Hannes Mehrer
@hannesmehrer.bsky.social
Computational neuroscientist, NeuroAI lab @EPFL
Reposted by Hannes Mehrer
Arguably this is 2 pages too many, given that grant decisions are mostly based on CV + abstract:
"We find that withholding proposal texts from panelists did not
detectibly impact their proposal rankings."
link.springer.com/article/10.1...
"We find that withholding proposal texts from panelists did not
detectibly impact their proposal rankings."
link.springer.com/article/10.1...
Do grant proposal texts matter for funding decisions? A field experiment - Scientometrics
Scientists and funding agencies invest considerable resources in writing and evaluating grant proposals. But do grant proposal texts noticeably change panel decisions in single blind review? We report...
link.springer.com
October 22, 2025 at 8:24 PM
Arguably this is 2 pages too many, given that grant decisions are mostly based on CV + abstract:
"We find that withholding proposal texts from panelists did not
detectibly impact their proposal rankings."
link.springer.com/article/10.1...
"We find that withholding proposal texts from panelists did not
detectibly impact their proposal rankings."
link.springer.com/article/10.1...
But to come back to focal neural effects of stimulation: without topography in the model I find it hard to see how to explicitly model the interaction of stimulation at multiple sites that might allow to obtain stronger behavioral effects than we observed using single-site stimulation.
October 9, 2025 at 6:31 AM
But to come back to focal neural effects of stimulation: without topography in the model I find it hard to see how to explicitly model the interaction of stimulation at multiple sites that might allow to obtain stronger behavioral effects than we observed using single-site stimulation.
Defining face-selective units in a non-topo model, increasing their activation level, and projecting that to the latents of a GAN used for image generation probably also results in face-related changes in model percepts. Is that more what you are asking?
October 9, 2025 at 6:31 AM
Defining face-selective units in a non-topo model, increasing their activation level, and projecting that to the latents of a GAN used for image generation probably also results in face-related changes in model percepts. Is that more what you are asking?
This allows eg our visualizations, where we stimulate face-selective regions - defined using a standard face-localizer - which then lead to face-related changes to model percepts (Figs 5, 9-15).
October 9, 2025 at 6:31 AM
This allows eg our visualizations, where we stimulate face-selective regions - defined using a standard face-localizer - which then lead to face-related changes to model percepts (Figs 5, 9-15).
Thanks, Adrian! The main purpose of using topo models is to allow the implementation of neural activation changes and their propagation across the cortical sheet using the topo model's in-silico equivalent of the cortex.
October 9, 2025 at 6:31 AM
Thanks, Adrian! The main purpose of using topo models is to allow the implementation of neural activation changes and their propagation across the cortical sheet using the topo model's in-silico equivalent of the cortex.
Absolutely agree that neural responses to the perturbations would have been very useful. While that type of data was not recorded in our experiments, the groups of Michael Beyeler @mbeyeler.bsky.social and Eduardo Fernandez just presented some great work in this direction: bsky.app/profile/mbey...
👁️🧠 New preprint: We demonstrate the first data-driven neural control framework for a visual cortical implant in a blind human!
TL;DR Deep learning lets us synthesize efficient stimulation patterns that reliably evoke percepts, outperforming conventional calibration.
www.biorxiv.org/content/10.1...
TL;DR Deep learning lets us synthesize efficient stimulation patterns that reliably evoke percepts, outperforming conventional calibration.
www.biorxiv.org/content/10.1...
October 9, 2025 at 3:35 AM
Absolutely agree that neural responses to the perturbations would have been very useful. While that type of data was not recorded in our experiments, the groups of Michael Beyeler @mbeyeler.bsky.social and Eduardo Fernandez just presented some great work in this direction: bsky.app/profile/mbey...
Thanks for the question, Konrad! Do you mean what percentage of variance of the neural effects of perturbations our topo models can explain? Would be great if we could investigate that, but we haven't recorded neural data during perturbation trials. Or what did you mean by observational data?
October 8, 2025 at 5:07 PM
Thanks for the question, Konrad! Do you mean what percentage of variance of the neural effects of perturbations our topo models can explain? Would be great if we could investigate that, but we haven't recorded neural data during perturbation trials. Or what did you mean by observational data?
Special thanks go out to Paolo Papale and Anna Mitola who initiated this collaboration and performed the in-vivo experiments. And to the rest of a great team: Ben Lonnqvist @benlonnqvist.bsky.social, Abdulkadir Gokce @akgokce.bsky.social, Martin Schrimpf @mschrimpf.bsky.social
October 7, 2025 at 3:22 PM
Special thanks go out to Paolo Papale and Anna Mitola who initiated this collaboration and performed the in-vivo experiments. And to the rest of a great team: Ben Lonnqvist @benlonnqvist.bsky.social, Abdulkadir Gokce @akgokce.bsky.social, Martin Schrimpf @mschrimpf.bsky.social
Take-home-message
Proof-of-principle that topographic models can guide stimulation of high-level cortex to bias object-level behavioral choices. A step toward next-generation visual prosthetics allowing more complex visual experience.
Proof-of-principle that topographic models can guide stimulation of high-level cortex to bias object-level behavioral choices. A step toward next-generation visual prosthetics allowing more complex visual experience.
October 7, 2025 at 3:22 PM
Take-home-message
Proof-of-principle that topographic models can guide stimulation of high-level cortex to bias object-level behavioral choices. A step toward next-generation visual prosthetics allowing more complex visual experience.
Proof-of-principle that topographic models can guide stimulation of high-level cortex to bias object-level behavioral choices. A step toward next-generation visual prosthetics allowing more complex visual experience.
Model perceptual changes via simulated microstimulation
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
October 7, 2025 at 3:22 PM
Model perceptual changes via simulated microstimulation
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
Experiment 2
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
October 7, 2025 at 3:22 PM
Experiment 2
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
Experiment 1
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
October 7, 2025 at 3:22 PM
Experiment 1
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
Visual stimuli via GANs
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)
October 7, 2025 at 3:22 PM
Visual stimuli via GANs
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)
How it works
1. Map the in-silico cortical sheet of a topographic model to the monkey cortex.
2. Optimize stimulation parameters by prototyping experiments in the model.
3. Only test those parameters in-vivo that are predicted to yield the largest behavioral effects.
1. Map the in-silico cortical sheet of a topographic model to the monkey cortex.
2. Optimize stimulation parameters by prototyping experiments in the model.
3. Only test those parameters in-vivo that are predicted to yield the largest behavioral effects.
October 7, 2025 at 3:22 PM
How it works
1. Map the in-silico cortical sheet of a topographic model to the monkey cortex.
2. Optimize stimulation parameters by prototyping experiments in the model.
3. Only test those parameters in-vivo that are predicted to yield the largest behavioral effects.
1. Map the in-silico cortical sheet of a topographic model to the monkey cortex.
2. Optimize stimulation parameters by prototyping experiments in the model.
3. Only test those parameters in-vivo that are predicted to yield the largest behavioral effects.
Stimulate high-level vs early visual cortex
Visual prosthetics in early visual areas can evoke simple percepts (letters), but they are limited by 1. electrode count and 2. low-level features. We target high-level cortex to elicit percepts of more complex objects.
Visual prosthetics in early visual areas can evoke simple percepts (letters), but they are limited by 1. electrode count and 2. low-level features. We target high-level cortex to elicit percepts of more complex objects.
October 7, 2025 at 3:22 PM
Stimulate high-level vs early visual cortex
Visual prosthetics in early visual areas can evoke simple percepts (letters), but they are limited by 1. electrode count and 2. low-level features. We target high-level cortex to elicit percepts of more complex objects.
Visual prosthetics in early visual areas can evoke simple percepts (letters), but they are limited by 1. electrode count and 2. low-level features. We target high-level cortex to elicit percepts of more complex objects.
Model perceptual changes via simulated microstimulation
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
October 7, 2025 at 2:37 PM
Model perceptual changes via simulated microstimulation
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
We visualized perceptual changes from simulated stimulations in model face-selective regions. This results in face-related changes: additional faces appear (#1), face becomes larger (#1161), or specific face-features get enhanced (#533).
Experiment 2
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
October 7, 2025 at 2:37 PM
Experiment 2
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
With a slightly different site-selection criterion, stimulation shifted behavior above baseline in monkey 1 (Cohen’s d=0.67), though our model was not able to accurately predict monkey behavior anymore.
Experiment 1
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
October 7, 2025 at 2:37 PM
Experiment 1
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
Model-predicted behavioral shifts correlated with stimulation-evoked behavioral shifts in both monkeys. While predicted model responses were strong, monkey behavior was not shifted above baseline.
Visual stimuli via GANs
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)
October 7, 2025 at 2:37 PM
Visual stimuli via GANs
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)
We generate image sequences that smoothly modulate neural activity along a stimulation site’s tuning dimension. This links visual input to the direction of activation changes resulting from microstimulation (Papale et al. 2024: www.biorxiv.org/content/10.1...)