Amygdala neurons

For more amygdala neurons, see drop down menu 'Social neurophysiology'.

Value Transition

Monkeys repeatedly choose between saving an earned juice reward for future consumption with interest and immediate spending the save reward. A group of amygdala neurons transitions from value coding to choice coding (left). Only a small number of amygdala neurons are necessary to make more than 90% accurate choice predictions (right). This is the kind of information the next postsynaptic neurons receive in order to execute the choice. Fine analysis reveals a gradual build-up of neuronal activity towards a spend choice (bottom). Thus, the neuronal activity tracks an internally controlled sequential choice progress in the absence of external cues, as it coccurs only in choice trials and not in externally instructed imperative trials and does not reflect reward expectation, sensory stimulation or action preparation. View the report here (Grabenhorst et al. 2013).

Reward prediction (V) learning depends on the reward being contingent on the stimulus. A reward may occur also in the background without a stimulus (non-contingently; p(reward|stimulus = p(reward|no stimulus)), but this reward does not add any information to the stimulus and does not induce learning, even though the stimulus is paired with the reward. Amygdala neurons capture this fundamental requirement (bottom). Thus, stimulus-reward pairing is not enough for learning, although it appears so when pairing and contingency are not separated (top). This is what Pavlov did not know but Rescorla discovered (with punishers; 1967). View the report here (Bermudez & Schultz 2010).

The activity of some amygdala neurons ramps up to an expected singular reward (blue) but shows a more sustained elevation of activity when rewards are more spread out and the expectation lasts over a longer period (blue). Thus, the reward expectation in these neurons depends on the time of the reward, exactly what expectations should do. View the report here (Bermudez et al. 2012).