Publications

Abstract

This chapter introduces the origins and development of our current anatomical terminology. It scrutinizes the historical evolution and etymological significance of the over 1900 official anatomical terms in the current nomenclature, underscoring their impact on the contemporary comprehension of cognitive neuroanatomy. The chapter traces unification efforts from the Basel Nomina Anatomica in 1895 to the 1998 Terminologia Anatomica, noting challenges arising from outdated terminology in light of recent anatomical advancements.

Highlighting the influence of terminologies on interpretations of brain anatomy, the chapter explores several anatomical mapping methods such as surface, sectional, connectional, and functional anatomy. It illuminates discrepancies and controversies, exemplified by divergent interpretations of the number of brain lobes and the definitions of 'Broca' and 'Wernicke' areas.

The chapter explores anatomical terms' historical and cultural underpinnings, encompassing mythonyms, eponyms, and cultural influences on nomenclature. It critically examines the implications of these terminologies on contemporary research and shows that Large Language Models mirror these discrepancies. It underscores the need for more inclusive and culturally sensitive approaches in anatomical education.

Lastly, we advocate for updating anatomical nomenclature, suggesting that a deeper understanding of these terminologies could provide insights and aid in resolving ongoing debates in the field. This examination sheds light on historical knowledge and emphasizes the dynamic interplay between language, culture, and anatomy in shaping our comprehension of the neurobiology of the brain and how we navigate neuroanatomy in the 21st century.

Abstract

The human brain is an intricate network of cortical regions interconnected by white matter pathways, dynamically supporting cognitive functions. While cortical asymmetries have been consistently reported, the asymmetry of white matter connections remains less explored. This chapter provides a brief overview of asymmetries observed at the cortical, subcortical, cytoarchitectural, and receptor levels before exploring the detailed connectional anatomy of the human brain. It thoroughly examines the lateralization and interindividual variability of 56 distinct white matter tracts, offering a comprehensive review of their structural characteristics and interindividual variability. Additionally, we provide an extensive update on the asymmetry of a wide range of white matter tracts using high-resolution data from the Human Connectome Project (7T HCP www.humanconnectome.org). Future research and advanced quantitative analyses are crucial to understanding fully how asymmetry contributes to interindividual variability. This comprehensive exploration enhances our understanding of white matter organization and its potential implications for brain function.

Abstract

The brain is the most magnificent structure, and we are only at the cusp of unraveling some of its complexity. Neuroanatomy is the best tool to map the brain's structural complexity. As such, neuroanatomy is not just an academic exercise; it serves our fundamental understanding of the neurobiology of cognition and improves clinical practice. A deepened anatomical understanding has advanced our conceptual grasp of the evolution of the brain, interindividual variability of cognition in health and disease, and the conceptual shift toward the emergence of cognition. For the past 20 years, diffusion imaging tractography has dramatically facilitated these advances by enabling the study of the delicate networks that orchestrate brain processes (for review, see Thiebaut de Schotten and Forkel, 2022). Several steps are consistent across all studied populations and brain states (health/disease) when analyzing tractography data. We discuss various considerations for dissections across populations and give practical tips on common pitfalls and features to improve the visualization of the dissections. We briefly discuss specific considerations for manual dissections in nonhuman primates. Lastly, we provide an atlas of regions of interest (ROIs) for the most commonly delineated white matter connections in the human brain.

Abstract

Brain tumors are classified as rare diseases, with an annual occurrence of 300,000 cases and account for an annual loss of 241,000 lives, highlighting their devastating nature. Recent advancements in diagnosis and treatment have significantly improved the management and care of brain tumors. This chapter provides an overview of the common types of primary brain tumors affecting language functions—gliomas and meningiomas. Techniques for identifying and mapping critical language areas, including the white matter language system, such as awake brain tumor surgery and diffusion-weighted tractography, are pivotal for understanding language localization and informing personalized treatment approaches. Numerous studies have demonstrated that gliomas in the dominant hemisphere can lead to (often subtle) impairments across various cognitive domains, with a particular emphasis on language. Recently, increased attention has been directed toward (nonverbal) cognitive deficits in patients with gliomas in the nondominant hemisphere, as well as cognitive outcomes in patients with meningiomas, a group historically overlooked. A patient-tailored approach to language and cognitive functions across the pre-, intra-, and postoperative phases is mandatory for brain tumor patients to preserve quality of life. Continued follow-up studies, in conjunction with advanced imaging techniques, are crucial for understanding the brain's potential for neuroplasticity and optimizing patient outcomes.

Abstract

Evolution, as we currently understand it, strikes a delicate balance between animals' ancestral history and adaptations to their current niche. Similarities between species are generally considered inherited from a common ancestor whereas observed differences are considered as more recent evolution. Hence comparing species can provide insights into the evolutionary history. Comparative neuroimaging has recently emerged as a novel subdiscipline, which uses magnetic resonance imaging (MRI) to identify similarities and differences in brain structure and function across species. Whereas invasive histological and molecular techniques are superior in spatial resolution, they are laborious, post-mortem, and oftentimes limited to specific species. Neuroimaging, by comparison, has the advantages of being applicable across species and allows for fast, whole-brain, repeatable, and multi-modal measurements of the structure and function in living brains and post-mortem tissue. In this review, we summarise the current state of the art in comparative anatomy and function of the brain and gather together the main scientific questions to be explored in the future of the fascinating new field of brain evolution derived from comparative neuroimaging.

Abstract

Social factors play a crucial role in the advancement of science. New findings are discussed and theories emerge through social interactions, which usually take place within local research groups and at academic events such as conferences, seminars, or workshops. This system tends to amplify the voices of a select subset of the community—especially more established researchers—thus limiting opportunities for the larger community to contribute and connect. Brainhack (https://brainhack.org/) events (or Brainhacks for short) complement these formats in neuroscience with decentralized 2- to 5-day gatherings, in which participants from diverse backgrounds and career stages collaborate and learn from each other in an informal setting. The Brainhack format was introduced in a previous publication (Cameron Craddock et al., 2016; Figures 1A and 1B). It is inspired by the hackathon model (see glossary in Table 1), which originated in software development and has gained traction in science as a way to bring people together for collaborative work and educational courses. Unlike many hackathons, Brainhacks welcome participants from all disciplines and with any level of experience—from those who have never written a line of code to software developers and expert neuroscientists. Brainhacks additionally replace the sometimes-competitive context of traditional hackathons with a purely collaborative one and also feature informal dissemination of ongoing research through unconferences.

Abstract

In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in grey matter and are limited in identifying anatomical circuitries supporting the interaction between brain regions. Mapping the brain circuits mediating the functional signal between brain regions would propel our understanding of the brain’s functional signatures and dysfunctions. We developed a method to unravel the relationship between brain circuits and functions: The Functionnectome. The Functionnectome combines the functional signal from fMRI with white matter circuits’ anatomy to unlock and chart the first maps of functional white matter. To showcase this method’s versatility, we provide the first functional white matter maps revealing the joint contribution of connected areas to motor, working memory, and language functions. The Functionnectome comes with an open-source companion software and opens new avenues into studying functional networks by applying the method to already existing datasets and beyond task fMRI.

Abstract

Clinical neuroscience research relying on animal models brought valuable translational insights into the function and pathologies of the human brain. The anatomical, physiological, and behavioural similarities between humans and mammals have prompted researchers to study cerebral mechanisms at different levels to develop and test new treatments. The vast majority of biomedical research uses rodent models, which are easily manipulable and have a broadly resembling organisation to the human nervous system but cannot satisfactorily mimic some disorders. For these disorders, macaque monkeys have been used as they have a more comparable central nervous system. Still, this research has been hampered by limitations, including high costs and reduced samples. This review argues that a squirrel monkey model might bridge the gap by complementing translational research from rodents, macaque, and humans. With the advent of promising new methods such as ultrasound imaging, tool miniaturisation, and a shift towards open science, the squirrel monkey model represents a window of opportunity that will potentially fuel new translational discoveries in the diagnosis and treatment of brain pathologies.

Abstract

A large amount of variability exists across human brains; revealed initially on a small scale by postmortem studies and,
more recently, on a larger scale with the advent of neuroimaging. Here we compared structural variability between human
and macaque monkey brains using grey and white matter magnetic resonance imaging measures. The monkey brain was
overall structurally as variable as the human brain, but variability had a distinct distribution pattern, with some key areas
showing high variability. We also report the first evidence of a relationship between anatomical variability and evolutionary
expansion in the primate brain. This suggests a relationship between variability and stability, where areas of low variability
may have evolved less recently and have more stability, while areas of high variability may have evolved more recently and
be less similar across individuals. We showed specific differences between the species in key areas, including the amount of
hemispheric asymmetry in variability, which was left-lateralized in the human brain across several phylogenetically recent
regions. This suggests that cerebral variability may be another useful measure for comparison between species and may add
another dimension to our understanding of evolutionary mechanisms.

Abstract

Patients with stroke offer a unique window into understanding human brain function. Mapping stroke lesions poses several challenges due to the complexity of the lesion anatomy and the mechanisms causing local and remote disruption on brain networks. In this prospective longitudinal study, we compare standard and advanced approaches to white matter lesion mapping applied to acute stroke patients with aphasia. Eighteen patients with acute left hemisphere stroke were recruited and scanned within two weeks from symptom onset. Aphasia assessment was performed at baseline and six-month follow-up. Structural and diffusion MRI contrasts indicated an area of maximum overlap in the anterior external/extreme capsule with diffusion images showing a larger overlap extending into posterior perisylvian regions. Anatomical predictors of recovery included damage to ipsilesional tracts (as shown by both structural and diffusion images) and contralesional tracts (as shown by diffusion images only). These findings indicate converging results from structural and diffusion lesion mapping methods but also clear differences between the two approaches in their ability to identify predictors of recovery outside the lesioned regions.

Abstract

Structural imaging based on computerized tomography (CT) and magnetic resonance imaging (MRI) has progressively replaced traditional post‐mortem studies in the process of identifying the neuroanatomical basis of language. In the clinical setting, the information provided by structural imaging has been used to confirm the exact diagnosis and formulate an individualized treatment plan. In the research arena, neuroimaging has permitted to understand neuroanatomy at the individual and group level. The possibility to obtain quantitative measures of lesions has improved correlation analyses between severity of symptoms, lesion load, and lesion location. More recently, the development of structural imaging based on diffusion MRI has provided valid solutions to two major limitations of more conventional imaging. In stroke patients, diffusion can visualize early changes due to a stroke that are otherwise not detectable with more conventional structural imaging, with important implications for the clinical management of acute stroke patients. Beyond the sensitivity to early changes, diffusion imaging tractography presents the possibility of visualizing the trajectories of individual white matter pathways connecting distant regions. A pathway analysis based on tractography is offering a new perspective in neurolinguistics. First, it permits to formulate new anatomical models of language function in the healthy brain and allows to directly test these models in the human population without any reliance on animal models. Second, by defining the exact location of the damage to specific white matter connections we can understand the contribution of different mechanisms to the emergence of language deficits (e.g., cortical versus disconnection mechanisms). Finally, a better understanding of the anatomical variability of different language networks is helping to identify new anatomical predictors of language recovery. In this chapter we will focus on the principles of structural MRI and, in particular, diffusion imaging and tractography and present examples of how these methods have informed our understanding of variance in language performances in the healthy brain and language deficits in patient populations.

Abstract

Insight in the developmental trajectory of the neuroanatomical reading correlates is important to understand related cognitive processes and disorders. In adults, a dual pathway model has been suggested encompassing a dorsal phonological and a ventral orthographic white matter system. This dichotomy seems not present in pre-readers, and the specific role of ventral white matter in reading remains unclear. Therefore, the present longitudinal study investigated the relation between ventral white matter and cognitive processes underlying reading in children with a broad range of reading skills (n = 61). Ventral pathways of the reading network were manually traced using diffusion tractography: the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF) and uncinate fasciculus (UF). Pathways were examined pre-reading (5–6 years) and after two years of reading acquisition (7–8 years). Dimension reduction for the cognitive measures resulted in one component for pre-reading cognitive measures and a separate phonological and orthographic component for the early reading measures. Regression analyses revealed a relation between the pre-reading cognitive component and bilateral IFOF and left ILF. Interestingly, exclusively the left IFOF was related to the orthographic component, whereas none of the pathways was related to the phonological component. Hence, the left IFOF seems to serve as the lexical reading route, already in the earliest reading stages.