This page contains doctoral, masters' and undergraduate theses carried out in the Niv lab throughout time.

Doctoral theses

Shin, Y.S. (2020). The organization of experiences and its effects on episodic memory and decision-making. Princeton Neuroscience Institute, Princeton University.

Rouhani, N. (2020). Reward prediction errors shape memory during reinforcement learning. Department of Psychology, Princeton University.

Radulescu, A. (2020). Computational mechanisms of selective attention during reinforcement learning. Department of Psychology, Princeton University.

Chan, S.C.Y. (2016). Inference and neural representations of the current situation and the underlying causal structure of the world. Princeton Neuroscience Institute, Princeton University.

Geana, A. (2015). Information sampling, learning and exploration. Department of Psychology, Princeton University.

Eldar, E. (2014). Focus versus breadth: the effects of neural gain on information processing. Princeton Neuroscience Institute, Princeton University.

Gershman, S. J. (2013). Memory modification in the brain: computational and experimental investigations. Department of Psychology, Princeton University.

Niv, Y. (2007). The effects of motivation on habitual instrumental behavior. The Hebrew University of Jerusalem [PDF]

Masters' theses

Kao, D. (2012). Reward preference in video games. Department of Computer Science, Princeton University.

Senior theses

Leong, Y.C. (2013). Learning what's relevant in a largely irrelevant world: the role of selective attention in learning. Department of Psychology, Princeton University.

McDonald, K. (2015). Asymmetric learning rates for positive and negative feedback: a formal model comparison. Department of Psychology, Princeton University.

Granovetter, M. C. (2015). Utilizing Neural Gain as a Model for Explaining Features of Autism Spectrum Disorders: The effects of constitutive locus coeruleus activity on attention-based learning. Department of Psychology, Princeton University.

Jaskir, A. (2017). Learning how to learn: the interaction between attention and learning as a mechanism for dimensionality reduction in the brain. Department of Computer Science, Princeton University.

Bu, J. (2017). Generalization of Value-Driven Attentional Capture into a Multidimensional World. Department of Psychology, Princeton University.

Newman, J. E. (2018). Confidence as an Arbiter of Attentional Allocation During Learning in Multidimensional Environments. Department of Neuroscience, Princeton University.

MacAulay, R. (2018). Economic Value and State Representations: Preparations to Decode the Role of the Human Orbitofrontal Cortex. Department of Neuroscience, Princeton University.

Lee, C. (2020). Mood-Driven Risk Preference: How Induced Mood Affects Risk-Sensitive Learning. Department of Neuroscience, Princeton University.

Yusina, S. (2022). Quantifying the latent-cause inference process and its relationship with schizotypy. Department of Neuroscience, Princeton University.

Aitsahalia, I. (2022). Controllability Priors Modulating Over- and Under-Segmentation of Latent Causes in Fear Conditioning. Department of Neuroscience, Princeton University.

Wang, H. (2022). Moral Inferencing Patterns within Complex Post-traumatic Stress Disorder Populations. Department of Psychology, Princeton University.