The Molecular and Cellular Cognition Society (MCCS) is an international organization intended to facilitate interchanges among laboratories in the field of Molecular and Cellular Cognition. The other two key goals of the Society are to promote the study of the molecular and cellular basis of cognitive function, and to educate the general public on key findings in the field, including their limitations and implications for health and society.

Although closely connected with behavioral genetics, MCC emphasizes the integration of molecular and cellular explanations of behavior, instead of focusing on the connections between genes and behavior. MCC is a field of neuroscience

Unlike Cognitive Neuroscience, which historically has focused on the connection between human brain systems and behavior, the field of Molecular and Cellular Cognition studies how molecular (i.e. receptor, kinase activation), intra-cellular (i.e. dendritic processes), and inter-cellular processes (i.e. synaptic plasticity; network representations such as place fields) modulate animal models of cognitive function.

History of Molecular and Cellular Cognition Society

​​​​​​​ The field of MCC has its roots in the pioneering studies of the role of NMDA receptor in long-term potentiation and spatial learning. The studies that crystallized the field used knock out mice to look at the role of the alpha calcium calmodulin kinase II and fyn kinase in hippocampal long-term potentiation and spatial learning.

Molecular cellular cognition became an organized field with the formation of the Molecular Cellular Cognition Society. Our organization has no membership fees and meetings that emphasize the participation of junior scientists. The first meeting took place in Orlando, Florida on November 1st, 2002. As of October, 2009 our society has organized 19 meetings in North America, Europe and Asia, and includes more than 2300 members.

Methods employed in MCC include transgenic organisms (i.e. mice), in vitro and in vivoelectrophysiology, and behavioral analysis. Modeling is becoming an essential component of the field because of the complexity of the multilevel data generated.