Advanced Data Analysis in Neuroscience Integrating Statistical and Computational Models (2017) (PDF) by Daniel Durstewitz

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Ebook Info

  • Published: 2017
  • Number of pages: 292
  • Format: PDF
  • File Size: 7.22 MB
  • Authors: Daniel Durstewitz

Description

“Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well

User’s Reviews

“Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well

Keywords

Free Download Advanced Data Analysis in Neuroscience Integrating Statistical and Computational Models in PDF format
Advanced Data Analysis in Neuroscience Integrating Statistical and Computational Models PDF Free Download
Download Advanced Data Analysis in Neuroscience Integrating Statistical and Computational Models 2017 PDF Free
Advanced Data Analysis in Neuroscience Integrating Statistical and Computational Models 2017 PDF Free Download
Download Advanced Data Analysis in Neuroscience Integrating Statistical and Computational Models PDF
Free Download Ebook Advanced Data Analysis in Neuroscience Integrating Statistical and Computational Models