Abstract
Predictive processing, a leading theoretical framework for sensory processing, suggests that the brain constantly generates predictions on the sensory world and that perception emerges from the comparison between these predictions and the actual sensory input. This requires two distinct neural elements: generative units, which encode the model of the sensory world; and prediction error units, which compare these predictions against the sensory input. Although predictive processing is generally portrayed as a theory of cerebral cortex function, animal and human studies over the last decade have robustly shown the ubiquitous presence of prediction error responses in several nuclei of the auditory, somatosensory, and visual subcortical pathways. In the auditory modality, prediction error is typically elicited using so-called oddball paradigms, where sequences of repeated pure tones with the same pitch are at unpredictable intervals substituted by a tone of deviant frequency. Repeated sounds become predictable promptly and elicit decreasing prediction error; deviant tones break these predictions and elicit large prediction errors. The simplicity of the rules inducing predictability make oddball paradigms agnostic about the origin of the predictions. Here, we introduce two possible models of the organizational topology of the predictive processing auditory network: (1) the global view, that assumes that predictions on the sensory input are generated at high-order levels of the cerebral cortex and transmitted in a cascade of generative models to the subcortical sensory pathways; and (2) the local view, that assumes that independent local models, computed using local information, are used to perform predictions at each processing stage. In the global view information encoding is optimized globally but biases sensory representations along the entire brain according to the subjective views of the observer. The local view results in a diminished coding efficiency, but guarantees in return a robust encoding of the features of sensory input at each processing stage. Although most experimental results to-date are ambiguous in this respect, recent evidence favors the global model.
Highlights
The massive bundle of corticofugal fibers stemming from auditory cortex and targeting nuclei of the subcortical auditory pathway (Winer, 1984, 2005b; Schofield, 2011) have posed a puzzling problem to the auditory neuroscience community for decades (Syka et al, 1988; Winer, 2005a; Robinson and McAlpine, 2009; He and Yu, 2010)
Extending this role to the corticofugal system between cerebral cortex and subcortical sensory pathway nuclei suggests that predictions drawn by generative models in cerebral cortex are conveyed to subcortical sensory neurons that encode prediction error (Von Kriegstein et al, 2008; Diaz et al, 2012; Malmierca et al, 2015)
Using Bayesian Model comparison, we showed that responses in the IC and MGB (Figure 2B) were far more likely to be produced by a mechanism following the principles of the global model than by a mechanism following the principles of the local model
Summary
The massive bundle of corticofugal fibers stemming from auditory cortex and targeting nuclei of the subcortical auditory pathway (Winer, 1984, 2005b; Schofield, 2011) have posed a puzzling problem to the auditory neuroscience community for decades (Syka et al, 1988; Winer, 2005a; Robinson and McAlpine, 2009; He and Yu, 2010). Over the last decade the auditory neuroscience community has robustly shown the predominance of neurons encoding prediction error neurons in subcortical sensory pathway nuclei (Anderson et al, 2009; Malmierca et al, 2009, 2014, 2019; Grimm et al, 2016; Parras et al, 2017; Carbajal and Malmierca, 2018) These results are often taken as proof that the corticofugal system is transmitting predictions, most experimental paradigms control predictability using simple rules that can be readily encoded at the same processing stage as the prediction error (Eytan et al, 2003; Mill et al, 2011; Wang et al, 2014; May et al, 2015); i.e., without needing a top-down system. We focus on audition because it is the modality where subcortical predictive processing has been explored the most in the last decade (Nelken and Ulanovsky, 2007; Garrido et al, 2009; Grimm et al, 2011; Escera and Malmierca, 2014; Malmierca et al, 2015; Heilbron and Chait, 2017; Carbajal and Malmierca, 2018)
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