Sex Differences in the Brain: Implications for Explaining Autism

Baron‐Cohen, Simon; Knickmeyer, Rebecca; Belmonte, Matthew K.

doi:10.1126/science.1115455

Cited by 950 publications

(787 citation statements)

References 76 publications

(59 reference statements)

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“…Since autism is a developmental disorder, these genes may affect or regulate the development of sexual dimorphism in the brain and in behavior. 56 The rationale for examining regression was based on previous work by Molloy et al, 27 where 34 families were identified with at least two affected individuals who showed regression. Signals in this earlier study were observed for chromosome 7 at 170.14 cM and chromosome 21 at 16.16 cM.…”

Section: Discussionmentioning

confidence: 99%

Evidence for multiple loci from a genome scan of autism kindreds

et al. 2006

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We performed a genome-wide linkage scan using highly polymorphic microsatellite markers. To minimize genetic heterogeneity, we focused on sibpairs meeting the strict diagnosis of autism. In our primary analyses, we observed a strong linkage signal (P = 0.0006, 133.16 cM) on chromosome 7q at a location coincident with other linkage studies. When a more relaxed diagnostic criteria was used, linkage evidence at this location was weaker (P = 0.01). The sample was stratified into families with only male affected subjects (MO) and families with at least one female affected subject (FC). The strongest signal unique to the MO group was on chromosome 11 (P = 0.0009, 83.82 cM), and for the FC group on chromosome 4 (P = 0.002, 111.41 cM). We also divided the sample into regression positive and regression negative families. The regression-positive group showed modest linkage signals on chromosomes 10 (P = 0.003, 0 cM) and 14 (P = 0.005, 104.2 cM). More significant peaks were seen in the regression negative group on chromosomes 3 (P = 0.0002, 140.06 cM) and 4 (P = 0.0005, 111.41 cM). Finally, we used language acquisition data as a quantitative trait in our linkage analysis and observed a chromosome 9 signal (149.01 cM) of P = 0.00006 and an empirical P-value of 0.0008 at the same location. Our work provides strong conformation for an autism locus on 7q and suggestive evidence for several other chromosomal locations. Diagnostic specificity and detailed analysis of the autism phenotype is critical for identifying autism loci.

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Section: Discussionmentioning

confidence: 99%

Evidence for multiple loci from a genome scan of autism kindreds

et al. 2006

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“…Several researchers have postulated that the cognitive style of a person or the adopted cognitive strategy in a situation is influenced by gender. In the empathizing-systemizing (E-S) theory of sex differences in cognitive style, males are held to be characterized by a stronger systemizing or analytical style, whereas female boast a stronger empathizing style (Baron-Cohen, Knickmeyer, & Belmonte, 2005). Strategy differences have even been advocated when interpreting gender differences in creative thinking.…”

Section: Gender and Cognitive Strategymentioning

confidence: 99%

Gender and creativity: an overview of psychological and neuroscientific literature

Abraham

2015

Brain Imaging and Behavior

175

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The topic of gender differences in creativity generates substantial scientific and public interest, but also courts considerable controversy. Owing to the heterogeneous nature of the findings associated with this line of research, the general picture often appears puzzling or obscure. The present article presents a selective overview of psychological and neuroscientific literature that has a relevant bearing on the theme of gender and creativity. Topics that are explored include the definition and methods of assessing creativity, a summary of behavioral investigations on gender in relation to creativity, postulations that have been forwarded to understand gender differences in creative achievement, gender-based differences in the structure and function of the brain, gender-related differences in behavioral performance on tasks of normative cognition, and neuroscientific studies of gender and creativity. The final section of the overview presents a detailed discussion of the idea that differences between men and women in creative cognition are best explained with reference to the gender-dependent adopted strategies or cognitive style when faced with generative tasks. Gender and Creativity 3Creativity refers to the singularly complex human ability to produce novel ideas, generate new solutions, and express oneself in a unique manner. Although prominent works of art and astounding scientific discoveries are the customary associations that are readily evoked when we consider the concept of creativity, our capacity to be creative is evident in virtually all aspects of human life when engaged in language and communication, choice and decision making, as well as planning and organization (Mark A. Runco & Pritzker, 2011;Sawyer, 2012). While the potential to be creative exists within each person, there is considerable individual variability in both the type and amount of creative output that is eventually produced over our lifetimes. A substantial proportion of the empirical investigations in creativity are directed at uncovering which variables have a positive or negative impact on creativity. Gender is one factor that has been explored in this regard within psychological research. This paper provides a general overview of psychological and neuroscientific research that has a direct or indirect bearing on the topic of gender and creativity. The first part of this paper is devoted to understanding what is meant by creativity in terms of definition and methods of assessment. This is followed by a summary of behavioral findings on gender-related differences in creative thinking and a discussion of the explanations that have been forwarded to understand such differences. Current knowledge concerning gender-based behavioral and neurobiological differences in other (non-creative) aspects of cognition is then explored. In the final part of the paper, implications of findings from neuroscientific studies of gender differences in creative thinking are discussed.Gender and Creativity 4

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Section: The Problemmentioning

confidence: 99%

“…Longitudinally, especially given autism's nature as a developmental disorder, measurements can be expected to change over the course of maturation and aging (Aylward, Minshew, Field, Sparks, & Singh, 2002;Carper, Moses, Tigue, & Courchesne, 2002). [The inconsistency of recent findings on the size of the amygdala at various ages is a case in point (Baron-Cohen, Knickmeyer, & Belmonte, 2005).] The consequent need to control and account for age particularly hampers retrospective efforts to combine separately ascertained samples.…”

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confidence: 99%

“…Cross-sectionally, autism's multiplicity of symptom profiles and neurobiological mechanisms makes it imperative to correlate imaging with other measures of potential endophenotypes, heightening the demand for large data sets which can be fractionated according to such measures. In addition, autism is much more common in males than in females, and sex differences extend to symptom profiles (McLennan, Lord, & Schopler, 1993) and possibly to mechanisms (Baron-Cohen et al, 2005), making it important to factor out sex as a variable, and magnifying the problem of sample size in the case of the smaller, female subgroup.The technical obstacles concern comparability of raw and derived data across scanners (Han et al, 2006;Jovicich et al, 2006) and analytical methods, as well as the problem of storage and retrieval of images and related subject variables. Adherence to fixed acquisition strategies is complicated by variables such as the radiopharmaceutical ligand chosen for a receptor of interest in PET, or the type of coil used in MRI or the type of crystal in PET.…”

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confidence: 99%

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Offering to Share: How to Put Heads Together in Autism Neuroimaging

Belmonte

Mazziotta

Minshew

et al. 2007

J Autism Dev Disord

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Data sharing in autism neuroimaging presents scientific, technical, and social obstacles. We outline the desiderata for a data-sharing scheme that combines imaging with other measures of phenotype and with genetics, defines requirements for comparability of derived data and NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript recommendations for raw data, outlines a core protocol including multispectral structural and diffusion-tensor imaging and optional extensions, provides for the collection of prospective, confound-free normative data, and extends sharing and collaborative development not only to data but to the analytical tools and methods applied to these data. A theme in these requirements is the need to preserve creative approaches and risk-taking within individual laboratories at the same time as common standards are provided for these laboratories to build on. KeywordsImaging; MRI; PET; Morphometry; Segmentation; Data sharing The ProblemTracing the behaviourally defined syndrome of autism to its neurobiological roots poses a difficulty since autism is heterogeneous in terms of its detailed symptom profiles (Ronald, Happé, & Plomin, 2005), genetic and environmental antecedents (Veenstra-Vanderweele, Christian, & Cook, 2004) and developmental mechanisms (Belmonte et al., 2004a). Because autism in this regard may be an amalgam of many unknown conditions, it seems a foregone conclusion that behaviourally ascertained groups of subjects contain large amounts of unmodelled variance, and that the relation between group size and statistical power is a steep one (Coon, 2006). This problem of sample size in the context of heterogeneous conditions is particularly acute in the domain of brain imaging, where costs are great and small samples are therefore more accepted and more usual. A solution seems clear in principle: the many small data sets collected by various investigators ought to be pooled into one large data set for analysis. Several obstacles, though, make such data sharing easier said than done. These obstacles are scientific, technical, and social-but not insurmountable.The scientific obstacles are matters of sample heterogeneity, which complicate the comparability of separately ascertained groups. This heterogeneity is both longitudinal and cross-sectional. Longitudinally, especially given autism's nature as a developmental disorder, measurements can be expected to change over the course of maturation and aging (Aylward, Minshew, Field, Sparks, & Singh, 2002;Carper, Moses, Tigue, & Courchesne, 2002). [The inconsistency of recent findings on the size of the amygdala at various ages is a case in point (Baron-Cohen, Knickmeyer, & Belmonte, 2005).] The consequent need to control and account for age particularly hampers retrospective efforts to combine separately ascertained samples. Cross-sectionally, autism's multiplicity of symptom profiles and neurobiological mechanisms makes it imperative to correlate imaging with other measures of potential endophenotypes, heightening the...

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Sex Differences in the Brain: Implications for Explaining Autism

Cited by 950 publications

References 76 publications

Evidence for multiple loci from a genome scan of autism kindreds

Evidence for multiple loci from a genome scan of autism kindreds

Gender and creativity: an overview of psychological and neuroscientific literature

Offering to Share: How to Put Heads Together in Autism Neuroimaging

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