Takemura Lab Seminar: ①Paule-Joanne Toussaint, ② Jean-Baptiste Poline (McGill University, Canada)
日時
2026年11月30日（月）14:30～15:45
形式
オンサイト
会場
生理学研究所明大寺地区実験棟１階 セミナー室A/B
共催
共同利用・共同研究システム形成事業 「学際領域展開ハブ形成プログラム」【スピン生命フロンティア (Spin-L)】
使用言語
英語
演者
Talk #1 Paule-Joanne Toussaint （14:30～15:00）
Research Associate, McGill University, Canada
Talk #2 Jean-Baptiste Poline （15:00～15:45）
Professor, McGill University, Canada
タイトル・抄録
Paule-Joanne Toussaint（14:30～15:00）
Title: Brain atlases in PET imaging: Anatomical and functional frameworks for neuroimaging research and clinical practice
Abstract: Positron emission tomography (PET) measures physiological and chemical processes in the brain, but its limited spatial resolution and reader-dependent interpretation complicate quantification. Brain atlases supply the anatomical and functional scaffolding needed for cross-subject normalisation, region-of-interest definition, and image segmentation. Here we survey atlases widely used in PET, from classical anatomical references (Brodmann, MNI, AAL) to functional and metabolic atlases (FDG normative cohorts, receptor maps, connectivity parcellations), and review the registration pipeline and partial volume effects, which can underestimate tracer uptake by up to 30% in small structures. Segmentation approaches are compared and linked to clinical applications in neurology (neurodegenerative diseases, epilepsy, tumours) and psychiatry. We highlight a shift toward deep learning-based segmentation approaches and the continued necessity of partial volume correction, underscoring challenges such as atlas mismatch in pathological brains and the lack of standardized benchmarks.
Jean-Baptiste Poline（15:00～15:45）
Title: Changing landscape for neuroimaging data sharing and data processings: towards distributed solutions in the era of data sovereignty
Abstract: In this presentation, I will review some of the challenges that neuroscience and neuroimaging are facing, and in particular the challenges of reproducible and generalizable studies in the context of data distributed and under variable legal and ethical constraints. The field of neuroscience is facing new questions on the impact of variable processings and the difficulty to generalize results. These challenges have both technical and sociological roots, and the solutions will therefore likely also be both technological and sociological. I will take some examples of neuroinformatics projects developed in my laboratory or in collaboration to transform how we share and analyze data with an example of the development of imaging biomarkers for Parkinson Disease. I will show preliminary results showing that distributed infrastructures can be leveraged for federated learning of Parkinson Disease progression. I will open the discussion on some key aspects to consider, for instance how these infrastructures can be maintained, how their governance structure can be thought of, and how this offers opportunities to build community of practices.