Georgetown University
Archakov_DeWitt_Kusmierek_et_al_2020_PNAS
The data include a T1 map, a functional dataset with multiple contrasts, and an aligned D99 atlas, plus additional functional dataset from monkey Ra (early training). Functional datasets are unthresholded statistical maps。
Usage Agreement
Creative Commons – Attribution-NonCommercial Share Alike (CC-BY-NC-SA)- Standard INDI data sharing policy. Prohibits use of the data for commercial purposes.
Species
Macaca mulatta
Sample Description (data were collected over several years)
- Sample size: 2
- Ra: male, 8-13 years
- Do: female, 6-9 years
Scanning preparations
Anesthesia procedures:
Anatomical scans: anesthetized, isoflurane anesthesia.
Functional scans: awake, performing auditory discrimination task under attentional control by saccade task.
Scan sequences
- Anatomical:
- T1
- Sequence: MP-RAGE sequence
- 4-5 averages
- Voxel resolution: 0.5 x 0.5 x 0.5 mm
- TE: 3.0ms
- TR: 2500ms
- Flip angle: 8°
- FOV: 116 × 96 × 128
- Matrix size: 232 × 192 × 256
- Functional:
- Sequence: interleaved single-shot gradient-echo echo-planar (GE-EPI) sequence
- 4-5 averages
- Voxel resolution: 0.5 x 0.5 x 0.5 mm
- TE: 34ms
- TR: 2180ms
- Flip angle: 90°
- FOV: 100 × 100
- Matrix size: 66 × 66
- Slice thickness: 1.9mm
- Collection Voxel size: 1.5 × 1.5 × 1.9
- Resampled Voxel size: 0.5 × 0.5 × 0.5
Publications
Personnel
- Denis Archakov, PhD
- Iain DeWitt, PhD
- Paweł Kuśmierek, PhD
- Michael Ortiz-Rios, PhD
- John W. VanMeter, PhD
- Mikko Sams, PhD
- Iiro P. Jääskeläinen, PhD
- Josef P. Rauschecker, PhD (PI)
Acknowledgements
Elyse Morin, Ding Cui, and Dr. Daniel Cameron contributed to the data acquisition and/or analysis. We thank Drs. Max Riesenhuber, Peter Turkeltaub, Xiong Jiang and Ms. Jessica Jacobs for comments on the manuscript, Dr. Lars Rogenmoser for advice on EMG recordings, and Jeff Bloch for help with data collection and analysis.
Funding
NIH R01DC014989
NSF PIRE-OISE-0730255
Academy of Finland #276643
Downloads
Click here to download the data. Users will first be prompted to log on to NITRC and will need to register with the 1000 Functional Connectomes Project website on NITRC to gain access to the PRIME-DE datasets.