Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex

Abstract

Detection of statistical irregularities, measured as a prediction error response, is fundamental to the 47 perceptual monitoring of the environment. We studied whether prediction error response is generated 48 by neural oscillations or asynchronous neuronal firing. Electrocorticography (ECoG) was carried out 49 in three monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials 50 (LFP) recorded over the auditory cortex underwent spectral principal component analysis, which 51 decoupled broadband and rhythmic components of LFP signal. We found that broadband component 52 generated prediction error response, whereas none of the rhythmic components encoded statistical 53 irregularities of sounds. The broadband component displayed more stochastic, asymmetrical 54 multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We 55 thus conclude that the prediction error response is encoded by asynchronous neuronal populations, 56 defined by irregular dynamical states which, unlike oscillatory rhythms, appear to enable the neural 57 representation of auditory prediction error response. 58 59 60

Feedback information sharing in the human brain reflects bistable perception in the absence of report

“…Taken together, and consistent with previously reported effects in the auditory domain (40), these results show that having an integrated versus a differentiated percept, goes hand in hand with front-to-back neural directed information integration and frontal differentiation brain measures. Next, we aim to establish to what extent these effects depend on the necessity for reporting perceptual transitions (task relevance of switches) and we further specify the timing of these effects by locking our analyses more closely to the perceptual transitions based on OKN crossings.…”

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

“…Cortical mechanisms of auditory prediction error (PE) have been extensively studied using evoked-related potentials (ERP) and spectral analyses (Canales-Johnson et al, 2021;Blenkmann et al, 2019;Chao et al, 2018;Jiang et al, 2022;Parras et al, 2017). A well-studied ERP marker of auditory PE is the mismatch negativity (MMN), an event-related potential (ERP) that peaks around 150-250 ms after the onset of an infrequent acoustic stimulus (Parras et al, 2017).…”

“…There is evidence that degeneracy in neural networks may provide various computational benefits, for example, enabling stable computations despite unstable neural dynamics (Driscoll et al, 2017;Druckmann and Chklovskii, 2012) and allowing the central nervous system to filter out unwanted noise (Moreno-Bote et al, 2014). The cortical markers of auditory PE have been observed in auditory subcortical and cortical structures of several species despite the differences in their neuroanatomical structures (Parras et al, 2017;Blenkmann et al, 2019;Canales-Johnson et al, 2021). This suggests that synergistic information is the outcome of distinct neural circuits computing error information in a complementary manner, providing the cortex with a flexible code for representing PE information distributively.…”

“…The dataset the current study used consists of ECoG recordings of implanted electrodes in three adult male common marmosets (Callithrix jacchus). The details of the complete dataset have been described previously (Canales-Johnson et al, 2021;Komatsu et al, 2015).…”

“…In order to obtain the BB, spectral decoupling of the raw ECoG was carried out (Canales-Johnson et al, 2021;Miller, 2019). To extract the course of broadband spectral activity, the spectral decoupling of the raw ECoG signal was carried out.…”