Stephanie Forkel

Publications

Displaying 1 - 4 of 4
  • 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.
  • 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.

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