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Figure 7
(A) Schematic of setup showing mouse on running wheel (lhs) viewing a virtual tunnel (rhs). (B) Trials consist of a 100 cm linear track. One second after the mice ran to the end of the tunnel, an auditory stimulus signaled that a water reward would be delivered two seconds later. 6 s after reward delivery, mice were transported to the start of the virtual tunnel. In a subset of trials, the rendering of the tunnel was paused at a random location, eliciting a visuomotor mismatch signal. Top right shows calcium imaging data for an example ‘mismatch neuron’ during 16 control and 16 mismatch trials. (C) Spiking data for example neuron obtained from exponential fits of the dF/F0 signals. Putative spikes were aligned to start (left), location of the animal on the track (middle), or mismatch onset (right). From top to bottom: raster plot of putative spike times; mean ± SEM of firing rates over trials (n = 105 trials, of which n = 16 mismatch trials); spiking deviation underlying ZETA; instantaneous firing rate. (D–I) Relationship between time-, location-, and mismatch-modulation. One point is one neuron. (D–F) ZETA-scores for example recording 6 (N = 120 neurons). (G–I) Analysis using a kernel-density estimate (KDE) to test whether joint-encoding of two features is more common than expected by chance (see Figure 1). (G) More neurons showed joint-encoding of both spatial and temporal location than expected by chance (p = 1.1 × 10–4). (H) Joint-encoding of temporal location and mismatch was not significantly different from chance (p = 0.932). (I) Location on the virtual track and visuomotor mismatch are less likely to be encoded by the same neuron than expected from chance (p = 2.0 × 10–5). See Figure 7—figure supplement 1 for more details on the KDE procedure.
Neurons in V1 encode either visuomotor mismatch signals or spatial location.