Kayson Fakhar

@Kaysonfakhar

PhD student , causality, biological and artificial brains, epistemology, and breaking stuff to see how they were working.

Germany
Vrijeme pridruživanja: listopad 2017.

Medijski sadržaj

  1. 24. pro 2019.
    Odgovor korisnicima

    He’s facing the camera since here it goes behind the poles

  2. 5. lis 2019.

    I would like to show you my non-academic side called “anxious monkey”. I released a few of my tracks from 2012 to 2018 on streaming services. Feedbacks will be appropriated Spotify: Apple Music: Others:

  3. 10. ruj 2019.

    A great day with at and on multiscale investigation of different states of consciousness. The focus on people’s personal experiences and its correlation with lower levels is so satisfying.

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  4. 3. ruj 2019.

    Had a pretty friendly online discussion with about understanding phenomena including the brain at today. I promise next time there’ll be a better microphone from our side!

  5. 19. kol 2019.

    So I evolved 20 networks with NEAT to play flappy bird and I expected them to converge in a similar topology but nope I have a network of 4-25-1 and another one like 2-0-1 both playing well. I gotta check this but seems like some evolved a connection from output back inside!

  6. 19. kol 2019.

    Feel free to contact us if you have a question or suggestion or whatever. We'll be more than happy to exchange ideas. I'm out.

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  7. 19. kol 2019.

    We put boxes too, one is a review of analytical tools that are used to infer causality from observational data. The other is an example of how neuroscience can use ground-truth computational models to address causality. Yes, this is one of our proposed solutions, inspired by many

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  8. 19. kol 2019.

    We then reviewed a few interventional tools such as optogenetics, chemogenetics, and electrical stimulation, focusing more on their potential confounds and how they might influence our causal knowledge about the brain. Of course, there will be a spatiotemporal figure about this/

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  9. 19. kol 2019.

    2. What can we call causal in the brain with respect to the produced behaviour? Neuronal elements or the information they transmit? inspired us on this one 3. Are the brain and behaviour decomposable in a sense that we can map distinguishable elements across levels?

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  10. 19. kol 2019.

    We started with the most common logical foundation of these explanations, i.e., Necessary and Sufficiency (NS), inspired by we argued that it's not a good idea to use it and we pointed to an alternative approach proposed by Mackie (1993)/

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  11. 19. kol 2019.

    Finally, our pre-print is out. "Neuronal Causes and Behavioural Effects: a Review on Logical, Methodological, and Technical Issues With Respect to Causal Explanations of Behaviour in Neuroscience" Let me summarize in a thread + here's a visual abstract:

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  12. 9. kol 2019.

    I settled on playing flappy bird for now and even this “simple” game is full of interesting issues. For example I evolved 5 networks so far with the same config ( 4 inputs, no initial connections, 1 output, everything is evolvable) and each end up having different architecture!

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  13. 24. srp 2019.

    My vision 😅 please fund

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  14. 24. srp 2019.

    I was thinking if I had a big science money I’d go for ‘s idea of simulating agents in their environments to cope with. Kinda like the idea of Open-ended evolution. I mean, it probably won’t answer how serotonin contributes to depression but answers my questions!

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  15. 10. srp 2019.

    Ma shallow NEAT with 128 input neurons and 6 output neurons + i guess 4 or 5 interneurons. Just look at this nonsense, how can you play space invaders you literally have 5 neurons as a brain

  16. 28. lip 2019.

    A stimulating talk by Andreas Nieder on the presence of numeracy in us, monkeys, craws and even DNNs that trained on photo categorization. I was thinking if we can investigate the fundamentals of calculations by a sequential-like task/

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  17. 27. lip 2019.

    Not only Berecht lab throws cool parties but they work on cool science too. Apparently, kinship is coded in different layers of the mice lateral septum. More kin response from deeper cells.

  18. 27. lip 2019.

    Pascal Fries reminding on so-called “off manifold” perturbations

  19. 21. lip 2019.

    Quite contrary to my naive expectations, a recurrent architecture seems to never learn how to play Sonic (population size from 10 to 256, up to 800 generations and 3 times total extinction) but a feed forward one does it pretty fast and dirty (population size around 20)

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  20. 8. lip 2019.

    But my favorite will be: - who does what in there using multi-perturbation approach and eventually, could a neuroscientist understand the good old Sonic the hedgehog? got any other suggestions?

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