Stimulus-Specific Prediction Error Neurons in Mouse Auditory Cortex

Sensation and expectation are embedded in mouse motor cortical activity

During behavior, the motor cortex sends copies of motor-related signals to sensory cortices. Here, we combine closed-loop behavior with large-scale physiology, projection-pattern-specific recordings, and circuit perturbations to show that neurons in mouse secondary motor cortex (M2) encode sensation and are influenced by expectation. When a movement unexpectedly produces a sound, M2 becomes dominated by sound-evoked activity. Sound responses in M2 are inherited partially from the auditory cortex and are routed back to the auditory cortex, providing a path for the reciprocal exchange of sensory-motor information during behavior. When the acoustic consequences of a movement become predictable, M2 responses to self-generated sounds are selectively gated off. These changes in single-cell responses are reflected in population dynamics, which are influenced by both sensation and expectation. Together, these findings reveal the embedding of sensory and expectation signals in motor cortical activity.

Suppression and omission effects in auditory predictive processing-Two of the same?

Recent theories describe perception as an inferential process based on internal predictive models that are adjusted by prediction violations (prediction error). Two different modulations of the auditory N1 event-related brain potential component are often discussed as an expression of auditory predictive processing. The sound-related N1 component is attenuated for self-generated sounds compared to the N1 elicited by externally generated sounds (N1 suppression). An omission-related component in the N1 time-range is elicited when the self-generated sounds are occasionally omitted (omission N1). Both phenomena were explained by action-related forward modelling, which takes place when the sensory input is predictable: prediction error signals are reduced when predicted sensory input is presented (N1 suppression) and elicited when predicted sensory input is omitted (omission N1). This common theoretical account is appealing but has not yet been directly tested. We manipulated the predictability of a sound in a self-generation paradigm in which, in two conditions, either 80% or 50% of the button presses did generate a sound, inducing a strong or a weak expectation for the occurrence of the sound. Consistent with the forward modelling account, an omission N1 was observed in the 80% but not in the 50% condition. However, N1 suppression was highly similar in both conditions. Thus, our results demonstrate a clear effect of predictability for the omission N1 but not for the N1 suppression. These results imply that the two phenomena rely (at least in part) on different mechanisms and challenge prediction related accounts of N1 suppression.

Learned response dynamics reflect stimulus timing and encode temporal expectation violations in superficial layers of mouse V1

The ability to recognize ordered event sequences is a fundamental component of sensory cognition and underlies the capacity to generate temporally specific expectations of future events based on previous experience. Various lines of evidence suggest that the primary visual cortex participates in some form of predictive processing, but many details remain ambiguous. Here we use two-photon calcium imaging in layer 2/3 (L2/3) of the mouse primary visual cortex (V1) to study changes to neural activity under a multi-day sequence learning paradigm with respect to prediction error responses, stimulus encoding, and time. We find increased neural activity at the time an expected, but omitted, stimulus would have occurred but no significant prediction error responses following an unexpected stimulus substitution. Sequence representations became sparser and less correlated with training, although these changes had no effect on decoding accuracy of stimulus identity or timing. Additionally, we find that experience modifies the temporal structure of stimulus responses to produce a bias towards predictive stimulus-locked activity. Finally, we find significant temporal structure during intersequence rest periods that was largely unchanged by training.

Learning within a sensory-motor circuit links action to expected outcome

The cortex integrates sound- and movement-related signals to predict the acoustic consequences of behavior and detect violations from expectations. Although expectation- and prediction-related activity has been observed in the auditory cortex of humans, monkeys, and mice during vocal and non-vocal acoustic behaviors, the specific cortical circuitry required for forming memories, recalling expectations, and making predictions remains unknown. By combining closed-loop behavior, electrophysiological recordings, longitudinal pharmacology, and targeted optogenetic circuit activation, we identify a cortical locus for the emergence of expectation and error signals. Movement-related expectation signals and sound-related error signals emerge in parallel in the auditory cortex and are concentrated in largely distinct neurons, consistent with a compartmentalization of different prediction-related computations. On a trial-by-trial basis, expectation and error signals are correlated in auditory cortex, consistent with a local circuit implementation of an internal model. Silencing the auditory cortex during motor-sensory learning prevents the emergence of expectation signals and error signals, revealing the auditory cortex as a necessary node for learning to make predictions. Prediction-like signals can be experimentally induced in the auditory cortex, even in the absence of behavioral experience, by pairing optogenetic motor cortical activation with sound playback, indicating that cortical circuits are sufficient for movement-like predictive processing. Finally, motor-sensory experience realigns the manifold dimensions in which auditory cortical populations encode movement and sound, consistent with predictive processing. These findings show that prediction-related signals reshape auditory cortex dynamics during behavior and reveal a cortical locus for the emergence of expectation and error.

The locus coeruleus as a global model failure system

Predictive processing models posit that brains constantly attempt to predict their sensory inputs. Prediction errors signal when these predictions are incorrect and are thought to be instructive signals that drive corrective plasticity. Recent findings support the idea that the locus coeruleus (LC) - a brain-wide neuromodulatory system - signals several types of prediction error. I discuss how these findings support models proposing that the LC signals global model failures: instances where predictions about the world are strongly violated. Focusing on the cortex, I explore the utility of this signal in learning rate control, how the LC circuit may compute the signal, and how this view may aid our understanding of neurodivergence.