Various behaviors are often referred to as """"""""hippocampal dependent"""""""" or """"""""cerebellar dependent."""""""" In reality, brain function largely involves interactions between brain systems, although these interactions are difficult to study. The abundance of forebrain projections to cerebellum highlights the central prominence of interactions between forebrain and cerebellum. The practical and conceptual advantages of trace eyelid conditioning represent an opportunity to study forebrain-cerebellum interactions in the context of a well-defined learned behavior. Delay eyelid conditioning engages the cerebellum relatively directly and does not require forebrain structures. In contrast, trace eyelid conditioning is disrupted by lesions of the cerebellum, hippocampus and medial prefrontal cortex (mPFC). A prominent theory asserts that cerebellum cannot learn with trace inputs, that forebrain structures activate cerebellar inputs during the silent trace-interval, and that these inputs engage normal cerebellar learning mechanisms to acquire appropriate trace responses. The key test of this theory - to record from the mossy fiber inputs to cerebellum activated by hippocampus and ? mPFC - has not been possible because these mossy fibers had not been identified. The proposed studies extend preliminary findings that have 1) confirmed with mossy fiber stimulation that cerebellum cannot learn with trace inputs, and 2) identified the mossy fibers essential for trace conditioning. The experiments will be completed as a prelude to recording in vivo from the mossy fibers essential for trace conditioning and from the mossy fibers activated directly by the tone conditioned stimulus. The auditory responses of these cells and the learning-dependent activity that develops with trace conditioning will be characterized. Reversible inactivation of hippocampus or mPFC can then be used to identify essential sources of input that drive the learning-dependent responses. Finally, using stimulation of mossy fibers, the sufficiency of these learning dependent responses to support cerebellar learning of appropriate trace responses will be tested. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
7R01MH074006-03
Application #
7176845
Study Section
Special Emphasis Panel (ZRG1-IFCN-C (02))
Program Officer
Osborn, Bettina D
Project Start
2005-04-15
Project End
2010-01-31
Budget Start
2007-02-01
Budget End
2008-01-31
Support Year
3
Fiscal Year
2007
Total Cost
$280,813
Indirect Cost
Name
University of Texas Austin
Department
Type
Organized Research Units
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
Halverson, Hunter E; Khilkevich, Andrei; Mauk, Michael D (2018) Cerebellar Processing Common to Delay and Trace Eyelid Conditioning. J Neurosci 38:7221-7236
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
Siegel, Jennifer J (2014) Modification of persistent responses in medial prefrontal cortex during learning in trace eyeblink conditioning. J Neurophysiol 112:2123-37
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
Li, Wen-Ke; Hausknecht, Matthew J; Stone, Peter et al. (2013) Using a million cell simulation of the cerebellum: network scaling and task generality. Neural Netw 47:95-102
Siegel, Jennifer J; Mauk, Michael D (2013) Persistent activity in prefrontal cortex during trace eyelid conditioning: dissociating responses that reflect cerebellar output from those that do not. J Neurosci 33:15272-84

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