caregiver voice patterns: Investigate whether caregiver voice patterns can predict the diagnosis and behavior of patients with neurocognitive disorders.
  • Conversational phrases: Analyze the use of phrases like “there you go” and other non-specific comments as indicators of conversational understanding or lack thereof.
  • Stereotyped communication signals: Explore the presence and significance of stereotyped communication signals, such as consistent laughter patterns, in neurocognitive conditions.
  • NIH Toolbox integration: Explore ways to integrate the NIH Toolbox into current research methodologies in computational linguistics.
  • Parkinsonism and empathy: Revisit the relationship between Parkinsonism (as measured by the Unified Parkinson’s Disease Rating Scale, UPDRS) and empathy in communication.
  • White matter and neurocognition: Investigate the relationship between viral inflammation and white matter changes in neurocognitive disorders. Compare white matter integrity in linguistic cohesion versus paralinguistic features of communication.
  • MLSE vs. machine learning: Investigate the effectiveness of the Minilinguistic State Exam (designed by Peter Garrard for Primary Progressive Aphasia) compared to machine learning approaches in assessing language impairments.
  • Neurocognitive audio progression: Compare minor and major neurocognitive audio patterns in Mild Cognitive Impairment (MCI) and dementia patients to identify progression markers.
  • Predicting Mild Behavioral Impairment (MBI): Use spontaneous communication analysis, including paralinguistic signals, sentiment analysis, facial expressions, and gestures, to predict the onset of MBI.
  • Attention in childhood and adult word-finding: Investigate the relationship between childhood attention patterns and word-finding abilities in adulthood.

Novel Applications and Community Engagement

  • Art from clock drawings: Explore the possibility of artwork inspired by clock drawing tests to raise awareness and funds for neurocognitive research.
  • Conversational metrics in business: Investigate the application of neurocognitive conversational metrics to assess the success, pitfalls, and perils of business meetings.
  • Improving disability education: Enhance disability-related curriculum in neurology and other medical training programs.
  • Community Action Board best practices: Investigate best practices for transitioning from a Boot Camp Translation model to a Community Action Board foundation in community-based participatory research.

If you’re interested in collaborating on any of these ideas or would like more information, please don’t hesitate to contact me. Your expertise and insights could be invaluable in advancing our understanding of neurocognitive communication disorders and developing innovative interventions.

– CSAND Lab Director, Peter Pressman, MD

Written with assistance from ChatGPT-4.

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