Our laboratory studies the neurobiology of learning, memory, and emotion. We use a multi-disciplinary approach including in vivo electrophysiology, in vivo calcium imaging, optogenetics, chemogenetics, viral tracing and immunohistochemistry techniques to investigate the brain circuits and neural ensemble dynamics underlying these neurobiological processes.
Neural circuit dynamics underlying learning and memory
Learning and memory are two of the most remarkable abilities of the brain. Our goal is to understand how activity and plasticity in neural circuits underlie both learning and the ability to transform newly learned information into long-term memory. In particular, we focus on the circuitry of the hippocampus and interconnected cortical/subcortical regions in learning and memory processes, and how alterations in these connections affect behavior. We also aim to discover ways by which learning and memory can be enhanced or weakened, and to develop innovative therapies for treatment of memory disorders such as amnesia and posttraumatic stress disorder (PTSD).
Neural circuitry of fear and anxiety
Fear and anxiety are essential natural instincts for survival and everyday life. While sometimes occurring together, they are two highly distinct emotions and brain states. Fear is short-lasting and usually evoked by a specific threat, while anxiety is characteristically slow-onset and long-lasting, elicited without immediate external threat. Our goal is to understand the neural circuitry and mechanisms that mediate fear and anxiety, respectively, with an emphasis on the amygdala and interconnected afferent/efferent regions. We also aim to determine how manipulation of these circuits may regulate levels of fear or anxiety, which could have clinical implications for treatment of pathological fear and anxiety disorders.
Funding
- The Pennsylvania CURE Grant (06/01/2021 – 05/31/2023)
- NIH Research Project Grant (R01 MH119102, 02/15/2019 – 11/30/2023)
Position Available
The Wang Lab is currently seeking to hire a postdoc to work on neural circuit dynamics underlying learning and memory consolidation. Preferred skills:
- in vivo electrophysiology (or in vivo imaging)
- basic programming with Matlab (or Python)
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