Twenty-two (9 female) right-handed native English speakers with normal or corrected-to-normal vision participated in the experiment (mean age: 24 years, range: 18-32). Informed consent was obtained in a manner approved by the institutional review board at New York University and subjects were paid for their participation. Three subjects were excluded from all analyses due to early termination of the experiment.
The stimulus set consisted of 336 English adjectives, 224 of which served as study items and 112 of which served as lures during a recognition memory test. To select these adjectives, we had 5 subjects rate the difficulty of imagining a set of 496 adjectives as either an object or a scene (between-subjects design) on a five-point scale (see below). The rating for each adjective was then z-transformed within subjects and a difference score for object vs. scene imagery was calculated across subjects. The 336 adjectives with the smallest difference scores, meaning adjectives that were most similarly imaginable for objects and scenes across subjects, were included in the final stimulus list (mean difference score = .39). Thus, we controlled for imagery difficulty across object and scene trials. For counterbalancing purposes, these 336 adjectives were divided into 3 lists of 112 adjectives each, and the assignment of ‘object image,’ ‘scene image,’ or ‘test lure’ to each adjective was rotated across subjects.
For each scanned 5-second encoding trial, subjects were presented with an adjective in black letters on a white background along with the cue ‘OBJECT’ or ‘SCENE’ above the adjective (). The order of object and scene trials was randomized. After 3.5 seconds, the adjective and cue disappeared and a rating screen was displayed for the remaining 1.5 seconds, showing the cue ‘RATING’ followed by the options ‘0 - 1 - 2 - 3 - 4’. Subjects were instructed to vividly imagine an object or a scene (depending on the cue) that could be described by the adjective for the entire 3.5 seconds and to indicate their success in the remaining 1.5 seconds via a button-press. Trials for which no response was given within the 1.5 seconds answering period were excluded from all analyses (average 3% +/− 1% across subjects). We encouraged subjects to focus only on objects or scenes, respectively, by instructing, “[…] For example, if the adjective is “dirty” and the cue is “object”, you should vividly imagine a dirty object, such as a full garbage can. Conversely, if the cue is “scene”, you should vividly imagine a dirty scene or place, such as a garbage dump or a messy room. It is crucial that for object trials, you only focus on imagining an object, without embedding it into a scene image. For scene trials, please avoid incorporating people into the scene if at all possible. Instead, focus on imagining a vivid spatial environment that describes the adjective.” For the imagery rating, the instructions were: “To rate the quality of your mental image, decide where it would fit on a scale from 0 to 4, where 0 indicates the failure to come up with a vivid mental image and 4 indicates that you successfully conjured up a vivid and detailed mental image.”
Following the encoding session, subjects were given an unscanned and self-paced surprise recognition memory test (), consisting of all 224 previously presented adjectives as well as 112 novel adjectives (lures). First, subjects were instructed to indicate whether the adjective was old (presented during the encoding session) or new (not presented during the encoding session). For adjectives endorsed as old, subjects were then prompted to indicate the imagery task with which they had encountered the adjective (object or scene imagery) including confidence ratings. Answer options were ‘sure object’ - ‘unsure object’ - ‘?’ - ‘unsure scene‘ - ‘sure scene’. Note that subjects were not forced to guess but could indicate they do not know the corresponding source (‘?’ response). This testing protocol was used to sort the scanned encoding trials based on successful and unsuccessful source encoding as a function of representational domain (object vs. scene trials). Successful and unsuccessful source encoding were operationalized by considering both accuracy and confidence during the subsequent source test: Trials leading to correct-‘sure’ responses were defined as successful source encoding and trials leading to incorrect-‘unsure’ or ‘?’ responses were defined as unsuccessful source encoding. Correct-‘unsure’ and incorrect-‘sure’ responses were not included in the analysis due to the ambiguous combination of accuracy and confidence. However, the results reported below remain the same when segmenting trials into ‘correct’ vs. ‘?/incorrect’ source memory, without taking confidence ratings into account. The item recognition component allowed us to isolate source memory by including only trials with successful item memory (i.e., ‘Hits’) but, since we are interested in differential source encoding effects across MTL regions, trials leading to unsuccessful item memory (i.e., ‘Misses’) are not considered further herein. Thus, to reiterate, our main conditions of interest were (i) successful source encoding, object trials, (ii) unsuccessful source encoding, object trials (iii) successful source encoding, scene trials and (iv) unsuccessful source encoding, scene trials, together representing a 2 (successful vs. unsuccessful source encoding) × 2 (object vs. scene trials) factorial design.
MRI scanning and data analysis
Scanning was performed on a 3-T Siemens Allegra MRI system using a whole-head coil. Functional data were acquired using a gradient-echo, echo-planar pulse sequence (TR = 1500 msec, TE = 30 msec, 27 slices oriented perpendicular to the hippocampal axis, 3 × 3 × 3 mm voxel size, 0.6 mm inter-slice gap, 317 volume acquisitions per run). The first eight volumes of each run were discarded to allow for magnetic field stabilization. High-resolution T1-weighted (MP-RAGE) images were collected for anatomical visualization. Foam padding was used to minimize head motion. Visual stimuli were projected onto a screen that was viewed through a mirror, and responses were collected with a magnet-compatible button box placed under the subject’s left hand.
The scanned encoding portion of the experiment was divided into eight runs, each encoding run consisting of 28 trials. Stimuli were presented in a slow event-related fashion, with each encoding trial followed by a sensorimotor baseline task [‘arrows-task’ (Stark and Squire, 2001
)]. Here, a sequence of arrows that randomly pointed to the left or to the right for 1 second was presented for the length of a baseline trial (10–13 seconds), and subjects pressed the left middle finger key if the arrow pointed to the left and the left index finger key if it pointed to the right.
Data were analyzed using SPM5 (Wellcome Department of Cognitive Neurology, London). During preprocessing, images were corrected for differences in slice acquisition timing, followed by motion correction across all runs. Structural images were co-registered to mean functional images resulting from motion correction. For the standard whole-brain analysis (see below), preprocessing further included spatial normalization of the co-registered structural image to a T1 template provided in SPM5. The resulting normalization parameters were then applied to the functional images, followed by spatial smoothing with a 6-mm full-width, half-maximum isotropic Gaussian kernel.
For statistical analyses, we used two separate analysis approaches: First, to assess the pattern of activation across the parahippocampal gyrus (PhG) while taking each subject’s MTL anatomy into account, we employed a hand-drawn anatomical region of interest (ROI) approach. Here, data were not normalized or smoothed during preprocessing. Based on each subject’s T1-weighted structural scan, we segmented the PhG into three equidistant portions: An anterior portion (ant-PhG) covering perirhinal cortex (PrC), a posterior portion (post-PhG) covering parahippocampal cortex (PhC), and a mid-PhG portion covering the transition between PrC and PhC. Anatomical demarcation was performed according to Insausti et al. (1998)
and Pruessner et al. (2002)
, starting at the most anterior portion of the PrC and ending at the most posterior portion of the PhC at the level of the posterior hippocampus. For each condition of interest, percent signal change relative to baseline was extracted within the resulting six ROIs (left and right ant-PhG, mid-PhG, post-PhG) via the MarsBaR toolbox (Brett et al., 2002
Second, to complement the ROI analysis and to query additional MTL regions, we employed a standard whole-brain General Linear Model (GLM) approach. Here, neural activity was modeled via boxcar functions spanning the 3.5 second imagery period and convolved with a canonical hemodynamic response function together with its first-order temporal derivative. The resulting vectors were then entered as regressors into a fixed-effects GLM together with nuisance regressors modeling run means and scanner drift after concatenating the eight encoding runs. Parameter estimates (beta weights) for each condition of interest were derived for each subject and carried forward to a second-level group analysis. Here, individual subjects’ beta weights for the four conditions of interest were entered into a repeated-measures ANOVA, and domain-preference during source encoding was assessed via directed contrast- and masking analyses (further detailed below).
Additional behavioral study
Given our behavioral results (see below), we conducted a separate behavioral study to directly assess the contributions of recollection and familiarity to source memory decisions in the current paradigm. Eleven (7 female) right-handed native English speakers with normal or corrected-to-normal vision participated in the experiment (mean age: 22 years, range: 19-26). Informed consent was obtained in a manner approved by the institutional review board at New York University and subjects were paid for their participation. One subject was excluded from all analyses for not responding on 34% of the trials and only giving imagery ratings of 4 on the remaining trials. The results, however, are unaffected by inclusion or exclusion of that subject. The same adjectives were used as in the main fMRI experiment. The encoding procedures were modified in two ways: first, we reduced the duration of the intervening arrows trials to 4 sec. Second, because we did not use lures during retrieval, all 336 adjectives were shown during the encoding session. Importantly, we modified the testing protocol to directly assess recollection and confidence levels for subjects’ source memory answers. Upon being presented with an adjective, subjects had six response options: recollect object - high confidence object - low confidence object - low confidence scene - high confidence scene - recollect scene. Subjects were instructed to use recollection and confidence in the following manner
“Recollection indicates that you recall specific details about the study phase including memory for the mental image that you generated on the study trial or any other details about the study phase that indicates whether you imagined an object or a scene. High and low confidence indicate that you are very sure or moderately sure, respectively, that you imagined an object or a scene, without being able to recollect specific details. Is this distinction clear? Please explain in your own words.”
Like for the main fMRI study, the retrieval portion was self-paced.