Associative-memory representations emerge as shared spatial patterns of theta activity spanning the primate temporal cortex.

Kiyoshi Nakahara,Isao Hasegawa,Atsuhiko Iijima,Yukiyasu Kamitani,Takafumi Suzuki,Ken Adachi,Takeshi Matsuo,Sayaka Sugiyama,Kei Majima,Hirohito Sawahata,Keisuke Kawasaki,Hisashi Tanigawa,Masaki Takeda,Ryota Nakata

doi:10.1038/ncomms11827

Abstract

Highly localized neuronal spikes in primate temporal cortex can encode associative memory; however, whether memory formation involves area-wide reorganization of ensemble activity, which often accompanies rhythmicity, or just local microcircuit-level plasticity, remains elusive. Using high-density electrocorticography, we capture local-field potentials spanning the monkey temporal lobes, and show that the visual pair-association (PA) memory is encoded in spatial patterns of theta activity in areas TE, 36, and, partially, in the parahippocampal cortex, but not in the entorhinal cortex. The theta patterns elicited by learned paired associates are distinct between pairs, but similar within pairs. This pattern similarity, emerging through novel PA learning, allows a machine-learning decoder trained on theta patterns elicited by a particular visual item to correctly predict the identity of those elicited by its paired associate. Our results suggest that the formation and sharing of widespread cortical theta patterns via learning-induced reorganization are involved in the mechanisms of associative memory representation.

Highlights

Localized neuronal spikes in primate temporal cortex can encode associative memory; whether memory formation involves area-wide reorganization of ensemble activity, which often accompanies rhythmicity, or just local microcircuit-level plasticity, remains elusive
The encoding of associative memory depends on the interplay between the visual association area TE and the medial temporal lobe (MTL), including Brodmann areas 35 and 36 (A35 and A36), the entorhinal cortex (ENT), the parahippocampal cortex (PH) and the hippocampus (HC)[1,5,6]
We further demonstrate that the spatial pattern similarity in theta activity emerges through novel PA learning

Summary

Results

A machine-learning decoder was trained on theta activity patterns evoked by one member of a particular paired associate that was presented as a cue. The pair-decoding accuracy was significantly higher than chance level (20%) during B100–300 ms after the cue onset (Fig. 3c; permutation test, 25,000 permutations, Po0.01, corrected, n 1⁄4 2 monkeys), indicating a marked trial-by-trial similarity of the theta activity patterns elicited by associated visual stimuli. To investigate functional area differences of the theta pattern similarity, we computed the pair-decoding accuracy separately in TE, A36, the ENT and the PH Both TE and A36 exhibited significantly higher decoding accuracy compared with chance

Discussion

25 ENT A36 PH TE ALL

Methods