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:

  1.  Multicellular recordings (action potentials in neurons, and calcium transients in neurons and astrocytes).
  2.  Computerized analysis to decode information embedded in action potentials and    calcium transients.
  3.  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].

 

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  1. Aljadeff, J., et al., Analysis of Neuronal Spike Trains, Deconstructed. Neuron, 2016. 91(2): p. 221-59.
  2. Nogueira, R., et al., Lateral orbitofrontal cortex anticipates choices and integrates prior with current information. Nat Commun, 2017. 8: p. 14823.
  3. 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.
  4. Arandia-Romero, I., et al., What can neuronal populations tell us about cognition? Curr Opin Neurobiol, 2017. 46: p. 48-57.
  5. Cunningham, J.P. and Z. Ghahramani, Linear Dimensionality Reduction: Survey, Insights, and Generalizations. Journal of Machine Learning Research, 2015. 16: p. 2859-2900.
  6. 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:

  1.  Multicellular recordings (action potentials in neurons, and calcium transients in neurons and astrocytes).
  2.  Computerized analysis to decode information embedded in action potentials and    calcium transients.
  3.  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].

 

 

 

  1. Aljadeff, J., et al., Analysis of Neuronal Spike Trains, Deconstructed. Neuron, 2016. 91(2): p. 221-59.
  2. Nogueira, R., et al., Lateral orbitofrontal cortex anticipates choices and integrates prior with current information. Nat Commun, 2017. 8: p. 14823.
  3. 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.
  4. Arandia-Romero, I., et al., What can neuronal populations tell us about cognition? Curr Opin Neurobiol, 2017. 46: p. 48-57.
  5. Cunningham, J.P. and Z. Ghahramani, Linear Dimensionality Reduction: Survey, Insights, and Generalizations. Journal of Machine Learning Research, 2015. 16: p. 2859-2900.
  6. 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.
Back to what we do