human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Intracranially recorded memory-related potentials reveal higher posterior than anterior hippocampal involvement in verbal encoding and retrieval"
  Abstract: The human hippocampus is essential for both encoding and recollection, but it remains controversial whether there is a functionally different involvement of anterior versus posterior parts of the hippocampus in these memory processes. In the present study, we examined encoding and retrieval processes via intrahippocampal recordings in 27 patients with unilateral temporal lobe epilepsy. Multicontact depth electrodes were implanted along the longitudinal axis of the hippocampus as part of the presurgical evaluation. In a continuous word recognition test, subjects had to indicate whether words were new or already presented. Recognized old words, as compared to new words, resulted in a larger P600 component, as well as in a larger late negative component (LNC, 600900 msec). In addition, subsequently remembered words elicited a larger positivity (400 to 900 msec) than later forgotten words. We found differences concerning the distribution along the hippocampus for the LNC old-new effect, reflecting successful retrieval, as well as for the subsequent memory effect, reflecting successful encoding. Both effects were larger the further posterior an electrode was located in the hippocampus. Findings are suggestive for a predominant posterior hippocampal involvement in both verbal encoding and retrieval.

Connected through hyperedge HE-1 (induced by source paper "Dissociable neural circuits for encoding and retrieval of object locations during active navigation in humans"):
  with members:
    (none)

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Economics