Stephanie Forkel

Publications

Displaying 1 - 11 of 11
  • 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.
  • Croxson, P., Forkel, S. J., Cerliani, L., & Thiebaut De Schotten, M. (2018). Structural Variability Across the Primate Brain: A Cross-Species Comparison. Cerebral Cortex, 28(11), 3829-3841. doi:10.1093/cercor/bhx244.

    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.
  • Forkel, S. J., & Catani, M. (2018). Lesion mapping in acute stroke aphasia and its implications for recovery. Neuropsychologia, 115, 88-100. doi:10.1016/j.neuropsychologia.2018.03.036.

    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.
  • Forkel, S. J., & Catani, M. (2018). Structural Neuroimaging. In A. De Groot, & P. Hagoort (Eds.), Research Methods in Psycholinguistics and the Neurobiology of Language: A Practical Guide (pp. 288-308). Hoboken: Wiley. doi:10.1002/9781394259762.ch15.

    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.
  • Vanderauwera, J., De Vos, A., Forkel, S. J., Catani, M., Wouters, J., Vandermosten, M., & Ghesquière, P. (2018). Neural organization of ventral white matter tracts parallels the initial steps of reading development: A DTI tractography study. Brain and Language, 183, 32-40. doi:10.1016/j.bandl.2018.05.007.

    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.
  • Catani, M., Craig, M. C., Forkel, S. J., Kanaan, R., Picchioni, M., Toulopoulou, T., Shergill, S., Williams, S., Murphy, D. G., & McGuire, P. (2011). Altered integrity of perisylvian language pathways in schizophrenia: Relationship to auditory hallucinations. Biological Psychiatry, 70(12), 1143-1150. doi:10.1016/j.biopsych.2011.06.013.

    Abstract

    Background: Functional neuroimaging supports the hypothesis that auditory verbal hallucinations (AVH) in schizophrenia result from altered functional connectivity between perisylvian language regions, although the extent to which AVH are also associated with an altered tract anatomy is less clear.

    Methods: Twenty-eight patients with schizophrenia subdivided into 17 subjects with a history of AVH and 11 without a history of hallucinations and 59 age- and IQ-matched healthy controls were recruited. The number of streamlines, fractional anisotropy (FA), and mean diffusivity were measured along the length of the arcuate fasciculus and its medial and lateral components.

    Results: Patients with schizophrenia had bilateral reduction of FA relative to controls in the arcuate fasciculi (p < .001). Virtual dissection of the subcomponents of the arcuate fasciculi revealed that these reductions were specific to connections between posterior temporal and anterior regions in the inferior frontal and parietal lobe. Also, compared with controls, the reduction in FA of these tracts was highest, and bilateral, in patients with AVH, but in patients without AVH, this reduction was reported only on the left.

    Conclusions: These findings point toward a supraregional network model of AVH in schizophrenia. They support the hypothesis that there may be selective vulnerability of specific anatomical connections to posterior temporal regions in schizophrenia and that extensive bilateral damage is associated with a greater vulnerability to AVH. If confirmed by further studies, these findings may advance our understanding of the anatomical factors that are protective against AVH and predictive of a treatment response.
  • Forkel, S. J., Dell’Acqua, F., Kalra, L., Williams, S. C., & Catani, M. (2011). Lateralisation of the Arcuate Fasciculus Predicts Aphasia Recovery at 6 Months. Procedia - Social and Behavioral Sciences, 23, 164-166. doi:10.1016/j.sbspro.2011.09.221.
  • Thiebaut de Schotten, M., Dell'Acqua, F., Forkel, S. J., Simmons, A., Vergani, F., Murphy, D. G. M., & Catani, M. (2011). A lateralized brain network for visuospatial attention. Nature Neuroscience, 14, 1245-1246. doi:10.1038/nn.2905.

    Abstract

    Right hemisphere dominance for visuospatial attention is characteristic of most humans, but its anatomical basis remains unknown. We report the first evidence in humans for a larger parieto-frontal network in the right than left hemisphere, and a significant correlation between the degree of anatomical lateralization and asymmetry of performance on visuospatial tasks. Our results suggest that hemispheric specialization is associated with an unbalanced speed of visuospatial processing.

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