Tessera
Folgen

JsonGeller

@jgeller1phd.bsky.social

Eye-tracking, Pupillometry, Word nerd, Learning and Memory, Language, R, Stats, Quant, Director Human Neuroscience Lab @bostoncollege www.drjasongeller.com

783 Posts1354 Follower712 Folgt
JsonGeller@jgeller1phd.bsky.social · 2w ago

The real answer to this question is every company used AI to derive their logo and there was only one anus in the training set 🤣

Olivia Guest · Ολίβια Γκεστ@olivia.science · 3w ago

> No single person suggests making a logo that resembles an anus, but when everyone's feedback gets incorporated, that's what often emerges. Risk aversion in corporate environments naturally pushes designs toward familiar, "safe" territory, which apparently means anatomical openings.

Henrik Singmann@singmann.bsky.social · 2mo ago

Finally out in Psychological Review (psycnet.apa.org/doi/10.1037/...), our update to Signal Detection Theory. We show that contrary to the prevailing Gaussian assumption, evidence distributions in recognition memory are likely minimum extreme Gumbel!

Figure 7: Illustration of the Gumbel-min Signal Detection Model Figure consists of three panels. Bottom-left panel: The Gumbel-min latent-strength distributions associated with SIGNAL (old) and NOISE (new) items. Top-left panel: The log likelihood ratio (log-LR) for the two latent-strength distributions. Right panel: The receiver operating characteristic function produced by the two latent-strength distributions. pH = hit probabilities; pFA = false-alarm probabilities.
Henrik Singmann@singmann.bsky.social · last yr.

Honey, we fixed Signal Detection Theory (SDT)! In this preprint, Constantin Meyer-Grant, David Kellen, Sam Harding, and I critically evaluate the (unequal-variance) Gaussian SDT model in recognition memory and pursue the Gumbel-min model as a principled alternative: doi.org/10.31234/osf... 🧵

Henrik Singmann@singmann.bsky.social · last yr.

Honey, we fixed Signal Detection Theory (SDT)! In this preprint, Constantin Meyer-Grant, David Kellen, Sam Harding, and I critically evaluate the (unequal-variance) Gaussian SDT model in recognition memory and pursue the Gumbel-min model as a principled alternative: doi.org/10.31234/osf... 🧵

Extreme-Value Signal Detection Theory for RecognitionMemory: The Parametric Road Not Taken

Signal Detection Theory has long served as a cornerstone of psychological research, particularly in recognition memory. Yet its conventional application hinges almost exclusively on the Gaussian…

doi.org

Jan Theeuwes@jthee.bsky.social · 2mo ago

Our newest finding: tiny microsaccades are biased toward the location that is about to be attentionally suppressed. This suggests that attention briefly precedes suppression: before the system can suppress a location, it first appears to select it.

Learned statistical regularity modulates anticipatory micro-saccades toward suppressed distractor locations - Nature Communications

Statistical learning guide attention by shaping anticipatory oculomotor behavior. Here, the authors show that microsaccades are biased to expected distractor locations before stimulus onset and predic...

nature.com

Dr Mircea Zloteanu 🌺🌞🍃@mzloteanu.bsky.social · 3mo ago

#statstab #524 {simglm}: Tidy simulation and power analyses Thoughts: As your design becomes more complex, simulation is the only way to go. #simulation #r #rstats #tidy #tidyverse #poweranalysis #design #tutorial simglm.brandonlebeau.org

Simulate Models Based on the Generalized Linear Model

Simulates regression models, including both simple regression and generalized linear mixed models with up to three level of nesting. Power simulations that are flexible allowing the specification of m...

simglm.brandonlebeau.org