Pattern learning reveals brain asymmetry to be linked to socioeconomic status

Poeppl, Timm B.; Dimas, Emile; Sakreida, Katrin; Kernbach, Julius M; Markello, Ross; Schöffski, Oliver; Koellinger, Philipp; Nave, Gideon; Farah, Martha J.; Mišić, Bratislav; Bzdok, Danilo

doi:10.1093/texcom/tgac020

Cited by 7 publications

(3 citation statements)

References 62 publications

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“…Across 3 data sets and a range of phenotypic measures, predictive models systematically failed in individuals who defy stereotypical profiles of high and low scorers. These results demonstrate limited model generalizability and that bias in phenotypic measures may be reflected in corresponding brain models, consistent with the findings that variables such as SES are associated with functional network organization and cortical structure into adulthood, and that brain measures mediate associations between SES and various outcomes, such as negative mood . A related issue is that phenotypic measures, often designed to capture complex behaviors, may not map onto single cognitive constructs and corresponding neurobiological systems …”

Section: Reaching Across Literatures To Increase the Accuracy Precisi...supporting

confidence: 64%

Clinical Promise of Brain-Phenotype Modeling

Greene

Constable

2023

JAMA Psychiatry

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ImportanceAssessing the link between whole-brain activity and individual differences in cognition and behavior has the potential to offer insights into psychiatric disorder etiology and change the practice of psychiatry, from diagnostic clarification to intervention. To this end, recent application of predictive modeling to link brain activity to phenotype has generated significant excitement, but clinical applications have largely not been realized. This Review explores explanations for the as yet limited practical utility of brain-phenotype modeling and proposes a path forward to fulfill this clinical potential.ObservationsClinical applications of brain-phenotype models are proposed and will require coordinated collaboration across the relatively siloed fields of psychometrics and computational neuroscience. Such interdisciplinary work will maximize the reliability and validity of modeled phenotypic measures, ensuring that resulting brain-based models are interpretable and useful. The models, in turn, may shed additional light on the neurobiological systems into which each phenotypic measure taps, permitting further phenotype refinement.Conclusions and RelevanceTogether, these observations reflect an opportunity: bridging the divide between phenotypic measure development and validation and measure end use for brain-phenotype modeling holds the promise that each may inform the other, yielding more precise and useful brain-phenotype models. Such models can in turn be used to reveal the macroscale neural bases of a given phenotype, advancing basic neuroscientific understanding and identifying circuits that can be targeted (eg, via closed-loop neurofeedback or brain stimulation) to slow, reverse, or even prevent functional impairment.

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Section: Reaching Across Literatures To Increase the Accuracy Precisi...supporting

confidence: 64%

Clinical Promise of Brain-Phenotype Modeling

Greene

Constable

2023

JAMA Psychiatry

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“…Finally, statistically salient coefficients had a distribution of 1000 LDA coefficients robustly different from 0. Specifically, they were interpreted as robustly different from zero if their two-sided confidence interval according to the 2.5/97.5% bootstrap-derived distribution did not include zero coefficient value, indicating the absence of an effect 147 . Finally, we compared LDA coefficients between different CNVs using Pearson’s correlation.…”

Section: Methodsmentioning

confidence: 99%

Using rare genetic mutations to revisit structural brain asymmetry

Kopal,

Kumar,

Shafighi

et al. 2024

Nat Commun

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Asymmetry between the left and right hemisphere is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variants, which typically exert small effects on brain-related phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We designed a pattern-learning approach to dissect the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior data fusion highlights the consequences of genetically controlled brain lateralization on uniquely human cognitive capacities.

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“…It is hypothesized that brain functional segregation, which refers to the lateralization of some functions in one hemisphere and some other functions in the opposite hemisphere, confers a selective advantage (Poeppl et al, 2022;Rogers, 2021). This could be by avoiding redundancy, preventing duplication of control systems which enhance the use of both hemispheres, increasing the brain's ability to perform multiple tasks simultaneously, maximizing available space, and allowing higher processing speed (Esteves, Lopes et al, 2020;Gerrits et al, 2020b;Güntürkün et al, 2020).…”

Section: Handedness and Cerebral Lateralizationmentioning

confidence: 99%

Development of laterality: Asymmetrical human behaviors and perceptual biases

Hamaoui¹

2022

Preprint

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Many asymmetries characterize human functioning at the behavioral level, such as handedness (right-handedness, left-handedness, mixed-handedness) and the cerebral level. Atypical laterality is frequently mentioned in scientific literature as part of the clinical picture of several neurodevelopmental and psychiatric disorders. Thus, understanding the neurodevelopmental mechanisms underlying laterality could shed light on the etiology of cognitive and motor difficulties. The goal of this thesis is twofold. Firstly, the theoretical objective was to investigate the involvement of the prenatal environment in the development of handedness. The influence of the vestibular system, fetal presentation, and other perinatal factors related to pregnancy complications and birth stressors were tested. Our results show no influence of the fetal presentation on the subsequent development of handedness. Perinatal adversities such as prematurity, low birthweight, and poor neonatal health reflected by very low Apgar scores however, appear to be risk factors which increase the prevalence of atypical handedness and motor impairments. Secondly, the applied objective was to simultaneously detect the different perceptual biases implicated in graphomotor productions. A 3D-2D transcription graphic task was proposed for identifying global patterns of drawing asymmetries, underpinned by cerebral lateralization, biomechanical constraints, and sociocultural influences. Our results suggest that cerebral lateralization, modulated by handedness and sex, influence graphomotor asymmetries in both children and adults. However, this influence is weaker in adults, which could be due to sociocultural influences.

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Pattern learning reveals brain asymmetry to be linked to socioeconomic status

Cited by 7 publications

References 62 publications

Clinical Promise of Brain-Phenotype Modeling

Clinical Promise of Brain-Phenotype Modeling

Using rare genetic mutations to revisit structural brain asymmetry

Development of laterality: Asymmetrical human behaviors and perceptual biases

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