RT @Runhao_Lu: 🚨New paper @brainstimj !⚡Using TMS-EEG & MVPA in a selec attention task, we show parietal alpha rh-TMS (entrainment) specifi…

@catrionascrivener.bsky.social

RT @mlueckel: Where to place an ultrasound transducer to optimally target a specific brain region in a given individual? We developed 𝗣𝗹𝗮𝗻…

RT @ArranReader: Happy to share a new preprint! Me and my excellent RA co-authors provide insight into how humans use a single hand to cumu…

RT @lauracrucianel1: 🌟Exciting PhD opportunity🌟 If you are interested in touch, interoception, mental health, please apply by the 15th of…

RT @num_ole: Why is motion correction a thing for fMRI but nobody quantifies it during #TMS? Well, we just put out a metric to easily quan…

Although perhaps not suprising, we recommend examining the spatial overlap between category-selective and retinotopic ROIs and take this overlap into account when drawing inferences about their responses - especially if image properties vary across space. 12/n

Using a representational similarity approach, we found numerically different model correlations across ROIs. However, these could not explain the pattern of responses we observed between ROIs. 7/n

How can we explain this structure? We first tested 7 candidate models: 3 scene dimensions (Content, Expanse, Distance), 2 modelling low-level visual features (GIST & LGN), 1 modelling high-level visual features (convolutional neural network), and navigational affordances. 6/n

Next, we assessed the activity within each field map while participants viewed 96 different scenes during multi-echo fMRI. The pattern of responses across OPA divisions grouped into 3 possible clusters: LO1 & LO2, V3A & V3B, and V7. 5/n

Next, we computed the visual field coverage for these maps using population receptive field modelling. All ROIs had a contralateral bias. Some represented the lower visual field (LO1 & LO2), the upper visual field (V7), or a full hemifield (V3A & V3B). 4/n

First, we calculated the overlap between the OPA and its visual field maps. Roughly 48% of the OPA overlapped five separate maps, whereas the other 52% overlapped cortex with no known visual field maps (OPA other). 3/n

Most fMRI research of the occipital place area (OPA) is based on the response across all voxels, averaging over the visual field maps that subdivide it (LO1, LO2, V3A, V3B & V7). Here we investigated the specific role played by OPA’s visual field maps during scene processing. 2/n

RT @Runhao_Lu: Happy to share our new results on neural basis of domain-general cognition!🧠 We've known the frontoparietal multiple-demand…

Looking forward to presenting our concurrent TMS-fMRI work on the role of the IPS in prioritising task-relevant visual information @AlexWoolgar @Runhao_Lu @Jade_BJackson