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Hasselmo ME, Alexander AS, Hoyland A, Robinson JC, Bezaire MJ, Chapman GW, Saudargiene A, Carstensen LC, Dannenberg H. The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation. Neuroscience 2020; 456:143-158. [PMID: 32278058 DOI: 10.1016/j.neuroscience.2020.03.048] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 03/30/2020] [Accepted: 03/31/2020] [Indexed: 12/16/2022]
Abstract
The space of possible neural models is enormous and under-explored. Single cell computational neuroscience models account for a range of dynamical properties of membrane potential, but typically do not address network function. In contrast, most models focused on network function address the dimensions of excitatory weight matrices and firing thresholds without addressing the complexities of metabotropic receptor effects on intrinsic properties. There are many under-explored dimensions of neural parameter space, and the field needs a framework for representing what has been explored and what has not. Possible frameworks include maps of parameter spaces, or efforts to categorize the fundamental elements and molecules of neural circuit function. Here we review dimensions that are under-explored in network models that include the metabotropic modulation of synaptic plasticity and presynaptic inhibition, spike frequency adaptation due to calcium-dependent potassium currents, and afterdepolarization due to calcium-sensitive non-specific cation currents and hyperpolarization activated cation currents. Neuroscience research should more effectively explore possible functional models incorporating under-explored dimensions of neural function.
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Affiliation(s)
- Michael E Hasselmo
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
| | - Andrew S Alexander
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
| | - Alec Hoyland
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
| | - Jennifer C Robinson
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
| | - Marianne J Bezaire
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
| | - G William Chapman
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
| | - Ausra Saudargiene
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
| | - Lucas C Carstensen
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
| | - Holger Dannenberg
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States
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Pastoll H, Garden DL, Papastathopoulos I, Sürmeli G, Nolan MF. Inter- and intra-animal variation in the integrative properties of stellate cells in the medial entorhinal cortex. eLife 2020; 9:52258. [PMID: 32039761 PMCID: PMC7067584 DOI: 10.7554/elife.52258] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 02/04/2020] [Indexed: 01/28/2023] Open
Abstract
Distinctions between cell types underpin organizational principles for nervous system function. Functional variation also exists between neurons of the same type. This is exemplified by correspondence between grid cell spatial scales and the synaptic integrative properties of stellate cells (SCs) in the medial entorhinal cortex. However, we know little about how functional variability is structured either within or between individuals. Using ex-vivo patch-clamp recordings from up to 55 SCs per mouse, we found that integrative properties vary between mice and, in contrast to the modularity of grid cell spatial scales, have a continuous dorsoventral organization. Our results constrain mechanisms for modular grid firing and provide evidence for inter-animal phenotypic variability among neurons of the same type. We suggest that neuron type properties are tuned to circuit-level set points that vary within and between animals.
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Affiliation(s)
- Hugh Pastoll
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Derek L Garden
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ioannis Papastathopoulos
- The Alan Turing Institute, London, United States.,School of Mathematics, Maxwell Institute and Centre for Statistics, University of Edinburgh, Edinburgh, United Kingdom
| | - Gülşen Sürmeli
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthew F Nolan
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
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Kang L, DeWeese MR. Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network. eLife 2019; 8:46351. [PMID: 31736462 PMCID: PMC6901334 DOI: 10.7554/elife.46351] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 11/15/2019] [Indexed: 11/17/2022] Open
Abstract
Grid cells fire in sequences that represent rapid trajectories in space. During locomotion, theta sequences encode sweeps in position starting slightly behind the animal and ending ahead of it. During quiescence and slow wave sleep, bouts of synchronized activity represent long trajectories called replays, which are well-established in place cells and have been recently reported in grid cells. Theta sequences and replay are hypothesized to facilitate many cognitive functions, but their underlying mechanisms are unknown. One mechanism proposed for grid cell formation is the continuous attractor network. We demonstrate that this established architecture naturally produces theta sequences and replay as distinct consequences of modulating external input. Driving inhibitory interneurons at the theta frequency causes attractor bumps to oscillate in speed and size, which gives rise to theta sequences and phase precession, respectively. Decreasing input drive to all neurons produces traveling wavefronts of activity that are decoded as replays.
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Affiliation(s)
- Louis Kang
- Redwood Center for Theoretical Neuroscience, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.,Department of Physics, University of California, Berkeley, Berkeley, United States
| | - Michael R DeWeese
- Redwood Center for Theoretical Neuroscience, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.,Department of Physics, University of California, Berkeley, Berkeley, United States
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Hasselmo ME, Stern CE. A network model of behavioural performance in a rule learning task. Philos Trans R Soc Lond B Biol Sci 2019; 373:rstb.2017.0275. [PMID: 29483357 DOI: 10.1098/rstb.2017.0275] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/30/2017] [Indexed: 01/04/2023] Open
Abstract
Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.
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Affiliation(s)
- Michael E Hasselmo
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Avenue, Boston, MA 02215, USA
| | - Chantal E Stern
- Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Avenue, Boston, MA 02215, USA
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Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells. J Theor Biol 2018; 449:23-34. [PMID: 29654854 PMCID: PMC5947116 DOI: 10.1016/j.jtbi.2018.04.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 04/02/2018] [Accepted: 04/09/2018] [Indexed: 02/07/2023]
Abstract
An SDE model of entorhinal cortex (EC) stellate cells is proposed. Experimentally observed action potential clustering is investigated in the model. Clusters are generated by subcritical-Hopf/homoclinic type bursting. Potential mechanisms underlying changes in EC dynamics in dementia are presented.
The entorhinal cortex is a crucial component of our memory and spatial navigation systems and is one of the first areas to be affected in dementias featuring tau pathology, such as Alzheimer’s disease and frontotemporal dementia. Electrophysiological recordings from principle cells of medial entorhinal cortex (layer II stellate cells, mEC-SCs) demonstrate a number of key identifying properties including subthreshold oscillations in the theta (4–12 Hz) range and clustered action potential firing. These single cell properties are correlated with network activity such as grid firing and coupling between theta and gamma rhythms, suggesting they are important for spatial memory. As such, experimental models of dementia have revealed disruption of organised dorsoventral gradients in clustered action potential firing. To better understand the mechanisms underpinning these different dynamics, we study a conductance based model of mEC-SCs. We demonstrate that the model, driven by extrinsic noise, can capture quantitative differences in clustered action potential firing patterns recorded from experimental models of tau pathology and healthy animals. The differential equation formulation of our model allows us to perform numerical bifurcation analyses in order to uncover the dynamic mechanisms underlying these patterns. We show that clustered dynamics can be understood as subcritical Hopf/homoclinic bursting in a fast-slow system where the slow sub-system is governed by activation of the persistent sodium current and inactivation of the slow A-type potassium current. In the full system, we demonstrate that clustered firing arises via flip bifurcations as conductance parameters are varied. Our model analyses confirm the experimentally suggested hypothesis that the breakdown of clustered dynamics in disease occurs via increases in AHP conductance.
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Ridler T, Matthews P, Phillips KG, Randall AD, Brown JT. Initiation and slow propagation of epileptiform activity from ventral to dorsal medial entorhinal cortex is constrained by an inhibitory gradient. J Physiol 2018; 596:2251-2266. [PMID: 29604046 DOI: 10.1113/jp275871] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Accepted: 03/08/2018] [Indexed: 12/31/2022] Open
Abstract
KEY POINTS The medial entorhinal cortex (mEC) has an important role in initiation and propagation of seizure activity. Several anatomical relationships exist in neurophysiological properties of mEC neurons; however, in the context of hyperexcitability, previous studies often considered it as a homogeneous structure. Using multi-site extracellular recording techniques, ictal-like activity was observed along the dorso-ventral axis of the mEC in vitro in response to various ictogenic stimuli. This originated predominantly from ventral areas, spreading to dorsal mEC with a surprisingly slow velocity. Modulation of inhibitory tone was capable of changing the slope of ictal initiation, suggesting seizure propagation behaviours are highly dependent on levels of GABAergic function in this region. A distinct disinhibition model also showed, in the absence of inhibition, a prevalence for interictal-like initiation in ventral mEC, reflecting the intrinsic differences in mEC neurons. These findings suggest the ventral mEC is more prone to hyperexcitable discharge than the dorsal mEC, which may be relevant under pathological conditions. ABSTRACT The medial entorhinal cortex (mEC) has an important role in the generation and propagation of seizure activity. The organization of the mEC is such that a number of dorso-ventral relationships exist in neurophysiological properties of neurons. These range from intrinsic and synaptic properties to density of inhibitory connectivity. We examined the influence of these gradients on generation and propagation of epileptiform activity in the mEC. Using a 16-shank silicon probe array to record along the dorso-ventral axis of the mEC in vitro, we found 4-aminopyridine application produces ictal-like activity originating predominantly in ventral areas. This activity spreads to dorsal mEC at a surprisingly slow velocity (138 μm s-1 ), while cross-site interictal-like activity appeared relatively synchronous. We propose that ictal propagation is constrained by differential levels of GABAergic control since increasing (diazepam) or decreasing (Ro19-4603) GABAA receptor activation, respectively, reduced or increased the slope of ictal initiation. The observation that ictal activity is predominately generated in ventral mEC was replicated using a separate 0-Mg2+ model of epileptiform activity in vitro. By using a distinct disinhibition model (co-application of kainate and picrotoxin) we show that additional physiological features (for example intrinsic properties of mEC neurons) still produce a prevalence for interictal-like initiation in ventral mEC. These findings suggest that the ventral mEC is more likely to initiate hyperexcitable discharges than the dorsal mEC, and that seizure propagation is highly dependent on levels of GABAergic expression across the mEC.
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Affiliation(s)
- Thomas Ridler
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Hatherly Laboratories, Prince of Wales Road, Exeter EX4 4PS, UK
| | - Peter Matthews
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Hatherly Laboratories, Prince of Wales Road, Exeter EX4 4PS, UK
| | | | - Andrew D Randall
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Hatherly Laboratories, Prince of Wales Road, Exeter EX4 4PS, UK
| | - Jonathan T Brown
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Hatherly Laboratories, Prince of Wales Road, Exeter EX4 4PS, UK
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D’Albis T, Kempter R. A single-cell spiking model for the origin of grid-cell patterns. PLoS Comput Biol 2017; 13:e1005782. [PMID: 28968386 PMCID: PMC5638623 DOI: 10.1371/journal.pcbi.1005782] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 10/12/2017] [Accepted: 09/18/2017] [Indexed: 11/19/2022] Open
Abstract
Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity.
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Affiliation(s)
- Tiziano D’Albis
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Richard Kempter
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Berlin, Germany
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Urdapilleta E, Si B, Treves A. Selforganization of modular activity of grid cells. Hippocampus 2017; 27:1204-1213. [PMID: 28768062 PMCID: PMC5697658 DOI: 10.1002/hipo.22765] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2017] [Revised: 07/20/2017] [Accepted: 07/28/2017] [Indexed: 11/07/2022]
Abstract
A unique topographical representation of space is found in the concerted activity of grid cells in the rodent medial entorhinal cortex. Many among the principal cells in this region exhibit a hexagonal firing pattern, in which each cell expresses its own set of place fields (spatial phases) at the vertices of a triangular grid, the spacing and orientation of which are typically shared with neighboring cells. Grid spacing, in particular, has been found to increase along the dorso‐ventral axis of the entorhinal cortex but in discrete steps, that is, with a modular structure. In this study, we show that such a modular activity may result from the self‐organization of interacting units, which individually would not show discrete but rather continuously varying grid spacing. Within our “adaptation” network model, the effect of a continuously varying time constant, which determines grid spacing in the isolated cell model, is modulated by recurrent collateral connections, which tend to produce a few subnetworks, akin to magnetic domains, each with its own grid spacing. In agreement with experimental evidence, the modular structure is tightly defined by grid spacing, but also involves grid orientation and distortion, due to interactions across modules. Thus, our study sheds light onto a possible mechanism, other than simply assuming separate networks a priori, underlying the formation of modular grid representations.
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Affiliation(s)
- Eugenio Urdapilleta
- División de Física Estadística e InterdisciplinariaCentro Atómico BarilocheS. C. de BarilocheRío Negro8400Argentina
| | - Bailu Si
- Shenyang Institute of Automation, Chinese Academy of SciencesShenyang110016China
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Electrical and Network Neuronal Properties Are Preferentially Disrupted in Dorsal, But Not Ventral, Medial Entorhinal Cortex in a Mouse Model of Tauopathy. J Neurosci 2016; 36:312-24. [PMID: 26758825 DOI: 10.1523/jneurosci.2845-14.2016] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
UNLABELLED The entorhinal cortex (EC) is one of the first areas to be disrupted in neurodegenerative diseases such as Alzheimer's disease and frontotemporal dementia. The responsiveness of individual neurons to electrical and environmental stimuli varies along the dorsal-ventral axis of the medial EC (mEC) in a manner that suggests this topographical organization plays a key role in neural encoding of geometric space. We examined the cellular properties of layer II mEC stellate neurons (mEC-SCs) in rTg4510 mice, a rodent model of neurodegeneration. Dorsoventral gradients in certain intrinsic membrane properties, such as membrane capacitance and afterhyperpolarizations, were flattened in rTg4510 mEC-SCs, while other cellular gradients [e.g., input resistance (Ri), action potential properties] remained intact. Specifically, the intrinsic properties of rTg4510 mEC-SCs in dorsal aspects of the mEC were preferentially affected, such that action potential firing patterns in dorsal mEC-SCs were altered, while those in ventral mEC-SCs were unaffected. We also found that neuronal oscillations in the gamma frequency band (30-80 Hz) were preferentially disrupted in the dorsal mEC of rTg4510 slices, while those in ventral regions were comparatively preserved. These alterations corresponded to a flattened dorsoventral gradient in theta-gamma cross-frequency coupling of local field potentials recorded from the mEC of freely moving rTg4510 mice. These differences were not paralleled by changes to the dorsoventral gradient in parvalbumin staining or neurodegeneration. We propose that the selective disruption to dorsal mECs, and the resultant flattening of certain dorsoventral gradients, may contribute to disturbances in spatial information processing observed in this model of dementia. SIGNIFICANCE STATEMENT The medial entorhinal cortex (mEC) plays a key role in spatial memory and is one of the first areas to express the pathological features of dementia. Neurons of the mEC are anatomically arranged to express functional dorsoventral gradients in a variety of neuronal properties, including grid cell firing field spacing, which is thought to encode geometric scale. We have investigated the effects of tau pathology on functional dorsoventral gradients in the mEC. Using electrophysiological approaches, we have shown that, in a transgenic mouse model of dementia, the functional properties of the dorsal mEC are preferentially disrupted, resulting in a flattening of some dorsoventral gradients. Our data suggest that neural signals arising in the mEC will have a reduced spatial content in dementia.
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Abstract
The medial entorhinal cortex (MEC) creates a neural representation of space through a set of functionally dedicated cell types: grid cells, border cells, head direction cells, and speed cells. Grid cells, the most abundant functional cell type in the MEC, have hexagonally arranged firing fields that tile the surface of the environment. These cells were discovered only in 2005, but after 10 years of investigation, we are beginning to understand how they are organized in the MEC network, how their periodic firing fields might be generated, how they are shaped by properties of the environment, and how they interact with the rest of the MEC network. The aim of this review is to summarize what we know about grid cells and point out where our knowledge is still incomplete.
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Affiliation(s)
- David C Rowland
- Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, 7491 Trondheim, Norway; , , ,
| | - Yasser Roudi
- Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, 7491 Trondheim, Norway; , , ,
| | - May-Britt Moser
- Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, 7491 Trondheim, Norway; , , ,
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, 7491 Trondheim, Norway; , , ,
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