IEM, HAS Budapest, Hungary
Neurocentre Magendie, INSERM, Bordeaux, France
"Prefrontal midbrain circuits control fear expression"
NIAAA, Rockville, USA
"Dissecting cortico-amygdala circuits underlying inhibition of fear"
Innsbruck University, Innsbruck, Austria
"Specialized amygdala inhibitory networks for emotional learning"
University of Tuebingen, Germany
"The intercalated cell network in the amygdala: New insights into plasticity and connectivity"
IEM HAS, Budapest, Hungary
"Subcortical control of fear learning via amygdala interneuron networks"
A central endeavor of modern neuroscience is to understand how mental, including the emotional states are controlled in the brain. One of the most studied emotional states is the fear state induced by external and/ or internal stimuli and characterized by a specific set of behavioral, physiological, hormonal, and autonomic responses. Previous studies have established that the prefrontal cortex, the amygdalar nuclei and the periaqueductal grey (PAG) play a critical role in controlling fear-related brain states. As emotional states correspond to the operation of defined neural circuits, uncovering circuit mechanisms underlying fear
acquisition, expression and extinction at network levels may provide critical advances of how fear state are regulated by distributed neural networks. The main goal of this symposium is to provide new insights into the mechanisms that control fear state and related associative learning allowing an animal to adapt to and survive everyday challenges. Speakers will present data how prefrontal midbrain circuits, cortico-amygdala networks, basal forebrain-amygdala afferents and local microcircuits within the amygdala control fear state and fear memory formation. Since the fear circuits are similar in mammals (including humans) revealing the circuit mechanisms underlying fear state-related associative learning should further our knowledge how normal emotional states are formed and maintained. Importantly, detailed understanding of fear-related neural processes under physiological conditions may lead to a deeper understanding of maladaptive changes in neural networks leading to pathological mental states, like anxiety or posttraumatic stress disorder.