Resting-state for 34 younger and 28 older adults

# Intrinsic Functional Connectivity and Mnemonic Discrimination Dataset

This repository contains data associated with the study:

**“Intrinsic functional connectivity in the default mode network predicts mnemonic discrimination: A connectome-based modeling approach”**
(Wahlheim, Christensen, Reagh, & Cassidy, 2022)

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## Overview

This dataset includes behavioral and neuroimaging data used to examine how intrinsic functional connectivity within the default mode network (DMN) predicts mnemonic discrimination ability across younger and older adults.

The study applies connectome-based predictive modeling (CPM) to link resting-state functional connectivity with memory performance.

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## Dataset Contents

- Resting-state fMRI connectivity matrices (DMN + hippocampal regions)
- Behavioral task performance data:
- Mnemonic Similarity Task (MST)
- Perceptual Discrimination Task (PDT)
- Derived cognitive indices:
- Lure Discrimination Index (LDI)
- Recognition scores
- Perceptual discrimination scores
- ROI definitions and connectivity features
- Analysis scripts (if included)

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## Participant Demographics

### Sample Size
- Total participants: 62
- Younger adults: 34 (sub-10xx)
- Older adults: 28 (sub-20xx)

### Age
- Younger adults:
- Range: 18–32 years
- Mean: 22.21 (SD = 3.65)

- Older adults:
- Range: 61–80 years
- Mean: 69.82 (SD = 5.64)

### Gender
- Younger adults: 20 female
- Older adults: 20 female

### Inclusion Criteria
- Right-handed
- No recent history of neurological disorders
- Cognitively healthy (MoCA ≥ 26)

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## Cognitive and Educational Measures

| Measure | Younger Adults (Mean ± SD) | Older Adults (Mean ± SD) |
|----------------------|---------------------------|---------------------------|
| Years of Education | 15.85 ± 2.50 | 15.75 ± 2.29 |
| Vocabulary | 29.03 ± 3.97 | 33.64 ± 3.12 |
| Processing Speed | 78.26 ± 13.27 | 63.36 ± 12.58 |
| Digit Span (Forward) | 8.71 ± 2.14 | 8.00 ± 2.09 |
| Digit Span (Backward)| 7.38 ± 2.22 | 6.82 ± 1.74 |
| MoCA Score | 28.26 ± 1.42 | 27.68 ± 1.39 |

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## Experimental Tasks

### Mnemonic Similarity Task (MST)

Participants:
- Encode images of everyday objects
- Classify test items as:
- Old (exact repeats)
- Similar (lures)
- New (novel)

Key metric:
- Lure Discrimination Index (LDI) = p(similar|lure) − p(similar|foil)

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### Perceptual Discrimination Task (PDT)

Participants judge whether object pairs are:
- Same
- Similar
- Different

This task controls for perceptual processing differences.

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## Neuroimaging Data

- Modality: Resting-state fMRI
- Scanner: Siemens 3T MRI
- Duration: ~10 minutes per participant
- Preprocessing: CONN toolbox pipeline

### Regions of Interest (ROIs)
- Default Mode Network (DMN) regions (Schaefer atlas)
- Hippocampal subregions:
- Head
- Body
- Tail (bilateral)

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## Modeling Approach

- Method: Connectome-Based Predictive Modeling (CPM)
- Goal: Predict mnemonic discrimination (LDI) from functional connectivity
- Cross-validation: Leave-one-subject-out

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## Key Findings (Summary)

- DMN connectivity predicts mnemonic discrimination
- Strongest contributions from temporal and prefrontal–temporal connections
- Younger adults show stronger predictive connectivity than older adults
- DMN connectivity does not predict recognition or perceptual discrimination

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## Data Access

Behavioral data, connectivity matrices, and scripts are available via:
- Open Science Framework (OSF)
- OpenNeuro

(Add direct links here if applicable)

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## Citation

Wahlheim, C. N., Christensen, A. P., Reagh, Z. M., & Cassidy, B. S. (2022).
Intrinsic functional connectivity in the default mode network predicts mnemonic discrimination: A connectome-based modeling approach.
Hippocampus, 32, 21–37.
https://doi.org/10.1002/hipo.23393

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## Notes

- Data are anonymized and intended for research use only
- Follow all applicable data use agreements and ethical guidelines