Itamar Lerner, Sue Peters, Iman Jashanmal, Mark A. Gluck1Center for Molecular & Behavioral Neuroscience, Rutgers University, Newark, NJ, USA

Sleep Mediation of Episodic Memory and Associative Learning: Part I: Preliminary Experimental Results

Experiment II: Probabilistic and Configural Learning

Conclusions and Future Directions

Contact Itamar Lerner, itamar.lerner@gmail.com Mark Gluck, P.I., gluck@pavlov.rutgers.edu

References AcknowledgementsSupported by Grant #7367437 for “Long-term Mobile Monitoring and Analysis of Sleep-Cognition Relationship” from the National Science Foundation’s Smart Health and Wellbeing program to M.A.G..

Born, J., & Wilhelm, I. (2012). System consolidation of memory during sleep. Psychological Research, 76: 192-203.

Medin, D. L., Atom, M. W., Edelson, S. M., & Freko, D. (1982). Correlated symptoms and simulated medical classification. Journal of Experimental Psychology: Learning, Memory, and Cogntion, 8 ,37-50.

Plihal, W. & Born, J. (1997). Sleep after learning aids memory recall. Journal of Cognitive Neuroscience, 9, 534 –547.

Pavel M, Gluck MA, Henkle V, 1988. Generalization by humans and multi-layer networks. Proceedings of the 10th Annual Conference of the Cognitive Neuroscience Society, 680-687.

Tucker, M. A., & Fishbein, W. (2008). Enhancement of declerative memory performance following a daytime nap is contingent on strength of initial task acquisition. Sleep, 31, 197-203.

Wagner, U., Gais, S., Haider, H., Verleger, R., Born, J. (2004). Sleep inspiresinsight. Nature 427, 352–355.

• Percentage of time in SWS and recall performance were correlated in experimental group (r =0.55, p< 0.07), similar to the classic findings found using sleep-labs

• Percentage of time in light sleep and recall performance were inversely correlated in experimental group (r=0.63, p<0.03), possibly because SWS comes on the expense of light sleep within total sleep time

• No correlation was found between recall and REM sleep

• Using the Zeo mobile sleep monitor, we were able to replicate findings from PSG studies which show a correlation between word pair retention and slow wave sleep.

• We found some early support that sleep facilitates rule extraction and insight in a Probabilistic and Configural Categorization Task (however, including demographic details may have hindered results by directing attention away from dimensions)

Future Directions:• Continue to run Paired Associates task with larger number of subjects• Remove demographic details in the Probabilistic and Configural task, and use Zeo to examine

participants’ SWS and REM in relation to performance

Experiment I:Paired-Associates

Behavioral

• Experimental group demonstrated significant improvement in recall between training and test session 1 (s1s2; m=0.0818; P<0.001; Graph A).

• Planned comparisons between experimental and control groups at test session 1 (Graphs A and C) revealed a trend for higher rate of recall in experimental group (p=0.09).

• No other differences reached significance

A. B.

C. D.

• Participants trained, with feedback, on first 8 patterns. Training continued until criterion or 10 epochs (160 trials) ended.

• After 12hrs, participants received additional training, and then test session (no feedback). Testing consisted of 32 trials, two presentations of the 8 stimuli trained on (i.e., retention trials) and of 8 novel stimuli (i.e., generalization trials).

Zeo-measures

Preliminary Results

MethodsMethods

Procedures

Introduction

Background:

General design: Training Sleep/Wake More training

Over the past decade, one night of sleep, traditionally measured at sleep labs with Polysomnography (PSG), has been shown to mediate various cognitive functions, from episodic memory to rule extraction and insight. Long-term study of sleep, however, requires mobile monitoring and multifaceted tasks. Here, we attempted to validate our Zeo mobile sleep-monitoring system and to build a task which would fit multi-night examinations of sleep-cognition relations

Classical findings show that sleep enhances:1.Episodic Memory 2.Rule Learning and Insight

1. Episodic memory: Paired Associates

Recall is better after SWS compared to either wake or Rapid-Eye Movement (REM) sleep (Plihal & Born, 1997)

2. Rule extraction & Insight: Number Reduction Task

Task description: Participants trained on memorizing pairs of words and later tested on recall of the second word based on the first.

Task description: Participants learned to produce a required response to a series of 7 digits based on a serial step-by-step computation over 2 digits at a time

Subjects that slept after first training were far more likely to gain insight into the hidden rule

Subjects in the sleep group that gained insight exhibited brainwaves with unique power spectrum during SWS post-training.

General design: Training Sleep/Wake Testing

Number of words recalled correlated with time spent in SWS (Tucker et al., 1998)

(Wagner et al., 2004)

• A hidden rule unknown to the subjects (last 3 digits always mirror first 3 digits) could allow faster responding if recognized

• Digits are always 1, 4 or 9.• For each 2 digits: If they are the same:

answer with same digit (e.g, 1,1 1 If they differ:

answer with the the third digit (e.g., 1,9 4)

Examine how sleep affects performance in a task which was previously shown to incorporate associative learning, rule extraction, strategy formation and and insight (Medin 1982; Pavel, Gluck, & Henkle, 1988)

Goals

Participants to date: 17 Healthy male undergraduate students ages 18-24. (Experimental group: n=9. Control group: n=8)General Design:

Preliminary Results• Sleep group showed increased accuracy by the end of second

training• Increased accuracy was mostly evident with the difficult patterns (patterns which are inconsistent with dimensions 1 & 2)• One Subject gained insight of the XOR rule in the sleep group.

None in the wake group

Participants to date: 18 Healthy male undergraduate students ages 18-24. (Experimental group: n = 11; control group: n= 7)

GoalsReplicate classic finding of SWS-mediated improvement in Paired-Associates learning, using the Zeo mobile system

General Design:

Accumulated error along training epochs (averaged across subjects) for each pattern during training, and for easy vs. difficult patterns

Born & Wilhelm, 2012

Sleep

Individual Subject Individual Subject

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InsightNo Insight