The coordination of activity across neocortical areas is essential for mammalian brain function. Understanding this process requires simultaneous functional measurements across the cortex. In order to dissociate direct cortico-cortical interactions from other sources of neuronal correlations, it is furthermore desirable to target cross-areal recordings to neuronal subpopulations that anatomically project between areas. Here, we combined anatomical tracers with a novel multi-area two-photon microscope to perform simultaneous calcium imaging across mouse primary (S1) and secondary (S2) somatosensory whisker cortex during texture discrimination behavior, specifically identifying feedforward and feedback neurons. We find that coordination of S1-S2 activity increases during motor behaviors such as goal-directed whisking and licking. This effect was not specific to identified feedforward and feedback neurons. However, these mutually projecting neurons especially participated in inter-areal coordination when motor behavior was paired with whisker-texture touches, suggesting that direct S1-S2 interactions are sensory-dependent. Our results demonstrate specific functional coordination of anatomically-identified projection neurons across sensory cortices.DOI: http://dx.doi.org/10.7554/eLife.14679.001

Visual intracortical and transthalamic pathways carry distinct information to cortical areasHighlights d Transthalamic pathway through pulvinar indirectly connects lower to higher cortical areas d This pathway combines input from V1 with that of many cortical and subcortical areas d Pulvinar conveys distinct visual and motor information to different higher visual areas d Direct intracortical and transthalamic pathways convey different information

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Sensory processing involves information flow between neocortical areas, assumed to rely on direct intracortical projections. However, cortical areas may also communicate indirectly via higher-order nuclei in the thalamus, such as the pulvinar or lateral posterior nucleus (LP) in the visual system. The fine-scale organization and function of these cortico-thalamo-cortical pathways remains unclear. We find that responses of mouse LP neurons projecting to higher visual areas likely derive from feedforward input from primary visual cortex (V1) combined with information from many cortical and subcortical areas, including superior colliculus. Signals from LP projections to different higher visual areas are tuned to specific features of visual stimuli and their locomotor context, distinct from the signals carried by direct intracortical projections from V1. Thus, visual transthalamic pathways are functionally specific to their cortical target, different from feedforward cortical pathways and combine information from multiple brain regions, linking sensory signals with behavioral context.

Dynamic pathways of information flow between distributed brain regions underlie the diversity of behaviour. However, it remains unclear how neuronal activity in one area causally influences ongoing population activity in another, and how such interactions change over time. Here we introduce a causal approach to quantify cortical interactions by pairing simultaneous electrophysiological recordings with neural perturbations. We found that the influence visual cortical areas had on each other was surprisingly variable over time. Both feedforward and feedback pathways reliably affected different subpopulations of target neurons at different moments during processing of a visual stimulus, resulting in dynamically rotating communication dimensions between the two cortical areas. The influence of feedback on primary visual cortex (V1) became even more dynamic when visual stimuli were associated with a reward, impacting different subsets of V1 neurons within tens of milliseconds. This, in turn, controlled the geometry of V1 population activity in a behaviourally relevant manner. Thus, distributed neural populations interact through dynamically reorganizing and context- dependent communication channels to evaluate sensory information.

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One of the most important issues in sensor networks is prolonging the network lifetime. In this paper, we demonstrate that given a constant number of nodes, how distribution of nodes affects the lifetime. For this purpose, we first show that in a network with cluster-based routing protocol, nodes do not have equal importance, and their importance depends on their location, and we determine the most critical regions. We prove that the uniform distribution of nodes is not a good distribution. Finally, we propose a solution for the best distribution that concentrates the population of nodes on critical areas. Simulation results of our proposed distribution show a remarkable increase in network lifetime.