Analysis of information transmission in the schaffer collaterals

A propagating ERKII switch forms zones of elevated dendritic activation correlated with plasticity

“…Other modeling studies that have specifically explored synapse clustering and spatial distribution of synapses also indicate that the connectivity profile may have functional consequences on neuronal excitability (Azouz, 2005). From anatomical studies the hippocampal network has been characterized as sparsely connected, and on theoretical grounds such an organization may improve memory capacity (Schultz and Rolls, 1999). Our indirect estimates of functional connectivity enrich the picture of sparse strong connections with a background of diffuse connections that may be available for subsequent strengthening.…”

“…Such zonation is of interest in network studies of hippocampal function (Schultz and Rolls, 1999). We predict that the ERKII activity spread is accompanied by greater Ca 2+ influx.…”

“…At the neuronal circuit level, the layout and placement of synapses determines the capacity for different forms of network function. These include single-cell computational operations arising out of regulation of dendritic action potentials (Hausser and Mel, 2003;Rudolph and Destexhe, 2003;Urakubo et al, 2004), and also network properties such as attractors in associative memory circuits (Frick and Johnston, 2005;Schultz and Rolls, 1999). In this study we characterize and predict the basis of this spatial unit of plasticity at the intersection of synaptic plasticity and dendritic excitability.…”

The impact of flavonoids on spatial memory in rodents: from behaviour to underlying hippocampal mechanisms

“…It has been demonstrated that the CA3-CA1 synapses are associatively modifiable, enabling an efficient retrieval of information from CA3. Interestingly, it has been shown that a considerable loss of information occurs between CA1 and CA3 if the synapses are non-modifiable [172,182]. The CA1 network receives a double set of inputs.…”

Estimating Information-Theoretic Quantities

“…Examples include analytical calculations of the information flow through models of neural circuits with parameters fit to anatomical and physiological data (Treves and Panzeri, 1995;Schultz and Treves, 1998;Schultz and Rolls, 1999), and parametric fitting of probabilistic models of neural spike firing (Paninski, 2004;Pillow et al, 2005Pillow et al, , 2008, of spike count distributions (Gershon et al, 1998;Clifford and Ibbotson, 2000), or of neural mass signals (Magri et al, 2009). It should come as no surprise that "there is no free lunch", and, although in principle information quantities can be computed exactly under such circumstances, the problem is moved to one of assessing model validity -an incorrect model can lead to a bias in either direction in the information computed.…”