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As a reminder, you should check the original article (https://www.nature.com/articles/s41467-025-63994-y https://www.nature.com/articles/s41467-025-63994-y) to

As a reminder, you should check the original article (https://www.nature.com/articles/s41467-025-63994-y https://www.nature.com/articles/s41467-025-63994-y) to get more extensive and accurate information.

dang 1y ago
Thanks, we'll put that link in the toptext as well.
foundart 1y ago
Indeed! Quite interesting. title: The neural basis for uncertainty processing in hierarchical decision making abstract: Hierarchical decisions in natural environments require processing uncertainty across multiple levels, but existing models struggle to explain how animals perform flexible, goal-directed behaviors under such conditions. Here we introduce CogLinks, biologically grounded neural architectures that combine corticostriatal circuits for reinforcement learning and frontal thalamocortical networks for executive control. Through mathematical analysis and targeted lesion, we show that these systems specialize in different forms of uncertainty, and their interaction supports hierarchical decisions by regulating efficient exploration, and strategy switching. We apply CogLinks to a computational psychiatry problem, linking neural dysfunction in schizophrenia to atypical reasoning patterns in decision making. Overall, CogLink fills an important gap in the computational landscape, providing a bridge from neural substrates to higher cognition.
nyrikki 1y ago
For those who are frustrated with the lack of a fleshed out limitations section, it seems well covered under the peer review which is in the link above or directly below [0] To me the paper is still very interesting, but concerns about computationally intractability and the hardness of approximation questions made me dig deeper. > Specifically, our model aims to bridge biological circuits and computations of uncertainty in a tractable manner. > To address this, we have carefully reframed our claims throughout the manuscript to emphasize that the model is a hypothesis generator rather than a definitive representation of biological circuitry. Under the "All models are wrong, some are useful" I have no doubt this will be useful to some. But I will admit that their claims in the response to Reviewer Comment 4.5 that they "emphasize that the model is a hypothesis generator" doesn't match the published paper IMHO; and that negatively impacted my view of the claims in an admittedly probably unfair manner. [0] https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-025-63994-y/MediaObjects/41467_2025_63994_MOESM3_ESM.pdf https://static-content.springer.com/esm/art%3A10.1038%2Fs414...

dang 1y ago

Thanks, we'll put that link in the toptext as well.

foundart 1y ago

Indeed! Quite interesting. title: The neural basis for uncertainty processing in hierarchical decision making abstract: Hierarchical decisions in natural environments require processing uncertainty across multiple levels, but existing models struggle to explain how animals perform flexible, goal-directed behaviors under such conditions. Here we introduce CogLinks, biologically grounded neural architectures that combine corticostriatal circuits for reinforcement learning and frontal thalamocortical networks for executive control. Through mathematical analysis and targeted lesion, we show that these systems specialize in different forms of uncertainty, and their interaction supports hierarchical decisions by regulating efficient exploration, and strategy switching. We apply CogLinks to a computational psychiatry problem, linking neural dysfunction in schizophrenia to atypical reasoning patterns in decision making. Overall, CogLink fills an important gap in the computational landscape, providing a bridge from neural substrates to higher cognition.

nyrikki 1y ago

For those who are frustrated with the lack of a fleshed out limitations section, it seems well covered under the peer review which is in the link above or directly below [0] To me the paper is still very interesting, but concerns about computationally intractability and the hardness of approximation questions made me dig deeper. > Specifically, our model aims to bridge biological circuits and computations of uncertainty in a tractable manner. > To address this, we have carefully reframed our claims throughout the manuscript to emphasize that the model is a hypothesis generator rather than a definitive representation of biological circuitry. Under the "All models are wrong, some are useful" I have no doubt this will be useful to some. But I will admit that their claims in the response to Reviewer Comment 4.5 that they "emphasize that the model is a hypothesis generator" doesn't match the published paper IMHO; and that negatively impacted my view of the claims in an admittedly probably unfair manner. [0] https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-025-63994-y/MediaObjects/41467_2025_63994_MOESM3_ESM.pdf https://static-content.springer.com/esm/art%3A10.1038%2Fs414...