The effect of learning to drum on behavior and brain function in autistic adolescents

The default mode network is associated with changes in internalizing and externalizing problems differently in adolescent boys and girls

Internalizing and externalizing problems that emerge during adolescence differentially increase boys' and girls' risk for developing psychiatric disorders. It is not clear, however, whether there are sex differences in the intrinsic functional architecture of the brain that underlie changes in the severity of internalizing and externalizing problems in adolescents. Using resting-state fMRI data and self-reports of behavioral problems obtained from 128 adolescents (73 females; 9-14 years old) at two timepoints, we conducted multivoxel pattern analysis to identify resting-state functional connectivity markers at baseline that predict changes in the severity of internalizing and externalizing problems in boys and girls 2 years later. We found sex-differentiated involvement of the default mode network in changes in internalizing and externalizing problems. Whereas changes in internalizing problems were associated with the dorsal medial subsystem in boys and with the medial temporal subsystem in girls, changes in externalizing problems were predicted by hyperconnectivity between core nodes of the DMN and frontoparietal network in boys and hypoconnectivity between the DMN and affective networks in girls. Our results suggest that different neural mechanisms predict changes in internalizing and externalizing problems in adolescent boys and girls and offer insights concerning mechanisms that underlie sex differences in the expression of psychopathology in adolescence.

Enhanced sensitivity to pitch perception and its possible relation to language acquisition in autism

Background and aims

Fascinations for or aversions to particular sounds are a familiar feature of autism, as is an ability to reproduce another person's utterances, precisely copying the other person's prosody as well as their words. Such observations seem to indicate not only that autistic people can pay close attention to what they hear, but also that they have the ability to perceive the finer details of auditory stimuli. This is consistent with the previously reported consensus that absolute pitch is more common in autistic individuals than in neurotypicals. We take this to suggest that autistic people have perception that allows them to pay attention to fine details. It is important to establish whether or not this is so as autism is often presented as a deficit rather than a difference. We therefore undertook a narrative literature review of studies of auditory perception, in autistic and nonautistic individuals, focussing on any differences in processing linguistic and nonlinguistic sounds.

Main contributions

We find persuasive evidence that nonlinguistic auditory perception in autistic children differs from that of nonautistic children. This is supported by the additional finding of a higher prevalence of absolute pitch and enhanced pitch discriminating abilities in autistic children compared to neurotypical children. Such abilities appear to stem from atypical perception, which is biased toward local-level information necessary for processing pitch and other prosodic features. Enhanced pitch discriminating abilities tend to be found in autistic individuals with a history of language delay, suggesting possible reciprocity. Research on various aspects of language development in autism also supports the hypothesis that atypical pitch perception may be accountable for observed differences in language development in autism.

Conclusions

The results of our review of previously published studies are consistent with the hypothesis that auditory perception, and particularly pitch perception, in autism are different from the norm but not always impaired. Detail-oriented pitch perception may be an advantage given the right environment. We speculate that unusually heightened sensitivity to pitch differences may be at the cost of the normal development of the perception of the sounds that contribute most to early language development.

Implications

The acquisition of speech and language may be a process that normally involves an enhanced perception of speech sounds at the expense of the processing of nonlinguistic sounds, but autistic children may not give speech sounds this same priority.

Improvised herding: Mapping biobehavioral mechanisms that underlie group efficacy during improvised social interaction

Improvisation is a natural occurring phenomenon that is central to social interaction. Yet, improvisation is an understudied area in group processes and intergroup relations. Here we build on theory and research about human herding to study the contributions of improvisation on group efficacy and its biobehavioral underpinnings. We employed a novel multimodal approach and integrative method when observing face-to-face interactions-51 triads (total N = 153) drummed together in spontaneous-free improvisations as a group, while their electrodermal activity was monitored simultaneously with their second-by-second rhythmic coordination on a shared electronic drum machine. Our results show that three hypothesized factors of human herding-physiological synchrony, behavioral coordination, and emotional contagion-predict a sense of group efficacy in its group members. These findings are some of the first to show herding at three levels (physiological, behavioral, and mental) in a single study and lay a basis for understanding the role of improvisation in social interaction.

Brain-wide connectome inferences using functional connectivity MultiVariate Pattern Analyses (fc-MVPA)

Current functional Magnetic Resonance Imaging technology is able to resolve billions of individual functional connections characterizing the human connectome. Classical statistical inferential procedures attempting to make valid inferences across this many measures from a reduced set of observations and from a limited number of subjects can be severely underpowered for any but the largest effect sizes. This manuscript discusses fc-MVPA (functional connectivity Multivariate Pattern Analysis), a novel method using multivariate pattern analysis techniques in the context of brain-wide connectome inferences. The theory behind fc-MVPA is presented, and several of its key concepts are illustrated through examples from a publicly available resting state dataset, including an analysis of gender differences across the entire functional connectome. Finally, Monte Carlo simulations are used to demonstrate the validity and sensitivity of this method. In addition to offering powerful whole-brain inferences, fc-MVPA also provides a meaningful characterization of the heterogeneity in functional connectivity across subjects.

The human connectome comprises billions of functional connections between distant brain areas. In recent years, analyses of functional Magnetic Resonance Imaging (fMRI) data have provided large amounts of information exploring the differences in the human connectome across individuals, developmental trajectories, or mental states. However, scientists’ ability to derive strong conclusions from the analysis of these data are often hindered by the sheer number of connections analyzed, where only connections that show exceptionally large effects are able to stand out against that vast background. This leads to results that tend to overemphasize similarities and mask out differences that are either weaker or distributed across multiple individual connections, potentially misleading conceptual models of the human connectome. This manuscript discusses a novel method for the analysis of the human connectome (functional connectivity Multivariate Pattern Analysis) that addresses these limitations and enables strong conclusions from fMRI data by combining classical statistics with modern pattern analysis techniques. This technique is exemplified using a publicly available database of resting state data to characterize some of the main aspects of the human connectome that differ across individuals, and to identify specific differences in the human connectome across gender.