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Ye H, Hendee J, Ruan J, Zhirova A, Ye J, Dima M. Neuron matters: neuromodulation with electromagnetic stimulation must consider neurons as dynamic identities. J Neuroeng Rehabil 2022; 19:116. [PMID: 36329492 PMCID: PMC9632094 DOI: 10.1186/s12984-022-01094-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 10/15/2022] [Indexed: 11/06/2022] Open
Abstract
Neuromodulation with electromagnetic stimulation is widely used for the control of abnormal neural activity, and has been proven to be a valuable alternative to pharmacological tools for the treatment of many neurological diseases. Tremendous efforts have been focused on the design of the stimulation apparatus (i.e., electrodes and magnetic coils) that delivers the electric current to the neural tissue, and the optimization of the stimulation parameters. Less attention has been given to the complicated, dynamic properties of the neurons, and their context-dependent impact on the stimulation effects. This review focuses on the neuronal factors that influence the outcomes of electromagnetic stimulation in neuromodulation. Evidence from multiple levels (tissue, cellular, and single ion channel) are reviewed. Properties of the neural elements and their dynamic changes play a significant role in the outcome of electromagnetic stimulation. This angle of understanding yields a comprehensive perspective of neural activity during electrical neuromodulation, and provides insights in the design and development of novel stimulation technology.
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Affiliation(s)
- Hui Ye
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Jenna Hendee
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Joyce Ruan
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Alena Zhirova
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Jayden Ye
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Maria Dima
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
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2
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Zhu T, Wei S, Wang Y. Post-Inhibitory Rebound Firing of Dorsal Root Ganglia Neurons. J Pain Res 2022; 15:2029-2040. [PMID: 35923842 PMCID: PMC9342929 DOI: 10.2147/jpr.s370335] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/02/2022] [Indexed: 01/06/2023] Open
Abstract
Background In the central nervous system, post-inhibitory rebound firing (RF) may mediate overactivity of neurons under pathophysiological condition. RF is also observed in dorsal root ganglion (IRA) neurons. However, the functional significance of RF in primary sensory neurons has remained unknown. After peripheral sensory nerve/neuron injury, DRG neurons exhibit hyperexcitability. Therefore, RF may play a role in neuropathic pain. Methods Chronic compression of DRG (CCD) is used as a neuropathic pain model. Rats were divided into 2 groups: Sham and CCD groups. Patch clamp was performed on the whole DRG and cultured DRG neurons to record RF and T-type Ca2+ currents. The blocker of T-type Ca2+ channels, NiCl2, was applied to DRG neurons. Results Rebound neurons were more excitable than non-rebound neurons. And they discharged RF with prominent after depolarizing potentials, which were blocked by NiCl2. After DRG injury, the proportion of rebound neurons augmented, and rebound neurons’ excitability increased. Meanwhile, the steady-state activation curve of T-type Ca2+ channels was shifted toward the left. Conclusion RF may be related to highly excitable neurons and sensitive to both depolarization and hyperpolarization. T-type Ca2+ channels were critical to RF, potentially enhancing the spontaneous firing of rebound neurons in response to resting membrane potential fluctuations.
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Affiliation(s)
- Tong Zhu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, 710061, People’s Republic of China
- Clinical Experimental Center, Xi’an International Medical Center Hospital, Xi’an, Shaanxi, 710100, People’s Republic of China
| | - Siqi Wei
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, 710061, People’s Republic of China
| | - Yuying Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, 710061, People’s Republic of China
- Institute of Neuroscience, Translational Medicine Institute, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, 710061, People’s Republic of China
- Key Laboratory of Environment and Genes Related to Diseases (Xi’an Jiaotong University), Ministry of Education, Xi’an, People’s Republic of China
- Correspondence: Yuying Wang, Email
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DiTullio RW, Balasubramanian V. Dynamical self-organization and efficient representation of space by grid cells. Curr Opin Neurobiol 2021; 70:206-213. [PMID: 34861597 PMCID: PMC8688296 DOI: 10.1016/j.conb.2021.11.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 11/09/2021] [Indexed: 10/19/2022]
Abstract
To plan trajectories and navigate, animals must maintain a mental representation of the environment and their own position within it. This "cognitive map" is thought to be supported in part by the entorhinal cortex, where grid cells are active when an animal occupies the vertices of a scaling hierarchy of periodic lattices of locations in an enclosure. Here, we review computational developments which suggest that the grid cell network is: (a) efficient, providing required spatial resolution with a minimum number of neurons, (b) self-organizing, dynamically coordinating the structure and scale of the responses, and (c) adaptive, re-organizing in response to changes in landmarks and the structure of the boundaries of spaces. We consider these ideas in light of recent discoveries of similar structures in the mental representation of abstract spaces of shapes and smells, and in other brain areas, and highlight promising directions for future research.
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Affiliation(s)
- Ronald W. DiTullio
- David Rittenhouse Laboratories & Computational Neuroscience Initiative, University of Pennsylvania, Philadelphia, PA 19104
| | - Vijay Balasubramanian
- David Rittenhouse Laboratories & Computational Neuroscience Initiative, University of Pennsylvania, Philadelphia, PA 19104
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Tukker JJ, Beed P, Brecht M, Kempter R, Moser EI, Schmitz D. Microcircuits for spatial coding in the medial entorhinal cortex. Physiol Rev 2021; 102:653-688. [PMID: 34254836 PMCID: PMC8759973 DOI: 10.1152/physrev.00042.2020] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism’s spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.
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Affiliation(s)
- John J Tukker
- Network Dysfunction, German Center for Neurodegenerative Diseases, Berlin, Germany
| | - Prateep Beed
- NeuroScientific Research Center, Charite Berlin, Germany
| | - Michael Brecht
- Systems Neuroscience, Humboldt University of Berlin, Berlin, Germany
| | - Richard Kempter
- Department of Biology, Institute for Theoretical Biology, Humbolt-Universität zu Berlin, Berlin, Germany
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience and Centre for the Biology of Memory, Norwegian University of Science and Technology
| | - Dietmar Schmitz
- Neuroscience Research Center, Charité Universitätsmedizin Berlin, Berlin, Germany
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Theta Oscillations Gate the Transmission of Reliable Sequences in the Medial Entorhinal Cortex. eNeuro 2021; 8:ENEURO.0059-20.2021. [PMID: 33820802 PMCID: PMC8208650 DOI: 10.1523/eneuro.0059-20.2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 01/11/2021] [Accepted: 01/12/2021] [Indexed: 11/21/2022] Open
Abstract
Stability and precision of sequential activity in the entorhinal cortex (EC) is crucial for encoding spatially guided behavior and memory. These sequences are driven by constantly evolving sensory inputs and persist despite a noisy background. In a realistic computational model of a medial EC (MEC) microcircuit, we show that intrinsic neuronal properties and network mechanisms interact with theta oscillations to generate reliable outputs. In our model, sensory inputs activate interneurons near their most excitable phase during each theta cycle. As the inputs change, different interneurons are recruited and postsynaptic stellate cells are released from inhibition. This causes a sequence of rebound spikes. The rebound time scale of stellate cells, because of an h–current, matches that of theta oscillations. This fortuitous similarity of time scales ensures that stellate spikes get relegated to the least excitable phase of theta and the network encodes the external drive but ignores recurrent excitation. In contrast, in the absence of theta, rebound spikes compete with external inputs and disrupt the sequence that follows. Further, the same mechanism where theta modulates the gain of incoming inputs, can be used to select between competing inputs to create transient functionally connected networks. Our results concur with experimental data that show, subduing theta oscillations disrupts the spatial periodicity of grid cell receptive fields. In the bat MEC where grid cell receptive fields persist even in the absence of continuous theta oscillations, we argue that other low frequency fluctuations play the role of theta.
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Wu YJ, Chien ME, Chiang CC, Huang YZ, Durand DM, Hsu KS. Delta oscillation underlies the interictal spike changes after repeated transcranial direct current stimulation in a rat model of chronic seizures. Brain Stimul 2021; 14:771-779. [PMID: 33989818 DOI: 10.1016/j.brs.2021.04.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/27/2021] [Accepted: 04/29/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Transcranial direct current stimulation (tDCS) provides a noninvasive polarity-specific constant current to treat epilepsy, through a mechanism possibly involving excitability modulation and neural oscillation. OBJECTIVE To determine whether EEG oscillations underlie the interictal spike changes after tDCS in rats with chronic spontaneous seizures. METHODS Rats with kainic acid-induced spontaneous seizures were subjected to cathodal tDCS or sham stimulation for 5 consecutive days. Video-EEG recordings were collected immediately pre- and post-stimulation and for the subsequent 2 weeks following stimulation. The acute pre-post stimulation and subacute follow-up changes of interictal spikes and EEG oscillations in tDCS-treated rats were compared with sham. Ictal EEG with seizure behaviors, hippocampal brain-derived neurotrophic factor (BDNF) protein expression, and mossy fiber sprouting were compared between tDCS and sham rats. RESULTS Interictal spike counts were reduced immediately following tDCS with augmented delta and diminished beta and gamma oscillations compared with sham. Cathodal tDCS also enhanced delta oscillations in normal rats. However, increased numbers of interictal spikes with a decrease of delta and theta oscillations were observed in tDCS-treated rats compared with sham during the following 2 weeks after stimulation. Resuming tDCS suppressed the increase of interictal spike activity. In tDCS rats, hippocampal BDNF protein expression was decreased while mossy fiber sprouting did not change compared with sham. CONCLUSIONS The inverse relationship between the changes of delta oscillation and interictal spikes during tDCS on and off stimulation periods indicates that an enhanced endogenous delta oscillation underlies the tDCS inhibitory effect on epileptic excitability.
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Affiliation(s)
- Yi-Jen Wu
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan 70457, Taiwan; Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70403, Taiwan.
| | - Miao-Er Chien
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan 70457, Taiwan
| | - Chia-Chu Chiang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Ying-Zu Huang
- Department of Neurology and Neuroscience Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan; Medical School and Healthy Aging Research Center, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
| | - Dominique M Durand
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Kuei-Sen Hsu
- Department of Pharmacology, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan; Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan.
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Zhang W, Li SS, Han Y, Xu XH. Sex Differences in Electrophysiological Properties of Mouse Medial Preoptic Area Neurons Revealed by In Vitro Whole-cell Recordings. Neurosci Bull 2021; 37:166-182. [PMID: 32888180 PMCID: PMC7870743 DOI: 10.1007/s12264-020-00565-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 05/14/2020] [Indexed: 10/23/2022] Open
Abstract
Despite extensive characterization of sex differences in the medial preoptic area (mPOA) of the hypothalamus, we know surprisingly little about whether or how male and female mPOA neurons differ electrophysiologically, especially in terms of neuronal firing and behavioral pattern generation. In this study, by performing whole-cell patch clamp recordings of the mPOA, we investigated the influences of sex, cell type, and gonadal hormones on the electrophysiological properties of mPOA neurons. Notably, we uncovered significant sex differences in input resistance (male > female) and in the percentage of neurons that displayed post-inhibitory rebound (male > female). Furthermore, we found that the current mediated by the T-type Ca2+ channel (IT), which is known to underlie post-inhibitory rebound, was indeed larger in male mPOA neurons. Thus, we have identified salient electrophysiological properties of mPOA neurons, namely IT and post-inhibitory rebound, that are male-biased and likely contribute to the sexually dimorphic display of behaviors.
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Affiliation(s)
- Wen Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, Shanghai, 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 200031, China
| | - Shuai-Shuai Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, Shanghai, 200031, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Ying Han
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, Shanghai, 200031, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiao-Hong Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, Shanghai, 200031, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 200031, China.
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Central Amygdala Projections to Lateral Hypothalamus Mediate Avoidance Behavior in Rats. J Neurosci 2021; 41:61-72. [PMID: 33188067 DOI: 10.1523/jneurosci.0236-20.2020] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 10/26/2020] [Accepted: 10/28/2020] [Indexed: 11/21/2022] Open
Abstract
Persistent avoidance of stress-related stimuli following acute stress exposure predicts negative outcomes such as substance abuse and traumatic stress disorders. Previous work using a rat model showed that the central amygdala (CeA) plays an important role in avoidance of a predator odor stress-paired context. Here, we show that CeA projections to the lateral hypothalamus (LH) are preferentially activated in male rats that show avoidance of a predator odor-paired context (termed Avoider rats), that chemogenetic inhibition of CeA-LH projections attenuates avoidance in male Avoider rats, that chemogenetic stimulation of the CeA-LH circuit produces conditioned place avoidance (CPA) in otherwise naive male rats, and that avoidance behavior is associated with intrinsic properties of LH-projecting CeA cells. Collectively, these data show that CeA-LH projections are important for persistent avoidance of stress-related stimuli following acute stress exposure.SIGNIFICANCE STATEMENT This study in rats shows that a specific circuit in the brain [i.e., neurons that project from the central amygdala (CeA) to the lateral hypothalamus (LH)] mediates avoidance of stress-associated stimuli. In addition, this study shows that intrinsic physiological properties of cells in this brain circuit are associated with avoidance of stress-associated stimuli. Further characterization of the CeA-LH circuit may improve our understanding of the neural mechanisms underlying specific aspects of stress-related disorders in humans.
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9
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Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions. PLoS Comput Biol 2020; 16:e1008503. [PMID: 33347433 PMCID: PMC7785241 DOI: 10.1371/journal.pcbi.1008503] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 01/05/2021] [Accepted: 11/09/2020] [Indexed: 12/23/2022] Open
Abstract
In this work, we introduce new phenomenological neuronal models (eLIF and mAdExp) that account for energy supply and demand in the cell as well as the inactivation of spike generation how these interact with subthreshold and spiking dynamics. Including these constraints, the new models reproduce a broad range of biologically-relevant behaviors that are identified to be crucial in many neurological disorders, but were not captured by commonly used phenomenological models. Because of their low dimensionality eLIF and mAdExp open the possibility of future large-scale simulations for more realistic studies of brain circuits involved in neuronal disorders. The new models enable both more accurate modeling and the possibility to study energy-associated disorders over the whole time-course of disease progression instead of only comparing the initially healthy status with the final diseased state. These models, therefore, provide new theoretical and computational methods to assess the opportunities of early diagnostics and the potential of energy-centered approaches to improve therapies. Neurons, even “at rest”, require a constant supply of energy to function. They cannot sustain high-frequency activity over long periods because of regulatory mechanisms, such as adaptation or sodium channels inactivation, and metabolic limitations. These limitations are especially severe in many neuronal disorders, where energy can become insufficient and make the neuronal response change drastically, leading to increased burstiness, network oscillations, or seizures. Capturing such behaviors and impact of energy constraints on them is an essential prerequisite to study disorders such as Parkinson’s disease and epilepsy. However, energy and spiking constraints are not present in any of the standard neuronal models used in computational neuroscience. Here we introduce models that provide a simple and scalable way to account for these features, enabling large-scale theoretical and computational studies of neurological disorders and activity patterns that could not be captured by previously used models. These models provide a way to study energy-associated disorders over the whole time-course of disease progression, and they enable a better assessment of energy-centered approaches to improve therapies.
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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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Dannenberg H, Alexander AS, Robinson JC, Hasselmo ME. The Role of Hierarchical Dynamical Functions in Coding for Episodic Memory and Cognition. J Cogn Neurosci 2019; 31:1271-1289. [PMID: 31251890 DOI: 10.1162/jocn_a_01439] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Behavioral research in human verbal memory function led to the initial definition of episodic memory and semantic memory. A complete model of the neural mechanisms of episodic memory must include the capacity to encode and mentally reconstruct everything that humans can recall from their experience. This article proposes new model features necessary to address the complexity of episodic memory encoding and recall in the context of broader cognition and the functional properties of neurons that could contribute to this broader scope of memory. Many episodic memory models represent individual snapshots of the world with a sequence of vectors, but a full model must represent complex functions encoding and retrieving the relations between multiple stimulus features across space and time on multiple hierarchical scales. Episodic memory involves not only the space and time of an agent experiencing events within an episode but also features shown in neurophysiological data such as coding of speed, direction, boundaries, and objects. Episodic memory includes not only a spatio-temporal trajectory of a single agent but also segments of spatio-temporal trajectories for other agents and objects encountered in the environment consistent with data on encoding the position and angle of sensory features of objects and boundaries. We will discuss potential interactions of episodic memory circuits in the hippocampus and entorhinal cortex with distributed neocortical circuits that must represent all features of human cognition.
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12
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Dramatically Amplified Thoracic Sympathetic Postganglionic Excitability and Integrative Capacity Revealed with Whole-Cell Patch-Clamp Recordings. eNeuro 2019; 6:ENEURO.0433-18.2019. [PMID: 31040159 PMCID: PMC6514441 DOI: 10.1523/eneuro.0433-18.2019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 04/15/2019] [Accepted: 04/16/2019] [Indexed: 12/02/2022] Open
Abstract
Thoracic paravertebral sympathetic postganglionic neurons (tSPNs) comprise the final integrative output of the distributed sympathetic nervous system controlling vascular and thermoregulatory systems. Considered a non-integrating relay, what little is known of tSPN intrinsic excitability has been determined by sharp microelectrodes with presumed impalement injury. We thus undertook the first electrophysiological characterization of tSPN cellular properties using whole-cell recordings and coupled results with a conductance-based model to explore the principles governing their excitability in adult mice of both sexes. Recorded membrane resistance and time constant values were an order of magnitude greater than values previously obtained, leading to a demonstrable capacity for synaptic integration in driving recruitment. Variation in membrane resistivity was the primary determinant controlling cell excitability with vastly lower currents required for tSPN recruitment. Unlike previous microelectrode recordings in mouse which observed inability to sustain firing, all tSPNs were capable of repetitive firing. Computational modeling demonstrated that observed differences are explained by introduction of a microelectrode impalement injury conductance. Overall, tSPNs largely linearly encoded injected current magnitudes over a broad frequency range with distinct subpopulations differentiable based on repetitive firing signatures. Thus, whole-cell recordings reveal tSPNs have more dramatically amplified excitability than previously thought, with greater intrinsic capacity for synaptic integration and with the ability for maintained firing to support sustained actions on vasomotor tone and thermoregulatory function. Rather than acting as a relay, these studies support a more responsive role and possible intrinsic capacity for tSPNs to drive sympathetic autonomic function.
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Ferrante M, Tahvildari B, Duque A, Hadzipasic M, Salkoff D, Zagha EW, Hasselmo ME, McCormick DA. Distinct Functional Groups Emerge from the Intrinsic Properties of Molecularly Identified Entorhinal Interneurons and Principal Cells. Cereb Cortex 2018; 27:3186-3207. [PMID: 27269961 DOI: 10.1093/cercor/bhw143] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Inhibitory interneurons are an important source of synaptic inputs that may contribute to network mechanisms for coding of spatial location by entorhinal cortex (EC). The intrinsic properties of inhibitory interneurons in the EC of the mouse are mostly undescribed. Intrinsic properties were recorded from known cell types, such as, stellate and pyramidal cells and 6 classes of molecularly identified interneurons (regulator of calcineurin 2, somatostatin, serotonin receptor 3a, neuropeptide Y neurogliaform (NGF), neuropeptide Y non-NGF, and vasoactive intestinal protein) in acute brain slices. We report a broad physiological diversity between and within cell classes. We also found differences in the ability to produce postinhibitory rebound spikes and in the frequency and amplitude of incoming EPSPs. To understand the source of this intrinsic variability we applied hierarchical cluster analysis to functionally classify neurons. These analyses revealed physiologically derived cell types in EC that mostly corresponded to the lines identified by biomarkers with a few unexpected and important differences. Finally, we reduced the complex multidimensional space of intrinsic properties to the most salient five that predicted the cellular biomolecular identity with 81.4% accuracy. These results provide a framework for the classification of functional subtypes of cortical neurons by their intrinsic membrane properties.
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Affiliation(s)
- Michele Ferrante
- Center for Memory and Brain.,Center for Systems Neuroscience.,Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Babak Tahvildari
- Department of Neurobiology.,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520-8001, USA
| | - Alvaro Duque
- Department of Neurobiology.,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520-8001, USA
| | - Muhamed Hadzipasic
- Interdepartmental Program in Neuroscience, Yale School of Medicine, New Haven, CT 06520-8001, USA
| | - David Salkoff
- Department of Neurobiology.,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520-8001, USA
| | - Edward William Zagha
- Department of Neurobiology.,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520-8001, USA
| | - Michael E Hasselmo
- Center for Memory and Brain.,Center for Systems Neuroscience.,Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - David A McCormick
- Department of Neurobiology.,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520-8001, USA
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Fernandez FR, Rahsepar B, White JA. Differences in the Electrophysiological Properties of Mouse Somatosensory Layer 2/3 Neurons In Vivo and Slice Stem from Intrinsic Sources Rather than a Network-Generated High Conductance State. eNeuro 2018; 5:ENEURO.0447-17.2018. [PMID: 29662946 PMCID: PMC5898699 DOI: 10.1523/eneuro.0447-17.2018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 03/01/2018] [Accepted: 03/20/2018] [Indexed: 01/29/2023] Open
Abstract
Synaptic activity in vivo can potentially alter the integration properties of neurons. Using recordings in awake mice, we targeted somatosensory layer 2/3 pyramidal neurons and compared neuronal properties with those from slices. Pyramidal cells in vivo had lower resistance and gain values, as well as broader spikes and increased spike frequency adaptation compared to the same cells in slices. Increasing conductance in neurons using dynamic clamp to levels observed in vivo, however, did not lessen the differences between in vivo and slice conditions. Further, local application of tetrodotoxin (TTX) in vivo blocked synaptic-mediated membrane voltage fluctuations but had little impact on pyramidal cell membrane input resistance and time constant values. Differences in electrophysiological properties of layer 2/3 neurons in mouse somatosensory cortex, therefore, stem from intrinsic sources separate from synaptic-mediated membrane voltage fluctuations.
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Affiliation(s)
- Fernando R Fernandez
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215
| | - Bahar Rahsepar
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215
| | - John A White
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215
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15
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Bonilla-Quintana M, Wedgwood KCA, O’Dea RD, Coombes S. An Analysis of Waves Underlying Grid Cell Firing in the Medial Enthorinal Cortex. JOURNAL OF MATHEMATICAL NEUROSCIENCE 2017; 7:9. [PMID: 28842863 PMCID: PMC5572897 DOI: 10.1186/s13408-017-0051-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Accepted: 08/08/2017] [Indexed: 06/07/2023]
Abstract
Layer II stellate cells in the medial enthorinal cortex (MEC) express hyperpolarisation-activated cyclic-nucleotide-gated (HCN) channels that allow for rebound spiking via an [Formula: see text] current in response to hyperpolarising synaptic input. A computational modelling study by Hasselmo (Philos. Trans. R. Soc. Lond. B, Biol. Sci. 369:20120523, 2013) showed that an inhibitory network of such cells can support periodic travelling waves with a period that is controlled by the dynamics of the [Formula: see text] current. Hasselmo has suggested that these waves can underlie the generation of grid cells, and that the known difference in [Formula: see text] resonance frequency along the dorsal to ventral axis can explain the observed size and spacing between grid cell firing fields. Here we develop a biophysical spiking model within a framework that allows for analytical tractability. We combine the simplicity of integrate-and-fire neurons with a piecewise linear caricature of the gating dynamics for HCN channels to develop a spiking neural field model of MEC. Using techniques primarily drawn from the field of nonsmooth dynamical systems we show how to construct periodic travelling waves, and in particular the dispersion curve that determines how wave speed varies as a function of period. This exhibits a wide range of long wavelength solutions, reinforcing the idea that rebound spiking is a candidate mechanism for generating grid cell firing patterns. Importantly we develop a wave stability analysis to show how the maximum allowed period is controlled by the dynamical properties of the [Formula: see text] current. Our theoretical work is validated by numerical simulations of the spiking model in both one and two dimensions.
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Affiliation(s)
- Mayte Bonilla-Quintana
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, University Park, NG7 2RD Nottingham, UK
| | - Kyle C. A. Wedgwood
- Centre for Biomedical Modelling and Analysis, University of Exeter, Living Systems Institute, Stocker Road, EX4 4QD Exeter, UK
| | - Reuben D. O’Dea
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, University Park, NG7 2RD Nottingham, UK
| | - Stephen Coombes
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, University Park, NG7 2RD Nottingham, UK
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Lőrincz A, Sárkány A. Semi-Supervised Learning of Cartesian Factors: A Top-Down Model of the Entorhinal Hippocampal Complex. Front Psychol 2017; 8:215. [PMID: 28270783 PMCID: PMC5318397 DOI: 10.3389/fpsyg.2017.00215] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2016] [Accepted: 02/03/2017] [Indexed: 01/27/2023] Open
Abstract
The existence of place cells (PCs), grid cells (GCs), border cells (BCs), and head direction cells (HCs) as well as the dependencies between them have been enigmatic. We make an effort to explain their nature by introducing the concept of Cartesian Factors. These factors have specific properties: (i) they assume and complement each other, like direction and position and (ii) they have localized discrete representations with predictive attractors enabling implicit metric-like computations. In our model, HCs make the distributed and local representation of direction. Predictive attractor dynamics on that network forms the Cartesian Factor "direction." We embed these HCs and idiothetic visual information into a semi-supervised sparse autoencoding comparator structure that compresses its inputs and learns PCs, the distributed local and direction independent (allothetic) representation of the Cartesian Factor of global space. We use a supervised, information compressing predictive algorithm and form direction sensitive (oriented) GCs from the learned PCs by means of an attractor-like algorithm. Since the algorithm can continue the grid structure beyond the region of the PCs, i.e., beyond its learning domain, thus the GCs and the PCs together form our metric-like Cartesian Factors of space. We also stipulate that the same algorithm can produce BCs. Our algorithm applies (a) a bag representation that models the "what system" and (b) magnitude ordered place cell activities that model either the integrate-and-fire mechanism, or theta phase precession, or both. We relate the components of the algorithm to the entorhinal-hippocampal complex and to its working. The algorithm requires both spatial and lifetime sparsification that may gain support from the two-stage memory formation of this complex.
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Hilscher MM, Leão RN, Edwards SJ, Leão KE, Kullander K. Chrna2-Martinotti Cells Synchronize Layer 5 Type A Pyramidal Cells via Rebound Excitation. PLoS Biol 2017; 15:e2001392. [PMID: 28182735 PMCID: PMC5300109 DOI: 10.1371/journal.pbio.2001392] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Accepted: 01/05/2017] [Indexed: 12/22/2022] Open
Abstract
Martinotti cells are the most prominent distal dendrite–targeting interneurons in the cortex, but their role in controlling pyramidal cell (PC) activity is largely unknown. Here, we show that the nicotinic acetylcholine receptor α2 subunit (Chrna2) specifically marks layer 5 (L5) Martinotti cells projecting to layer 1. Furthermore, we confirm that Chrna2-expressing Martinotti cells selectively target L5 thick-tufted type A PCs but not thin-tufted type B PCs. Using optogenetic activation and inhibition, we demonstrate how Chrna2-Martinotti cells robustly reset and synchronize type A PCs via slow rhythmic burst activity and rebound excitation. Moreover, using optical feedback inhibition, in which PC spikes controlled the firing of surrounding Chrna2-Martinotti cells, we found that neighboring PC spike trains became synchronized by Martinotti cell inhibition. Together, our results show that L5 Martinotti cells participate in defined cortical circuits and can synchronize PCs in a frequency-dependent manner. These findings suggest that Martinotti cells are pivotal for coordinated PC activity, which is involved in cortical information processing and cognitive control. Cognitive functions and information processing are linked to the coordination of neuronal events and activities. This coordination is achieved through the synchronization of neuronal signals within subnetworks. Local networks contain different types of nerve cells, each of them playing distinct roles in the synchronization mechanism. To understand how synchronization is initiated and maintained, we have identified one of the key players using genetic strategies; we have identified a subtype of nicotine receptors uniquely expressed in cortical Martinotti cells. Because of their architecture and connection properties, Martinotti cells are able to synchronize ongoing activity of unconnected pyramidal cells (PCs). We show that this mechanism only applies to one subtype of PCs, thereby demonstrating that Martinotti cell inhibition is not spread randomly. By testing optimal firing patterns of Martinotti cells, we are able to coordinate the firing of this specific PC subtype over longer periods of time, showing how one unique interneuron is contributing to information processing.
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Affiliation(s)
- Markus M. Hilscher
- Unit of Developmental Genetics, Department of Neuroscience, Uppsala University, Uppsala, Sweden
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
- * E-mail: (MMH); (KK)
| | - Richardson N. Leão
- Unit of Developmental Genetics, Department of Neuroscience, Uppsala University, Uppsala, Sweden
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Steven J. Edwards
- Unit of Developmental Genetics, Department of Neuroscience, Uppsala University, Uppsala, Sweden
| | - Katarina E. Leão
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Klas Kullander
- Unit of Developmental Genetics, Department of Neuroscience, Uppsala University, Uppsala, Sweden
- * E-mail: (MMH); (KK)
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