The brain transforms physical sensory stimuli into meaningful perceptions. In animals making choices about sensory stimuli, neuronal activity in successive cortical stages reflects a progression from sensation to decision. Feedforward and feedback pathways connecting cortical areas are critical for this transformation. However, the computational roles of these pathways are poorly understood because pathway-specific activity has rarely been monitored during a perceptual task. Using cellular-resolution, pathway-specific imaging, we measured neuronal activity across primary (S1) and secondary (S2) somatosensory cortices of mice performing a tactile detection task. S1 encoded the stimulus better than S2, while S2 activity more strongly reflected perceptual choice. S1 neurons projecting to S2 fed forward activity that predicted choice. Activity encoding touch and choice propagated in an S1–S2 loop along feedforward and feedback axons. Our results suggest that sensory inputs converge into a perceptual outcome as feedforward computations are reinforced in a feedback loop.

Cortical synaptic strengths vary substantially from synapse to synapse and exhibit a skewed distribution with a small fraction of synapses generating extremely large depolarizations. Using multiple whole-cell recordings from rat hippocampal CA3 pyramidal cells, we found that the amplitude of unitary excitatory postsynaptic conductances approximates a lognormal distribution and that in the presence of synaptic background noise, the strongest fraction of synapses could trigger action potentials in postsynaptic neurons even with single presynaptic action potentials, a phenomenon termed interpyramid spike transmission (IpST). The IpST probability reached 80%, depending on the network state. To examine how IpST impacts network dynamics, we simulated a recurrent neural network embedded with a few potent synapses. This network, unlike many classical neural networks, exhibited distinctive behaviors resembling cortical network activity in vivo. These behaviors included the following: 1) infrequent ongoing activity, 2) firing rates of individual neurons approximating a lognormal distribution, 3) asynchronous spikes among neurons, 4) net balance between excitation and inhibition, 5) network activity patterns that was robust against external perturbation, 6) responsiveness even to a single spike of a single excitatory neuron, and 7) precise firing sequences. Thus, IpST captures a surprising number of recent experimental findings in vivo. We propose that an unequally biased distribution with a few select strong synapses helps stabilize sparse neuronal activity, thereby reducing the total spiking cost, enhancing the circuit responsiveness, and ensuring reliable information transfer.

SUMMARYSensory perception depends on interactions among cortical areas. These interactions are mediated by canonical patterns of connectivity in which higher areas send feedback projections to lower areas via neurons in superficial and deep layers. Here, we probed the circuit basis of interactions among two areas critical for touch perception in mice, whisker primary (wS1) and secondary (wS2) somatosensory cortices. Neurons in layer 4 of wS2 (S2L4) formed a major feedback pathway to wS1. Feedback from wS2 to wS1 was organized somatotopically. Spikes evoked by whisker deflections occurred nearly as rapidly in wS2 as in wS1, including among putative S2L4 → S1 feedback neurons. Axons from S2L4 → S1 neurons sent stimulus orientation-specific activity to wS1. Optogenetic excitation of S2L4 neurons modulated activity across both wS2 and wS1, while inhibition of S2L4 reduced orientation tuning among wS1 neurons. Thus, a non-canonical feedback circuit, originating in layer 4 of S2, rapidly modulates early tactile processing.