The mismatch negativity (MMN) is a key biomarker of automatic deviance detection thought to emerge from 2 cortical sources. First, the auditory cortex (AC) encodes spectral regularities and reports frequency-specific deviances. Then, more abstract representations in the prefrontal cortex (PFC) allow to detect contextual changes of potential behavioral relevance. However, the precise location and time asynchronies between neuronal correlates underlying this frontotemporal network remain unclear and elusive. Our study presented auditory oddball paradigms along with “no-repetition” controls to record mismatch responses in neuronal spiking activity and local field potentials at the rat medial PFC. Whereas mismatch responses in the auditory system are mainly induced by stimulus-dependent effects, we found that auditory responsiveness in the PFC was driven by unpredictability, yielding context-dependent, comparatively delayed, more robust and longer-lasting mismatch responses mostly comprised of prediction error signaling activity. This characteristically different composition discarded that mismatch responses in the PFC could be simply inherited or amplified downstream from the auditory system. Conversely, it is more plausible for the PFC to exert top-down influences on the AC, since the PFC exhibited flexible and potent predictive processing, capable of suppressing redundant input more efficiently than the AC. Remarkably, the time course of the mismatch responses we observed in the spiking activity and local field potentials of the AC and the PFC combined coincided with the time course of the large-scale MMN-like signals reported in the rat brain, thereby linking the microscopic, mesoscopic, and macroscopic levels of automatic deviance detection.

32According to predictive coding theory, perception emerges through the interplay of neural circuits 33 that generate top-down predictions about environmental statistical regularities and those that 34 generate bottom-up error signals to sensory deviations. Prediction error signals are hierarchically 35 organized from subcortical structures to the auditory cortex. Beyond the auditory cortex, the 36 prefrontal cortices integrate error signals to update prediction models. Here, we recorded neuronal 37 activity in the medial prefrontal cortex of the anesthetized rat while presenting oddball and control 38 stimulus sequences, designed to separate prediction errors from repetition suppression effects of 39 mismatch responses. Robust mismatch signals were mostly due to prediction errors. The encoding of 40 a regularity representation and the repetition suppression effect over the course of repeated stimuli 41 were fast. Medial prefrontal cells encode stronger prediction errors than lower levels in the auditory 42 hierarchy. These neurons may, therefore, represent the neuronal basis of a fundamental mechanism 43 of hierarchical inference. 44 45 46 Keywords: auditory processing, predictive coding, prediction error, mismatch negativity, medial 47 prefrontal cortex, anaesthesia, neuronal activity 48 49 3 50 51 100 unpredictable deviations from the auditory background. These cells may, therefore, represent the 101 neuronal basis of predictive activity in FCs. 102 103 104 Results 105Context-dependent responses across fields in mPFC. 106 To seek experimental evidence for predictive coding signals in the mPFC, we recorded neuronal 107 activity across all fields in 33 urethane-anesthetized rats. We recorded 83 multiunits (AGM [medial 108 agranular cortex]: 25; ACC [anterior cingulate cortex]: 20; PL [prelimbic cortex]: 20; IL [infralimbic 109 cortex]: 18) and tested 384 tones (AGM: 13; ACC: 90; PL: 81; IL: 81) as part of oddball paradigms 110 and suitable control sequences, namely, cascade and many-standards conditions (Fig. 1). Figure 2 111 illustrates 5 examples of electrolytic lesions in three Nissl-stained sections at different recording sites 112 across the mPFC. Regardless of their anatomical location in all mPFC fields, we found sound-driven 113 neuronal activity to pure tones (0.6-42.5 kHz; 25-70 dB SPL). We assessed significantly increased 114 responses to sound by comparing baseline-corrected spike counts after stimulus presentation against 115 a simulated null peristimulus time histograms (PSTH) with a firing rate equal to the baseline 116 (detailed in Methods). We tested the neuronal response to each pure tone as either being deviant, 117 standard, or part of a control sequence and only included those frequency tones that demonstrated a 118 significant response to any condition. Thus, 86.2% (331/384) of deviant stimuli evoked a significant 119 neuronal discharge, while 26.6% (102/384) of standard stimuli, 26.6% (102/384) of many-standards 120 stimuli and 32.3% (124/384) of cascade stimuli evoked a firing rate ...

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