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Friedrich, P., Forkel, S. J., Amiez, C., Balsters, J. H., Coulon, O., Fan, L., Goulas, A., Hadj-Bouziane, F., Hecht, E. E., Heuer, K., Jiang, T., Latzman, R. D., Liu, X., Loh, K. K., Patil, K. R., Lopez-Persem, A., Procyk, E., Sallet, J., Toro, R., Vickery, S. Friedrich, P., Forkel, S. J., Amiez, C., Balsters, J. H., Coulon, O., Fan, L., Goulas, A., Hadj-Bouziane, F., Hecht, E. E., Heuer, K., Jiang, T., Latzman, R. D., Liu, X., Loh, K. K., Patil, K. R., Lopez-Persem, A., Procyk, E., Sallet, J., Toro, R., Vickery, S., Weis, S., Wilson, C., Xu, T., Zerbi, V., Eickoff, S. B., Margulies, D., Mars, R., & Thiebaut de Schotten, M. (2021). Imaging evolution of the primate brain: The next frontier? NeuroImage, 228: 117685. doi:10.1016/j.neuroimage.2020.117685.
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.Additional information
Friedrich_etal_2021_imaging evolution of the primate brain.pdf -
Gau, R., Noble, S., Heuer, K., Bottenhorn, K. L., Bilgin, I. P., Yang, Y.-F., Huntenburg, J. M., Bayer, J. M., Bethlehem, R. A., Rhoads, S. A., Vogelbacher, C., Borghesani, V., Levitis, E., Wang, H.-T., Van Den Bossche, S., Kobeleva, X., Legarreta, J. H., Guay, S., Atay, S. M., Varoquaux, G. P. Gau, R., Noble, S., Heuer, K., Bottenhorn, K. L., Bilgin, I. P., Yang, Y.-F., Huntenburg, J. M., Bayer, J. M., Bethlehem, R. A., Rhoads, S. A., Vogelbacher, C., Borghesani, V., Levitis, E., Wang, H.-T., Van Den Bossche, S., Kobeleva, X., Legarreta, J. H., Guay, S., Atay, S. M., Varoquaux, G. P., Huijser, D. C., Sandström, M. S., Herholz, P., Nastase, S. A., Badhwar, A., Dumas, G., Schwab, S., Moia, S., Dayan, M., Bassil, Y., Brooks, P. P., Mancini, M., Shine, J. M., O’Connor, D., Xie, X., Poggiali, D., Friedrich, P., Heinsfeld, A. S., Riedl, L., Toro, R., Caballero-Gaudes, C., Eklund, A., Garner, K. G., Nolan, C. R., Demeter, D. V., Barrios, F. A., Merchant, J. S., McDevitt, E. A., Oostenveld, R., Craddock, R. C., Rokem, A., Doyle, A., Ghosh, S. S., Nikolaidis, A., Stanley, O. W., Uruñuela, E., Anousheh, N., Arnatkeviciute, A., Auzias, G., Bachar, D., Bannier, E., Basanisi, R., Basavaraj, A., Bedini, M., Bellec, P., Benn, R. A., Berluti, K., Bollmann, S., Bollmann, S., Bradley, C., Brown, J., Buchweitz, A., Callahan, P., Chan, M. Y., Chandio, B. Q., Cheng, T., Chopra, S., Chung, A. W., Close, T. G., Combrisson, E., Cona, G., Constable, R. T., Cury, C., Dadi, K., Damasceno, P. F., Das, S., De Vico Fallani, F., DeStasio, K., Dickie, E. W., Dorfschmidt, L., Duff, E. P., DuPre, E., Dziura, S., Esper, N. B., Esteban, O., Fadnavis, S., Flandin, G., Flannery, J. E., Flournoy, J., Forkel, S. J., Franco, A. R., Ganesan, S., Gao, S., García Alanis, J. C., Garyfallidis, E., Glatard, T., Glerean, E., Gonzalez-Castillo, J., Gould van Praag, C. D., Greene, A. S., Gupta, G., Hahn, C. A., Halchenko, Y. O., Handwerker, D., Hartmann, T. S., Hayot-Sasson, V., Heunis, S., Hoffstaedter, F., Hohmann, D. M., Horien, C., Ioanas, H.-I., Iordan, A., Jiang, C., Joseph, M., Kai, J., Karakuzu, A., Kennedy, D. N., Keshavan, A., Khan, A. R., Kiar, G., Klink, P. C., Koppelmans, V., Koudoro, S., Laird, A. R., Langs, G., Laws, M., Licandro, R., Liew, S.-L., Lipic, T., Litinas, K., Lurie, D. J., Lussier, D., Madan, C. R., Mais, L.-T., Mansour L, S., Manzano-Patron, J., Maoutsa, D., Marcon, M., Margulies, D. S., Marinato, G., Marinazzo, D., Markiewicz, C. J., Maumet, C., Meneguzzi, F., Meunier, D., Milham, M. P., Mills, K. L., Momi, D., Moreau, C. A., Motala, A., Moxon-Emre, I., Nichols, T. E., Nielson, D. M., Nilsonne, G., Novello, L., O’Brien, C., Olafson, E., Oliver, L. D., Onofrey, J. A., Orchard, E. R., Oudyk, K., Park, P. J., Parsapoor, M., Pasquini, L., Peltier, S., Pernet, C. R., Pienaar, R., Pinheiro-Chagas, P., Poline, J.-B., Qiu, A., Quendera, T., Rice, L. C., Rocha-Hidalgo, J., Rutherford, S., Scharinger, M., Scheinost, D., Shariq, D., Shaw, T. B., Siless, V., Simmonite, M., Sirmpilatze, N., Spence, H., Sprenger, J., Stajduhar, A., Szinte, M., Takerkart, S., Tam, A., Tejavibulya, L., Thiebaut de Schotten, M., Thome, I., Tomaz da Silva, L., Traut, N., Uddin, L. Q., Vallesi, A., VanMeter, J. W., Vijayakumar, N., di Oleggio Castello, M. V., Vohryzek, J., Vukojević, J., Whitaker, K. J., Whitmore, L., Wideman, S., Witt, S. T., Xie, H., Xu, T., Yan, C.-G., Yeh, F.-C., Yeo, B. T., & Zuo, X.-N. (2021). Brainhack: Developing a culture of open, inclusive, community-driven neuroscience. Neuron, 109(11), 1769-1775. doi:10.1016/j.neuron.2021.04.001.
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.Additional information
supplementary information -
Nozais, V., Forkel, S. J., Foulon, C., Petit, L., & Thiebaut de Schotten, M. (2021). Functionnectome as a framework to analyse the contribution of brain circuits to fMRI. Communications Biology, 4: 1035. doi:10.1038/s42003-021-02530-2.
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.Additional information
supplementary information -
Royo, J., Forkel, S. J., Pouget, P., & Thiebaut de Schotten, M. (2021). The squirrel monkey model in clinical neuroscience. Neuroscience and Biobehavioral Reviews, 128, 152-164. doi:10.1016/j.neubiorev.2021.06.006.
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. -
Forkel, S. J., & Catani, M. (2019). Diffusion imaging methods in language sciences. In G. I. De Zubicaray, & N. O. Schiller (
Eds. ), The Oxford Handbook of Neurolinguistics (pp. 212-228). Oxford: Oxford University Press.Abstract
The field of neuroanatomy of language is moving forward at a fast pace. This
progression is partially due to the development of diffusion tractography, which
has been used to describe white matter connections in the living human brain.
For the field of neurolinguistics this advancement is timely and important for
two reasons. First, it allows clinical researchers to liberate themselves from
neuroanatomical models of language derived from animal studies. Second, for
the first time, it offers the possibility of testing network correlates of
neurolinguistic models directly in the human brain. This chapter introduces the
reader to general principles of diffusion imaging and tractography. Examples of
its applications, such as tract analysis, will be used to explicate its potentials and
limitations. -
Thiebaut de Schotten, M., Friedrich, P., & Forkel, S. J. (2019). One size fits all does not apply to brain lateralisation. Physics of Life Reviews, 30, 30-33. doi:10.1016/j.plrev.2019.07.007.
Abstract
Our understanding of the functioning of the brain is primarily based on an average model of the brain's functional organisation, and any deviation from the standard is considered as random noise or a pathological appearance. Studying pathologies has, however, greatly contributed to our understanding of brain functions. For instance, the study of naturally-occurring or surgically-induced brain lesions revealed that language is predominantly lateralised to the left hemisphere while perception/action and emotion are commonly lateralised to the right hemisphere. The lateralisation of function was subsequently replicated by task-related functional neuroimaging in the healthy population. Despite its high significance and reproducibility, this pattern of lateralisation of function is true for most, but not all participants. Bilateral and flipped representations of classically lateralised functions have been reported during development and in the healthy adult population for language, perception/action and emotion. Understanding these different functional representations at an individual level is crucial to improve the sophistication of our models and account for the variance in developmental trajectories, cognitive performance differences and clinical recovery. With the availability of in vivo neuroimaging, it has become feasible to study large numbers of participants and reliably characterise individual differences, also referred to as phenotypes. Yet, we are at the beginning of inter-individual variability modelling, and new theories of brain function will have to account for these differences across participants. -
Forkel, S. J. (2015). Heinrich Sachs (1863–1928). Journal of Neurology, 262, 498-500. doi:10.1007/s00415-014-7517-2.
Abstract
The nineteenth century witnessed some of the greatest neuroanatomists of all times. Amongst them is the largely forgotten Heinrich Sachs, a student of Carl Wernicke in Breslau. -
Forkel, S. J., Mahmood, S., Vergani, F., & Catani, M. (2015). The white matter of the human cerebrum: Part I The occipital lobe by Heinrich Sachs. Cortex, 62, 182-202. doi:10.1016/j.cortex.2014.10.023.
Abstract
This is the first complete translation of Heinrich Sachs' outstanding white matter atlas dedicated to the occipital lobe. This work is accompanied by a prologue by Prof Carl Wernicke who for many years was Sachs' mentor in Breslau and enthusiastically supported his work.
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