Investigating Predictive Coding in Younger and Older Children Using MEG and a Multi-Feature Auditory Oddball Paradigm

Abstract

There is mounting evidence for predictive coding theory from computational, neuroimaging, and psychological research. However there remains a lack of research exploring how predictive brain function develops across childhood. To address this gap, we used paediatric magnetoencephalography (MEG) to record the evoked magnetic fields of 18 younger children (M = 4.1 years) and 19 older children (M = 6.2 years) as they listened to a 12-minute auditory oddball paradigm. For each child, we computed a MisMatch Field (MMF): an electrophysiological component that is widely interpreted as a neural signature of predictive coding. Consistent with our hypotheses, the older children showed significantly larger MMF amplitudes relative to the younger children. Furthermore, the older children showed a significantly larger MMF amplitude in the right inferior frontal gyrus (IFG; 0.312 to 0.33 s) relative to the younger children, p < .05. These findings support the idea that predictive brain function develops during childhood, with increasing involvement of the frontal cortex in response to prediction errors. These findings contribute to a deeper understanding of the brain function underpinning child cognitive development.

Unshared Realities: A Rhetorical, Double-Empathy Perspective on Autistic University Students’ Lived Experiences of Academic Acculturation

“…Specifically, I have explored the possibility that this kind of lived experience (or, perezhivanie) might lead to autistic students typifying social learning experiences differently compared to nonautistic people. Indeed, this finding aligns with neuroscientific and predictive coding accounts (or, Bayesian statistics, see section 2.2.3.1) of autistic peoples' distinct predictions and constructions of their physical environment (Palmer et al, 2017;Pellicano & Burr, 2012;Rapaport et al, 2022). That is, neuroscientific techniques together with advanced statistical modelling as is used in predictive coding studies have found that autistic people's predictions or expectations (or, typifications) of their physical environment are distinct from that of nonautistic people (Pellicano 127 & Burr, 2012;Rapaport et al, 2022).…”

“…Typically, experience in interacting with the world results in learning more accurate predictions (top-down processing) of "reality" over time, but in the case of autistic peoples' experiences and perceptions, Pellicano and Burr (2012) found that autistic people rely more on incoming sensory information (bottom-up) rather than learned predictions. Other researchers (Lawson et al, 2014;Rapaport et al, 2022) have found quite the opposite. That is, they found that autistic people use prior, but over-specified (or, over detailed) predictions from previously encountered experiences.…”

“…Miller (1984) also argued that a rhetorical situation and its exigence are not only being perceived, but are defined, or socially constructed, from earlier, antecedent, and recurrent experiences (similar to the predictions, or priors, conceptualized in predictive coding studies, e.g., Palmer et al, 2017;Pellicano & Burr, 2012;Rapaport et al, 2022). Indeed, such a definition of the social needs or exigences invites a certain type of social response (verbal or nonverbal) which therefore becomes typified (Schutz & Luckmann, 1973).…”

“…Next, I describe the concept of typification as it relates to findings from neuroscience and predictive coding studies (Palmer et al, 2017;Pellicano & Burr, 2012;Rapaport et al, 2022).…”

“…In this multiphase study, I have described autistic peoples' distinct sensory and perceptual experiential learning (Mottron et al, 2006;Pellicano, 2013;Rapaport et al, 2022;Stevenson et al, 2014), especially their reports of noticing greater detail in their physical and social environments.. Specifically, I have explored the possibility that this kind of lived experience (or, perezhivanie) might lead to autistic students typifying social learning experiences differently compared to nonautistic people.…”