Jackie "of
all trades"






Qi Lin


Post-Doctoral Fellow
New York University
Department of Psychology

James Madison University
BS in Psychology, 2004

Duke University
PhD in Psychology and Neuroscience, 2012
PhD Advisor, Dr. Kevin S. LaBar



My primary area of research focuses on the brain systems involved in the acquisition and inhibition of fear in humans. One of the most elegant processes humans and other animals possess to detect and react to signals of danger in the environment is classical conditioning, wherein stimuli associated with an aversive event acquire the capacity to elicit defensive behaviors. One of the primary goals of my research is to examine ways in which fear conditioning - - typically considered an evolutionarily conserved system shared across species - - interacts with other cognitive systems to determine how and what we fear in our environment.

One avenue of my research examines the ways humans utilize prior knowledge and inferential reasoning to generalize information about an aversive event to seemingly innocuous stimuli that are only indirectly related to the event. For example, an individual who survives an automobile accident may associate a number of stimuli or situations to the event that did not directly contribute to the accident, e.g. the song on the radio, the type of car involved, the time of day of the accident, or the neighborhood the accident occurred in. Later, these cues may act as strong reminders that evoke a sense of anxiety or fear. We use functional MRI to examine brain activity during fear learning and generalization, with a focus on the interaction between subcortical (e.g. the amygdala) and cortical (e.g. prefrontal and extrastriate visual cortex) regions.

Once acquired, it is often necessary for us to overcome (or extinguish) a fear that does not serve an adaptive function. For example, a fear of cars (and information associated with cars and driving) is maladaptive in most cases because we frequently encounter cars and many of us need to drive a car on a regular basis. Thus, another important goal of my research is to understand how it is that we overcome our fears, and to devise new experimental techniques to bolster this ability for individuals suffering from fear disorders. We focus on brain regions known from rodent models to be important for fear extinction, e.g. the ventromedial PFC, amygdala, and hippocampus.

Peer Reviewed Research Papers:
Dunsmoor, J.E., Murty, V.P., Davachi, L. & Phelps, E.A. (2015). Emotional learning selectively and retroactively strengthens episodic memories for related events. Nature.

Dymond, S., Dunsmoor, J.E., Vervliet, B., Roche, B. & Hermans, D. (2015). Fear Generalization in Humans: Systematic Review and Implications for Anxiety Disorder Research. Behavior Therapy.

Dunsmoor, J.E., Campese, V.D., Ceceli, A.O., LeDoux, J.E. & Phelps, E.A. (2015). Novelty-facilitated extinction: Providing a novel outcome in place of an expected threat diminishes recovery of defensive responses. Biological Psychiatry.

Ahs, F., Dunsmoor, J.E., Zielinski, D. & LaBar, K.S. (2015). Spatial proximity amplifies valence in emotional memory and defensive approach-avoidance. Neuropsychologia.

Dunsmoor, J.E. & Murphy, G.L. (2015). Categories, concepts, and conditioning: How humans generalize fear. Trends in Cognitive Sciences, 19, 73-77.

Dunsmoor, J.E. & Murphy, G.L. (2014). Stimulus typicality determines how broadly fear is generalized. Psychological Science, 25, 1816-1821.

Dunsmoor, J.E., Ahs, F., Zielinski, D. & LaBar, K.S. (2014). Extinction in multiple virtual reality contexts diminishes fear reinstatement in humans. Neurobiology of Learning & Memory, 113, 157-164.

Dunsmoor, J.E., Martin, A., & LaBar, K.S. (2013). Aversive learning modulates cortical representations of object categories. Cerebral Cortex.

Dunsmoor, J.E. & LaBar, K.S. (2013). Effects of discrimination training on fear generalization gradients and perceptual classification in humans. Behavioral Neuroscience, 127, 350-356.

Dunsmoor, J.E. & LaBar, K.S. (2012). Brain activity associated with the omission of an aversive event reveals effects of fear learning and generalization. Neurobiology of Learning & Memory, 97, 301-312.

Dunsmoor, J.E., Martin, A. & LaBar, K.S. (2012). The role of conceptual knowledge in learning and retention of conditioned fear. Biological Psychology, 89, 300-305.

Cain, M.S., Dunsmoor, J.E., LaBar, K.S. & Mitroff SR (2011) Anticipatory anxiety hinders detection of a second target in dual-target search. Psychological Science, 22, 866-871.

Dunsmoor, J.E., Prince, S.E., Murty, V.P., Kragel, P.A. & LaBar, K.S. (2011) Neurobehavioral mechanisms of human fear generalization. Neuroimage, 55, 1878-1888.

Dunsmoor, J.E., White, A.J. & LaBar, K.S. (2011) Conceptual similarity promotes higher-order fear learning. Learning & Memory, 18, 156-160.

Dunsmoor, J.E. & Schmajuk, N.A. (2009) Interpreting patterns of brain activation in human fear conditioning with an attentional-associative learning model. Behavioral Neuroscience, 123, 851-855.

Dunsmoor, J.E., Mitroff, S.R. & LaBar, K.S. (2009). Generalization of conditioned fear along a dimension of increasing fear intensity. Learning and Memory, 16, 460-469.

Dunsmoor, J.E., Bandettini, P.A. & Knight, D.C. (2008). Neural correlates of unconditioned response diminution during Pavlovian conditioning. Neuroimage, 40, 811-817.

Dunsmoor, J.E., Bandettini, P.A. & Knight, D.C. (2007). Impact of continuous versus intermittent CS-UCS pairing on human brain activation during Pavlovian fear conditioning. Behavioral Neuroscience, 121, 635-642.

Book Chapters and Commentaries:
Dunsmoor, J.E. & LaBar, K.S. (2012). Neural basis of human fear learning. In: Vuilleumier, P. and Armony, J., editors. Handbook of Human Affective Neuroscience (in revision). Cambridge, England: Cambridge University Press.

Dunsmoor, J.E., Ahs, F. & LaBar, K.S. (2011) Neurocognitive mechanisms of fear conditioning and vulnerability to anxiety. Frontiers Hum Neuroscience, 5, 35.

Schmajuk, N.A., Kutlu, M.G., Dunsmoor, J.E. & Laurrauri, J.A. (2010). Attention, associations, and configurations in conditioning. In: Schmajuk, N.A., editor. Computational Models of Conditioning. Cambridge, England: Cambridge University Press.