Figure - available from: Frontiers in Human Neuroscience
This content is subject to copyright.
Cross-species comparison of the ratio between corpus callosum mid-sagittal area and brain size. The values used to construct this scatterplot as well as the references of the publications, from which these values were derived, can be found in Supplementary Table 4. Note that for humans, brain size was measured in cm³. The explained variance of this linear regression is R² = 0.644.
Source publication
Twenty years ago, Ringo and colleagues proposed that maintaining absolute connectivity in larger compared with smaller brains is computationally inefficient due to increased conduction delays in transcallosal information transfer and expensive with respect to the brain mass needed to establish these additional connections. Therefore, they postulate...
Similar publications
Despite a better understanding of brain language organization into large-scale cortical networks, the underlying white matter (WM) connectivity is still not mastered. Here we combined diffusion tensor imaging (DTI) fiber tracking (FT) and language functional magnetic resonance imaging (fMRI) in twenty healthy subjects to gain new insights into the...
Citations
... The copyright holder for this preprint (which this version posted April 6, 2024. ; https://doi.org/10.1101/2024.04.05.586081 doi: bioRxiv preprint compatible with the idea that more lateralized regions have a smaller density of interhemispheric connections (2,64). ...
Hemispheric lateralization is linked to potential cognitive advantages. It is considered a driving force behind the generation of human intelligence. However, establishing quantitative links between the degree of lateralization and intelligence in humans remains elusive. In this study, we propose a novel framework that utilizes the hyperaligned multidimensional representation space derived from hemispheric functional gradients to compute between-hemisphere distances within this space. Our analysis improves the functional alignment between the hemispheres, making it possible to delineate aspects of human brain lateralization that relate to individual differences in cognitive ability more precisely. Applying this framework to the Human Connectome Project (HCP) large cohort (N = 777) identified the highest functional divergence within the frontoparietal control network across the two hemispheres. We found that spatial variability in between-hemisphere functional divergence aligned with the lateralized response patterns across multiple tasks, cortical myelination and evolutionary expansion. Furthermore, both global divergence between the cerebral hemispheres and regional divergence within the multiple demand network were positively associated with fluid composite score and partially mediated the influence of brain size on individual differences in fluid intelligence. Together, these findings illuminate the profound significance of brain lateralization as a fundamental organizational principle of the human brain, providing direct evidence that hemispheric lateralization supports human fluid intelligence.
... DeCasien et al. focused their critique on our analysis of regional brain volumes, but I will add that Eliot et al. [1] also dove deeply into many other brain features oftdescribed as "sexually dimorphic". Most of these, such as the 6% greater gray matter-to-white matter ratio [20,23] and the higher interhemispheric-to-intrahemispheric connectivity ratio [24] in women are fully attributable to brain size. (Bigger brains have proportionally less gray matter and less efficient interhemispheric connectivity, regardless of sex [25][26][27].) ...
Human brain sex differences have fascinated scholars for centuries and become a key focus of neuroscientists since the dawn of MRI. We recently published a major review in Neuroscience and Biobehavioral Reviews showing that most male–female brain differences in humans are small and few have been reliably replicated. Although widely cited, this work was the target of a critical Commentary by DeCasien et al. (Biol Sex Differ 13:43, 2022). In this response, I update our findings and confirm the small effect sizes and pronounced scatter across recent large neuroimaging studies of human sex/gender difference. Based on the sum of data, neuroscientists would be well-advised to take the null hypothesis seriously: that men and women’s brains are fundamentally similar, or “monomorphic”. This perspective has important implications for how we study the genesis of behavioral and neuropsychiatric gender disparities.
... Hemisferio derecho: Se observan diferencias más destacables en relación a las áreas y perímetros entre el sexo femenino donde no presentan prácticamente variaciones y el masculino que disminuye con la edad.Hemisferio izquierdo: El área de la sustancia gris del GTS-I es ligeramente mayor en la mujer que en el varón a partir de los 85 años. En síntesis, los resultados son ( Graficas 10,11,12,13): En el Estudio comparativo entre ambos hemisferios y sexo masculino y femenino con relación al área de las 3 zonas medidas muestra que: El GH (Área 41: Córtex auditivo primario Izquierdo) aumenta con la edad en el sexo femenino y disminuye en el masculino. El PT (Área 42: Córtex auditivo asociativo) en el sexo femenino, no sufre grandes variaciones en el lado derecho. ...
... Investigaciones recientes sobre las interconexiones neuronales en 138 cerebros (grandes y pequeños) utilizando tractografia, señalan una interacción significativa entre el tamaño del cerebro y el tipo de conectividad. La conectividad estructural intrahemisférica es más fuerte en los cerebros más grandes, mientras que la conectividad interhemisférica aumenta sólo marginalmente en cerebros grandes en comparación con los más pequeños [13]. Las diferencias en la conectividad interhemisférica e intrahemisférica son inducidos por el tamaño del cerebro y no por el género. ...
... Las diferencias en la conectividad interhemisférica e intrahemisférica son inducidos por el tamaño del cerebro y no por el género. Estos resultados también son compatibles con la idea de que, en una región más asimétrica, es menor la densidad de las conexiones interhemisféricas, cuanto mayor sea la densidad de las conexiones intrahemisférica [13]. Un estudio de Resonancia magnética [20] en 104 participantes sobre el volumen cortical el grosor y la superficie corticales de la corteza auditiva ofrece un análisis de las asimetrías estructurales en 5 regiones anatómicamente definidas (giros de Heschl, surco de Heschl, plano temporal, plano polar, circunvolución temporal superior) de la corteza auditiva humana. ...
Resumen Diferencias anatómicas interhemisféricas en la corteza auditiva humana El procesamiento auditivo en la corteza cerebral, está compuesto por una red interconectada de áreas auditivas y áreas relacionadas, reguladas dinámicamente por las propiedades neuroquímicas de las neuronas y sus proyecciones. Estudios de resonancia magnética funcional revelan diferencias en la activación del sistema auditivo central entre el cerebro joven y viejo. La corteza auditiva es afectada no sólo por los efectos del envejecimiento en sí mismo, sino también por la falta de estimulación como consecuencia de la disfunción del oído interno. El objetivo del presente trabajo es examinar, a través de métodos cuantitativos, las variaciones del área y perímetro de la corteza auditiva: Giro de Heschl (GH), Plano Temporal (PT) y Giro Temporal Superior (GTS). En cerebros humanos postmortem, de adultos de edades comprendidas entre 59-97 años. Nuestros resultados muestran que los parámetros medidos del GH, PT y GTS fueron menores en los sujetos de edad avanzada en el hemisferio izquierdo salvo en las ultimas edades en el sexo femenino. Estos resultados sugieren que, además de los cambios periféricos descritos en sujetos de edad avanzada, también están presentes cambios en la parte central del sistema auditivo. Summary Interhemispheric anatomical differences in the human auditory cortex Auditory processing in the cerebral cortex is composed of an interconnected network of auditory and related areas, dynamically regulated by the neurochemical properties of neurons and their projections. Functional magnetic resonance imaging studies reveal differences in activation of the central auditory system between the young and old brain. The auditory cortex is affected not only by the effects of aging itself, but also by the lack of stimulation because of inner ear dysfunction. The objective of the present work is to examine, through quantitative methods, the variations of the area and perimeter of the auditory cortex: Heschl's Gyrus (GH), Temporal Plane (PT) and Superior Temporal Gyrus (GTS). In postmortem human brains of adults aged between 59-97 years. Our results show a tendency to register lower values in the area and perimeter of the GH, PT and GTS in the elderly subjects in the left hemisphere except in the later ages in the female sex. These results suggest that, in addition to the peripheral changes described in elderly subjects, changes are also present in the central part of the auditory system. Introducción La audición y el funcionamiento del sistema auditivo han despertado el interés de numerosos científicos a lo largo de la historia. Este interés se debe a la capacidad exclusiva del ser humano de emitir y comprender un conjunto de sonidos complejos que denominamos lenguaje. El lenguaje es un hecho cultural diferencial en el que se basa buena parte de la evolución humana [8-10]. La audición puede definirse como un proceso fisiológico específico que permite al ser vivo recibir y analizar las vibraciones de las moléculas del medio externo, dentro de un amplio rango de frecuencias e intensidades [8-10]. Los sonidos naturales suelen ser sonidos complejos que se caracterizan por su amplio espectro de frecuencias y su patrón temporal. El receptor auditivo periférico, debe descomponer estos sonidos complejos en frecuencias simples, generando una información que se trasmite al Sistema Nervioso Central (SNC). A través de la vía auditiva este mensaje llega a la corteza auditiva donde se lleva a cabo el análisis final de dicho mensaje. Para que el proceso de la audición sea más efectivo, el SNC debe efectuar además otras tareas, entre las que destaca la localización de la fuente sonora, el análisis de la intensidad (magnitud del estímulo), el
... Se acreditarmos nos comentários midiáticos em janeiro de 2014, os pesquisadores americanos teriam descoberto que as diferentes conexões cerebrais entre os sexos estariam na origem das diferenças de comportamento entre mulheres e homens (INGALHALIKAR et al., 2014). Todavia, os dados experimentais apresentados na publicação científica estão muito longe de permitir chegar às conclusões anunciadas (FILLOD, 2014;HÄNGGI et al., 2014;LUDERS et al., 2014). Por fim, essa publicação recebeu uma série de críticas severas em estudos posteriores que mostravam que as diferenças de conexões nervosas entre os sexos desapareciam quando o tamanho do cérebro era considerado nas comparações (COUPÉ et al., 2017;HÄNGGI et al., 2014;LUDERS et al., 2014;PINTZKA et al., 2015). ...
... Todavia, os dados experimentais apresentados na publicação científica estão muito longe de permitir chegar às conclusões anunciadas (FILLOD, 2014;HÄNGGI et al., 2014;LUDERS et al., 2014). Por fim, essa publicação recebeu uma série de críticas severas em estudos posteriores que mostravam que as diferenças de conexões nervosas entre os sexos desapareciam quando o tamanho do cérebro era considerado nas comparações (COUPÉ et al., 2017;HÄNGGI et al., 2014;LUDERS et al., 2014;PINTZKA et al., 2015). ...
... ARTIGO do cérebro, diversos estudos usando IRM mostram variações dependendo do sexo no volume de massa cinzenta (na qual estão concentrados os corpos celulares dos neurônios) e de massa branca (constituída de fibras nervosas dos corpos celulares dos neurônios). Desde o nascimento até a idade adulta, as meninas têm em média um pouco mais de massa cinzenta e os meninos de massa branca(DEAN, 2017;GIEDD, 2012;GILMORE, 2012;HÄNGGI et al., 2014).Essas diferenças cerebrais abriram espaço para todo tipo de especulações que pretendiam explicar as diferenças entre os sexos quanto à orientação no espaço, o raciocínio, a intuição, etc. Contudo, estudos recentes questionam a interpretação das diferenças anatômicas entre os cérebros de mulheres e homens. De fato, essas diferenças são apenas aparentes. ...
Apesar dos avanços no conhecimento em neurociências, percebemos que os preconceitos e estereótipos sobre as diferenças de atitudes e comportamentos entre os sexos estão ainda presentes no espaço público. A mídia e a internet nos inundam de velhos clichês que consideram as mulheres naturalmente dotadas para a empatia, mas incapazes de ler um mapa rodoviário, enquanto os homens seriam essencialmente bons em matemática e competitivos. Estes discursos fazem crer que nossas aptidões e personalidades são programadas em nossos cérebros e imutáveis. As pesquisas recentes mostram o contrário. Graças a suas formidáveis propriedades de “plasticidade”, o cérebro fabrica constantemente novos circuitos neurais, dependendo das aprendizagens e experiências de vida. O conceito de plasticidade cerebral é primordial para abordar a questão da origem das diferenças e semelhanças entre ossexos. Ele traz uma explicação neurobiológica fundamental para entender os mecanismos que participam da construção das nossas identidades de mulheres e homens, reforçando e enriquecendo as pesquisas em ciências humanas sobre o gênero.
... Larger brains need more or thicker white matter pathways to interconnect more distant regions, and interhemispheric traffic grows inefficient with increases in brain size (Zhang and Sejnowski, 2000). Hence, men's brains have ;6% higher white:gray matter ratio (Pintzka et al., 2015;Ritchie et al., 2018) and a lower ratio of interhemispheric to intrahemispheric connections (Ingalhalikar et al., 2014) than women's brains, both of which are attributable to brain size, not sex per se (Lewis et al., 2009;Hänggi et al., 2014). In other words, such measures differ between large-and small-headed men as much as between men and women, so are unlikely relevant to behavioral or clinical gender differences. ...
Long overlooked in neuroscience research, sex and gender are increasingly included as key variables potentially impacting all levels of neurobehavioral analysis. Still, many neuroscientists do not understand the difference between the terms “sex” and “gender,” the complexity and nuance of each, or how to best include them as variables in research designs. This TechSights article outlines rationales for considering the influence of sex and gender across taxa, and provides technical guidance for strengthening the rigor and reproducibility of such analyses. This guidance includes the use of appropriate statistical methods for comparing groups as well as controls for key covariates of sex (e.g., total intracranial volume) and gender (e.g., income, caregiver stress, bias). We also recommend approaches for interpreting and communicating sex- and gender-related findings about the brain, which have often been misconstrued by neuroscientists and the lay public alike.
... Thus, the effects of sex or frequent psychiatric comorbidities could not be assessed. In the case of sex, considering that CM is more prevalent in women compared to EM (Scher et al., 2019), and that interhemispheric connectivity is larger in women (Ingalhalikar et al., 2014, Hänggi et al., 2014, the analysis of men and women could help to understand whether interhemispheric connectivity is a causative factor for migraine. It is important to mention that, even though it has been argued that differences in interhemispheric connectivity only re ect differences in brain size or intracranial volume (Hänggi et al. 2014), we have found no correlation between brain size and migraine (see Supplementary Material). ...
... In the case of sex, considering that CM is more prevalent in women compared to EM (Scher et al., 2019), and that interhemispheric connectivity is larger in women (Ingalhalikar et al., 2014, Hänggi et al., 2014, the analysis of men and women could help to understand whether interhemispheric connectivity is a causative factor for migraine. It is important to mention that, even though it has been argued that differences in interhemispheric connectivity only re ect differences in brain size or intracranial volume (Hänggi et al. 2014), we have found no correlation between brain size and migraine (see Supplementary Material). ...
The structure of the brain can be characterized as a set of interconnected regions, using the concept of connectome. It has been shown that the connectome is altered in patients with migraine, presenting a series of structural connections differences with respect to healthy subjects. Relating these structural alterations to the specific characteristics of migraine is a difficult task. One approach is to study the effects of these alterations on the dynamic processes that can take place in the connectome. An ubiquitous process in brain networks is the synchronization of neuronal populations. It depends not only on the network but also on the properties of the units being synchronized. Fortunately, the contribution of the network structure can be calculated independently, thus defining the network synchronizability.
Connectome synchronizability and structural connectivity were assessed using diffusion-weighted magnetic resonance imaging data from 56 female patients with episodic migraine, 60 female patients with chronic migraine (CM) and 39 female healthy controls (HC). We found that whole-brain synchronizability was significantly larger in CM than in HC. The analysis of the synchronizability of subnetworks showed that differences between CM and HC were larger for subnetworks involving regions from different hemispheres. Moreover, the number of interhemispheric streamlines was significantly larger in CM than in HC, whereas no such difference appeared between intrahemispheric streamlines. The largest contributions to these differences come from the interhemispheric connections from three regions: left superior frontal gyrus, right precentral cortex, and right caudate.
... Females have greater within-network connectivity while males have greater between-network connectivity (9). These differences are modulated by brain size (13), genetics (14) and hormonal fluctuations (15)(16)(17)(18), but must also reflect other biological, social, and environmental influences. ...
Background:
Individual differences in functional brain connectivity can be used to predict both the presence of psychiatric illness and variability in associated behaviors. However, despite evidence for sex differences in functional network connectivity and in the prevalence, presentation, and trajectory of psychiatric illnesses, the extent to which disorder-relevant aspects of network connectivity are shared or unique across the sexes remains to be determined.
Methods:
In this work, we used predictive modeling approaches to evaluate whether shared or unique functional connectivity correlates underlie the expression of psychiatric illness-linked behaviors in males and females in data from the Adolescent Brain Cognitive Development study (n=5260; 2571 females).
Results:
We demonstrate that functional connectivity profiles predict individual differences in externalizing behaviors in males and females, but only predict internalizing behaviors in females. Furthermore, models trained to predict externalizing behaviors in males generalize to predict internalizing behaviors in females, and models trained to predict internalizing behaviors in females generalize to predict externalizing behaviors in males. Finally, the neurobiological correlates of many behaviors are largely shared within and across sexes: functional connections within and between heteromodal association networks including default, limbic, control, and dorsal attention networks are associated with internalizing and externalizing behaviors.
Conclusions:
Taken together, these findings suggest that shared neurobiological patterns may manifest as distinct behaviors across the sexes. Based on these results, we recommend that both clinicians and researchers carefully consider how sex may influence the presentation of psychiatric illnesses, especially those along the internalizing-externalizing spectrum.
... The corpus callosum tends to be larger or thicker in males when brain size is ignored, while it is larger in females when brain size is accounted for. The relatively stronger structural connectivity between the hemispheres in the female brain, has been previously attributed to reflect difference in brain size rather than being a sex-specific effect (Hänggi, Fövenyi, Liem, Meyer, & Jäncke, 2014;Jäncke et al., 2015;Jäncke et al., 1997;. In an influential paper, Ringo, Doty, Demeter, and Simard (1994) proposed that maintaining interhemispheric connectivity in larger compared to smaller brains becomes computationally inefficient, as the increased inter-cortical distances increase the conduction delays to a degree that they cannot be compensated. ...
... In an influential paper, Ringo, Doty, Demeter, and Simard (1994) proposed that maintaining interhemispheric connectivity in larger compared to smaller brains becomes computationally inefficient, as the increased inter-cortical distances increase the conduction delays to a degree that they cannot be compensated. As consequence, larger compared with smaller brains exhibit reduced inter-and enhanced intra-hemispheric connectivity (Hänggi et al., 2014) and the ratio of callosal to brain size is accordingly decreased in larger brains (Jäncke et al., 1997;Leonard et al., 2008). As the female brain is on average smaller than the male (Jäncke et al., 2015), the here found sex differences in the corpus callosum in favour of females, potentially reflects the higher ratio of callosal size to brain volume in smaller brains. ...
Originating from a series of morphometric studies conducted in the 1980s, it appears a widely held belief in cognitive neuroscience that the corpus callosum is larger in non-right handers than in right handers (RH). However, a recent meta-analysis challenges this belief by not finding significant differences in corpus callosum size between handedness groups. Yet, relying on the available published data, the meta-analysis was not able to account for a series of factors potential influencing its outcome, such as confounding effects of brain size differences and a restricted spatial resolution of previous callosal segmentation strategies. To address these remaining questions, we here analysed the midsagittal corpus callosum of N = 1057 participants from the Human Connectome Project (HCP 1200 Young Adults) to compare handedness groups based on consistency (e.g., consistent RH vs. mixed handers, MH) and direction of hand preference (e.g., RH vs. left handers). A possible relevance of brain-size differences was addressed by analysing callosal variability by both using forebrain volume (FBV) as covariate and utilising relative area (callosal area/thickness divided by FBV) as dependent variable. Callosal thickness was analysed at 100 measuring points along the structure to achieve high spatial resolution to detect subregional effects. However, neither of the conducted analyses was able to find significant handedness-related differences in callosal and the respective effect-sizes estimates were small. For example, comparing MH and consistent RH, the effect sizes for difference in callosal area were below a Cohen’s d = 0.1 (irrespective of how FBV was included), and narrow confidence intervals allowed to exclude effects above | d | = 0.2. Analysing thickness, effect sizes were below d = 0.2 with confidence intervals not extending above | d | = 0.3. In this, the possible range of population effect sizes of hand preference on callosal morphology appears well below the effects commonly reported for factors like age, sex, or brain size. Effects on cognition or behaviour accordingly can be considered small, questioning the common practise to attribute performance differences between handedness groups to differences in callosal architecture.
... In fact, results from Ingalhalikar and colleagues (Ingalhalikar et al. 2014) indicate that females exhibit stronger structural interhemispheric connectivity than men, unlike males in which the intra-hemispheric connections prevail compared to the other sex. However, other works suggest that such results do not hold if differences in brain volume are taken into account (Hänggi et al. 2014;Martinez et al. 2017). A related issue is that of sexual differences in hemispheric lateralization. ...
... This study was based on the hypothesis that women have more homotopic co-activations due to greater integration of their connectome. However, it appears that sex differences in connectivity are actually an effect of brain volume (Hänggi et al. 2014;Martínez et al. 2017). For our analysis this is not particularly relevant: given that women tend to have smaller brains than men, it follows that they will tend to have greater interhemispheric integration and, based on our results, stronger homotopic co-activations. ...
An element of great interest in functional connectivity is ‘homotopic connectivity’ (HC), namely the connectivity between two mirrored areas of the two hemispheres, mainly mediated by the fibers of the corpus callosum. Despite a long tradition of studying sexual dimorphism in the human brain, to our knowledge only one study has addressed the influence of sex on HC.
We investigated the issue of homotopic co-activations in women and men using a coordinate-based meta-analytic method and data from the BrainMap database. A first unexpected observation was that the database was affected by a sex bias: women-only groups are investigated less often than men-only ones, and they are more often studied in certain domains such as emotion compared to men, and less in cognition. Implementing a series of sampling procedures to equalize the size and proportion of the datasets, our results indicated that females exhibit stronger interhemispheric co-activation than males, suggesting that the female brain is less lateralized and more integrated than that of males. In addition, males appear to show less intense but more extensive co-activation than females. Some local differences also appeared. In particular, it appears that primary motor and perceptual areas are more co-activated in males, in contrast to the opposite trend in the rest of the brain. This argues for a multidimensional view of sex brain differences and suggests that the issue should be approached with more complex models than previously thought.
... Although speculative, a larger brain might require larger axonal diameter and higher degree of myelination to maintain conduction time along the longer axons (Liewald et al., 2014), and more intrahemispheric connections as long-range connections become increasingly inefficient in larger brains (Ringo et al., 1994). Support for this theory has been found in humans, where larger brains have greater intrahemispheric connectivity, as measured with DTI, than smaller brains, independent on sex (Hänggi et al., 2014). Finally, the spatially heterogeneous expansion of WM (Warling et al., 2021) and cortical surface area (Reardon et al., 2018) with increasing brain size may also lead to subtle changes in WM microstructure that may be observed using DTI. ...
Whether head size and/or biological sex influence proxies of white matter (WM) microstructure such as fractional anisotropy (FA) and mean diffusivity (MD) remains controversial. Diffusion tensor imaging (DTI) indices are also associated with age, but there are large discrepancies in the spatial distribution and timeline of age-related differences reported. The aim of this study was to evaluate the associations between intracranial volume (ICV), sex, and age and DTI indices from WM in a population-based study of healthy individuals (n = 812) aged 50-66 in the Nord-Trøndelag health survey. Semiautomated tractography and tract-based spatial statistics (TBSS) analyses were performed on the entire sample and in an ICV-matched sample of men and women. The tractography results showed a similar positive association between ICV and FA in all major WM tracts in men and women. Associations between ICV and MD, radial diffusivity and axial diffusivity were also found, but to a lesser extent than FA. The TBSS results showed that both men and women had areas of higher and lower FA when controlling for age, but after controlling for age and ICV only women had areas with higher FA. The ICV matched analysis also demonstrated that only women had areas of higher FA. Age was negatively associated with FA across the entire WM skeleton in the TBSS analysis, independent of both sex and ICV. Combined, these findings demonstrated that both ICV and sex contributed to variation in DTI indices and emphasized the importance of considering ICV as a covariate in DTI analysis.
