Preprint alert 🚨I am excited about our new paper titled “The representational nature of spatio-temporal recurrent processing in visual object recognition.” 🥳🌟
https://t.co/5wJJDxUl7V
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And it's out in @JOCN_Journal! We added a feedforward CNN control and showed that for certain stimuli, recurrence can help with better predicting scene categorization in humans in terms of neural reps, behaviour and the brain-behaviour link: https://t.co/6ikTJom05L
My first preprint is out! (Are #tweeprints still a thing?) Work with Antoniya Boyanova, @pmkumar1308, Klaus Obermayer, @timkietzmann and Radek Cichy. Thread below (1/7):
On to work of other labs that we have been involved in: Agnessa Karapetian from Radek Cichy’s lab combines EEG, behavioural data, and RCNNs to identify and model the brain-behaviour relationship for human scene categorization.
Location/Time: P-2B.38, Fri, 25 Aug, 13:00 - 15:00
My first preprint is out! (Are #tweeprints still a thing?) Work with Antoniya Boyanova, @pmkumar1308, Klaus Obermayer, @timkietzmann and Radek Cichy. Thread below (1/7):
Empirically identifying and computationally modelling the brain-behaviour relationship for human scene categorization https://t.co/D0RAXWYoGY #biorxiv_neursci
Lastly, we evaluated BLnet (Spoerer et al., 2020) as a model of scene categorization in humans by correlating (1) human & model representations, (2) human & model RTs, and (3) human representations & model RTs, and observed human-model similarities on all levels (6/7)
Very happy to share that the first paper of my PhD in #JNeurosci is now online 🥳 Together with Radek Cichy and @martin_hebart we asked whether the recognition of line drawings relies on similar neural mechanisms as those used for recognizing natural objects. 🧵1/7
Happy it is online @CurrentBiology now😊Using multivariate assessments of EEG data, we characterized visual category representations in the human infant brain👶🧠 @CCNBerlin
Snapshots see below:
https://t.co/aGtx5DrUFa
New big EEG dataset alert!
Gifford et al. @CCNBerlin @fupsych @FU_Berlin released on @NeuroImage_EiC a large and rich (10 subjects, 16,740 images, 82,160 trials per subject) EEG data set for modeling visual object recognition. https://t.co/BWvYzNCmWA