Peer Reviewed Journal Publications

Lerner, I., Lupkin, S.M., Tsai, A. & Gluck, M.A. (2021). Sleep to Remember, Sleep to Forget: Opposite Effects of Rapid Eye Movement Sleep on Recall and Discrimination of Fear Memories. Neurobiology of Learning and Memory, 180, 107413.

Praveen, P.K., Skorheim, S.W, Hubbard, R.J., Ketz, N.A., Roach, S.M., Lerner, I., Jones, A.P., Bradley, R., Bryant, N.B., Hartholt, A., Mullins, T.S., Choe, J., Clark, V.P., Howard, M.D. (2020). One-Shot Tagging During Wake and Cueing During Sleep With Spatiotemporal Patterns of Transcranial Electrical Stimulation Can Boost Long-Term Metamemory of Individual Episodes in Humans. Frontiers in Neuroscience, 16:1416. doi:10.3389/fnins.2019.01416

Lerner, I., Gluck, M.A. (2019). Sleep and the Extraction of Hidden Regularities: A Systematic Review and the Importance of Temporal Rules. Sleep Medicine Reviews, 47, 39-50.

Lerner, I., Ketz, N. A., Jones, A.P., Bryant, N.B., Robert, B., Skorheim, S.W., Hartholt, A., Rizzo, A.S., Gluck, M.A., Clark, V.P., Pilly, P.K. (2019). Transcranial Current Stimulation During Sleep Facilitates Insight into Temporal Rules, but does not Consolidate Memories of Individual Sequential Experiences. Scientific Reports, 9, 1516. doi: 10.1038/s41598-018-36107-7

Lerner, I., Sojitra, R., Gluck, M.A. (2018). How age affects reinforcement learning. Aging (Albany NY). 10(12), 3630-3631.

Lerner, I. & Gluck, M.A. (2018). Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps. Frontiers in Human Neuroscience, 12: 404, (as part of Research Topic: Learning and Memory). doi:10.3389/fnhum.2018.00404

Sojitra, R. * , Lerner, I. * , Petok, J.R., & Gluck, M.A. (2018). Age Affects Reinforcement Learning Through Dopamine-Based Laerning Imbalance and High Decision Noise – Not Through Parkinsonian Mechanisms Neurobiology of Aging, 68, 102-113.
* Co-first author, Equal contribution

Lerner, I. *, Lupkin, S.M. *, Sinha, N., Tsai, A., & Gluck, M.A. (2017). Baseline Levels of Rapid-Eye-Movement Sleep May Protect Against Excessive Activity in Fear-Related Neural Circuits. Journal of Neuroscience, 37 (46), 11233-11244.
• Paper chosen for press promotion and featured in media outlets including Time, the Atlantic, Huffington Post, CTV, and others. See Media Coverage.

Lerner, I. (2017). Unsupervised Temporal Learning during Sleep Supports Insight. Conference on Cognitive Computational Neuroscience (CCN) 2017. Archived at:

Lerner, I., Lupkin, S.M., Corter, J.E., Peters, S.E, Cannella, L., & Gluck, M.A. (2016). The influence of sleep on emotional and cognitive processing is primarily trait- (but not state-) dependent. Neurobiology of Learning and Memory, 134, 275-286.

Lerner, I., Armstrong, B.C., & Frost, R. (2014). What can we learn from learning models about sensitivity to letter-order in visual word recognition? Journal of Memory and Language, 77, 4-58.

Lerner, I., Bentin, S., & Shriki, O. (2014). Integrating the Automatic and the Controlled: Strategies in Semantic Priming in an Attractor Network with Latching Dynamics. Cognitive Science, 38(8), 1562-1603. 

Lerner, I., & Shriki, O. (2014). Internally- and externally-driven network transitions as a basis for automatic and strategic processes in semantic priming: theory and experimental validation. Frontiers in Psychology 5:314. doi: 10.3389/fpsyg.2014.00314

Lerner, I., Bentin, S., & Shriki, O. (2012). Spreading Activation in an Attractor Network with Latching Dynamics: Automatic Semantic Priming Revisited. Cognitive Science, 36 (8), 1339-1382.

Lerner, I., Bentin, S., & Shriki, O. (2012). Excessive Attractor Instability Accounts for Semantic Priming in Schizophrenia. PLoS One, 7 (7):e40663.doi:10.1371/journal.pone.0040663

Lerner, I., Bentin, S., & Shriki, O. (2010). Automatic and controlled processes in semantic priming: an attractor neural network model with latching dynamics. In S. Ohlsson & R. Catrambone (Eds.) Proceedings of the 32rd Annual Conference of the Cognitive Science Society, (pp 1112-1117). Mahwah, NJ: Lawrence Erlbaum.

Book Chapters

Lerner, I. (2017). Sleep is for the brain: Contemporary computational approaches in the study of sleep and memory and a Novel ‘Temporal Scaffolding’ Hypothesis. In: A. Moustafa (Ed), Computational Models of Brain and Behavior (pp. 245-256). Hoboken, NJ: Wiley.

Manuscripts Submitted or in Preparation

Lerner, I. & Gluck, M.A. Slow Wave Sleep Creates False Compound Memories. In Preparation.