Distributed representations of prediction error signals across the cortical hierarchy are synergistic

Abstract

An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in three common awake marmosets and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy in auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.

Predictive learning shapes the representational geometry of the human brain

“…Furthermore, our results suggest that the dominance of synergistic encoding in the human brain is independent of contextual regularity. This is consistent with recent evidence from the marmoset brain suggesting that predictive processing is characterized by synergistic dynamics (43).…”

“…Thus, we asked if prediction error signals resulted from distributed processing across a network of brain regions rather than independent processing within each of these regions. We employed Partial Information Decomposition (33) to decompose the joint mutual information of pairs of brain regions about error signals 90-120 ms post tone onset into redundant and synergistic components (43, 44) (Fig. 4A).…”

“…For example, in the Rao and Ballard model (6) the prediction error is computed independently at each hierarchical level. However, the large-scale synergistic component in our results suggests that each brain region encodes only partial information needed for the error computation, which is then broadcasted into the network and integrated with feedback and recurrent connections to eventually process the prediction error (43). Thus, our results support theories of predictive processing that do not necessarily require the hierarchical processing postulated by traditional predictive coding theories of perception (85).…”

Neural interactions in the human frontal cortex dissociate reward and punishment learning

“…Triadic synergistic interactions between the continuous spike counts recorded within and across areas of the visuomotor network have been shown to carry behaviorally-relevant information and to display the strongest modulations during the processing of visual information and movement execution ( Varley et al, 2023 ). Finally, cortical representations of prediction error signals in the acoustic domain observed tone-related and instantaneous redundant interactions, such as time-lagged synergistic interactions within and across temporal and frontal regions of the auditory system ( Gelens et al, 2023 ).…”

Neural interactions in the human frontal cortex dissociate reward and punishment learning

“…Triadic synergistic interactions between the continuous spike counts recorded within and across areas of the visuomotor network have been shown to carry behaviorally-relevant information and to display the strongest modulations during the processing of visual information and movement execution (Varley et al, 2023 ). Finally, cortical representations of prediction error signals in the acoustic domain observed tone-related and instantaneous redundant interactions, such as timelagged synergistic interactions within and across temporal and frontal regions of the auditory system (Gelens et al, 2023 ).…”