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| Hauptseite > Publikationsdatenbank > Towards multi-modal, multi-species brain atlases: part one > print |
| Hauptseite > Publikationsdatenbank > Towards multi-modal, multi-species brain atlases: part one > print |
| 001 | 1008581 | ||
| 005 | 20230929112536.0 | ||
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| 100 | 1 | _ | |a Mars, Rogier B. |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Towards multi-modal, multi-species brain atlases: part one |
| 260 | _ | _ | |a Heidelberg |c 2023 |b Springer |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a Neuroanatomical knowledge is a fundamental component of neuroimaging analyses, since it enables researchers to interpret their findings in the context of the underlying cytoarchitectonic, molecular and connectional segregation of the brain. The digital era of neuroscience and current open science practices have resulted in the generation and availability of numerous datasets reflecting different aspects of the brain’s structural and functional segregation. This pertains not only the human brain, or that of non-human primates or rodents (Grandjean et al. 2023; Milham et al. 2018), the most commonly used animal models in neuroscience, but also the brains of other animal models, such as the mini pig (Bjarkam et al. 2017) and squirrel monkey (Orset et al. 2023), and even wider ranges of species across the mammalian class (Tendler et al. 2022; Suarez et al. 2022). |
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| 700 | 1 | _ | |a Palomero-Gallagher, Nicola |0 P:(DE-Juel1)131701 |b 1 |e Corresponding author |
| 773 | _ | _ | |a 10.1007/s00429-023-02656-5 |g Vol. 228, no. 5, p. 1041 - 1044 |0 PERI:(DE-600)2303775-1 |n 5 |p 1041 - 1044 |t Brain structure & function |v 228 |y 2023 |x 1863-2653 |
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