Repeating patterns: Predictive processing suggests an aesthetic learning role of the basal ganglia in repetitive stereotyped behaviors

An active inference perspective for the amygdala complex

The amygdala is a heterogeneous network of subcortical nuclei with central importance in cognitive and clinical neuroscience. Various experimental designs in human psychology and animal model research have mapped multiple conceptual frameworks (e.g., valence/salience and decision making) to ever more refined amygdala circuitry. However, these predominantly bottom up-driven accounts often rely on interpretations tailored to a specific phenomenon, thus preventing comprehensive and integrative theories. We argue here that an active inference model of amygdala function could unify these fractionated approaches into an overarching framework for clearer empirical predictions and mechanistic interpretations. This framework embeds top-down predictive models, informed by prior knowledge and belief updating, within a dynamical system distributed across amygdala circuits in which self-regulation is implemented by continuously tracking environmental and homeostatic demands.

Pre-attentive representation of prediction certainty in autism: A mismatch negativity (MMN) study

According to predictive processing theories of perception, the brain generates predictions to prepare for sensory input, and calibrates certainty of predictions based on their likelihood. When an input doesn't match the prediction, an error signal leads to updating of the predictive model. Prior research suggests altered prediction certainty in autism, but predictive processing occurs across the cortical hierarchy, and the stage(s) of processing where prediction certainty breaks down is unknown. We therefore tested the integrity of prediction certainty in autism at pre-attentive and relatively automatic processing stages using the pre-attentive Mismatch Negativity (MMN) brain response. The MMN occurs in response to a "deviant" presented in a stream of "standards" and is measured while the participant performs an orthogonal task. Most critically, MMN amplitude typically varies with the level of certainty associated with the prediction. We recorded high-density EEG while presenting adolescents and young adults with and without autism with repetitive tones every half second (the standard) interspersed with infrequent pitch and inter-stimulus-interval (ISI) deviants. Pitch and ISI deviant probabilities were manipulated at 4, 8, or 16% within a block of trials to test whether MMN amplitude varied in a typical manner with respect to probability. For both groups, Pitch-MMN amplitude increased as the probability of deviance decreased. Unexpectedly, ISI-MMN amplitude did not reliably vary by probability in either group. Our Pitch-MMN findings suggest intact neural representation of pre-attentive prediction certainty in autism, addressing a critical knowledge gap in autism research. The implications of these findings are considered.

LAY SUMMARY

Our brains are always trying to predict what will happen next. For example, when you open your utensil drawer, it would be surprising to see books because your brain expected to see utensils. In our study, we looked at whether the brains of autistic individuals automatically and accurately recognize when something unexpected happens. Results showed similar brain patterns in individuals with and without autism, suggesting that responses to prediction violations are generated in a typical manner during early cortical information processing.

Three-dimensional pseudocontinuous arterial spin labeling perfusion imaging shows cerebral blood flow perfusion decline in attention-deficit/hyperactivity disorder children

PURPOSE

To investigate the feasibility of three-dimensional pseudocontinuous arterial spin labeling (3D-pcASL) perfusion imaging in the brain of children with Attention-deficit/hyperactivity disorder (ADHD).

METHODS

A total of 78 ADHD children aged 5-13 years were prospectively selected as the study group, and 89 healthy children matched in age and sex were selected as the control group. All children underwent MRI conventional sequence, 3D-pcASL, and 3D-T1 sequence scans. The brain gray and white matter volume and cerebral blood flow (CBF) perfusion values were obtained by software post-processing, and were compared and analyzed in the two groups to find out their characteristics in the brain of ADHD children.

RESULTS

The total brain volume and total CBF values were lower in ADHD children than in healthy children (P < 0.05); the gray and white matter volumes in the frontal lobe, temporal lobe, hippocampus, caudate nucleus, putamen, globus pallidus and other brain regions were lower in ADHD children than in healthy children (P < 0.05); the gray matter CBF values in the frontal lobe, temporal lobe, hippocampus, caudate nucleus, putamen, globus pallidus and other brain regions were lower in ADHD children than in healthy children (P < 0.05); the differences between the white matter CBF values of white matter in the said brain regions of ADHD children and healthy children were not statistically significant (P > 0.05); and the CBF values in frontal lobe and caudate nuclei could distinguish ADHD children (AUC > 0.05, P < 0.05).

CONCLUSION

The 3D-pcASL technique showed reduced cerebral perfusion in some brain regions of ADHD children.