Cambridge Team Decodes Multidimensional Meaning From Combined 4–200 Hz Cortical Signals
A collaboration involving the University of Cambridge analyzed surface electrocorticography recordings from the human ventral anterior temporal lobe. It found significant decoding of graded, multidimensional semantic information when signals across 4-200 Hz were considered together, but not from individual frequency bands. Using representational similarity learning on time-frequency power and phase data, the researchers compared three hypotheses about how semantic information maps onto signal frequencies. The authors interpret the findings as supporting transfrequency coding, in which some information emerges only when multiple frequencies are considered jointly. The study has not been peer reviewed.