Reinstatement of Context During Sleep and Its Subsequent Effect on Memory: an fMRI Study
Condition: Sleep; Consolidation
Study type: Interventional

Summary: 
      Memory benefits from sleep and these benefits are putatively achieved through reactivation of
      the neural memory trace during sleep. Studies examining the effects of reactivation commonly
      focus on single, isolated items - but real-life memories never exist in a vacuum. Individual
      memories are bound to the context (e.g., the location, time and state of mind in which they
      are encoded) and this context is later reinstated to recall the details related to the
      memory. The question of how context participated in the process of sleep reactivation has
      never been directly examined. This experiment will monitor brain activity during memory
      encoding, sleep and finally retrieval to investigate the role context plays in sleep-related
      memory consolidation. Monitoring will be done using functional magnetic resonance imaging
      (fMRI) and electroencephalographic (EEG) recordings. Participants will go through a series of
      training trials, in which they will have to learn to associate several small images of items
      or animals with a larger image of scenes - and also learn the spatial location of these
      smaller images on the screen. The order of the presented images and the scenes in which they
      are embedded will remain constant throughout training, creating a solid, consistent temporal
      context in which item memories will be embedded. After training, participants will receive a
      90 minute nap opportunity, during which the sounds associated with specific images will be
      unobtrusively presented. I expect memory for the spatial location of the cued images to
      improve. Importantly, I hypothesize that this effect will carry over to other items
      associated with the same scene (i.e., embedded in the same context) and that the temporal
      order in which the images were learned will govern this effect. I will use the EEG and fMRI
      data to estimate, on the basis of neuronal pattern activity, the level of contextual
      reinstatement and will build on these data, in combination with the behavioral results, to
      model the level of contextual involvement during sleep. These results could pave the way
      towards a unified theory of sleep's role in memory consolidation, which would encompass
      computational models of context and memory as well.
    

Detailed description: 
      Each participant will be run in a single afternoon, which includes a 90-minute nap
      opportunity. This study will be divided into three continuous sessions. The first and third
      sessions will be done inside the MRI scanner, whereas the middle session will be conducted
      outside of the scanner, while recording electrophysiological data. The crucial manipulation
      involves the careful control of temporal context, which is accomplished by preserving the
      temporal order of trials during training and using spatial scenes as markers of context.

      This is a within-subjects study. The main manipulation is the unobtrusive presentation of
      sounds during sleep, a technique called targeted memory reactivation (TMR). All participants
      will hear these sounds, but the specific sounds each one will hear will be different. The
      results will then be compared within participant, not between different groups or
      individuals. Appropriate statistical methods for such analyses include paired t-test and
      repeated measures analysis of variance. The choice of which sounds will be presented to each
      participant will be made based on their performance in the pre-sleep test. This will be done
      in an attempt to balance pre-sleep scores between presented and unpresented stimuli to remove
      statistical noise. Both the participant and the experimenter will be blind to which sounds
      will be presented, and the selection will be automatically made by the computer. This
      technique has been extensively used and has no known risks.

      There are two main reasons that using a within-subject design reduces the required sample
      size. First, the lack of a between-subject independent variable intuitively requires less
      participants. Second, the level of statistical noise due to individual differences is reduced
      (i.e., because each participant is compared with their own scores). Previous TMR studies,
      which have found significant cuing effects, commonly used 20-25 participants. I plan to
      include at least 30 participants in this study, after omitting participants who could not
      complete the task and those who were not sufficiently cued during sleep. Having 30
      participants will allow the use of more powerful statistical methods (in accordance with the
      common rule of thumb derived from the central limit theorem, which states that means based on
      sample sizes of more than 30 participants can be assumed to follow a normal distribution). I
      expect the context-related TMR effect (see summary) to be smaller in magnitude relative to
      the common effect size observed in spatial learning TMR studies (Hedge's g = 0.39 based on a
      recent meta-analysis15). This is why I included a higher sample size. It is important to note
      that even if this benefit will be of a smaller magnitude, as I expect, it will still be
      indicative of the underlying neurocognitive process and therefore extremely valuable for our
      mechanistic understanding of the role of context in sleep. Aiming at a sample size of at
      least 30 participants and assuming an omission rate of 80%, I therefore plan to have 38
      participants altogether.

      Here is a brief summary of the procedure:

      Stimuli: 12 images of spatial scenes (e.g., a beach) will each be arbitrarily associated with
      five smaller images of objects or animals. As described later, half of the scenes will be
      associated with a right hand motion and half with the left - and half of each of these groups
      will be cued during sleep. Each of the 60 images will each have a unique 2D position on a
      circular grid presented on the screen and will be accompanied by a specific, congruent sound
      (e.g., cat - meow).

      fMRI Localizer: After the participant is first put in the scanner and a basic anatomical scan
      is complete, they will be exposed to all the different scenes while being scanned. This will
      later be used to classify scene-specific blood-oxygen-level-dependent (BOLD) responses.

      Training: First, participants will learn to associate scenes with a hand motion. They will
      repeatedly see each scene on either the left or right side of the screen and be asked to
      imagine touching the image on the projected screen. In this and every following training
      block, the scenes will be presented in a participant-specific, non-randomized order. Next,
      participant will be exposed to all 60 images' locations on the grid and asked to associate
      the image with the scene and remember the location. The images for each scene will
      consistently be presented in the same order within the scene, and therefore the order of the
      60 images will be maintained throughout training. The left/right sides of the screen will be
      used for each scene in accordance with its designated hand in the previous training stage.
      After two rounds of exposure, participants will go through a similar positioning phase of
      training. They will be shown the image and the scene and asked to associate them. Then, they
      will see the circular grid without the image on it and asked to imagine touching the correct
      location with the appropriate hand. The next screen will show the image in its correct
      location and ask participants to signal whether or not they knew the location. The next image
      will be presented after a short inter-trial interval. An image's location is considered
      learned when it was marked as correct twice in a row. Blocks will be repeated in the same
      order until all locations are learned. For the images which were already learned, the
      repeated block will employ an alternative task to avoid over-learning while maintaining the
      temporal order of items.

      Pre-sleep test (in scanner): After training, participants will be presented with all images
      in a pseudo-random order and asked to imagine touching their correct location on the grid
      with the appropriate hand.

      Pre-sleep test (EEG): Outside the scanner, the participant will be fitted with an EEG cap and
      then asked to take another test. Here, images will again be randomized and participants will
      first be asked to imagine touching the correct location and then ordered to actually touch
      the correct position. Subsequent measures of change in spatial memory will be based on the
      performance in this test. Throughout the task, the act of imagining the hand motion is not
      used to decode the exact position on the screen in which the participant thinks the item
      should be located. Instead, imagined hand motion will serve as a rough measure of hemisphere
      specific reactivation, that will then be used to classify reactivation during sleep in the
      EEG, as done in 64. Although this decoding will primarily be done using EEG and not fMRI, the
      instructions to imagine hand motion are the same for all phases of the experiment in order to
      maintain consistency throughout the task.

      Sleep: During NREM (non-rapid eye movement) sleep, the sounds associated with specific images
      will be presented unobtrusively. The scenes from which these images will be chosen will be
      half of the right- and half of the left-handed ones. For each of these scenes, one image will
      be cued, positioned in either the 2nd, 3rd or 4th place in that set's training sequence. The
      choice of which sounds to present will be made in a manner that will balance pre-sleep
      results and therefore enhance the contrast between sleep-related effects for cued and
      non-cued images.

      Post-sleep test (EEG): At least 10 minutes after the end of the nap, participants will start
      this test, which will be identical to the Pre-sleep test (EEG).

      Post-sleep test (in scanner): Identical to the Post-sleep test (in scanner). Scene-image
      association test: Finally, participants will be shown each image in a randomized order and
      asked to indicate which of four presented scenes is associated with it.

      fMRI Localizer: Same as the first. Participants will finally be thanked, debriefed, paid and
      dismissed.
    

Intervention name(s): Targeted memory reactivation (sounds)
Intervention type(s): Behavioral
Intervention description(s): I will unobtrusively and repeatedly present learning-related sounds during sleep using speakers. This method was shown to improve memory in various tasks. The sounds will be presented several seconds apart and the volume will be so adjusted as not to disturb the participant's sleep. The sounds will be presented during non-rapid eye movement sleep (sleep stage 2 and slow wave sleep). The sounds presented will be congruently related to the images in the previous learning task. This manipulation is within-subject - all participants will get it, but different specific sounds will be presented for each individual participant.
Intervention model: Single Group Assignment
Masking: None (Open Label)
Primary purpose: Basic Science