From the perspective of neural coding, the considerable trial-totrial variability in the responses of neurons to sensory stimuli is puzzling. Trial-to-trial response variability is typically interpreted in terms of "noise" (i.e., it represents either intrinsic noise of the system or information unrelated to the stimuli). However, trial-totrial response variability can be considerably different across stimuli, suggesting that it could also provide an important contribution to the information conveyed by the neural responses about the stimuli. To test this hypothesis, we addressed the problem of discriminating stimulus location from the spike-count responses of neurons recorded in the ventro-postero-medial (VPM) nucleus of the thalamus in anesthetized rats. Using a recently developed information theory approach, we verified that differences between stimuli in the trial-to-trial spike-count variability of the responses provided an important contribution to the overall information carried by the neurons. In addition, we found that the relatively reliable (sub-Poisson) firing regime of our VPM neurons was not only more informative, but also more redundant between neurons compared with a more variable (Poisson) firing regime with the same total number of spikes. The typical increase in trial-to-trial response variability from the periphery to the cortex could therefore serve as a strategy to reduce redundancy between neurons and promote efficient sparse coding distributed in large populations of neurons. Overall, our data suggest that the trial-to-trial response variability plays a critical role in establishing the tradeoff between total information and redundancy between neurons in population codes.A major challenge for system neuroscience is to understand the basic elements of the neural code. Because single neurons typically respond to different stimuli with different average firing rates, possibly the simplest hypothesis is that neurons use a ratecoding scheme to represent sensory information (1, 2). However, average firing rates do not necessarily represent a complete description of the neural responses, partly because neurons can respond with a high degree of variability to different repetitions of the same stimulus (3). Trial-to-trial variability in the neural responses can be due to synaptic noise (4, 5) or can represent information that is not directly related to the stimulus, e.g., information about the state of the system (6-8). However, the relation between trial-to-trial variability in the responses of neurons and the information conveyed by those neurons remains unclear (9).The rate-coding hypothesis was originally formulated on the basis of classic works in peripheral nerves (10,11). Indeed, at the first stages of sensory processing, the trial-to-trial variability can be so low that neural responses can be almost deterministic (12-14), i.e., neurons respond with virtually the same number of spikes to different repetitions of the same stimulus. In the ideal deterministic regime, single-trial responses ar...