Assessing directed information as a method for inferring functional connectivity in neural ensembles
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Statistical models of neural activity are integral to modern neuroscience. Recently interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on ne ...
Statistical models of neural activity are at the core of the field of modern computational neuroscience. The activity of single neurons has been modeled to successfully explain dependencies of neural dynamics to its own spiking history, to external stimuli ...
The coordinated, collective spiking activity of neuronal populations encodes and processes information. One approach towards understanding such population based computation is to fit statistical models to simultaneously recorded spike trains and use these ...
Schizophrenia is a devastating psychiatric illness characterized by deterioration of cognitive and emotional processing. It has been hypothesized that aberrant cortical connectivity is implicated in the disease (Friston, 1998), yet previous studies of func ...
Neurons in the brain form highly complex networks through synaptic connections. Traditionally, functional connectivity between neurons has been explored using methods such as correlations, which do not contain any notion of directionality. Recently, an inf ...
Neural circuits closer to the periphery tend to be organised in a topological way, i.e. stimuli which are spatially close tend to be mapped onto neighbouring processing neurons. The goal of this study is to show how motion features (optic-flow), which have ...
It is plausible to hypothesize that the spiking responses of certain neurons represent functions of the spiking signals of other neurons. A natural ensuing question concerns how to use experimental data to infer what kind of a function is being computed. M ...
Multiple measures have been developed to quantify the similarity between two spike trains. These measures have been used for the quantification of the mismatch between neuron models and experiments as well as for the classification of neuronal responses in ...
The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for ...
Information theory has been used as an organizing principle in neuroscience for several decades. Estimates of the mutual information (MI) between signals acquired in neurophysiological experiments are believed to yield insights into the structure of the un ...
