# Computational Neuroscience

## Awesome Computational Neuroscience ¶

To contribute, see code of contribution

Computational neuroscience is a multidisciplinary science that joins biology/neuroscience, medicine, biophysics, psychology, computer science, mathematics, and statistics to study the nervous system using computational approaches.

This list of schools and researchers in computational neuroscience, theoretical neuroscience, (and systems neuroscience) aims to give a global perspective of researchers in the field, make it easier to apply to the listed institutions, and also provide a reasonable way to find an advisor.

In addition to names of PIs, excerpts of their academic biographies, and links to their publications, many of the researchers are qualified with a small scale "+/=/- computational." The metric is subjective to the editor of that material but it generally breaks down as: (+) refers to a researcher the university identifies as a computational neuroscientist, their bio consistently identifies a significant component of their research is in the field, and they have a significant body of work in the field. (=) refers to the fact that the university identifies them as practicing computational research and they have occasionally produced articles in the field. (-) means that the university identifies them as practicing computational neuroscience, their bio might also mention it, but articles could not be found that represent this material. As with ratings, this metric might change for a researcher over time as they publish more.

## Europe¶

### Germany¶

#### INI¶

| PI(Ph.D.s) | Research Areas | Research | +/=/- computational | | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | ------------------- | | Cheng, Sen | Our first approach is modeling, including mathematic models as well as computer simulation of complex networks. While all models are simplified, we aim to build biologically realistic models that capture the essence of the neural circuit mechanism underlying learning and memory. Our second approach is data-mining. We develop methods for model-based data analysis and apply such methods to experimental data. These data include electrophysiological and EEG recordings as well as behavioral data. We collaborate closely with neuroscientists on the RUB campus and at other universities in Germany and abroad. | [Lab](https://www.ini.rub.de/the_institute/people/sen-cheng/#publications) | + |

### Italy¶

#### SISSA¶

| PI(Ph.D.s) | Research Areas | Research | +/=/- computational | | ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------- | ------------------- | | Treves, Alessandro | [Hippocampal Processing: The aim is to understand how the hippocampus contributes to memory, focusing on modelling coding strategies within each structure of the hippocampal formation (e.g. self-organization of grid representations), as well as interactions between different structures. Neural Basis of Language: The aim is to describe network behaviour that could subserve Language production. A class of reduced Potts models of large semantic associative networks, endowed with adaptation, naturally displays Latching dynamics, i.e. hopping from one attractor to the next. Such dynamics may be associated with a network capacity for infinite recursion, which is considered as the core of several higher cognitive functions.](https://people.sissa.it/~ale/limbo.html) | [Google](https://scholar.google.com/citations?hl=en&user=I2Y8X5AAAAAJ&view_op=list_works&sortby=pubdate) | + |

## North America¶

#### Ontario¶

##### University of Waterloo¶
| PI(Ph.D.s) | Research Areas | Research | +/=/- computational | | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------- | ------------------- | | Anderson, Britt | [Dr. Anderson combines computational and empirical approaches in the study of spatial attention and general cognitive ability.](https://uwaterloo.ca/centre-for-theoretical-neuroscience/people-profiles/britt-anderson) | [Lab](https://brittlab.uwaterloo.ca/publications/) | + | | Campbell, Sue Ann | [Her main research interest is in the mathematical modelling of neural systems at the single cell and small network level.](https://uwaterloo.ca/centre-for-theoretical-neuroscience/people-profiles/sue-ann-campbell) | [Google](https://scholar.google.com/citations?hl=en&user=KgioDk8AAAAJ&view_op=list_works&sortby=pubdate) | + | | Danckert, James | [Dr. Danckert’s research explores the role of parietal cortex in the control of visually guided actions and examines the consequences of injury to this part of the brain.](https://uwaterloo.ca/danckert-attention-group/) | [Google](https://scholar.google.com/citations?hl=en&user=Bb2jD2QAAAAJ&view_op=list_works&sortby=pubdate) | = | | Eliasmith, Chris | [With Charles Anderson, I have developed a general method for building large-scale, biologically detailed models of neural systems. I have applied this method in a variety of contexts, including rat navigation, working memory, lamprey swimming, hemineglect, and language-based reasoning.](https://uwaterloo.ca/centre-for-theoretical-neuroscience/people-profiles/chris-eliasmith) | [Google](https://scholar.google.com/citations?hl=en&user=KOBO-6QAAAAJ&view_op=list_works&sortby=pubdate) | + | | Fugelsang, Jonathan | [To understand the mechanisms underlying these processes, I use both behavioural and functional brain imaging (e.g., ERP, Functional Magnetic Resonance Imaging $fMRI$) methodologies.](https://uwaterloo.ca/psychology/people-profiles/jonathan-fugelsang) | [Google](https://scholar.google.com/citations?hl=en&user=FD3P_78AAAAJ&view_op=list_works&sortby=pubdate) | - | | Ingalls, Brian (More computational biology than neuroscience) | [We use mathematical models and experimental methods to investigate the behaviour of intracellular molecular networks and cell-to-cell interactions. This work ranges from fundamental studies of biology to applications in biotechnology and health](https://uwaterloo.ca/scholar/bingalls/) | [Google](https://scholar.google.com/citations?hl=en&user=Td4gEp0AAAAJ&view_op=list_works&sortby=pubdate) | + | | Kapre, Nachiket (CS only, unrelated) | [Digital systems, Embedded computing systems, Reconfigurable computing, FPGA Architecture, Applications, Compilers](https://uwaterloo.ca/electrical-computer-engineering/profile/nachiket) | [Google](https://scholar.google.com/citations?hl=en&user=JxwwXHMAAAAJ&view_op=list_works&sortby=pubdate) | + | | Marriott, Paul (Applied math, some NS) | [His interests focus on using geometric ideas, for example differential or convex geometry in statistics. He has recently been working on geometric methods to understand mixture models.](https://uwaterloo.ca/centre-for-theoretical-neuroscience/people-profiles/paul-marriott) | [Google](https://scholar.google.com/citations?hl=en&user=hX40SzUAAAAJ&view_op=list_works&sortby=pubdate) | + | | Orchard, Jeff | [My research aim is to uncover mechanisms that underlie the computational and organizational aspects of the brain. For example, what function does feedback play in our brains, and how do our expectations influence our perceptions? I study these questions by modelling neural networks.](https://cs.uwaterloo.ca/~jorchard/UWaterloo/Home.html) | [Google](https://scholar.google.com/citations?hl=en&user=cAfBytAAAAAJ&view_op=list_works&sortby=pubdate) | + | | Spafford, J. David | [Major projects in Dr. Spafford's lab focus on the: a) cellular and molecular mechanisms underlying calcium channel expression and localization in developing synapses; b) modulation of calcium channel function by G proteins, phosphorylation and synaptic proteins; c) isolation and characterization of anti-calcium channel toxins for caveolin 1 (Cav1), Cav2 and Cav3 calcium channels.](https://uwaterloo.ca/centre-for-theoretical-neuroscience/people-profiles/j-david-spafford) | | - | | Tripp, Bryan | [The central goal of the lab is to develop increasingly realistic computer/robotic models of the dorsal visual pathways and the networks that control eye and limb motion.](https://uwaterloo.ca/centre-for-theoretical-neuroscience/people-profiles/bryan-tripp) | [Google](https://scholar.google.com/citations?hl=en&user=OUMJw3oAAAAJ&view_op=list_works&sortby=pubdate) | + |

### United States¶

#### U.S. West¶

##### University of California San Diego¶
Sejnowski, Terrence
##### University of Texas, Austin¶
| PI(Ph.D.s) | Research Areas | Research | +/=/- computational | | --------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------- | ------------------- | | Goris, Robbe | [He uses behavioral experiments, computational theory, and monkey electrophysiology to study representation and computation in the primate visual system](http://ctcn.utexas.edu/member/robbe-goris/) | [Lab](http://ctcn.utexas.edu/publications/) | + | | Fiete, Ila | [uses computational and theoretical approaches to understand the nature of distributed coding, error correction, and dynamical mechanisms that underlie representation and computation in the brain](http://ctcn.utexas.edu/member/ila-fiete/) | [Lab](http://clm.utexas.edu/fietelab/publications.html) | + | | Geisler, Bill | [research combines behavioral studies, neurophysiological studies, studies of natural stimuli, and mathematical analysis](http://ctcn.utexas.edu/member/bill-geisler/) | [Lab](https://liberalarts.utexas.edu/cps/faculty/wsg8#publications) | + | | Huth, Alex | [Our lab uses quantitative, computational methods to try to understand how the human brain processes the natural world. In particular, we are focused on understanding how the meaning of language is represented in the brain](https://www.cs.utexas.edu/~huth/) | [Lab](https://www.cs.utexas.edu/~huth/publications.html) | + | | Soloveichik, David | [(molecular programming), theoretical connections between distributed computing and molecular information processing. David is also interested in understanding how neural networks can execute distributed computing algorithms](http://ctcn.utexas.edu/member/david-soloveichik/) | [Google](https://scholar.google.com/citations?hl=en&user=dSPQHDoAAAAJ&view_op=list_works&sortby=pubdate) | + | | Taillefumier, Thibaud | [We develop novel analytical and algorithmic tools to address questions at the interface of Systems Neuroscience and Applied Mathematics](https://mathneuro.cns.utexas.edu/research) | [Lab](https://mathneuro.cns.utexas.edu/publications) | + | | Tran, Ngoc Mai | [probabilistic and combinatorial questions arising from tropical geometry and neuroscience](http://ctcn.utexas.edu/member/ngoc-mai-tran/) | [Lab](https://web.ma.utexas.edu/users/ntran/publications.html) | + |

#### U.S. Central¶

##### Indiana University¶

Cognitive and Computational Neuroscience