Corticofugal projections to evolutionarily ancient, sub-cortical structures are ubiquitous across mammalian sensory systems. These “descending” pathways enable the neocortex to control ascending sensory representations in a predictive or feedback manner, but the underlying cellular mechanisms are poorly understood. Here we combine optogenetic approaches with in vivo and in vitro patch-clamp electrophysiology to study the projection from mouse auditory cortex to the inferior colliculus (IC), a major descending auditory pathway that controls IC neuron feature selectivity, plasticity and auditory perceptual learning. Although individual auditory cortico-collicular synapses were generally weak, IC neurons often integrated inputs from multiple corticofugal axons that generated reliable, tonic depolarizations even during prolonged presynaptic activity. Latency measurements in vivo showed that descending signals reach the IC within 30 ms of sound onset, which in IC neurons corresponded to the peak of synaptic depolarizations evoked by short sounds. Activating ascending and descending pathways at latencies expected in vivo caused a NMDA receptor dependent, supra-linear EPSP summation, indicating that descending signals can non linearly amplify IC neurons’ moment-to-moment acoustic responses. Our results shed light upon the synaptic bases of descending sensory control, and imply that heterosynaptic cooperativity contributes to the auditory cortico-collicular pathway’s role in plasticity and perceptual learning.

This excel file contains the raw data values used to generate the figures in the paper. The data are from electrophysiological experiments of inferior colliculus neurons, recorded using whole-cell patch-clamp in brain slices and in anesthetized mice (most figures) or extracellular recordings in awake mice (Figure 7 - Supplement 1B, Figure 7 - Supplement 2). Data processing is described in the Methods section of the paper; values are rounded to 2-4 decimal points for consistency.

For all tabs, datapoints across rows represent matched observations from the same neuron.

Figure 4C,D ; Figure 4 - Supplement 1 ; Figure 5G ; Figure 8B: Datapoints from the same neurons are matched across rows and columns.

For Figure 7 - Supplement 2: LFP and multi-unit data values corresponding to the same recording session are denoted by the recording # column. Multi-unit data for recording # 3 and # 10 were not analyzed owing to low signal-to-noise ratio of the multi-unit clusters after high-pass filtering (see Methods).