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1 Mathematical Sciences and Technology, Norwegian University of Life Sciences, Aas, Norway
2 Neurosciences and Radiology, University of California San Diego, La Jolla, California, United States; Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, Massachusetts, United States
3 Psychology, Hungarian Academy of Sciences, Budapest, Hungary; Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, Massachusetts, United States
4 Neurosciences and Radiology, University of California San Diego, La Jolla, California, United States
* To whom correspondence should be addressed. E-mail: Gaute.Einevoll{at}umb.no.
We present a new method, laminar population analysis (LPA), for analysis of laminar-electrode (linear multielectrode) data, where physiological constraints are explicitly incorporated in the mathematical model: The high-frequency band (multi-unit activity; MUA) is modeled as a sum over contributions from firing activity of multiple cortical populations, while the low-frequency band (local field potential; LFP) is assumed to reflect the dendritic currents due to synaptic inputs evoked by this firing. The method is applied to stimulus-averaged laminar-electrode data from barrel cortex of anesthetized rat following single whisker flicks. Two sample data sets, distinguished by stimulus paradigm, type of applied anesthesia and electrical boundary conditions, are investigated in detail. These data sets are well accounted for by a model with four cortical populations: one supragranular, one granular, and two infragranular populations. Population CSDs (the CSD signatures following firing in a particular population) provided by LPA, are further used to estimate the synaptic connection pattern between the various populations using a new LFP template-fitting technique, where LFP population templates are found by the electrostatic forward solution based on results from compartmental modelling of morphologically reconstructed neurons. Our analysis confirms previous experimental findings regarding the synaptic connections from neurons in the granular layer onto neurons in the supragranular layers and provides predictions about other synaptic connections. Further, the time-dependence of the stimulus-evoked population firing activity is predicted, and the temporal ordering of response onset is found to be compatible with earlier findings.
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