Summary The response of cortical neurons to a sensory stimulus is shaped by the network in which they are embedded. Here we establish a role of parvalbumin (PV)-expressing cells, a large class of inhibitory neurons that target the soma and perisomatic compartments of pyramidal cells, in controlling cortical responses. By bidirectionally manipulating PV cell activity in visual cortex we show that these neurons strongly modulate layer 2/3 pyramidal cell spiking responses to visual stimuli while only modestly affecting their tuning properties. PV cells' impact on pyramidal cells is captured by a linear transformation, both additive and multiplicative, with a threshold. These results indicate that PV cells are ideally suited to modulate cortical gain and establish a causal relationship between a select neuron type and specific computations performed by the cortex during sensory processing.

The relationship between synaptic excitation and inhibition (E/I ratio), two opposing forces in the mammalian cerebral cortex, affects many cortical functions like feature selectivity and gain1,2. Individual pyramidal cells show stable E/I ratios in time despite fluctuating cortical activity levels because when excitation increases, inhibition increases proportionally through the increased recruitment of inhibitory neurons, a phenomenon referred to as excitation-inhibition balance3–9. However, little is known about the distribution of E/I ratios across pyramidal cells. Through their highly divergent axons inhibitory neurons indiscriminately contact most neighboring pyramidal cells10,11. Is inhibition homogeneously distributed or is it individually matched to the different amounts of excitation received by distinct pyramidal cells? Here we discover that pyramidal cells in layer 2/3 of mouse primary visual cortex (V1) each receive inhibition in a similar proportion to their excitation. As a consequence E/I ratios are equalized across pyramidal cells. This matched inhibition is mediated by parvalbumin-expressing (PV) but not somatostatin-expressing (SOM) inhibitory neurons and results from the independent adjustment of synapses originating from the same PV cell but targeting different pyramidal cells. Furthermore, this match is activity-dependent as it is disrupted by perturbing pyramidal cell activity. Thus, the equalization of E/I ratios across pyramidal cells reveals an unexpected degree of order in the spatial distribution of synaptic strengths and indicates that the relationship between cortex’s two opposing forces is stabilized not only in time but also in space.

SUMMARY Neurons recruited for local computations exhibit rhythmic activity at gamma frequencies. The amplitude and frequency of these oscillations are continuously modulated depending on stimulus and behavioral state. This modulation is believed to crucially control information flow across cortical areas. Here we report that in the rat hippocampus gamma oscillation amplitude and frequency vary rapidly, from one cycle to the next. Strikingly, the amplitude of one oscillation predicts the interval to the next. Using in vivo and in vitro whole-cell recordings, we identify the underlying mechanism. We show that cycle-by-cycle fluctuations in amplitude reflect changes in synaptic excitation spanning over an order of magnitude. Despite these rapid variations, synaptic excitation is immediately and proportionally counterbalanced by inhibition. These rapid adjustments in inhibition instantaneously modulate oscillation frequency. So, by rapidly balancing excitation with inhibition, the hippocampal network is able to swiftly modulate gamma oscillations over a wide band of frequencies.

The balance between excitation and inhibition in the cortex is crucial in determining sensory processing. Because the amount of excitation varies, maintaining this balance is a dynamic process; yet the underlying mechanisms are poorly understood. We show here that the activity of even a single layer 2/3 pyramidal cell in the somatosensory cortex of the rat generates widespread inhibition that increases disproportionately with the number of active pyramidal neurons. This supralinear increase of inhibition results from the incremental recruitment of somatostatin-expressing inhibitory interneurons located in layers 2/3 and 5. The recruitment of these interneurons increases tenfold when they are excited by two pyramidal cells. A simple model demonstrates that the distribution of excitatory input amplitudes onto inhibitory neurons influences the sensitivity and dynamic range of the recurrent circuit. These data show that through a highly sensitive recurrent inhibitory circuit, cortical excitability can be modulated by one pyramidal cell.

The design of modern scientific experiments requires the control and monitoring of many different data streams. However, the serial execution of programming instructions in a computer makes it a challenge to develop software that can deal with the asynchronous, parallel nature of scientific data. Here we present Bonsai, a modular, high-performance, open-source visual programming framework for the acquisition and online processing of data streams. We describe Bonsai's core principles and architecture and demonstrate how it allows for the rapid and flexible prototyping of integrated experimental designs in neuroscience. We specifically highlight some applications that require the combination of many different hardware and software components, including video tracking of behavior, electrophysiology and closed-loop control of stimulation.