But the basic principles NLG919 of the model, including the requirement for LGN variability and correlations, receptive field elongation, and a compressive nonlinearity in the transformation between LGN activity and Vm will likely still apply. In the same way that LGN variability propagates to the cortex, variability in retinal

ganglion cells might propagate to the LGN: retinal response variability is contrast dependent (Berry et al., 1997) and correlated between nearby cells (Meister et al., 1995). Variability in retinal ganglion cells, however, is much lower than that of LGN neurons (Levine and Troy, 1986, Levine et al., 1992, Levine et al., 1996 and Kara et al., 2000). Some noise may therefore be introduced at the level of LGN by intrathalamic or feedback

circuitry (Levine and Troy, 1986). These results, taken together with the strong synaptic connectivity between retinal ganglion cells and LGN neurons, suggest that a large portion of LGN variability and correlation may originate in the retina. Although response variability is observed throughout the brain, we can suggest on the basis of our data selleck chemicals llc that this variability may not need to be generated independently at each stage of processing. A large fraction of variability can be passed from area to area as long as sufficient correlations exist among the neurons in the input area. It should be emphasized, however, that the strength of the correlations need not be particularly high. A correlation of ∼0.2 among LGN neurons was sufficient to explain the response variability in simple cells, and similar correlation levels (0.1–0.3) have been observed in spike responses of primate V1 (Kohn and Smith, 2005, Smith and Kohn, 2008 and Gutnisky and Dragoi, 2008) and other cortical areas (Gawne et al., 1996, Cohen and Newsome, 2008 and Cohen and Maunsell, 2009). From previous work

(Finn et al., 2007), it is known that weak (low contrast) preferred Mephenoxalone stimuli generate disproportionately large spike responses compared to strong (high contrast) null-oriented stimuli, even though they evoke similar mean depolarizations. This selective amplification is caused by the higher Vm variability for the former stimuli. We can now attribute that increase in variability to the combination of two factors: increase in variability at low stimulus strength in the thalamic inputs and an increase in the number of simultaneously active inputs for preferred stimuli. These factors seem generic: strong stimuli have been observed to reduce variability in a number of cortical areas (Churchland et al., 2010). It seems likely, then, that mechanisms similar to the ones we have identified here might operate throughout the neocortex. Experiments were performed on anesthetized adult female cats aged 4–6 months. Anesthesia was induced with a ketamine-HCl (30 mg/kg i.m.)/acepromazine maleate (0.3 mg/kg i.m.) mixture and maintained by intravenous infusion of sodium thiopental (1–2 mg/kg/hr) or propofol (5–10 mg/kg/hr) and sufentanil (0.75–1.