Learning from unexpected events in the neocortical microcircuit

Author:

Gillon Colleen J.ORCID,Pina Jason E.ORCID,Lecoq Jérôme A.ORCID,Ahmed Ruweida,Billeh Yazan N.ORCID,Caldejon Shiella,Groblewski Peter,Henley Timothy M.ORCID,Kato India,Lee EricORCID,Luviano Jennifer,Mace KylaORCID,Nayan Chelsea,Nguyen Thuyanh V.,North Kat,Perkins Jed,Seid Sam,Valley Matthew T.,Williford Ali,Bengio YoshuaORCID,Lillicrap Timothy P.ORCID,Richards Blake A.ORCID,Zylberberg JoelORCID

Abstract

AbstractScientists have long conjectured that the neocortex learns the structure of the environment in a predictive, hierarchical manner. According to this conjecture, expected, predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of information. It is theorized that the neocortex then changes the representation of incoming stimuli, guided by differences in the responses to expected and unexpected events. In line with this conjecture, different responses to expected and unexpected sensory features have been observed in spiking and somatic calcium events. However, it remains unknown whether these unexpected event signals occur in the distal apical dendrites where many top-down signals are received, and whether these signals govern subsequent changes in the brain’s stimulus representations. Here, we show that both somata and distal apical dendrites of cortical pyramidal neurons exhibit distinct unexpected event signals that systematically change over days. These findings were obtained by tracking the responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons over multiple days in primary visual cortex of awake, behaving mice using two-photon calcium imaging. Many neurons in both layers 2/3 and 5 showed large differences between their responses to expected and unexpected events. Interestingly, these responses evolved in opposite directions in the somata and distal apical dendrites. These differences between the somata and distal apical dendrites may be important for hierarchical computation, given that these two compartments tend to receive bottom-up and top-down information, respectively.

Publisher

Cold Spring Harbor Laboratory

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