The Faces of Predictive Coding

Abstract

Recent neurophysiological accounts of predictive coding hypothesized that a mismatch of prediction and sensory evidence-a prediction error (PE)-should be signaled by increased gamma-band activity (GBA) in the cortical area where prediction and evidence are compared. This hypothesis contrasts with alternative accounts where violated predictions should lead to reduced neural responses. We tested these hypotheses by violating predictions about face orientation and illumination direction in a Mooney face-detection task, while recording magnetoencephalographic responses in a large sample of 48 human subjects. The investigated predictions, acquired via lifelong experience, are known to be processed at different time points and brain regions during face recognition.Behavioral responses confirmed the induction of PEs by our task. Beamformer source analysis revealed an early PE signal for unexpected orientation in visual brain areas followed by a PE signal for unexpected illumination in areas involved in 3D shape from shading and spatial working memory. Both PE signals were reflected by increases in high-frequency (68 -140 Hz) GBA. In high-frequency GBA we also observed a late interaction effect in visual brain areas, probably corresponding to a high-level PE signal. In addition, increased high-frequency GBA for expected illumination was observed in brain areas involved in attention to internal representations. Our results strongly support the hypothesis that increased GBA signals PEs. Additionally, GBA may represent attentional effects.

Layer and rhythm specificity for predictive routing

“…The central idea is that alpha/beta feeds back predictions down the cortical hierarchy while gamma feeds forward unexpected inputs up the hierarchy. This is supported by human electro/magnetoencephalography (MEG/EEG) studies and a recent monkey electrocorticography study (Arnal and Giraud, 2012;Auksztulewicz and Friston, 2016;Bauer et al, 2006;Brodski et al, 2015;Chao et al, 2018;Mayer et al, 2016;van Pelt et al, 2016;Todorovic et al, 2011). Further, alpha/beta power is higher in deep-layer cortex and gamma power is higher in superficial layers (Bastos et al, 2018;Maier et al, 2010;Smith et al, 2013).…”

Higher performers upregulate brain signal variability in response to more feature-rich visual input

“…It is this former type of uncertainty that seems most relevant to the current study. Faces are an excellent candidate for consideration as a relatively certain distribution/prior (Brodski et al 2015;Brodski-Guerniero et al 2017). Humans are considered face experts in general relative to other stimulus categories (Carey and Diamond 1977;Carey 1992), and faces can be reduced to a limited number of statistical dimensions, yet still be processed, discriminated, and recognized (Sirovich and Kirby 1987;O'toole et al 1993;Tsao and Livingstone 2008).…”

From symbols to icons: the return of resemblance in the cognitive neuroscience revolution

“…Kaplan and Craver 2011b) at present, pitched largely at Marr's (1982) "algorithmic" level of description with only tentative proposals about how the functional roles it identifies are realised in cortical circuitry (cf. Brodski et al 2015;Gordon et al 2017;Weilnhammer et al 2017). 6 Nevertheless, it nicely illustrates the points we are making, and manifests how a regulative and thoroughly predictive perspective on brain function harmonises with an iconic approach to cognitive representation.…”