The early visual system is responsible for encoding a complex spatiotemporal pattern of light. It transform this pattern into spikes which can then be read by downstream neurons. What strategies should neurons employ while transforming the input pattern? In the best of all possible worlds, neurons encode only information that other nearby neurons haven't already encoded leading to a highly sparse highly non-redundant coding scheme. What receptive field features lead to such a sparse, non- redundant coding scheme. For linear receptive fields, the presence of a classical surround correlates well with the response sparseness and de-correlatation. I measure the strength of this surround in the rodent dLGN and find that the surround strength in the un-anesthetized rodent is optimized for maximal sparseness and decorrelation for a majority of cells. Apart from the linear receptive field, neurons in the dLGN of many species are known to have powerful non-linear processing. Further, multiple response features of dLGN neurons have been attributed to these non -linear effects. I show that a simple linear model is capable of explaining many of these features. However, I identify multiple other response features that linear models are inherently incapable of explaining. I show that rodent dLGN neurons show atleast some of these features

A hallmark of the anterior cingulate cortex (ACC) is its functional heterogeneity. Functional and imaging studies revealed its importance in the encoding of anxiety-related and social stimuli, but it is unknown how microcircuits within the ACC encode these distinct stimuli. One type of inhibitory interneuron, which is positive for vasoactive intestinal peptide (VIP), is known to modulate the activity of pyramidal cells in local microcircuits, but it is unknown whether VIP cells in the ACC (VIPACC) are engaged by particular contexts or stimuli. Additionally, recent studies demonstrated that neuronal representations in other cortical areas can change over time at the level of the individual neuron. However, it is not known whether stimulus representations in the ACC remain stable over time. Using in vivo Ca2+ imaging and miniscopes in freely behaving mice to monitor neuronal activity with cellular resolution, we identified individual VIPACC that preferentially activated to distinct stimuli across diverse tasks. Importantly, although the population-level activity of the VIPACC remained stable across trials, the stimulus-selectivity of individual interneurons changed rapidly. These findings demonstrate marked functional heterogeneity and instability within interneuron populations in the ACC. This work contributes to our understanding of how the cortex encodes information across diverse contexts and provides insight into the complexity of neural processes involved in anxiety and social behavior.