# Development of Episodic Future Thinking: Limits, Flexibility, and Neural Correlates

> **NIH NIH F32** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2020 · $28,590

## Abstract

PROJECT SUMMARY/ABSTRACT
The primary goal of the proposed project is to better understand the development and capacity of episodic
future thinking (EFT). In Aim 1, I will quantify the capacity of EFT in 2-, 3-, and 4-year-olds and examine how
capacity changes as a result of age, and identify the neural correlates of EFT processes. In Aim 2, I will
examine the developmental origins and neural correlates of early EFT using a novel implicit EFT task with 18-
24-month-old infants. In both Aims, EEG will be collected while children and infants complete the episodic
future thinking tasks. The proposed project will be the first to examine the capacity of EFT, the first to examine
the developmental origins of EFT in infancy, and the first to examine the neural signatures of EFT in infancy
and early childhood. We predict that EFT capacity will increase with development. We also predict that infants
(18-24 months) will show evidence of implicitly measured (anticipatory looking) EFT ability. Finally, we expect
that similar neural regions (frontal and temporal) that are active during EFT in adults will be active in children
and infants, and that EEG coherence (functional connectivity) between these regions will increase as age and
EFT capacity increases.

## Key facts

- **NIH application ID:** 10007880
- **Project number:** 5F32HD094554-03
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Tashauna Blankenship
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $28,590
- **Award type:** 5
- **Project period:** 2018-09-01 → 2021-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10007880

## Citation

> US National Institutes of Health, RePORTER application 10007880, Development of Episodic Future Thinking: Limits, Flexibility, and Neural Correlates (5F32HD094554-03). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10007880. Licensed CC0.

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