# Systems neuroscience

### Systems neuroscience

The study of how neural circuits give rise to higher-brain functions. A prototypical study in systems neuroscience includes three components:

- Multicellular recordings (action potentials in neurons, and calcium transients in neurons and astrocytes).
- Computerized analysis to decode information embedded in action potentials and calcium transients.
- Simultaneous measurement of a cognitive or behavioral function. Statistical tools to correlate cell activity and function include generalized linear models [1, 2], linear classifiers [3] [4], dimensionality reduction [5], and artificial neural networks [6].

*Aljadeff, J., et al., Analysis of Neuronal Spike Trains, Deconstructed. Neuron, 2016.***91**(2): p. 221-59.*Nogueira, R., et al., Lateral orbitofrontal cortex anticipates choices and integrates prior with current information. Nat Commun, 2017.***8**: p. 14823.*Quian Quiroga, R. and S. Panzeri, Extracting information from neuronal populations: information theory and decoding approaches. Nat Rev Neurosci, 2009.***10**(3): p. 173-85.*Arandia-Romero, I., et al., What can neuronal populations tell us about cognition? Curr Opin Neurobiol, 2017.***46**: p. 48-57.*Cunningham, J.P. and Z. Ghahramani, Linear Dimensionality Reduction: Survey, Insights, and Generalizations. Journal of Machine Learning Research, 2015.***16**: p. 2859-2900.*Paninski, L. and J.P. Cunningham, Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience. Curr Opin Neurobiol, 2018.***50**: p. 232-241.

### Systems neuroscience

The study of how neural circuits give rise to higher-brain functions. A prototypical study in systems neuroscience includes three components:

- Multicellular recordings (action potentials in neurons, and calcium transients in neurons and astrocytes).
- Computerized analysis to decode information embedded in action potentials and calcium transients.
- Simultaneous measurement of a cognitive or behavioral function. Statistical tools to correlate cell activity and function include generalized linear models [1, 2], linear classifiers [3] [4], dimensionality reduction [5], and artificial neural networks [6].

- Aljadeff, J., et al.,
*Analysis of Neuronal Spike Trains, Deconstructed.*Neuron, 2016.**91**(2): p. 221-59. - Nogueira, R., et al.,
*Lateral orbitofrontal cortex anticipates choices and integrates prior with current information.*Nat Commun, 2017.**8**: p. 14823. - Quian Quiroga, R. and S. Panzeri,
*Extracting information from neuronal populations: information theory and decoding approaches.*Nat Rev Neurosci, 2009.**10**(3): p. 173-85. - Arandia-Romero, I., et al.,
*What can neuronal populations tell us about cognition?*Curr Opin Neurobiol, 2017.**46**: p. 48-57. - Cunningham, J.P. and Z. Ghahramani,
*Linear Dimensionality Reduction: Survey, Insights, and Generalizations.*Journal of Machine Learning Research, 2015.**16**: p. 2859-2900. - Paninski, L. and J.P. Cunningham,
*Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience.*Curr Opin Neurobiol, 2018.**50**: p. 232-241.