Eyelid conditioning in rabbits is an unusually direct and experimentally tractable window on the function of the cerebellum. Cerebellar patients experience debilitating motor impairments and increasing evidence indicates that in humans the lateral most portions of cerebellum contribute to various cognitive functions. Understanding the internal operations of the cerebellum is therefore both important clinically, and important for the opportunity it provides to apply an experimentally tractable behavior to the analysis of the neural basis of cognition. We propose to continue ongoing efforts that use eyelid conditioning to understand both what the cerebellum computes and how its neurons and synapses accomplish this computation. The proposed studies represent an important shift in focus to high-density in vivo recordings of cerebellar neurons during the acquisition and execution of key behavioral properties of eyelid conditioning. The opportunity to learn these modern and highly stable recording techniques from our colleague Jim Knierim allows us to address fundamental questions that have been largely beyond reach before. Since these techniques permit recording of many neurons for longer periods of time than possible with standard metal electrode techniques, we will be able to record cerebellar neurons during learning and extinction of cerebellar-mediated eyelid responses rather than just during expression of already learned responses. Since these techniques easily permit separation of simple and complex spikes from Purkinje cell recordings, we will analyze climbing fiber inputs to the cerebellum during learning and extinction, which goes to the heart of issues about learning, extinction, timing, and expression of cerebellar mediated responses. We also propose to extend previous work identifying both the presence of learning-dependent plasticity in cerebellar nucleus and a tractable way to study it. This advantage will be used to study this plasticity, induced in vivo by learning, at a level of resolution equivalent to what can be accomplished with bath application experiments in brain slices.
| Halverson, Hunter E; Khilkevich, Andrei; Mauk, Michael D (2018) Cerebellar Processing Common to Delay and Trace Eyelid Conditioning. J Neurosci 38:7221-7236 |
| Khilkevich, Andrei; Zambrano, Juan; Richards, Molly-Marie et al. (2018) Cerebellar implementation of movement sequences through feedback. Elife 7: |
| Khilkevich, Andrei; Canton-Josh, Jose; DeLord, Evan et al. (2018) A cerebellar adaptation to uncertain inputs. Sci Adv 4:eaap9660 |
| Hoffmann, Loren C; Zara, S James; DeLord, Evan D et al. (2018) Medial Auditory Thalamus Is Necessary for Expression of Auditory Trace Eyelid Conditioning. J Neurosci 38:8831-8844 |
| Hausknecht, Matthew; Li, Wen-Ke; Mauk, Michael et al. (2017) Machine Learning Capabilities of a Simulated Cerebellum. IEEE Trans Neural Netw Learn Syst 28:510-522 |
| Khilkevich, Andrei; Halverson, Hunter E; Canton-Josh, Jose Ernesto et al. (2016) Links Between Single-Trial Changes and Learning Rate in Eyelid Conditioning. Cerebellum 15:112-21 |
| Halverson, Hunter E; Hoffmann, Loren C; Kim, Yujin et al. (2016) Systematic variation of acquisition rate in delay eyelid conditioning. Behav Neurosci 130:553-62 |
| Halverson, Hunter E; Khilkevich, Andrei; Mauk, Michael D (2015) Relating cerebellar purkinje cell activity to the timing and amplitude of conditioned eyelid responses. J Neurosci 35:7813-32 |
| Moya, Maria V; Siegel, Jennifer J; McCord, Eedann D et al. (2014) Species-specific differences in the medial prefrontal projections to the pons between rat and rabbit. J Comp Neurol 522:3052-74 |
| Siegel, Jennifer J (2014) Modification of persistent responses in medial prefrontal cortex during learning in trace eyeblink conditioning. J Neurophysiol 112:2123-37 |
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