Rhythmic neural activity is a hallmark of brain function, used ubiquitously to structure neural information. In mammalian olfaction, repetitive sniffing sets the principal rhythm but little is known about its role in sensory coding. Here, we show that mitral and tufted cells, the two main classes of olfactory bulb projection neurons, tightly lock to this rhythm, but to opposing phases of the sniff cycle. This phase shift is established by local inhibition that selectively delays mitral cell activity. Furthermore, while tufted cell phase is unperturbed in response to purely excitatory odorants, mitral cell phase is advanced in a graded, stimulus-dependent manner. Thus, phase separation by inhibition forms the basis for two distinct channels of olfactory processing.

Circuits in the brain possess a remarkable ability to orchestrate activities on different timescales, but how distinct circuits interact to sculpt diverse rhythms remains unresolved. The olfactory bulb is a classic example where slow, theta, and fast, gamma, rhythms coexist. Furthermore inhibitory interneurons generally implicated in rhythm generation are segregated into distinct layers, neatly separating local from global motifs. Here, combining intracellular recordings in vivo with circuit-specific optogenetic interference we dissect the contribution of inhibition to rhythmic activity in the mouse olfactory bulb. We found that the two inhibitory circuits control rhythms on distinct timescales: local, glomerular networks coordinate theta activity, regulating baseline and odor-evoked inhibition; granule cells orchestrate gamma synchrony and spike timing. Surprisingly, they did not contribute to baseline rhythms, or sniff-coupled odor-evoked inhibition despite their perceived dominance. Thus, activities on theta and gamma time scales are controlled by separate, dissociable inhibitory networks in the olfactory bulb.

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.