Aaron Kerlin, PhD
Assistant Professor, Department of Neuroscience
PhD, Neurobiology, Harvard University
BA, Neuroscience, Oberlin College
Dendritic computations critical to learning
As we learn a new skill, how does our brain change to store information about the actions involved? Cortical neurons receive information from the thousands of synaptic inputs onto the dendritic tree. Learning occurs when the efficacy of these inputs change in response to patterns of activity. Within the dendrite, location-dependent learning rules and interactions between inputs sculpt these changes.
The Kerlin Lab uses advanced two-photon microscopy techniques to understand how dendritic compartments and individual synapses within the motor cortex are modified as mice learn to perform new tasks. Recent work has identified a distinct loop between cortex and thalamus that maintains motor plans in the absence of overt action. By tracking and manipulating dendritic activity while monitoring the kinematics of action, we are determining the critical subcellular loci for the learning of new motor plans. Clarifying the biophysical events that drive normal plasticity will help us identify ways to shift cortical plasticity into regimes that favor the improvement of cognitive motor disorders or rehabilitation after damage to motor systems.
Kerlin, AM, Boaz, M, Flickinger, D, MacLennan, BJ, Dean, MB, Davis, C, Spruston, N & Svoboda, K 2019, ‘Functional clustering of dendritic activity during decision-making’ Elife vol. 8, pii: e46966. https://doi.org/10.7554/eLife.46966
Dana, H, Sun, Y, Mohar, B, Hulse, BK, Kerlin, AM, Hasseman, JP, Tsegaye, G, Tsang, A, Wong, A, Patel, R, Macklin, JJ, Chen, Y, Konnerth, A, Jayaraman, V, Looger, LL, Schreiter, ER, Svoboda, K & Kim, DS 2019, ‘High-performance calcium sensors for imaging activity in neuronal populations and microcompartments’ Nat Methods, vol. 16, no. 7, pp. 649-657.
Goldey, GJ, Roumis, DK, Glickfeld, LL, Kerlin, AM, Reid, RC, Bonin, V, Schafer, DP & Andermann, ML 2014, 'Removable cranial windows for long-term imaging in awake mice' Nature Protocols, vol. 9, no. 11, pp. 2515-2538. https://doi.org/10.1038/nprot.2014.165
Liu, R, Milkie, DE, Kerlin, AM, MacLennan, B & Ji, N 2014, 'Direct phase measurement in zonal wavefront reconstruction using multidither coherent optical adaptive technique' Optics Express, vol. 22, no. 2, pp. 1619-1628. https://doi.org/10.1364/OE.22.001619
Wang, C, Liu, R, Milkie, DE, Sun, W, Tan, Z, Kerlin, AM, Chen, TW, Kim, DS & Ji, N 2014, 'Multiplexed aberration measurement for deep tissue imaging in vivo' Nature Methods, vol. 11, no. 10, pp. 1037-1040. https://doi.org/10.1038/nmeth.3068
Andermann, ML, Kerlin, AM, Roumis, DK, Glickfeld, LL & Reid, RC 2011, 'Functional specialization of mouse higher visual cortical areas' Neuron, vol. 72, no. 6, pp. 1025-1039. https://doi.org/10.1016/j.neuron.2011.11.013
Bock, DD, Lee, WCA, Kerlin, AM, Andermann, ML, Hood, G, Wetzel, AW, Yurgenson, S, Soucy, ER, Kim, HS & Reid, RC 2011, 'Network anatomy and in vivo physiology of visual cortical neurons' Nature, vol. 471, no. 7337, pp. 177-184. https://doi.org/10.1038/nature09802
Kerlin, AM, Andermann, ML, Berezovskii, VK & Reid, RC 2010, 'Broadly Tuned Response Properties of Diverse Inhibitory Neuron Subtypes in Mouse Visual Cortex' Neuron, vol. 67, no. 5, pp. 858-871. https://doi.org/10.1016/j.neuron.2010.08.002
Andermann, ML, Kerlin, AM & Reid, RC 2010, 'Chronic cellular imaging of mouse visual cortex during operant behavior and passive viewing' Frontiers in Cellular Neuroscience, vol. 4, no. MAR, 3. https://doi.org/10.3389/fncel.2010.00003
Kerlin, AM & Lindsley, TA 2008, 'NeuroRhythmics: Software for analyzing time-series measurements of saltatory movements in neuronal processes' Journal of Neuroscience Methods, vol. 173, no. 1, pp. 147-152. https://doi.org/10.1016/j.jneumeth.2008.05.006