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What do dendritic nonlinearities tell a neuron about signals injected into the dendrite? Linear and nonlinear dendritic components affect how time-varying inputs are transformed into action potentials (APs), but the relative contribution of each component is unclear. We developed a novel systems-identification approach to isolate the nonlinear response of layer 5 pyramidal neuron dendrites in mouse prefrontal cortex in response to dendritic current injections. We then quantified the nonlinear component and its effect on the soma, using functional models composed of linear filters and static nonlinearities. Both noise and waveform current injections revealed linear and nonlinear components in the dendritic response. The nonlinear component consisted of fast Na+spikes that varied in amplitude 10-fold in a single neuron. A functional model reproduced the timing and amplitude of the dendritic spikes and revealed that they were selective to a preferred input dynamic (~4.5 ms rise time). The selectivity of the dendritic spikes became wider in the presence of additive noise, which was also predicted by the functional model. A second functional model revealed that the dendritic spikes were weakly boosted before being linearly integrated at the soma. For both our noise and waveform dendritic input, somatic APs were dependent on the somatic integration of the stimulus, followed a subset of large dendritic spikes, and were selective to the same input dynamics preferred by the dendrites. Our results suggest that the amplitude of fast dendritic spikes conveys information about high-frequency features in the dendritic input, which is then combined with low-frequency somatic integration.NEW & NOTEWORTHY The nonlinear response of layer 5 mouse pyramidal dendrites was isolated with a novel systems-based approach. In response to dendritic current injections, the nonlinear component contained mostly fast, variable-amplitude, Na+spikes. A functional model accounted for the timing and amplitude of the dendritic spikes and revealed that dendritic spikes are selective to a preferred input dynamic, which was verified experimentally. Thus, fast dendritic nonlinearities behave as high-frequency feature detectors that influence somatic action potentials.

We have addressed the source and nature of the persistent neural activity that bridges the stimulus-free gap between the conditioned stimulus (CS) and unconditioned stimulus (US) during trace eyelid conditioning. Previous work has demonstrated that this persistent activity is necessary for trace eyelid conditioning: CS-elicited activity in mossy fiber inputs to the cerebellum does not extend into the stimulus-free trace interval, which precludes the cerebellar learning that mediates conditioned response expression. In behaving rabbits we used in vivo recordings from a region of medial prefrontal cortex (mPFC) that is necessary for trace eyelid conditioning to test the hypothesis that neurons there generate activity that persists beyond CS offset. These recordings revealed two patterns of activity during the trace interval that would enable cerebellar learning. Activity in some cells began during the tone CS and persisted to overlap with the US, whereas in other cells, activity began during the stimulus-free trace interval. Injection of anterograde tracers into this same region of mPFC revealed dense labeling in the pontine nuclei, where recordings also revealed tone-evoked persistent activity during trace conditioning. These data suggest a corticopontine pathway that provides an input to the cerebellum during trace conditioning trials that bridges the temporal gap between the CS and US to engage cerebellar learning. As such, trace eyelid conditioning represents a well-characterized and experimentally tractable system that can facilitate mechanistic analyses of cortical persistent activity and how it is used by downstream brain structures to influence behavior.

We used micro-infusions during eyelid conditioning in rabbits to investigate the relative contributions of cerebellar cortex and the underlying deep nuclei (DCN) to the expression of cerebellar learning. These tests were conducted using two forms of cerebellum-dependent eyelid conditioning for which the relative roles of cerebellar cortex and DCN are controversial: delay conditioning, which is largely unaffected by forebrain lesions, and trace conditioning, which involves interactions between forebrain and cerebellum. For rabbits trained with delay conditioning, silencing cerebellar cortex by micro-infusions of the local anesthetic lidocaine unmasked stereotyped short-latency responses. This was also the case after extinction as observed previously with reversible blockade of cerebellar cortex output. Conversely, increasing cerebellar cortex activity by micro-infusions of the GABAA antagonist picrotoxin reversibly abolished conditioned responses. Effective cannula placements were clustered around the primary fissure and deeper in lobules hemispheric lobule IV (HIV) and hemispheric lobule V (HV) of anterior lobe. In well-trained trace conditioned rabbits, silencing this same area of cerebellar cortex or reversibly blocking cerebellar cortex output also unmasked short-latency responses. Because Purkinje cells are the sole output of cerebellar cortex, these results provide evidence that the expression of well-timed conditioned responses requires a well-timed decrease in the activity of Purkinje cells in anterior lobe. The parallels between results from delay and trace conditioning suggest similar contributions of plasticity in cerebellar cortex and DCN in both instances.

Trace eyelid conditioning is a form of associative learning that requires several forebrain structures and cerebellum. Previous work suggests that at least two conditioned stimulus (CS)-driven signals are available to the cerebellum via mossy fiber inputs during trace conditioning: one driven by and terminating with the tone and a second driven by medial prefrontal cortex (mPFC) that persists through the stimulus-free trace interval to overlap in time with the unconditioned stimulus (US). We used electric stimulation of mossy fibers to determine whether this pattern of dual inputs is necessary and sufficient for cerebellar learning to express normal trace eyelid responses. We find that presenting the cerebellum with one input that mimics persistent activity observed in mPFC and the lateral pontine nuclei during trace eyelid conditioning and another that mimics tone-elicited mossy fiber activity is sufficient to produce responses whose properties quantitatively match trace eyelid responses using a tone. Probe trials with each input delivered separately provide evidence that the cerebellum learns to respond to the mPFC-like input (that overlaps with the US) and learns to suppress responding to the tone-like input (that does not). This contributes to precisely timed responses and the well-documented influence of tone offset on the timing of trace responses. Computer simulations suggest that the underlying cerebellar mechanisms involve activation of different subsets of granule cells during the tone and during the stimulus-free trace interval. These results indicate that tone-driven and mPFC-like inputs are necessary and sufficient for the cerebellum to learn well-timed trace conditioned responses.