# The scope, cause and consequences of age-related decline in neural distinctiveness and brain signal variability in healthy and pathological aging (Funded Extension)

> **NIH NIH F99** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $27,757

## Abstract

Project Summary
Normal aging is typically associated with pervasive declines in cognitive, motor and sensory function, however,
there are substantial individual differences: some older adults experience mild impairments while others
experience severe cognitive declines. Understanding the neural bases of individual differences during aging is
imperative in designing future interventions to address age-related cognitive impairments. Using behavioural
testing, functional MRI, spectroscopy and pharmacological manipulations in human adults, I propose to
investigate the scope, cause and consequences of age-related decline in two neural factors that may play a
role in these individual differences: (1) neural distinctiveness (how similar/confusable neural activation patterns
are in response to different stimulus categories) and (2) brain signal variability (moment-to-moment change in
neural activity independent of task). Both these measures have been found to decline with age and both have
been associated with individual differences in behavior. During the predoctoral (F99) phase of the training, my
research will focus on healthy aging: 1) investigating the scope and cause (specifically role of GABA levels) of
age-related decline in neural distinctiveness in sensory regions, 2) the cause of age-related declines in brain
signal variability, and 3) the behavioral consequences of age-related declines in these two neural measures.
During the postdoctoral (K00) phase, I will extend my previous research to again study neural distinctiveness
and brain signal variability, but now in the context of memory and hippocampal dysfunction, and in a clinical
population (patients with Mild Cognitive Impairment, MCI). I will use task-based fMRI to measure neural
distinctiveness, resting-state fMRI to measure brain signal variability, and MR spectroscopy to measure levels
of various neurotransmitters (including glutamine, glutamate, NAA, and GABA), all in the hippocampus, in
healthy younger and older adults as well as MCI patients. I will also collect behavioral data from the same
participants during the Mnemonic similarity task (MST), a highly sensitive measure of hippocampal dysfunction.
I propose to investigate a) age-related changes in neural distinctiveness and resting state variability in the
hippocampus, b) the neurochemical basis of these neural changes, and c) the behavioral and pathological
consequences of these neural changes. For all the MCI patients, I will also have access to a rich dataset of
other biomarkers (e.g., longitudinal measures of CSF and PET-based amyloid and tau) collected at UCI’s
Alzheimer’s Disease Research Center (ADRC). I will therefore be able to examine neural distinctiveness and
brain signal variability in the context of the Amyloid Tau Neurodegeneration (biomarker profiling) Framework.
Together, this research could lead to the development of preclinical markers for AD and open new avenues for
early pharmacological interventions to treat ...

## Key facts

- **NIH application ID:** 10399334
- **Project number:** 3F99AG068517-01S1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Poortata Shirish Lalwani
- **Activity code:** F99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $27,757
- **Award type:** 3
- **Project period:** 2021-09-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10399334

## Citation

> US National Institutes of Health, RePORTER application 10399334, The scope, cause and consequences of age-related decline in neural distinctiveness and brain signal variability in healthy and pathological aging (Funded Extension) (3F99AG068517-01S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10399334. Licensed CC0.

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