Honors & Awards
Vallee Scholar Award, The Vallee Foundation (2019)
Young Investigator Award, Society for Neuroscience (2018)
Office of Naval Research Young Investigator Award, Office of Naval Research (2018)
James S McDonnell Foundation Scholar, James S McDonnell Foundation Scholar (2016 - 2022)
Robertson Neuroscience Investigator – New York Stem Cell Foundation, New York Stem Cell Foundation (2015-2019)
Klingenstein-Simons Fellowship Award in the Neurosciences, Klingenstein-Simons Foundation (2014-2017)
Sloan Fellow, Alfred P. Sloan Foundation (2013-2015)
Peter and Patricia Gruber International Research Award, The Gruber Foundation (2012)
BA, Baylor University, Psychology (2002)
PhD, Boston University, Neuroscience (2008)
Current Research and Scholarly Interests
My laboratory studies the cellular and molecular mechanisms underlying the organization of cortical circuits important for spatial navigation and memory. We are particularly focused on medial entorhinal cortex, where many neurons fire in spatially specific patterns and thus offer a measurable output for molecular manipulations. We combine electrophysiology, genetic approaches and behavioral paradigms to unravel the mechanisms and behavioral relevance of non-sensory cortical organization. Our first line of research is focused on determining the cellular and molecular components crucial to the neural representation of external space by functionally defined cell types in entorhinal cortex (grid, border and head direction cells). We plan to use specific targeting of ion channels, combined with in vivo tetrode recordings, to determine how channel dynamics influence the neural representation of space in the behaving animal. A second, parallel line of research, utilizes a combination of in vivo and in vitro methods to further parse out ionic expression patterns in entorhinal cortices and determine how gradients in ion channels develop. Ultimately, our work aims to understand the ontogenesis and relevance of medial entorhinal cortical topography in spatial memory and navigation.
- Mathematical Tools for Neuroscience
NBIO 228 (Spr)
- Neuroscience Systems Core
NEPR 203 (Spr)
- The Nervous System
NBIO 206 (Win)
Independent Studies (9)
- Directed Reading in Neurobiology
NBIO 198 (Spr)
- Directed Reading in Neurobiology
NBIO 299 (Spr)
- Directed Reading in Neurosciences
NEPR 299 (Aut, Win, Spr, Sum)
- Directed Study
BIOE 391 (Win)
- Graduate Research
NBIO 399 (Spr)
- Graduate Research
NEPR 399 (Aut, Win, Spr, Sum)
- Medical Scholars Research
NBIO 370 (Spr)
- Out-of-Department Undergraduate Research
BIO 199X (Aut, Win)
- Undergraduate Research
NBIO 199 (Aut, Win, Spr)
- Directed Reading in Neurobiology
- Prior Year Courses
Doctoral Dissertation Reader (AC)
Deniz Bingul, Luke Brezovec, Lucas Encarnacion-Rivera, Sedona Ewbank, Gabriel Mel, Josh Melander, Ethan Richman, Daniel Shaykevich, Nate Stockham, Yandan Wang, Ilana Zucker-Scharff
Postdoctoral Faculty Sponsor
Emily Aery Jones, Frances Cho, Can Dong, Samuel Levy, Mari Sosa
Doctoral Dissertation Advisor (AC)
Tucker Fisher, Charlotte Herber, Lavonna Mark, Francis Masuda, Linnie Warton, John Wen
Graduate and Fellowship Programs
Neural circuit dynamics of drug-context associative learning in the mouse hippocampus.
2022; 13 (1): 6721
The environmental context associated with previous drug consumption is a potent trigger for drug relapse. However, the mechanism by which neural representations of context are modified to incorporate information associated with drugs of abuse remains unknown. Using longitudinal calcium imaging in freely behaving mice, we find that unlike the associative learning of natural reward, drug-context associations for psychostimulants and opioids are encoded in a specific subset of hippocampal neurons. After drug conditioning, these neurons weakened their spatial coding for the non-drug paired context, resulting in an orthogonal representation for the drug versus non-drug context that was predictive of drug-seeking behavior. Furthermore, these neurons were selected based on drug-spatial experience and were exclusively tuned to animals' allocentric position. Together, this work reveals how drugs of abuse alter the hippocampal circuit to encode drug-context associations and points to the possibility of targeting drug-associated memory in the hippocampus.
View details for DOI 10.1038/s41467-022-34114-x
View details for PubMedID 36344498
Experience-dependent contextual codes in the hippocampus.
The hippocampus contains neural representations capable of supporting declarative memory. Hippocampal place cells are one such representation, firing in one or few locations in a given environment. Between environments, place cell firing fields remap (turning on/off or moving to a new location) to provide a population-wide code for distinct contexts. However, the manner by which contextual features combine to drive hippocampal remapping remains a matter of debate. Using large-scale in vivo two-photon intracellular calcium recordings in mice during virtual navigation, we show that remapping in the hippocampal region CA1 is driven by prior experience regarding the frequency of certain contexts and that remapping approximates an optimal estimate of the identity of the current context. A simple associative-learning mechanism reproduces these results. Together, our findings demonstrate that place cell remapping allows an animal to simultaneously identify its physical location and optimally estimate the identity of the environment.
View details for DOI 10.1038/s41593-021-00816-6
View details for PubMedID 33753945
Mouse entorhinal cortex encodes a diverse repertoire of self-motion signals.
2021; 12 (1): 671
Neural circuits generate representations of the external world from multiple information streams. The navigation system provides an exceptional lens through which we may gain insights about how such computations are implemented. Neural circuits in the medial temporal lobe construct a map-like representation of space that supports navigation. This computation integrates multiple sensory cues, and, in addition, is thought to require cues related to the individual's movement through the environment. Here, we identify multiple self-motion signals, related to the position and velocity of the head and eyes, encoded by neurons in a key node of the navigation circuitry of mice, the medial entorhinal cortex (MEC). The representation of these signals is highly integrated with other cues in individual neurons. Such information could be used to compute the allocentric location of landmarks from visual cues and to generate internal representations of space.
View details for DOI 10.1038/s41467-021-20936-8
View details for PubMedID 33510164
Dynamic and reversible remapping of network representations in an unchanging environment.
Neurons in the medial entorhinal cortex alter their firing properties in response to environmental changes. This flexibility in neural coding is hypothesized to support navigation and memory by dividing sensory experience into unique episodes. However, it is unknown how the entorhinal circuit as a whole transitions between different representations when sensory information is not delineated into discrete contexts. Here we describe rapid and reversible transitions between multiple spatial maps of an unchanging task and environment. These remapping events were synchronized across hundreds of neurons, differentially affected navigational cell types, and correlated with changes in running speed. Despite widespread changes in spatial coding, remapping comprised a translation along a single dimension in population-level activity space, enabling simple decoding strategies. These findings provoke reconsideration of how the medial entorhinal cortex dynamically represents space and suggest a remarkable capacity of cortical circuits to rapidly and substantially reorganize their neural representations.
View details for DOI 10.1016/j.neuron.2021.07.005
View details for PubMedID 34363753
Distance-tuned neurons drive specialized path integration calculations in medial entorhinal cortex.
2021; 36 (10): 109669
During navigation, animals estimate their position using path integration and landmarks, engaging many brain areas. Whether these areas follow specialized or universal cue integration principles remains incompletely understood. We combine electrophysiology with virtual reality to quantify cue integration across thousands of neurons in three navigation-relevant areas: primary visual cortex (V1), retrosplenial cortex (RSC), and medial entorhinal cortex (MEC). Compared with V1 and RSC, path integration influences position estimates more in MEC, and conflicts between path integration and landmarks trigger remapping more readily. Whereas MEC codes position prospectively, V1 codes position retrospectively, and RSC is intermediate between the two. Lowered visual contrast increases the influence of path integration on position estimates only in MEC. These properties are most pronounced in a population of MEC neurons, overlapping with grid cells, tuned to distance run in darkness. These results demonstrate the specialized role that path integration plays in MEC compared with other navigation-relevant cortical areas.
View details for DOI 10.1016/j.celrep.2021.109669
View details for PubMedID 34496249
Entorhinal velocity signals reflect environmental geometry.
The entorhinal cortex contains neurons that represent self-location, including grid cells that fire in periodic locations and velocity signals that encode running speed and head direction. Although the size and shape of the environment influence grid patterns, whether entorhinal velocity signals are equally influenced or provide a universal metric for self-motion across environments remains unknown. Here we report that speed cells rescale after changes to the size and shape of the environment. Moreover, head direction cells reorganize in an experience-dependent manner to align with the axis of environmental change. A knockout mouse model allows dissociation of the coordination between cell types, with grid and speed cells, but not head direction cells, responding in concert to environmental change. These results point to malleability in the coding features of multiple entorhinal cell types and have implications for which cell types contribute to the velocity signal used by computational models of grid cells.
View details for DOI 10.1038/s41593-019-0562-5
View details for PubMedID 31932764
Remembered reward locations restructure entorhinal spatial maps.
Science (New York, N.Y.)
2019; 363 (6434): 1447–52
Ethologically relevant navigational strategies often incorporate remembered reward locations. Although neurons in the medial entorhinal cortex provide a maplike representation of the external spatial world, whether this map integrates information regarding learned reward locations remains unknown. We compared entorhinal coding in rats during a free-foraging task and a spatial memory task. Entorhinal spatial maps restructured to incorporate a learned reward location, which in turn improved positional decoding near this location. This finding indicates that different navigational strategies drive the emergence of discrete entorhinal maps of space and points to a role for entorhinal codes in a diverse range of navigational behaviors.
View details for PubMedID 30923222
Principles governing the integration of landmark and self-motion cues in entorhinal cortical codes for navigation.
To guide navigation, the nervous system integrates multisensory self-motion and landmark information. We dissected how these inputs generate spatial representations by recording entorhinal grid, border and speed cells in mice navigating virtual environments. Manipulating the gain between the animal's locomotion and the visual scene revealed that border cells responded to landmark cues while grid and speed cells responded to combinations of locomotion, optic flow and landmark cues in a context-dependent manner, with optic flow becoming more influential when it was faster than expected. A network model explained these results by revealing a phase transition between two regimes in which grid cells remain coherent with or break away from the landmark reference frame. Moreover, during path-integration-based navigation, mice estimated their position following principles predicted by our recordings. Together, these results provide a theoretical framework for understanding how landmark and self-motion cues combine during navigation to generate spatial representations and guide behavior.
View details for PubMedID 30038279
Grid scale drives the scale and long-term stability of place maps
2018; 21 (2): 270-+
Medial entorhinal cortex (MEC) grid cells fire at regular spatial intervals and project to the hippocampus, where place cells are active in spatially restricted locations. One feature of the grid population is the increase in grid spatial scale along the dorsal-ventral MEC axis. However, the difficulty in perturbing grid scale without impacting the properties of other functionally defined MEC cell types has obscured how grid scale influences hippocampal coding and spatial memory. Here we use a targeted viral approach to knock out HCN1 channels selectively in MEC, causing the grid scale to expand while leaving other MEC spatial and velocity signals intact. Grid scale expansion resulted in place scale expansion in fields located far from environmental boundaries, reduced long-term place field stability and impaired spatial learning. These observations, combined with simulations of a grid-to-place cell model and position decoding of place cells, illuminate how grid scale impacts place coding and spatial memory.
View details for PubMedID 29335607
View details for PubMedCentralID PMC5823610
A Multiplexed, Heterogeneous, and Adaptive Code for Navigation in Medial Entorhinal Cortex
2017; 94 (2): 375-?
Medial entorhinal grid cells display strikingly symmetric spatial firing patterns. The clarity of these patterns motivated the use of specific activity pattern shapes to classify entorhinal cell types. While this approach successfully revealed cells that encode boundaries, head direction, and running speed, it left a majority of cells unclassified, and its pre-defined nature may have missed unconventional, yet important coding properties. Here, we apply an unbiased statistical approach to search for cells that encode navigationally relevant variables. This approach successfully classifies the majority of entorhinal cells and reveals unsuspected entorhinal coding principles. First, we find a high degree of mixed selectivity and heterogeneity in superficial entorhinal neurons. Second, we discover a dynamic and remarkably adaptive code for space that enables entorhinal cells to rapidly encode navigational information accurately at high running speeds. Combined, these observations advance our current understanding of the mechanistic origins and functional implications of the entorhinal code for navigation. VIDEO ABSTRACT.
View details for DOI 10.1016/j.neuron.2017.03.025
View details for Web of Science ID 000399451400020
View details for PubMedID 28392071
Environmental Boundaries as an Error Correction Mechanism for Grid Cells
2015; 86 (3): 827-839
Medial entorhinal grid cells fire in periodic, hexagonally patterned locations and are proposed to support path-integration-based navigation. The recursive nature of path integration results in accumulating error and, without a corrective mechanism, a breakdown in the calculation of location. The observed long-term stability of grid patterns necessitates that the system either performs highly precise internal path integration or implements an external landmark-based error correction mechanism. To distinguish these possibilities, we examined grid cells in behaving rodents as they made long trajectories across an open arena. We found that error accumulates relative to time and distance traveled since the animal last encountered a boundary. This error reflects coherent drift in the grid pattern. Further, interactions with boundaries yield direction-dependent error correction, suggesting that border cells serve as a neural substrate for error correction. These observations, combined with simulations of an attractor network grid cell model, demonstrate that landmarks are crucial to grid stability.
View details for DOI 10.1016/j.neuron.2015.03.039
View details for Web of Science ID 000354069800021
View details for PubMedID 25892299
Remapping in a recurrent neural network model of navigation and context inference.
Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ('remap') in response to changing contextual factors such as environmental cues, task conditions, and behavioral states, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.
View details for DOI 10.7554/eLife.86943
View details for PubMedID 37410093
A positively tuned voltage indicator for extended electrical recordings in the brain.
2023; 20 (7): 1104-1113
Genetically encoded voltage indicators (GEVIs) enable optical recording of electrical signals in the brain, providing subthreshold sensitivity and temporal resolution not possible with calcium indicators. However, one- and two-photon voltage imaging over prolonged periods with the same GEVI has not yet been demonstrated. Here, we report engineering of ASAP family GEVIs to enhance photostability by inversion of the fluorescence-voltage relationship. Two of the resulting GEVIs, ASAP4b and ASAP4e, respond to 100-mV depolarizations with ≥180% fluorescence increases, compared with the 50% fluorescence decrease of the parental ASAP3. With standard microscopy equipment, ASAP4e enables single-trial detection of spikes in mice over the course of minutes. Unlike GEVIs previously used for one-photon voltage recordings, ASAP4b and ASAP4e also perform well under two-photon illumination. By imaging voltage and calcium simultaneously, we show that ASAP4b and ASAP4e can identify place cells and detect voltage spikes with better temporal resolution than commonly used calcium indicators. Thus, ASAP4b and ASAP4e extend the capabilities of voltage imaging to standard one- and two-photon microscopes while improving the duration of voltage recordings.
View details for DOI 10.1038/s41592-023-01913-z
View details for PubMedID 37429962
All-optical physiology resolves a synaptic basis for behavioral timescale plasticity.
Learning has been associated with modifications of synaptic and circuit properties, but the precise changes storing information in mammals have remained largely unclear. We combined genetically targeted voltage imaging with targeted optogenetic activation and silencing of pre- and post-synaptic neurons to study the mechanisms underlying hippocampal behavioral timescale plasticity. In mice navigating a virtual-reality environment, targeted optogenetic activation of individual CA1 cells at specific places induced stable representations of these places in the targeted cells. Optical elicitation, recording, and modulation of synaptic transmission in behaving mice revealed that activity in presynaptic CA2/3 cells was required for the induction of plasticity in CA1 and, furthermore, that during induction of these place fields in single CA1 cells, synaptic input from CA2/3 onto these same cells was potentiated. These results reveal synaptic implementation of hippocampal behavioral timescale plasticity and define a methodology to resolve synaptic plasticity during learning and memory in behaving mammals.
View details for DOI 10.1016/j.cell.2022.12.035
View details for PubMedID 36669484
Neural ensembles in navigation: From single cells to population codes.
Current opinion in neurobiology
2022; 78: 102665
The brain can represent behaviorally relevant information through the firing of individual neurons as well as the coordinated firing of ensembles of neurons. Neurons in the hippocampus and associated cortical regions participate in a variety of types of ensembles to support navigation. These ensemble types include single cell codes, population codes, time-compressed sequences, behavioral sequences, and engrams. We present the physiological basis and behavioral relevance of ensemble firing. We discuss how these traditional definitions of ensembles can constrain or expand potential analyses due to the underlying assumptions and abstractions made. We highlight how coding can change at the ensemble level while underlying single cell codes remain intact. Finally, we present how ensemble definitions could be broadened to better understand the full complexity of the brain.
View details for DOI 10.1016/j.conb.2022.102665
View details for PubMedID 36542882
A unified theory for the computational and mechanistic origins of grid cells.
The discovery of entorhinal grid cells has generated considerable interest in how and why hexagonal firing fields might emerge in a generic manner from neural circuits, and what their computational significance might be. Here, we forge a link between the problem of path integration and the existence of hexagonal grids, by demonstrating that such grids arise in neural networks trained to path integrate under simple biologically plausible constraints. Moreover, we develop a unifying theory for why hexagonal grids are ubiquitous in path-integrator circuits. Such trained networks also yield powerful mechanistic hypotheses, exhibiting realistic levels of biological variability not captured by hand-designed models. We furthermore develop methods to analyze the connectome and activity maps of our networks to elucidate fundamental mechanisms underlying path integration. These methods provide a road map to go from connectomic and physiological measurements to conceptual understanding in a manner that could generalize to other settings.
View details for DOI 10.1016/j.neuron.2022.10.003
View details for PubMedID 36306779
- From Rats to Humans: how novel behavioral paradigms and reinforcement learning can bridge the gap in translation. Lab animal 2022
- Task engagement turns on spatial maps. Nature neuroscience 2022
- Fifty years of the brain's sense of space NATURE 2021
The grid code for ordered experience.
Nature reviews. Neuroscience
Entorhinal cortical grid cells fire in a periodic pattern that tiles space, which is suggestive of a spatial coordinate system. However, irregularities in the grid pattern as well as responses of grid cells in contexts other than spatial navigation have presented a challenge to existing models of entorhinal function. In this Perspective, we propose that hippocampal input provides a key informative drive to the grid network in both spatial and non-spatial circumstances, particularly around salient events. We build on previous models in which neural activity propagates through the entorhinal-hippocampal network in time. This temporal contiguity in network activity points to temporal order as a necessary characteristic of representations generated by the hippocampal formation. We advocate that interactions in the entorhinal-hippocampal loop build a topological representation that is rooted in the temporal order of experience. In this way, the structure of grid cell firing supports a learned topology rather than a rigid coordinate frame that is bound to measurements of the physical world.
View details for DOI 10.1038/s41583-021-00499-9
View details for PubMedID 34453151
Navigating for reward.
Nature reviews. Neuroscience
An organism's survival can depend on its ability to recall and navigate to spatial locations associated with rewards, such as food or a home. Accumulating research has revealed that computations of reward and its prediction occur on multiple levels across a complex set of interacting brain regions, including those that support memory and navigation. However, how the brain coordinates the encoding, recall and use of reward information to guide navigation remains incompletely understood. In this Review, we propose that the brain's classical navigation centres - the hippocampus and the entorhinal cortex - are ideally suited to coordinate this larger network by representing both physical and mental space as a series of states. These states may be linked to reward via neuromodulatory inputs to the hippocampus-entorhinal cortex system. Hippocampal outputs can then broadcast sequences of states to the rest of the brain to store reward associations or to facilitate decision-making, potentially engaging additional value signals downstream. This proposal is supported by recent advances in both experimental and theoretical neuroscience. By discussing the neural systems traditionally tied to navigation and reward at their intersection, we aim to offer an integrated framework for understanding navigation to reward as a fundamental feature of many cognitive processes.
View details for DOI 10.1038/s41583-021-00479-z
View details for PubMedID 34230644
- Spatial memory: Place cell activity is causally related tobehavior. Current biology : CB 2021; 31 (7): R335–R337
Multiple head direction signals within entorhinal cortex: origin and function.
Current opinion in neurobiology
2020; 64: 32–40
Sensory systems show hierarchical computation, starting from primary sensory receptors, with information transformed into multimodal representations as they move through subcortical and cortical brain regions. Here, we discuss recent evidence illustrating that the signaling of direction within the mammalian brain is likewise transformed and multiplexed as it progresses from subcortical regions that contain tightly direction-coupled neurons through thalamus to regions that support navigation, such as the subiculum, entorhinal cortex and hippocampus. Such transformations in the directional signal as it ascends from thalamus to higher-order regions may allow the directional system to support a repertoire of behaviors that go beyond an animal orienting in space.
View details for DOI 10.1016/j.conb.2020.01.015
View details for PubMedID 32088661
Topography in the Bursting Dynamics of Entorhinal Neurons.
2020; 30 (7): 2349–59.e7
Medial entorhinal cortex contains neural substrates for representing space. These substrates include grid cells that fire in repeating locations and increase in scale progressively along the dorsal-to-ventral entorhinal axis, with the physical distance between grid firing nodes increasing from tens of centimeters to several meters in rodents. Whether the temporal scale of grid cell spiking dynamics shows a similar dorsal-to-ventral organization remains unknown. Here, we report the presence of a dorsal-to-ventral gradient in the temporal spiking dynamics of grid cells in behaving mice. This gradient in bursting supports the emergence of a dorsal grid cell population with a high signal-to-noise ratio. In vitro recordings combined with a computational model point to a role for gradients in non-inactivating sodium conductances in supporting the bursting gradient in vivo. Taken together, these results reveal a complementary organization in the temporal and intrinsic properties of entorhinal cells.
View details for DOI 10.1016/j.celrep.2020.01.057
View details for PubMedID 32075768
- The fruit fly gets oriented NATURE 2019; 576 (7785): 42–43
- The Shifting Sands of Cortical Divisions NEURON 2019; 102 (1): 8–11
The Shifting Sands of Cortical Divisions.
2019; 102 (1): 8–11
In this issue of Neuron, a new study by Minderer et al. (2019) examines the activity of thousands of cortical neurons during a navigation task and reveals that features of the task encoded by neurons vary smoothly across cortex rather than falling into functionally discrete cortical regions.
View details for PubMedID 30946829
Emergent elasticity in the neural code for space.
Proceedings of the National Academy of Sciences of the United States of America
Upon encountering a novel environment, an animal must construct a consistent environmental map, as well as an internal estimate of its position within that map, by combining information from two distinct sources: self-motion cues and sensory landmark cues. How do known aspects of neural circuit dynamics and synaptic plasticity conspire to accomplish this feat? Here we show analytically how a neural attractor model that combines path integration of self-motion cues with Hebbian plasticity in synaptic weights from landmark cells can self-organize a consistent map of space as the animal explores an environment. Intriguingly, the emergence of this map can be understood as an elastic relaxation process between landmark cells mediated by the attractor network. Moreover, our model makes several experimentally testable predictions, including (i) systematic path-dependent shifts in the firing fields of grid cells toward the most recently encountered landmark, even in a fully learned environment; (ii) systematic deformations in the firing fields of grid cells in irregular environments, akin to elastic deformations of solids forced into irregular containers; and (iii) the creation of topological defects in grid cell firing patterns through specific environmental manipulations. Taken together, our results conceptually link known aspects of neurons and synapses to an emergent solution of a fundamental computational problem in navigation, while providing a unified account of disparate experimental observations.
View details for PubMedID 30482856
Self-motion processing in visual and entorhinal cortices: Inputs, integration, and implications for position coding.
Journal of neurophysiology
The sensory signals generated by self-motion are complex and multimodal, but the ability to integrate these signals into a unified self-motion percept to guide navigation is essential for animal survival. Here, we summarize classic and recent work on self-motion coding in the visual and entorhinal cortices of the rodent brain. We compare motion processing in rodent and primate visual cortices, highlighting the strengths of classic primate work in establishing causal links between neural activity and perception, and discuss the integration of motor and visual signals in rodent visual cortex. We then turn to the medial entorhinal cortex (MEC), where calculations using self-motion to update position estimates are thought to occur. We focus on several key sources of self-motion information to MEC: the medial septum, which provides locomotor speed information; visual cortex, whose input has been increasingly recognized as essential to both position and speed tuned MEC cells; and the head direction system, which is a major source of directional information for self-motion estimates. These inputs create a large and diverse group of self-motion codes in MEC, and great interest remains in how these self-motion codes might be integrated by MEC grid cells to estimate position. However, which signals are used in these calculations and the mechanisms by which they are integrated remain controversial. We end by proposing future experiments that could further our understanding of the interactions between MEC cells that code for self-motion and position, and clarify the relationship between the activity of these cells and spatial perception.
View details for PubMedID 30089025
Heterogeneity in hippocampal place coding.
Current opinion in neurobiology
2018; 49: 158–67
The discovery of place cells provided fundamental insight into the neural basis by which the hippocampus encodes spatial memories and supports navigation and prompted the development of computational models to explain the emergence of their spatial selectively. Many such works posit that input from entorhinal grid cells is critical to the formation of place fields, a prediction that has received mixed experimental support. Potentially reconciling seemingly conflicting findings is recent work indicating that subpopulations of pyramidal neurons are functionally distinct and may be driven to varying degrees by different inputs. Additionally, new studies have demonstrated that hippocampal principal neurons encode a myriad of features extending beyond current position. Here, we highlight recent evidence for how extensive heterogeneity in connectivity and genetic expression could interact with membrane biophysics to enable place cells to encode a diverse range of stimuli. These recent findings highlight the need for more computational models that integrate these heterogeneous features of hippocampal principal neurons.
View details for PubMedID 29522977
From entorhinal neural codes to navigation
2018; 21 (1): 7–8
View details for PubMedID 29269761
Cell types for our sense of location: where we are and where we are going
2017; 20 (11): 1474–82
Technological advances in profiling cells along genetic, anatomical and physiological axes have fomented interest in identifying all neuronal cell types. This goal nears completion in specialized circuits such as the retina, while remaining more elusive in higher order cortical regions. We propose that this differential success of cell type identification may not simply reflect technological gaps in co-registering genetic, anatomical and physiological features in the cortex. Rather, we hypothesize it reflects evolutionarily driven differences in the computational principles governing specialized circuits versus more general-purpose learning machines. In this framework, we consider the question of cell types in medial entorhinal cortex (MEC), a region likely to be involved in memory and navigation. While MEC contains subsets of identifiable functionally defined cell types, recent work employing unbiased statistical methods and more diverse tasks reveals unsuspected heterogeneity and adaptivity in MEC firing patterns. This suggests MEC may operate more as a generalist circuit, obeying computational design principles resembling those governing other higher cortical regions.
View details for PubMedID 29073649
Environmental boundaries as a mechanism for correcting and anchoring spatial maps
JOURNAL OF PHYSIOLOGY-LONDON
2016; 594 (22): 6501-6511
Ubiquitous throughout the animal kingdom, path integration-based navigation allows an animal to take a circuitous route out from a home base and using only self-motion cues, calculate a direct vector back. Despite variation in an animal's running speed and direction, medial entorhinal grid cells fire in repeating place-specific locations, pointing to the medial entorhinal circuit as a potential neural substrate for path integration-based spatial navigation. Supporting this idea, grid cells appear to provide an environment-independent metric representation of the animal's location in space and preserve their periodic firing structure even in complete darkness. However, a series of recent experiments indicate that spatially responsive medial entorhinal neurons depend on environmental cues in a more complex manner than previously proposed. While multiple types of landmarks may influence entorhinal spatial codes, environmental boundaries have emerged as salient landmarks that both correct error in entorhinal grid cells and bind internal spatial representations to the geometry of the external spatial world. The influence of boundaries on error correction and grid symmetry points to medial entorhinal border cells, which fire at a high rate only near environmental boundaries, as a potential neural substrate for landmark-driven control of spatial codes. The influence of border cells on other entorhinal cell populations, such as grid cells, could depend on plasticity, raising the possibility that experience plays a critical role in determining how external cues influence internal spatial representations.
View details for DOI 10.1113/JP270624
View details for Web of Science ID 000389029900007
View details for PubMedID 26563618
View details for PubMedCentralID PMC5108900
Large scale in vivo recordings to study neuronal biophysics.
Current opinion in neurobiology
2015; 32: 1-7
Over the last several years, technological advances have enabled researchers to more readily observe single-cell membrane biophysics in awake, behaving animals. Studies utilizing these technologies have provided important insights into the mechanisms generating functional neural codes in both sensory and non-sensory cortical circuits. Crucial for a deeper understanding of how membrane biophysics control circuit dynamics however, is a continued effort to move toward large scale studies of membrane biophysics, in terms of the numbers of neurons and ion channels examined. Future work faces a number of theoretical and technical challenges on this front but recent technological developments hold great promise for a larger scale understanding of how membrane biophysics contribute to circuit coding and computation.
View details for DOI 10.1016/j.conb.2014.09.009
View details for PubMedID 25291296
- Large scale in vivo recordings to study neuronal biophysics CURRENT OPINION IN NEUROBIOLOGY 2015; 32: 1-7
- Neuroscience: Internal compass puts flies in their place. Nature 2015; 521 (7551): 165-166
Spatial representation: maps of fragmented space.
2015; 25 (9): R362-3
Grid cells in medial entorhinal cortex are thought to act as a neural metric for spatial navigation. A new study has examined the ability of grid cells to use self-motion cues to form a global map across fragmented spaces.
View details for DOI 10.1016/j.cub.2015.02.065
View details for PubMedID 25942547
- Computational diversity in the hippocampus: a matter of components. journal of physiology 2015; 593 (7): 1525-1526
- Imagine a journey through time and space. Nature neuroscience 2015; 18 (2): 163-164
Hyperpolarization-Activated Cyclic Nucleotide-Gated 1 Independent Grid Cell-Phase Precession in Mice
2014; 24 (3): 249-256
View details for Web of Science ID 000331333900001
Topography of head direction cells in medial entorhinal cortex.
2014; 24 (3): 252-262
Neural circuits in the medial entorhinal cortex (MEC) support translation of the external environment to an internal map of space, with grid and head direction neurons providing metrics for distance and orientation.We show here that head direction cells in MEC are organized topographically. Head direction tuning varies widely across the entire dorsoventral MEC axis, but in layer III there is a gradual dorsal-to-ventral increase in the average width of the directional firing field. Sharply tuned cells were encountered only at the dorsal end of MEC. Similar topography was not observed among head direction cells in layers V-VI. At all MEC locations, in all layers, the preferred firing direction (directional phase) showed a uniform distribution. The continuity of the dorsoventral tuning gradient coexisted with discrete topography in the spatial scale of simultaneously recorded grid cells.The findings point to dorsoventral gradients as a fundamental property of entorhinal circuits, upon which modular organization may be expressed in select subpopulations.
View details for DOI 10.1016/j.cub.2013.12.002
View details for PubMedID 24440398
- The neural encoding of space in parahippocampal cortices FRONTIERS IN NEURAL CIRCUITS 2012; 6
Phase precession and variable spatial scaling in a periodic attractor map model of medial entorhinal grid cells with realistic after-spike dynamics
2012; 22 (4): 772-789
We present a model that describes the generation of the spatial (grid fields) and temporal (phase precession) properties of medial entorhinal cortical (MEC) neurons by combining network and intrinsic cellular properties. The model incorporates network architecture derived from earlier attractor map models, and is implemented in 1D for simplicity. Periodic driving of conjunctive (position × head-direction) layer-III MEC cells at theta frequency with intensity proportional to the rat's speed, moves an 'activity bump' forward in network space at a corresponding speed. The addition of prolonged excitatory currents and simple after-spike dynamics resembling those observed in MEC stellate cells (for which new data are presented) accounts for both phase precession and the change in scale of grid fields along the dorso-ventral axis of MEC. Phase precession in the model depends on both synaptic connectivity and intrinsic currents, each of which drive neural spiking either during entry into, or during exit out of a grid field. Thus, the model predicts that the slope of phase precession changes between entry into and exit out of the field. The model also exhibits independent variation in grid spatial period and grid field size, which suggests possible experimental tests of the model.
View details for DOI 10.1002/hipo.20939
View details for Web of Science ID 000301776200011
View details for PubMedID 21484936
Spatial Representation: Maps in a Temporal Void
2011; 21 (23): R962-R964
It has been suggested that the matrix-like firing structure of entorhinal grid cells is caused by interference between membrane oscillations at slightly different theta frequencies. A recent report suggests that grid signals can be generated in the absence of theta oscillations.
View details for Web of Science ID 000298028100018
View details for PubMedID 22153167
Grid Cells Use HCN1 Channels for Spatial Scaling
2011; 147 (5): 1159-1170
Entorhinal grid cells have periodic, hexagonally patterned firing locations that scale up progressively along the dorsal-ventral axis of medial entorhinal cortex. This topographic expansion corresponds with parallel changes in cellular properties dependent on the hyperpolarization-activated cation current (Ih), which is conducted by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels. To test the hypothesis that grid scale is determined by Ih, we recorded grid cells in mice with forebrain-specific knockout of HCN1. We find that, although the dorsal-ventral gradient of the grid pattern was preserved in HCN1 knockout mice, the size and spacing of the grid fields, as well as the period of the accompanying theta modulation, was expanded at all dorsal-ventral levels. There was no change in theta modulation of simultaneously recorded entorhinal interneurons. These observations raise the possibility that, during self-motion-based navigation, Ih contributes to the gain of the transformation from movement signals to spatial firing fields.
View details for DOI 10.1016/j.cell.2011.08.051
View details for Web of Science ID 000297376600025
View details for PubMedID 22100643
Frequency of Subthreshold Oscillations at Different Membrane Potential Voltages in Neurons at Different Anatomical Positions on the Dorsoventral Axis in the Rat Medial Entorhinal Cortex
JOURNAL OF NEUROSCIENCE
2011; 31 (35): 12683-12694
Neurons from layer II of the medial entorhinal cortex show subthreshold membrane potential oscillations (SMPOs) which could contribute to theta-rhythm generation in the entorhinal cortex and to generation of grid cell firing patterns. However, it is unclear whether single neurons have a fixed unique oscillation frequency or whether their frequency varies depending on the mean membrane potential in a cell. We therefore examined the frequency of SMPOs at different membrane potentials in layer II stellate-like cells of the rat medial entorhinal cortex in vitro. Using whole-cell patch recordings, we found that the fluctuations in membrane potential show a broad band of low power frequencies near resting potential that transition to more narrowband oscillation frequencies with depolarization. The transition from broadband to narrowband frequencies depends on the location of the neuron along the dorsoventral axis in the entorhinal cortex, with dorsal neurons transitioning to higher-frequency oscillations relative to ventral neurons transitioning to lower-frequency oscillations. Once SMPOs showed a narrowband frequency, systematic frequency changes were not observed with further depolarization. Using a Hodgkin-Huxley-style model of membrane currents, we show that differences in the influence of depolarization on the frequency of SMPOs at different dorsal to ventral positions could arise from differences in the properties of the h current. The properties of frequency changes in this data are important for evaluating models of the generation of grid cell firing fields with different spacings along the dorsal-to-ventral axis of medial entorhinal cortex.
View details for DOI 10.1523/JNEUROSCI.1654-11.2011
View details for Web of Science ID 000294451900031
View details for PubMedID 21880929
Computational Models of Grid Cells
2011; 71 (4): 589-603
Grid cells are space-modulated neurons with periodic firing fields. In moving animals, the multiple firing fields of an individual grid cell form a triangular pattern tiling the entire space available to the animal. Collectively, grid cells are thought to provide a context-independent metric representation of the local environment. Since the discovery of grid cells in 2005, a number of models have been proposed to explain the formation of spatially repetitive firing patterns as well as the conversion of these signals to place signals one synapse downstream in the hippocampus. The present article reviews the most recent developments in our understanding of how grid patterns are generated, maintained, and transformed, with particular emphasis on second-generation computational models that have emerged during the past 2-3 years in response to criticism and new data.
View details for DOI 10.1016/j.neuron.2011.07.023
View details for Web of Science ID 000294521600006
View details for PubMedID 21867877
Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory
BEHAVIOURAL BRAIN RESEARCH
2010; 215 (2): 261-274
Understanding the mechanisms of episodic memory requires linking behavioral data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action.
View details for DOI 10.1016/j.bbr.2009.12.010
View details for Web of Science ID 000282505600011
View details for PubMedID 20018213
Cholinergic Modulation of the Resonance Properties of Stellate Cells in Layer II of Medial Entorhinal Cortex
JOURNAL OF NEUROPHYSIOLOGY
2010; 104 (1): 258-270
In vitro whole cell patch-clamp recordings of stellate cells in layer II of medial entorhinal cortex show a subthreshold membrane potential resonance in response to a sinusoidal current injection of varying frequency. Physiological recordings from awake behaving animals show that neurons in layer II medial entorhinal cortex, termed "grid cells," fire in a spatially selective manner such that each cell's multiple firing fields form a hexagonal grid. Both the spatial periodicity of the grid fields and the resonance frequency change systematically in neurons along the dorsal to ventral axis of medial entorhinal cortex. Previous work has also shown that grid field spacing and acetylcholine levels change as a function of the novelty to a particular environment. Using in vitro whole cell patch-clamp recordings, our study shows that both resonance frequency and resonance strength vary as a function of cholinergic modulation. Furthermore, our data suggest that these changes in resonance properties are mediated through modulation of h-current and m-current.
View details for DOI 10.1152/jn.00492.2009
View details for Web of Science ID 000279586400024
View details for PubMedID 20445030
Evaluation of the Oscillatory Interference Model of Grid Cell Firing through Analysis and Measured Period Variance of Some Biological Oscillators
PLOS COMPUTATIONAL BIOLOGY
2009; 5 (11)
Models of the hexagonally arrayed spatial activity pattern of grid cell firing in the literature generally fall into two main categories: continuous attractor models or oscillatory interference models. Burak and Fiete (2009, PLoS Comput Biol) recently examined noise in two continuous attractor models, but did not consider oscillatory interference models in detail. Here we analyze an oscillatory interference model to examine the effects of noise on its stability and spatial firing properties. We show analytically that the square of the drift in encoded position due to noise is proportional to time and inversely proportional to the number of oscillators. We also show there is a relatively fixed breakdown point, independent of many parameters of the model, past which noise overwhelms the spatial signal. Based on this result, we show that a pair of oscillators are expected to maintain a stable grid for approximately t = 5mu(3)/(4pisigma)(2) seconds where mu is the mean period of an oscillator in seconds and sigma(2) its variance in seconds(2). We apply this criterion to recordings of individual persistent spiking neurons in postsubiculum (dorsal presubiculum) and layers III and V of entorhinal cortex, to subthreshold membrane potential oscillation recordings in layer II stellate cells of medial entorhinal cortex and to values from the literature regarding medial septum theta bursting cells. All oscillators examined have expected stability times far below those seen in experimental recordings of grid cells, suggesting the examined biological oscillators are unfit as a substrate for current implementations of oscillatory interference models. However, oscillatory interference models can tolerate small amounts of noise, suggesting the utility of circuit level effects which might reduce oscillator variability. Further implications for grid cell models are discussed.
View details for DOI 10.1371/journal.pcbi.1000573
View details for Web of Science ID 000274228500021
View details for PubMedID 19936051
A phase code for memory could arise from circuit mechanisms in entorhinal cortex
2009; 22 (8): 1129-1138
Neurophysiological data reveals intrinsic cellular properties that suggest how entorhinal cortical neurons could code memory by the phase of their firing. Potential cellular mechanisms for this phase coding in models of entorhinal function are reviewed. This mechanism for phase coding provides a substrate for modeling the responses of entorhinal grid cells, as well as the replay of neural spiking activity during waking and sleep. Efforts to implement these abstract models in more detailed biophysical compartmental simulations raise specific issues that could be addressed in larger scale population models incorporating mechanisms of inhibition.
View details for DOI 10.1016/j.neunet.2009.07.012
View details for Web of Science ID 000271175800010
View details for PubMedID 19656654
Knock-Out of HCN1 Subunit Flattens Dorsal-Ventral Frequency Gradient of Medial Entorhinal Neurons in Adult Mice
JOURNAL OF NEUROSCIENCE
2009; 29 (23): 7625-7630
Layer II stellate cells at different locations along the dorsal to ventral axis of medial entorhinal cortex show differences in the frequency of intrinsic membrane potential oscillations and resonance (Giocomo et al., 2007). The frequency differences scale with differences in the size and spacing of grid-cell firing fields recorded in layer II of the medial entorhinal cortex in behaving animals. To determine the mechanism for this difference in intrinsic frequency, we analyzed oscillatory properties in adult control mice and adult mice with a global deletion of the HCN1 channel. Data from whole-cell patch recordings show that the oscillation frequency gradient along the dorsal-ventral axis previously shown in juvenile rats also appears in control adult mice, indicating that the dorsal-ventral gradient generalizes across age and species. Knock-out of the HCN1 channel flattens the dorsal-ventral gradient of the membrane potential oscillation frequency, the resonant frequency, the time constant of the "sag" potential and the amplitude of the sag potential. This supports a role of the HCN1 subunit in the mechanism of the frequency gradient in these neurons. These findings have important implications for models of grid cells and generate predictions for future in vivo work on entorhinal grid cells.
View details for DOI 10.1523/JNEUROSCI.0609-09.2009
View details for Web of Science ID 000267130800027
View details for PubMedID 19515931
Time constants of h current in layer II stellate cells differ along the dorsal to ventral axis of medial Entorhinal cortex
JOURNAL OF NEUROSCIENCE
2008; 28 (38): 9414-9425
Chronic recordings in the medial entorhinal cortex of behaving rats have found grid cells, neurons that fire when the rat is in a hexagonal array of locations. Grid cells recorded at different dorsal-ventral anatomical positions show systematic changes in size and spacing of firing fields. To test possible mechanisms underlying these differences, we analyzed properties of the hyperpolarization-activated cation current I(h) in voltage-clamp recordings from stellate cells in entorhinal slices from different dorsal-ventral locations. The time constant of h current was significantly different between dorsal and ventral neurons. The time constant of h current correlated with membrane potential oscillation frequency and the time constant of the sag potential in the same neurons. Differences in h current could underlie differences in membrane potential oscillation properties and contribute to grid cell periodicity along the dorsal-ventral axis of medial entorhinal cortex.
View details for DOI 10.1523/JNEUROSCI.3196-08.2008
View details for Web of Science ID 000259288900010
View details for PubMedID 18799674
Computation by Oscillations: Implications of Experimental Data for Theoretical Models of Grid Cells
2008; 18 (12): 1186-1199
Recordings in awake, behaving animals demonstrate that cells in medial entorhinal cortex (mEC) show "grid cell" firing activity when a rat explores an open environment. Intracellular recording in slices from different positions along the dorsal to ventral axis show differences in intrinsic properties such as subthreshold membrane potential oscillations (MPO), resonant frequency, and the presence of the hyperpolarization-activated cation current (h-current). The differences in intrinsic properties correlate with differences in grid cell spatial scale along the dorsal-ventral axis of mEC. Two sets of computational models have been proposed to explain the grid cell firing phenomena: oscillatory interference models and attractor-dynamic models. Both types of computational models are briefly reviewed, and cellular experimental evidence is interpreted and presented in the context of both models. The oscillatory interference model has variations that include an additive model and a multiplicative model. Experimental data on the voltage-dependence of oscillations presented here support the additive model. The additive model also simulates data from ventral neurons showing large spacing between grid firing fields within the limits of observed MPO frequencies. The interactions of h-current with synaptic modification suggest that the difference in intrinsic properties could also contribute to differences in grid cell properties due to attractor dynamics along the dorsal to ventral axis of mEC. Mechanisms of oscillatory interference and attractor dynamics may make complementary contributions to the properties of grid cell firing in entorhinal cortex.
View details for DOI 10.1002/hipo.20501
View details for Web of Science ID 000261871800005
View details for PubMedID 19021252
Neuromodulation by glutamate and acetylcholine can change circuit dynamics by regulating the relative influence of afferent input and excitatory feedback
2007; 36 (2): 184-200
Substances such as acetylcholine and glutamate act as both neurotransmitters and neuromodulators. As neuromodulators, they change neural information processing by regulating synaptic transmitter release, altering baseline membrane potential and spiking activity, and modifying long-term synaptic plasticity. Slice physiology research has demonstrated that many neuromodulators differentially modulate afferent, incoming information compared to intrinsic and recurrent processing in cortical structures such as piriform cortex, neocortex, and the hippocampus. The enhancement of afferent (external) pathways versus the suppression at recurrent (internal) pathways could cause cortical dynamics to switch between a predominant influence of external stimulation to a predominant influence of internal recall. Modulation of afferent versus intrinsic processing could contribute to the role of neuromodulators in regulating attention, learning, and memory effects in behavior.
View details for DOI 10.1007/s12035-007-0032-z
View details for Web of Science ID 000250305300004
View details for PubMedID 17952661
Temporal frequency of subthreshold oscillations scales with entorhinal grid cell field spacing
2007; 315 (5819): 1719-1722
Grid cells in layer II of rat entorhinal cortex fire to spatial locations in a repeating hexagonal grid, with smaller spacing between grid fields for neurons in more dorsal anatomical locations. Data from in vitro whole-cell patch recordings showed differences in frequency of subthreshold membrane potential oscillations in entorhinal neurons that correspond to different positions along the dorsal-to-ventral axis, supporting a model of physiological mechanisms for grid cell responses.
View details for DOI 10.1126/science.1139207
View details for Web of Science ID 000245106900042
View details for PubMedID 17379810
View details for PubMedCentralID PMC2950607
Grid cell firing may arise from interference of theta frequency membrane potential oscillations in single neurons
2007; 17 (12): 1252-1271
Intracellular recording and computational modelling suggest that interactions of subthreshold membrane potential oscillation frequency in different dendritic branches of entorhinal cortex stellate cells could underlie the functional coding of continuous dimensions of space and time. Among other things, these interactions could underlie properties of grid cell field spacing. The relationship between experimental data on membrane potential oscillation frequency (f) and grid cell field spacing (G) indicates a constant scaling factor H = fG. This constant scaling factor between temporal oscillation frequency and spatial periodicity provides a starting constraint that is used to derive the model of Burgess et al. (Hippocampus, 2007). This model provides a consistent quantitative link between single cell physiological properties and properties of spiking units in awake behaving animals. Further properties and predictions of this model about single cell and network physiological properties are analyzed. In particular, the model makes quantitative predictions about the change in membrane potential, single cell oscillation frequency, and network oscillation frequency associated with speed of movement, about the independence of single cell properties from network theta rhythm oscillations, and about the effect of variations in initial oscillatory phase on the pattern of grid cell firing fields. These same mechanisms of subthreshold oscillations may play a more general role in memory function, by providing a method for learning arbitrary time intervals in memory sequences.
View details for DOI 10.1002/hipo.20374
View details for Web of Science ID 000251553400012
View details for PubMedID 17924530
Difference in time course of modulation of synaptic transmission by group II versus group III metabotropic glutamate receptors in region CA1 of the hippocampus
2006; 16 (11): 1004-1016
We investigated the time course of modulation of synaptic transmission by group II and group III metabotropic glutamate receptors in region CA1 of the hippocampus. In the presence of 50 microM picrotoxin, pressure pulse application of 1 mM glutamate resulted in a fast onset of suppression of synaptic transmission in stratum lacunosum moleculare and a slower onset of suppression in stratum radiatum, with both effects returning to baseline over the course of several minutes. Application of 50 microM of the group II agonist (2R,4R)-APDC in stratum lacunosum moleculare resulted in the same fast onset of suppression while having no effect in stratum radiatum. Pressure pulse application of 100 microM DL-AP4 in stratum lacunosum moleculare and stratum radiatum resulted in a much slower onset of suppression of synaptic transmission than (2R,4R)-APDC. Suppression by (2R,4R)-APDC was accompanied by a rapid enhancement of paired pulse facilitation, indicative of a presynaptic mechanism. This demonstrates that activation of group II mGluRs in the hippocampus causes a fast onset of suppression in stratum lacunosum moleculare, while activation of group III mGluRs causes a slower onset of suppression. The difference in time course for group II vs. group III mGluRs suggests a different functional role, with group II playing a potential role in making synapses act as low pass filters.
View details for DOI 10.1002/hipo.20231
View details for Web of Science ID 000241833500010
View details for PubMedID 17039485
Nicotinic modulation of glutamatergic synaptic transmission in region CA3 of the hippocampus
EUROPEAN JOURNAL OF NEUROSCIENCE
2005; 22 (6): 1349-1356
Cholinergic modulation of synaptic transmission in the hippocampus appears to be involved in learning, memory and attentional processes. In brain slice preparations of hippocampal region CA3, we have explored the effect of nicotine on the afferent connections of stratum lacunosum moleculare (SLM) vs. the intrinsic connections of stratum radiatum (SR). Nicotine application had a lamina-selective effect, causing changes in synaptic transmission only in SLM. The nicotinic effect in SLM was characterized by a transient decrease in synaptic potential size followed by a longer period of enhancement of synaptic transmission. The effect was blocked by gamma-aminobutyric acid (GABA)ergic antagonists, indicating the role of GABAergic interneurons in the observed nicotinic effect. The biphasic nature of the nicotinic effect could be due to a difference in receptor subtypes, as supported by the effects of the nicotinic antagonists mecamylamine and methyllycaconitine. Nicotinic modulation of glutamatergic synaptic transmission could complement muscarinic suppression of intrinsic connections, amplifying incoming information and providing a physiological mechanism for the memory-enhancing effect of nicotine.
View details for DOI 10.1111/j.1460-9568.2005.04316.x
View details for Web of Science ID 000232142000009
View details for PubMedID 16190890