DOI: 10.5061/dryad.b2rbnzsr2
title: Data for: Hippocampal encoding of memories in human infants

description: Humans lack memories of specific events from the first few years of life.
 We investigated the mechanistic basis of this infantile amnesia by
 scanning the brains of awake infants with functional magnetic resonance
 imaging while they performed a subsequent memory task. Greater activity in
 the hippocampus during the viewing of novel photographs was related to
 later memory-related looking behavior beginning around one year of age,
 suggesting that the capacity to encode individual memories comes online
 during infancy. The availability of encoding mechanisms for episodic
 memory during a period of human life that is later lost from our
 autobiographical record implies that post-encoding mechanisms, whereby
 memories from infancy become inaccessible for retrieval, may be more
 responsible for infantile amnesia.
description: # Data for: Hippocampal encoding of memories in human infants --- Yates,
 T. S., Fel, J., Choi, D., Trach, J. E., Behm, L., Ellis, C. T., &
 Turk-Browne, N. B. Hippocampal encoding of memories in human infants. This
 directory contains de-identified raw and preprocessed infant fMRI data for
 our project on one-shot visual memory. The scripts located at
 [https://github.com/ntblab/infant_neuropipe/tree/SubMem_Categories/](https://github.com/ntblab/infant_neuropipe/tree/SubMem_Categories/) were used to run the analyses. The scan sequences are as follows: * PETRA: TR1 = 3.32 ms, TR2 = 2250 ms, TE = 0.07 ms, flip angle = 6 degrees, matrix = 320 x 320, slices = 320, resolution = 0.94 mm isotropic, radial slices = 30,000 * T2* gradient-echo EPI: TR = 2 s, TE = 30 ms, flip angle = 71 degrees, matrix = 64 x 64, slices = 34, resolution = 3 mm isotropic, interleaved slice acquisition All files with the suffix '.nii.gz' or '.nii' can be opened using the freely-available fMRIB Software Library ([https://fsl.fmrib.ox.ac.uk/fsl/fslwiki](FSL)) or open-source software FreeSurfer ([https://surfer.nmr.mgh.harvard.edu/](FreeSurfer)). ## Description of the data and file structure Files in these folders contain raw and preprocessed infant fMRI data. Participant-specific files are labeled with the participant code at the start. The final number (_X) reflects the session number. These infant participant IDs are consistent across datasets from the NTB Lab. Run numbers indicate the nth run that was retained in that participant's session. If the number has a letter after it (e.g. functional03a) then that indicates it is a pseudorun and there is other data from this run that has been removed (because it pertained to another task, not reported here). All data within a run is continuous, no interleaved time points were removed. * **hipp_vol_information.csv**: Summary table of the volume and length of the hippocampus and medial temporal lobe regions created through infant ASHS, including the participant ID, participant age (in months), the volume of the regions (mm^3), the length of the regions (mm), and the location of the centroid in MNI space. Values in the final three columns are in the order: left hippocampus, right hippocampus, left MTL, right MTL. * **participant_information.csv**: Summary table of the participant information, including the participant ID, participant age (in months), participant sex (male or female), the proportion of TRs that were usable after motion exclusion (prop_TR_motion), the proportion of frames in which the infant was looking on-screen (prop_looking), the proportion of frames that were coded the same between gaze coders (eye_reliability), the number of gaze coders (num_coders), the number of total encoding trials that were usable (Encode_Trials), and the number of trials in which infants showed a familiarity/novelty preference (Familiar_Pref and Novel_Pref). * **anatomicals_masked**: Anatomical images used for alignment. Facial information has been stripped for anonymity by masking the anatomical image with a manually-tuned brain mask. These were collected using the PETRA sequence for infants. In some cases, more than one scan has been averaged to improve quality. * **contrast_maps**: Statistical (z-statistic) maps for each participant used as the input to the ROI and whole-brain analyses. Folders are separated by the different statistical analyses (GLMs) that were run (listed below). All files are in MNI 152 1mm space (and labeled as ''registered_standard'') and thus aligned across participants. - **Binary** and **Binary_Unique**: *zstat1*: Novelty-preference encoding trials &gt; GIF baseline; *zstat2*: Familiarity-preference encoding trials &gt; GIF baseline; *zstat3*: Visual paired comparison test trials &gt; GIF baseline; *zstat4*: Familiarity-preference encoding trials &gt; Novelty-preference encoding trials; *zstat5*: Novelty-preference encoding trials &gt; Visual paired comparison test trials; *zstat6*: Familiarity-preference encoding trials &gt; Visual paired comparison test trials; *zstat7*: Familiarity-preference and Novelty-preference encoding trials &gt; Visual paired comparison test trials * **Binary_Categories**: *zstat1*: All Novelty-preference encoding trials &gt; GIF baseline; *zstat2*: All Familiarity-preference encoding trials &gt; GIF baseline; *zstat3*: Visual paired comparison test trials &gt; GIF baseline; *zstat4*: All Familiarity-preference encoding trials &gt; All Novelty-preference encoding trials; *zstat5*: Familiarity-preference encoding trials (Faces) &gt; Novelty-preference encoding trials (Faces); *zstat6*: Familiarity-preference encoding trials (Objects) &gt; Novelty-preference encoding trials (Objects); *zstat7*: Familiarity-preference encoding trials (Places) &gt; Novelty-preference encoding trials (Places); *zstat8*: Novelty-preference encoding trials (Faces) &gt; Novelty-preference encoding trials (Objects); *zstat9*: Novelty-preference encoding trials (Faces) &gt; Novelty-preference encoding trials (Places); *zstat10*: Novelty-preference encoding trials (Objects) &gt; Novelty-preference encoding trials (Places); *zstat11*: Familiarity-preference encoding trials (Faces) &gt; Familiarity-preference encoding trials (Objects); *zstat12*: Familiarity-preference encoding trials (Faces) &gt; Familiarity-preference encoding trials (Places); *zstat13*: Familiarity-preference encoding trials (Objects) &gt; Familiarity-preference encoding trials (Places) * **Binary_DelayLength**: *zstat1*: All Novelty-preference encoding trials &gt; GIF baseline; *zstat2*: All Familiarity-preference encoding trials &gt; GIF baseline; *zstat3*: Visual paired comparison test trials &gt; GIF baseline; *zstat4*: All Familiarity-preference encoding trials &gt; All Novelty-preference encoding trials; *zstat5*: Familiarity-preference encoding trials (Short Delay) &gt; Novelty-preference encoding trials (Short Delay); *zstat6*: Familiarity-preference encoding trials (Long Delay) &gt; Novelty-preference encoding trials (Long Delay); *zstat7*: Familiarity-preference encoding trials (Short Delay) &gt; Familiarity-preference encoding trials (Long Delay); *zstat8*: Novelty-preference encoding trials (Short Delay) &gt; Novelty-preference encoding trials (Long Delay) * **Binary_Retrieval**: *zstat1*: Novelty-preference test trials &gt; GIF baseline; *zstat2*: Familiarity-preference test trials &gt; GIF baseline; *zstat3*: All encoding trials &gt; GIF baseline; *zstat4*: Familiarity-preference test trials &gt; Novelty-preference test trials; *zstat5*: Novelty-preference test trials &gt; All encoding trials; *zstat6*: Familiarity-preference test trials &gt; All encoding trials; *zstat7*: Familiarity-preference and Novelty-preference test trials &gt; All encoding trials * **Control**: *zstat1*: All encoding trials &gt; GIF baseline; *zstat2*: All visual paired comparison test trials &gt; GIF baseline; *zstat3*: All visual paired comparison test trials &gt; All encoding trials; *sigmasquareds*: residual variance from the GLM model * **LowHighPref**: *zstat1*: Low (weak) preference encoding trials &gt; GIF baseline; *zstat2*: High (strong) preference encoding trials &gt; GIF baseline; *zstat3*: Visual paired comparison test trials &gt; GIF baseline; *zstat4*: High (strong) preference encoding trials &gt; Low (weak) preference encoding trials; *zstat5*: Low (weak) preference encoding trials &gt; Visual paired comparison test trials; *zstat6*: High (strong) preference encoding trials &gt; Visual paired comparison test trials; *zstat7*: Low (weak) and High (strong) encoding trials &gt; Visual paired comparison test trials * **Parametric**: *zstat1*: Parametric familiarity preference during encoding trials; *zstat2*: Main effect of encoding (All encoding trials &gt; GIF baseline); *zstat3*: Main effect of test (Visual paired comparison test trials &gt; GIF baseline) * **Parametric_Retrieval**: *zstat1*: Parametric familiarity preference during test trials; *zstat2*: Main effect of test trials (All visual paired comparison test trials &gt; GIF baseline); *zstat3*: Main effect of encoding (All encoding trials &gt; GIF baseline) * **Task**: *zstat1*: All trials (encoding and test) &gt; GIF baseline; *zstat2*: Face trials (encoding and test) &gt; GIF baseline; *zstat3*: Object trials (encoding and test) &gt; GIF baseline; *zstat4*: Place trials (encoding and test) &gt; GIF baseline; *zstat5*: Face trials &gt; Object trials; *zstat6*: Face trials &gt; Place trials; *zstat7*: Place trials &gt; Object trials * **looking_behavior**: MATLAB files containing a summary of infants' looking behavior across the task, as coded manually by gaze coders. These files can still be opened without an active MATLAB license (by using the function `loadmat` from Scipy in Python --- see code notebook for example). This structure contains the following information: the agreed-upon gaze code for each frame in each trial of the experiment ('Timecourse_All'), the trial and block number for each trial ('TrialNames'), the index in the timecourse at which a trial starts ('TrialOnsets'), the index in the timecourse at which a trial stops ('TrialOffsets'), the median frame duration ('MedFrameDur'), the stimulus/stimuli that were shown on that trial ('StimNames'), the image category of face, place, or object ('StimCategory'), whether or not the trial was a visual paired comparison test trial or encoding trial ('isVPC'), the side of the VPC that contained the familiar image if this was a test trial ('VPCSide'), the encoding trial in which infants saw the image at test if this was a test trial ('Encode_VPC_Pair'), the delay between encoding and test in seconds if this was a test trial ('Encode_VPC_Delay'), whether the trial should be usable based on looking at the screen ('EyeInclude'), whether the trial should be usable based on low motion ('MotionInclude'), and the reliability in gaze coding between gaze coders ('Reliability'). * **masks**: Contains nifti files for the standard-space regions of interest as well as the intersect brain mask across participants. Fusiform face area ('bilateral_FFA'), occipital object area ('bilateral_OOA'), and parahippocampal place area ('bilateral_PPA') were created by making 10 mm radius spheres at the peak activation values from [https://neurosynth.org/](Neurosynth) meta-analyses maps for "face", "object," and "place," respectively. * **plots**: Empty folder to contain figures created from the notebook. * **randomise**: Outputs of the whole-brain group level analysis of statistical maps for contrasts (using the numbering and folder structure described for contrast_maps above; with the exception of 'Binary_Unique' since not enough participants would be included) created using FSL's randomise function. Analyses were either run across all subjects ('all') or within the different age groups ('younger' or 'older'). Files with a name that contains 'corrp' visualize the one minus p-values for a given correction technique (e.g., threshold-free-cluster-enhancement, or TFCE); otherwise, values are the estimated t-statistics without correction. In all cases, a one-sample t-test (i.e., a sign flip test) was run with randomise, so 'tstat1' refers to the given contrast and 'tstat2' refers to the reverse contrast (e.g., Task/zstat5_all_tstat1.nii.gz: Face &gt; Object; Task/zstat5_all_tstat2.nii.gz: Object &gt; Face). * **raw_nifti:** Raw functional data for each run where task data was collected in these participants. If another task, not reported here, was completed in the same run then a pseudo-run was created in which the TRs corresponding to this task were sliced and separated. * **raw_timing**: Timing information for the start of each block and event for each participant. For each file the first column is the onset of the event or block, the second column is the duration of the event or block and the third column is the weight. Each participant has many timing files according to different ways of looking at the task and their behavior. 'Block' has the timing for the entire block of the task. 'Condition_Encode' and 'Condition_VPC' have the timing for the encoding trials and visual paired comparison test trials, respectively. 'Condition_Faces' 'Condition_Places' and 'Condition_Objects' have the timing for those three visual categories, respectively. All other timing files are created based on the participants' looking behavior for different trials. 'NovelPref' means a preference for the new item atthe test, 'FamiliarPref' means a preference for the old item at the test, 'LowPreference' means weak preferences in either direction, and 'HighPreference' means strong preferences in either direction. These files can be separated by stimulus category (Faces, Places, and Objects) or delay between encoding and test (ShortDelay and LongDelay). Some participants have additional timing files labeled 'Unique' to mark the encoding trials that showed unique images from previous sessions (due to a coding error affecting 5 subjects, a small number of images may have been repeated over repeat sessions). 'Parametric' has the timing for usable encoding trials with the last column being a z-scored parametric regressor based on the amount of familiar looking and 'Parametric_MainEffect' is identical with the last column containing 1s to model the main effect. Files with 'Test' in the name have timing for the test trials (rather than the encoding trials) based on the behavior listed. Please reference the code for more details. **run_burn_in.txt**: File with subject name, functional run, and number of TRs in the burn-in for that run (by default, it should be 3, but it may differ) **segmentations_native**: Contains nifti mask files for the left/right hippocampus and MTL registered to a participant's native brain space. These files were created by applying the ANTs transformations (described below) to the standard space segmentations from ASHS. **segmentations_standard**: Contains nifti mask files for the left/right hippocampus and MTL as created by running an infant-trained ASHS on each participant's high-resolution anatomical image (registered to standard space). Files with the suffix '-TY_ant' have been manually segmented further into anterior and posterior hippocampal subregions (defined by a line drawn perpendicular to the edge of the hippocampal head). **transformation_mats**: The 4x4 affine transformation matrix (in .mat format) to align each functional in raw_nifti to the high-resolution anatomical for that participant. NOTE: Files with the suffix '.mat' in this folder are not MATLAB files, but rather files that are used by FSL to align brain images. **transformation_ANTs**: Contains ANTs folders for each participant. These were created by run_ANTs_highres2standard.sh and were used to create the nonlinear registration to infant standard and linear registration to adult MNI standard. NOTE: Files with the suffix '.mat' in these folders are not MATLAB files, but rather files that are used by FSL to align brain images. * **example_func2highres.nii.gz**: functional image of the centroid TR that minimizes the Euclidian distance between TRs aligned to highres anatomical space * **example_func2infant_standard.nii.gz**: functional image of the centroid TR that minimizes the Euclidian distance between TRs aligned to infant standard space * **example_func2standard.nii.gz**: functional image of the centroid TR that minimizes the Euclidian distance between TRs aligned to adult MNI standard space * **example_func.nii.gz**: functional image of the centroid TR in its native 3mm space * **fs_alignment.mat**: transformation matrix that aligns fs_vol.nii.gz to highres_brain.nii.gz (6 degrees of freedom) * **fs_brain.nii.gz**: freesurfer-outputted highres anatomical image rotated and masked to only show brain voxels * **fs_vol.nii.gz**: freesurfer-outputted highres anatomical image in 1mm space * **highres2infant_standard_0GenericAffine.mat**: transformation matrix used to move from highres to infant standard space * **highres2infant_standard_1InverseWarp.nii.gz**: warp file used by ANTs to move from infant standard space to highres * **highres2infant_standard_1Warp_3mm.nii.gz**: warp file used by ANTs to move from high resolution to infant standard space (while maintaining 3mm functional space) * **highres2infant_standard_1Warp.nii.gz**: warp file used by ANTs to move from high resolution to infant standard space * **highres2infant_standard_InverseWarped.nii.gz**: infant standard image aligned to highres space via ANTs * **highres2infant_standard_Warped.nii.gz**: highres anatomical image aligned to infant standard space via ANTs * **highres2standard.nii.gz**: highres anatomical image aligned to adult MNI standard space * **infant_standard2standard.mat**: linear transformation matrix between infant standard and adult MNI standard space * **highres_brain.nii.gz**: highres anatomical image masked to only show brain voxels * **infant_standard.nii.gz**: infant standard image, determined based on the child's age * **mask.nii.gz**: mask to facilitate anatomical alignment to standard, manually edited from freesurfer output ## Sharing/Access information All data needed to replicate the analyses have been provided here. Hippocampal segmentations were created using an infant-trained ASHS model. More information on this model including how to download and use it can be found here: [https://datadryad.org/stash/dataset/doi:10.5061/dryad.05qfttf6z](https://datadryad.org/stash/dataset/doi:10.5061/dryad.05qfttf6z). ## Code/Software The scripts in the infant_neuropipe repository can be used to run the analyses reported in the paper. The SubMem_Categories.ipynb notebook can regenerate the figures. Scripts in that directory can rerun the analyses, refer to the notebook and analysis README for more direction. Questions about the data or analyses can be directed to Tristan Yates, [tsy2105@columbia.edu](mailto:tsy2105@columbia.edu) (long-term email: [tristansyates@gmail.com](mailto:tristansyates@gmail.com))