Huge shoutout and thanks to the amazing co-authors and our participants! @sinico.bsky.social Alice Rossi Sebastiano Francesca Garbarini Luigi Cattaneo @cimecunitrento.bsky.social

This builds on pioneering work by researchers like Shiffrar & Freyd, who first showed how biomechanical constraints influence perception. Our study demonstrates these effects against competing unconscious influences.

Why does this matter? Our research suggests that body knowledge is uniquely robust in shaping perception. This has implications for understanding:
Visual processing systems
Body representations
Human-computer interaction design
Virtual reality experiences

This didn't happen with clock hands. Participants' perception of clock hands followed the prime regardless of direction when primed with either clockwise or counterclockwise motion.
Our bodies shape what we see in ways that object knowledge doesn't.

💡 Key insight: When we unconsciously used masked priming to suggest hand movements in biomechanically impossible directions, participants showed resistance - they still perceived movements aligned with body constraints despite the visual priming!

The big question: Does our body knowledge influence perception differently than object knowledge? We found that body knowledge creates a stronger perceptual bias than object knowledge - it's harder to "trick" our perception of human movement than object movement!

In two experiments, we compared how people perceive the rotation of human hands vs. clock hands. While clock hands were generally perceived as rotating clockwise, human hands were perceived differently based on whether their rotations violated the biomechanics of our bodies.

In two experiments, we compared how people perceive the rotation of human hands vs. clock hands. While clock hands were generally perceived as rotating clockwise, human hands were perceived differently based on whether their rotations violated the biomechanics of our bodies.

And to the rest of the amazing team and resources! 7/7
@coreykeller.bsky.social @juhagogulski.bsky.social @jessicamross8.bsky.social @stanfordpntlab.bsky.social @stanfordmedicine.bsky.social Manjima Sarkar, Jade Truong, Lily Forman!!

Big shout out to my co-first author 👏 @chrisclineneuro.bsky.social

Interested in learning more? Read the full paper in Clinical Neurophysiology! doi.org/10.1016/j.cl... 5/7

Key findings: Optimization reduced artifacts by 63% and increased early local TMS-evoked potentials (EL-TEPs), a measure of prefrontal excitability, by 75%! #EEG #TMS #TMSEEG 4/7

We introduce a novel method for optimizing TMS parameters in the dlPFC. Based on EEG responses, this closed-loop procedure optimizes TMS coil angle, location, and intensity in real time. 3/7

Why is this important? The dlPFC is a depression treatment target, but we need clinic-ready ways to measure stimulation effects. TMS-EEG can help, but artifacts obscure responses. 2/7