Our lab studies how the retina processes visual information and has identified cells that detect the sign of defocus, helping to understand eye growth mechanisms:
lnkd.in/eAWQ6szY
This work is part of the PREMYOM project, which aims to personalize strategies for myopia prevention: premyom.com
Nearly half of the world’s population could be myopic by 2050. High myopia carries risks of complications that can lead to severe vision loss or even blindness.
Happy to have been interviewed on France Inter yesterday, following a Le Monde article on the global myopia epidemic:
lnkd.in/e8DXwdR3
lnkd.in/eKFcYZZ2
Happy to share my first work with a connection to myopia, a collaboration with EssilorLuxottica
www.science.org/doi/10.1126/...
13/
Thanks to @tom-quetu.bsky.social, @touchmovelab.bsky.social, and our supporters:
@frm-officiel.bsky.social, @fondationdefrance.bsky.social , @ec.europa.eu, @agencerecherche.bsky.social, @c-brains.bsky.social.
12/
We propose that sweep coding in layer 5a may be related to texture decoding.
The longer integration time makes it possible to combine current sensory inputs with modulatory signals — possibly motor-related — from higher order POm.
11/
This reveals a new dimension in thalamocortical computation:
🔹 Fine, fast features like sticks are inherited from thalamus
🔸 Broader, global features like sweeps are computed in cortex via temporal integration
10/
So where do sweeps come from?
In layer 5a, we found that sweep-tuned neurons integrate stick inputs from VPM and POm over longer timescales.
9/
Recordings in VPM and POm showed that both thalamic nuclei primarily encode sticks.
POm adds some diversity, but sweep tuning is not clearly present.
8/
Sticks dominated in layer 4 and 3.
Sweeps were found in layers 5a and 5b.
But can these features be inherited from the thalamus?
7/
We identified two distinct types of responses in the cortex:
🔴 Sticks — brief, fast, single-whisker deflections
⚫ Sweeps — broad, multi-whisker movements with large angular changes
These were tuned to perpendicular axes in the feature space.
6/
We confirmed this with an independent sparse noise stimulus — random single-whisker deflections — and separated the two functional populations.
5/
But cells were not uniformly selective across this space.
They tended to cluster around two specific feature angles — suggesting a subspace tuning.
4/
We found that the whisker movements that elicited the strongest responses belonged to a low dimensional feature space.
We could project each cell’s preferred stimulus into this space: the closer to the edge, the more selective.
3/
Velocity came out on top, as seen in rats (Harrell et al. 2020), and contrary to stick-slip models where velocity and acceleration are encoded equally.
2/
We designed Gaussian white noise stimuli — optimized to test position, velocity, acceleration — to find which parameter was best encoded by neurons.
1/
We used a unique setup: 24 whiskers deflected with micrometer precision and millisecond timing.
This allowed us to deliver naturalistic, reproducible input across the full whisker pad, while recording neurons multiple in the barrel cortex.
🧵New preprint from @tom-quetu.bsky.social and me, done in Dan Shulz’s lab @touchmovelab.bsky.social at @neuropsi.bsky.social :
We uncover how a tactile code emerges in cortical layer 5a from temporal integration of thalamic input.
www.biorxiv.org/content/10.1...
Let’s break it down 👇
13/
Thanks to @tom-quetu.bsky.social @touchmovelab.bsky.social , and our supporters:
@frm-officiel.bsky.social , @fondationdefrance.bsky.social , @ec.europa.eu , @agencerecherche.bsky.social , @c-brains.bsky.social
12/
We propose that sweep coding in layer 5a may be related to texture decoding.
The longer integration time makes it possible to combine current sensory inputs with modulatory signals — possibly motor-related — from POm.
11/
This reveals a new dimension in thalamocortical computation:
🔹 Fine, fast features like sticks are inherited from thalamus
🔸 Broader, global features like sweeps are computed in cortex via temporal integration
10/
So where do sweeps come from?
In layer 5a, we found that sweep-tuned neurons integrate stick inputs from VPM and POm over longer timescales — and are probably modulated by POm.
9/
Recordings in VPM and POm showed that both thalamic nuclei primarily encode sticks.
POm adds some diversity, but sweep tuning is not clearly present.
8/
Sticks dominated in layer 4 and 3.
Sweeps were found in layers 5a and 5b.
But can these features be inherited from the thalamus?
7/
We identified two distinct types of responses in cortex:
🔴 Sticks — brief, fast, single-whisker deflections
⚫ Sweeps — broad, multi-whisker movements with large angular changes
These were tuned to perpendicular axes in the feature space.
6/
We confirmed this with an independent sparse noise stimulus — random single-whisker deflections — and separated the two functional populations.
5/
But cells were not uniformly selective across this space.
They tended to cluster around two specific feature angles — suggesting subspace angle tuning.
4/
We found that the whisker movements that elicited the strongest responses belonged to a low dimensional feature space.
We could project each cell’s preferred stimulus into this space: the closer to the edge, the more selective.
3/
Velocity came out on top, as seen in rats (Harrell et al. 2020), and contrary to stick-slip models where velocity and acceleration are encoded equally.
2/
We designed and tested optimized kinematic stimulus spaces — position, velocity, acceleration — to find which parameter was best encoded by neurons.
