Associate Professor of neuroscience and psychology living in Utrecht, Netherlands. Mostly researching spatial and quantity processing in the human brain with 7T
Joined December 2019
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ben harvey retweeted
1/3 I am recruiting graduate students interested in understanding the cognitive and neural mechanisms that support mathematical cognition and executive functions and how those relate to math development. Join me in Nashville at Vanderbilt! Due Dec. 1st . Reach out if interested!
Either of Ted Chiang's books, Exhalation and "Stories of Your Life and Others". Both incredible, page turners, with a slight sci-fi edge.
Our new paper at Nature Communications shows how visual timing-tuned neural responses emerge gradually through the visual hierarchy and abstract temporal responses from spatial responses. With @evi_hendrikx
@Jacob_M_Paul Martijn van Ackooij @NathanvdStoep
doi.org/10.1038/s41467-022-3…
ben harvey retweeted
In our new article w/Shir Hofstter @benmarkharvey @serge_dumoulin in Cell Rep, we ask how attention affects neural numerosity-selective response and find that attention is necessary to numerosity response, while without attention, response to preferred numerosity is suppressed.
Our new article describes tuned responses to the duration and rate of auditory events in the human brain using 7T fMRI. While these responses are similar to those seen for visual event timing, the brain areas involved are very different: auditory cortices. doi.org/10.1016/j.neuroimage…
But instead of estimating numerosity directly from images, we estimate numerosity from the early visual representation of images. This is so straightforward in a spatial frequency based image representation that any animal with such spatial frequency processing could do the same.
Because it has been unclear how numerosity could be estimated from the visual image, many researchers have concluded that we don't really perceive numerosity, but some non-numerical feature that might be easier to estimate. Here we propose that we do truly estimate numerosity.
This explains why neural population response amplitudes in early visual cortex and neural networks follow numerosity so closely: they follow Fourier power more closely. But from this early visual representation, truly numerosity selective neural responses can be easily derived.
Animal visual systems use a spatial frequency based image representation. In the spatial frequency domain, numerosity becomes very clear: Fourier power at all orientations and spatial frequencies follows numerosity closely (but nonlinearly) regardless of item size and spacing.
Ever since I started thinking about numerosity, I have wondered how the visual system estimates numerosity so easily without large effects of item size and spacing. Our new paper at Nature Communication with @Jacob_M_Paul shows how this could be done.
nature.com/articles/s41467-0…