Congrats! I’m looking forward to reading this.
Woohoo, congrats!!
I also agree with Nico’s point above that some of this is definitional. My bias is to base those definitions on brain mechanisms, which am optimistic we as a field are on the cusp of figuring out. Thanks for a fun conversation!
That feels like the definition of selective attention (not necessarily spatial). We think the most parsimonious explanation is that stimulants enhance the brain’s natural selective mechanisms. Not at all inconsistent with the general story here, but an interplay between motivation/attention 5/
This hyper attention feels similar to reports from humans that they need to focus on their desired task before taking stimulants, or they will focus on whatever is in front of them (like the toothbrush example from David Sedaris). 4/
That hyper attention isn’t optimal (in our task, 20% of changes happen at the uncued location, so optimal is to continue to allocate some attention to the uncued location. 3/
But I also agree with @douglasruff.bsky.social that motivation doesn’t explain all our results. We saw improvement at the attended location, and no change or worsening at the unattended location. 2/
I like this paper! @ndosenbach.bsky.social is right that our macaque results are mostly consistent with a general increase in motivation/arousal/alertness. 1/
Amazing, congratulations!!
We have two SfN presentations this morning, featuring star grad student 1st authors Grace DiRisio and Sylvia Durian. Cheng Xue is an author on both & not only is he an incredible scientist, he's also an incredible advertiser/communicator; check out his cartoons! x.com/_chengxue/st...
We’re excited about the connections in this work, between behavior, species, individual differences, brain areas, and neuronal mechanisms. We would love your feedback!
www.biorxiv.org/content/10.1...
Keon is on the job market (ideally in Canada) & has incredibly exciting plans for his future lab. He will use neurophysiology-inspired psychophysics to study how perception and cognition differ across the lifespan and across neurotypical and neurodiverse people. Hire him! www.keonallen.com 8/
This study reflects Keon’s pioneering spirit. He came to our visual neurophysiology lab from a background in psychology and haptic perception and built bridges between fields, from Bayesian models and online behavior to neuronal mechanisms of cue integration. 7/
Together, these results suggest that the brain combines information differently within and across sensory modalities, perhaps from different circuitry in sensory & association areas. These distinctions seem to be conserved across species, and deviations could be diagnostic for brain differences. 6/
Doug conducted parallel neurophysiological experiments in which a visual cue was combined with a causal manipulation.
Electrical microstimulation in visual cortex was integrated with sensory motion cues.
Stimulation in prefrontal cortex instead pushed choices toward winner-take-all. 5/
These strategies varied across people. Age and self-reported ADHD or Autism influenced which cues were judged most accurately and how they were integrated, suggesting that individual differences in multisensory combination may reflect broader cognitive or neural traits. 4/
Keon measured cue combination in large cohorts of neurodiverse participants who made judgments based on multiple cues.
People combined two visual cues nearly optimally. When vision and sound conflicted, behavior became winner-take-all, usually but not always favoring the more reliable cue. 3/
Many studies test how subjects combine information from well-practiced cues with feedback. But we often need to combine unfamiliar signals. For example, we might try to match what we see and hear when a new appliance beeps.
Keon and Doug Ruff asked how brains do that. 2/
New preprint from the lab! 🎉
Postdoc Keon Allen led this study exploring how subjects combine sources of sensory information, including unfamiliar & cross-modal cues, and what that can tell us about decision-making, neural mechanisms, and neurodiversity.
www.biorxiv.org/content/10.1... 🧵🧪1/
I’m sorry that I won’t be in San Diego to join you. But I hope it’s wonderful, and a heartfelt thank you for everything you do for our community.
Thank you! Your work was definitely the inspiration for a lot of this.
Thanks, Hannah!
Ha! My student was the one who realized we should cite your paper. Maybe she should earn a second PhD in history...
Thank you, especially for the laugh!
We are excited about potential applications of this work, from artificial intelligence to translational efforts to fix memory disorders. This highlights a central value of our field: using curiosity-driven science for broad impact. We’d love your feedback! doi.org/10.1101/2025.09.22.677855 /end
This is the first chapter of Grace’s thesis, and there is so much more to come. She is something special, and I am going to thoroughly enjoy seeing her take our field by storm. 9/
These findings show that the building blocks of fast, high-capacity memory are present in mid-level visual cortex. Take-home: cognition is distributed. And stay tuned: Grace’s next papers will explore mechanisms by which these signals interact with the larger network and are disrupted in disease. 8/
We also found faster response dynamics to familiar images, consistent with pattern completion. This means that after the first couple of image fragments, V4 already signaled the whole image (but only during successful memory). The hippocampus does this, but we were surprised to see it in V4. 🤯 7/
We found all of these neuronal signatures in V4. But the only ones that reliably predicted behavior were related to how consistent population responses were during memory encoding and retrieval. More consistent responses = greater memory success. 6/
We looked for proposed neuronal signatures of memory, including:
• magnitude coding
• repetition suppression
• sparse coding
• population response consistency (=similar responses to novel and familiar images) 5/
