During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brain’s ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the "paradoxical effect" predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit.

Although we know much about the capacity of neurons to integrate synaptic inputs in vitro, less is known about synaptic integration in vivo. Here we address this issue by investigating the integration of inputs from the two eyes in mouse primary visual cortex. We find that binocular inputs to layer 2/3 pyramidal neurons are integrated sublinearly in an amplitude-dependent manner. Sublinear integration was greatest when binocular responses were largest, as occurs at the preferred orientation and binocular disparity, and highest contrast. Using voltage-clamp experiments and modeling, we show that sublinear integration occurs postsynaptically. The extent of sublinear integration cannot be accounted for solely by nonlinear integration of excitatory inputs, even when they are activated closely in space and time, but requires balanced recruitment of inhibition. Finally, we show that sublinear binocular integration acts as a divisive form of gain control, linearizing the output of binocular neurons and enhancing orientation selectivity.

Neurons receive thousands of synaptic inputs that are distributed in space and time. The systematic study of how neurons process these inputs requires a technique to stimulate multiple yet highly targeted points of interest along the neuron's dendritic tree. Three-dimensional multi-focal patterns produced via holographic projection combined with two-photon photolysis of caged compounds can provide for highly localized release of neurotransmitters within each diffraction-limited focus, and in this way emulate simultaneous synaptic inputs to the neuron. However, this technique so far cannot achieve time-dependent stimulation patterns due to fundamental limitations of the hologram-encoding device and other factors that affect the consistency of controlled synaptic stimulation. Here, we report an advanced technique that enables the design and application of arbitrary spatio-temporal photostimulation patterns that resemble physiological synaptic inputs. By combining holographic projection with a programmable high-speed light-switching array, we have overcome temporal limitations with holographic projection, allowing us to mimic distributed activation of synaptic inputs leading to action potential generation. Our experiments uniquely demonstrate multi-site two-photon glutamate uncaging in three dimensions with submillisecond temporal resolution. Implementing this approach opens up new prospects for studying neuronal synaptic integration in four dimensions.