Neuroscience Graduate Program at UCSF
Learning and Spatial Coding in the Hippocampal-Cortical Circuit
The ability to use experience to guide behavior (to learn) is one of the most remarkable abilities of the brain. Our goal is to understand how activity and plasticity in neural circuits underlie both learning and the ability to use learned information to make decisions. In particular, our laboratory focuses on the circuitry of the hippocampus and anatomically related regions. We use a combination of techniques, including large scale multielectrode recording, targeted optogenetic interventions and behavioral manipulations of awake, behaving animals to understand how the brain learns and remembers.
Anatomical organization of the hippocampus
The hippocampal formation has a unique anatomical organization in that the connectivity between adjacent hippocampal regions is almost exclusively unidirectional. The majority of neocortical input to the hippocampus comes in through the superficial layers of the entorhinal cortex and connections proceed through the dentate gyrus, to CA3 and on to CA1 (the hippocampus proper), and then to the subiculum. Nearly all neocortically bound outputs from the hippocampus originate in CA1 and the subiculum and target cells in the deep layers of the entorhinal cortex, which projects both to numerous neocortical regions as well as to back to the superficial layers of the entorhinal cortex. Our research uses that organization to compare patterns of activity across regions and to use the similarities and differences among the patterns to identify the transformations that occur in the hippocampal circuit.
An animal model for hippocampal function
Numerous researchers have shown that a human without a hippocampus is unable to form new memories of facts or events. In rodents these same structures play an essential role in animal's abilities to learn about and remember complex associations, including tasks where the animal must learn and remember information about a set of spatial cues in order to navigate through an environment. Event/fact memory in humans and spatial memory in rodents both require learning complex relationships, and that parallel strongly suggests that qualitatively similar processing occurs in the human and the rat hippocampus.
Learning in the hippocampus and cortex
Previous studies have shown that neurons throughout the hippocampal formation show place specific firing patterns, where a given neuron is active only in a subregion of the animal's environment. Most of these studies focused on describing patterns of activity during well learned tasks, and we therefore know little about neural processing during learning. We have developed a spatial alternation task that animals can learn over the course of a few days of exposure. We have shown that rapid learning in this task requires an intact hippocampus, and thus this task provides a powerful paradigm for examining the relationship between dynamic patterns of neural activity and changes in behavior.
Although the hippocampus is essential for spatial learning, storing and retrieving new information requires complex networks spread throughout the brain. One prominent hypothesis states that learning takes place first in the hippocampus and over time information is transferred to neocortical regions in a process known as consolidation. We are therefore recording both in the hippocampus and in downstream areas to understand how hippocampal and cortical circuits could support learning, consolidation and memory guided behavior.
These studies continue to provide important new insights into how the brain changes as animals learn and how memory retrieval might occur, but these insights are fundamentally correlational in nature. We have therefore been developing and apply new techniques, including optogenetic manipulations, to take these correlational hypotheses and turn them into causal understanding. We can now express optically activated channels in specific subpopulations of neurons in the rat hippocampus and activate these channels with an implanted fiber optic. We have also combined this optical activation with large scale multielectrode recording, allowing us to manipulate the circuit and record the results both locally and in more distant brain regions.
For more information, please visit the Frank Laboratory Web Site.
P. Walter German
Margaret Carr, Neuroscience Graduate Program
Kenneth Kay, Bioengineering Graduate Program
Jeanette Wickelgren, Neuroscience Graduate Program
Peer Reviewed Publications
Jadhav SP, Kemere C, German PW, Frank LM (2012) Awake hippocampal sharp-wave ripples support spatial memory. Science. 336(60 87):1454-1458.
Carr, MF, Karlsson, MP & Frank, LM (2012). Transient slow gamma synchrony underlies hippocampal memory replay. Neuron. 75: 700-713.
Kim S, Ganguli S, Frank LM (2012) Spatial information outflow from the hippocampal circuit: distributed spatial coding and phase precession in the subiculum. Journal of Neuroscience. Aug 22;32(34):11539-58.
Dabaghian Y, Mémoli F, Frank L, Carlsson G (2012) A Topological Paradigm for Hippocampal Spatial Map Formation Using Persistent Homology. PLoS Computational Biology 8(8): e1002581. doi:10.1371/journal.pcbi. 1002581
Anikeeva P, Andalman A, Witten I, Warden M, Goshen I, Grosenick L, Gunaydin L, Frank LM, Deisseroth K. (2011). Optetrode: a multichannel readout for optogenetic control. Nature Neuroscience. Dec 4;15(1):163-70.
Li J, Medina J, Frank LM, Lisberger SG (2011) Acquisition of neural learning in cerebellum and cerebral cortex for smooth pursuit eye movements. Journal of Neuroscience. Sep 7;31(36):12716-26.
Singer AC, Karlsson MP, Nathe AR, Carr MF, Frank LM (2010) Experience-dependent development of coordinated hippocampal spatial activity representing the similarity of related locations. Journal of Neuroscience. Sept. 1, 2010, 30(35):11586-11604.
Singer AC, Frank LM (2009) Reward enhances reactivation of recent experience in the hippocampus. Neuron. Dec 24; 64(6): 910-921.
Karlsson MP, Frank LM (2009) Awake replay of remote experiences in the hippocampus. Nature Neuroscience. Jul;12(7):913-8.
Kim SM, Frank LM (2009) Hippocampal lesions impair rapid learning of a continuous spatial alternation task. PLoS ONE 4:e5494.
Karlsson M, Frank LM (2008) A network mechanism for the formation of sparse, informative representations in the hippocampus. Journal of Neuroscience. Dec 24;28(52):14271-81.
Cheng S, Frank LM (2008) New experiences enhance coordinated neural activity in the hippocampus. Neuron. Jan 24;57(2):303-13.
Frank LM, Brown EN, Stanley GB (2006) Hippocampal and cortical place cell plasticity: Implications for episodic memory. Hippocampus. 16(9):775-84.
Frank LM, Stanley GB, Brown EN (2004) Hippocampal plasticity across multiple days of exposure to novel environments. Journal of Neuroscience, Sep 1;24(35):7681-9.
Eden UT, Frank LM, Barbieri R, Solo V, Brown EN (2004) Dynamic analysis of neural coding by point process adaptive filtering. Neural Computation, 16:971-998.
Barbieri R, Frank LM, Nguyen DP, Quirk MC, Solo V, Wilson MA, Brown EN (2004) Dynamic analyses of information encoding in neural ensembles. Neural Computation, 16: 277-307.
Smith AC, Frank LM, Wirth S, Yanike M, Hu D, Kubota Y, Graybiel AM, Suzuki WA, Brown EN (2004) Dynamic analysis of learning in behavioral experiments. Journal of Neuroscience, 24: 447-461.
Wirth S, Yanike M, Frank LM, Smith AC, Brown EN, Suzuki WA (2003) Single neurons in the monkey hippocampus and learning of new associations. Science, 300: 1578-1581.
Nguyen DP, Frank LM, Brown EN (2003) An application of reversible-jump Markov chain Monte Carlo to spike classification of multi-unit extracellular recordings. Network, 14: 61-82.
Frank LM, Eden, UT, Wilson, MA, Brown, EN (2002) Contrasting patterns of receptive field plasticity in the hippocampus and the entorhinal cortex: an adaptive filtering approach. Journal of Neuroscience. May 1, 22(9).
Brown EN, Barbieri R, Ventura V, Kass R, Frank LM (2002) A note on the time-rescaling theorem and its implications for neural data analysis. Neural Computation. 14(2):325-46.
Brown EN, Nguyen DP, Frank LM, Wilson MA, Solo V (2001) An analysis of neural receptive field dynamics by point process adaptive filtering. Proceedings of the National Academy of Sciences, 98(21): 12261-12266.
Frank LM, Brown EN, and Wilson MA (2001) A comparison of the firing properties of putative excitatory and inhibitory neurons from CA1 and the entorhinal cortex. Journal of Neurophysiology, 86(4): 2029-2049.
Barbieri R, Frank LM, Quirk MC, Wilson MA, Brown EN (2001) Diagnostic methods for statistical models of place cell spiking activity. Neurocomputing, 38 (4):1087-1093.
Barbieri, R, Quirk MC, Frank LM , Wilson MA , Brown EN (2001) Construction and analysis of
non-Poisson stimulus response models of neural spike train activity. Journal of Neuroscience Methods, 105: 25-37, 2001.
Frank LM, Brown EN, and Wilson MA (2000) Trajectory encoding in the hippocampus and entorhinal cortex. Neuron, 27: 169-178.
Barbieri R, Frank LM, Quirk MC, Wilson MA, Brown EN (2000) A time-dependent analysis of spatial information encoding in the rat hippocampus. Neurocomputing, 32: 629-635.
Brown EN, Frank LM, Tang D, Quirk MC, Wilson MA (1998) A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells. Journal of Neuroscience, 18: 7411-7425.
Book Chapters, Commentaries and Reviews
Carr MF, Jadav S, Frank LM. (2011) Hippocampal replay in the awake state: a potential physiological substrate of memory consolidation and retrieval. Nature Neuroscience. Jan 26;14:147-153.
Jadhav SP, Frank LM (2009) Reactivating memories for consolidation. Neuron, 62: 745-746.
Frank LM, Brown EN (2003) Persistent activity and memory in the entorhinal cortex. Trends in Neurosciences, 26: 400-401.
Nathe AR, Frank LM (2003) Making space for rats: from synapse to place code. Neuron, 39: 730-731.
Frank LM, Brown, EN, Wilson, MA (2002) Entorhinal place cells: Trajectory encoding. In The Neural Basis of Navigation: Evidence from Single Cell Recording. (P. Sharp Ed.) Kluwer Press. pp. 97-116.