Recruitment and regulation of phosphatidylinositol phosphate kinase type 1 gamma by the FERM domain of talin

Membrane phosphoinositides control a variety of cellular processes through the recruitment and/or regulation of cytosolic proteins. One mechanism ensuring spatial specificity in phosphoinositide signalling is the targeting of enzymes that mediate their metabolism to specific subcellular sites. Phosphatidylinositol phosphate kinase type 1 gamma (PtdInsPKI gamma) is a phosphatidylinositol-4-phosphate 5-kinase that is expressed at high levels in brain, and is concentrated at synapses. Here we show that the predominant brain splice variant of PtdInsPKI gamma (PtdInsPKI gamma-90) binds, by means of a short carboxy-terminal peptide, to the FERM domain of talin, and is strongly activated by this interaction. Talin, a principal component of focal adhesion plaques, is also present at synapses. PtdInsPKI gamma-90 is expressed in non-neuronal cells, albeit at much lower levels than in neurons, and is concentrated at focal adhesion plaques, where phosphatidylinositol-4,5-bisphosphate has an important regulatory role. Overexpression of PtdInsPKI gamma-90, or expression of its C-terminal domain, disrupts focal adhesion plaques, probably by local disruption of normal phosphoinositide balance. These findings define an interaction that has a regulatory role in cell adhesion and suggest new similarities between molecular interactions underlying synaptic junctions and general mechanisms of cell adhesion.     

Correlation between neural spike trains increases with firing rate

Populations of neurons in the retina, olfactory system, visual and somatosensory thalamus, and several cortical regions show temporal correlation between the discharge times of their action potentials (spike trains). Correlated firing has been linked to stimulus encoding, attention, stimulus discrimination, and motor behaviour. Nevertheless, the mechanisms underlying correlated spiking are poorly understood, and its coding implications are still debated. It is not clear, for instance, whether correlations between the discharges of two neurons are determined solely by the correlation between their afferent currents, or whether they also depend on the mean and variance of the input. We addressed this question by computing the spike train correlation coefficient of unconnected pairs of in vitro cortical neurons receiving correlated inputs. Notably, even when the input correlation remained fixed, the spike train output correlation increased with the firing rate, but was largely independent of spike train variability. With a combination of analytical techniques and numerical simulations using 'integrate-and-fire' neuron models we show that this relationship between output correlation and firing rate is robust to input heterogeneities. Finally, this overlooked relationship is replicated by a standard threshold-linear model, demonstrating the universality of the result. This connection between the rate and correlation of spiking activity links two fundamental features of the neural code.