Forwarded from datascienceinfo
Think Bayes by Allen Downey B.pdf
11.7 MB
Join us for the FENS 2020 Virtual Forum, where scientists will present the newest scientific and technological advances in understanding the various nervous systems, and where you'll have the opportunity to meet, chat and connect!
Link: Website
#Neuroscience
Follow: @theTuringMachine
Link: Website
#Neuroscience
Follow: @theTuringMachine
Forwarded from Complex Systems Studies
💡 Easy Parallel Computing with IPython
https://andrewmellor.co.uk/blog/articles/2015/04/30/easy-parallel/
https://andrewmellor.co.uk/blog/articles/2015/04/30/easy-parallel/
Andrew Mellor
Easy Parallel Computing with IPython
After speaking to a number of academics involved with Monte Carlo simulations, I realised many of them resort to creating bash noscripts to run a number of python instances of simulation before writing another noscript to piece the data back together. It turns…
Forwarded from Complex Systems Studies
Students, postdocs, and faculty interested in networks?
The Complex Networks Winter Online Workshop
https://www.surveymonkey.com/r/8H6FGDH
The Complex Networks Winter Online Workshop
https://www.surveymonkey.com/r/8H6FGDH
Forwarded from Scientific Programming (ZiAEE)
KCNI Virtual Summer School
ChrowdCast Link:
https://www.crowdcast.io/e/s4qmka1v/1
Password for the Session:
Neuroinformatics
GitHup
ChrowdCast Link:
https://www.crowdcast.io/e/s4qmka1v/1
Password for the Session:
Neuroinformatics
GitHup
crowdcast
Krembil Centre for Neuroinformatics Summer School 2020
Register now for Krembil Centre for Neuroinformatics Summer School 2020 on crowdcast, scheduled to go live on July 6, 2020, 10:45 AM EDT.
the Turing Machine
https://journals.physiology.org/doi/pdf/10.1152/physrev.1990.70.2.513
Functional Comparison of Neurotransmitter Receptor Subtypes in Mammalian Central Nervous System
#Neuroscience
Follow: @theTuringMachine
#Neuroscience
Follow: @theTuringMachine
the Turing Machine
10.1146@annurev-neuro-092619-094115.pdf
Significant experimental, computational, and theoretical work has identified rich structure within the coordinated activity of interconnected neural pop- ulations. An emerging challenge now is to uncover the nature of the asso- ciated computations, how they are implemented, and what role they play in driving behavior. We term this computation through neural population dy- namics. If successful, this framework will reveal general motifs of neural pop- ulation activity and quantitatively describe how neural population dynamics implement computations necessary for driving goal-directed behavior. Here, we start with a mathematical primer on dynamical systems theory and ana- lytical tools necessary to apply this perspective to experimental data. Next, we highlight some recent discoveries resulting from successful application of dynamical systems. We focus on studies spanning motor control, timing, decision-making, and working memory. Finally, we briefly discuss promis- ing recent lines of investigation and future directions for the computation through neural population dynamics framework.