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Schapiro KA, Rittenberg JD, Kenngott M, Marder E. I h Block Reveals Separation of Timescales in Pyloric Rhythm Response to Temperature Changes in Cancewr borealis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.04.592541. [PMID: 38766157 PMCID: PMC11100622 DOI: 10.1101/2024.05.04.592541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Motor systems operate over a range of frequencies and relative timing (phase). We studied the contribution of the hyperpolarization-activated inward current (I h ) to frequency and phase in the pyloric rhythm of the stomatogastric ganglion (STG) of the crab, Cancer borealis as temperature was altered from 11°C to 21°C. Under control conditions, the frequency of the rhythm increased monotonically with temperature, while the phases of the pyloric dilator (PD), lateral pyloric (LP), and pyloric (PY) neurons remained constant. When we blocked I h with cesium (Cs + ) PD offset, LP onset, and LP offset were all phase advanced in Cs + at 11°C, and the latter two further advanced as temperature increased. In Cs + the steady state increase in pyloric frequency with temperature diminished and the Q 10 of the pyloric frequency dropped from ∼1.75 to ∼1.35. Unexpectedly in Cs + , the frequency displayed non-monotonic dynamics during temperature transitions; the frequency initially dropped as temperature increased, then rose once temperature stabilized, creating a characteristic "jag". Interestingly, these jags were still present during temperature transitions in Cs + when the pacemaker was isolated by picrotoxin, although the temperature-induced change in frequency recovered to control levels. Overall, these data suggest that I h plays an important role in the ability of this circuit to produce smooth transitory responses and persistent frequency increases by different mechanisms during temperature fluctuations.
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Branchi I. Uncovering the determinants of brain functioning, behavior and their interplay in the light of context. Eur J Neurosci 2024. [PMID: 38558227 DOI: 10.1111/ejn.16331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health.
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Affiliation(s)
- Igor Branchi
- Center for Behavioral Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy
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3
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Hampton D, Kedia S, Marder E. Alterations in network robustness upon simultaneous temperature and pH perturbations. J Neurophysiol 2024; 131:509-515. [PMID: 38264774 DOI: 10.1152/jn.00483.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 01/23/2024] [Accepted: 01/23/2024] [Indexed: 01/25/2024] Open
Abstract
Nervous systems have evolved to function consistently in the face of the normal environmental fluctuations experienced by animals. The stomatogastric nervous system (STNS) of the crab, Cancer borealis, produces a motor output that has been studied for its remarkable robustness in response to single global perturbations. Changes in environments, however, are often complex and multifactorial. Therefore, we studied the robustness of the pyloric network in the stomatogastric ganglion (STG) in response to simultaneous perturbations of temperature and pH. We compared the effects of elevated temperatures on the pyloric rhythm at control, acid, or base pHs. In each pH recordings were made at 11°C, and then the temperature was increased until the rhythms became disorganized ("crashed"). Pyloric burst frequencies and phase relationships showed minor differences between pH groups until reaching close to the crash temperatures. However, the temperatures at which the rhythms were disrupted were lower in the two extreme pH conditions. This indicates that one environmental stress can make an animal less resilient to a second stressor.NEW & NOTEWORTHY Resilience to environmental fluctuations is important for all animals. It is common that animals encounter multiple stressful events at the same time, the cumulative impacts of which are largely unknown. This study examines the effects of temperature and pH on the nervous system of crabs that live in the fluctuating environments of the Northern Atlantic Ocean. The ranges of tolerance to one perturbation, temperature, are reduced under the influence of a second, pH.
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Affiliation(s)
- David Hampton
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts, United States
| | - Sonal Kedia
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts, United States
| | - Eve Marder
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts, United States
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Reva M, Rössert C, Arnaudon A, Damart T, Mandge D, Tuncel A, Ramaswamy S, Markram H, Van Geit W. A universal workflow for creation, validation, and generalization of detailed neuronal models. PATTERNS (NEW YORK, N.Y.) 2023; 4:100855. [PMID: 38035193 PMCID: PMC10682753 DOI: 10.1016/j.patter.2023.100855] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/24/2023] [Accepted: 09/12/2023] [Indexed: 12/02/2023]
Abstract
Detailed single-neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools focus on a limited set of specific features characteristic of a single neuron. Here, we present a generalized automated workflow for the creation of robust electrical models and illustrate its performance by building cell models for the rat somatosensory cortex. Each model is based on a 3D morphological reconstruction and a set of ionic mechanisms. We use an evolutionary algorithm to optimize neuronal parameters to match the electrophysiological features extracted from experimental data. Then we validate the optimized models against additional stimuli and assess their generalizability on a population of similar morphologies. Compared to the state-of-the-art canonical models, our models show 5-fold improved generalizability. This versatile approach can be used to build robust models of any neuronal type.
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Affiliation(s)
- Maria Reva
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Christian Rössert
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Alexis Arnaudon
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Tanguy Damart
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Darshan Mandge
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Anıl Tuncel
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Srikanth Ramaswamy
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
- Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, School of Life Sciences, École polytechnique fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
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5
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Needs D, Wu T, Nguyen HX, Henriquez CS, Bursac N. Prokaryotic voltage-gated sodium channels are more effective than endogenous Na v1.5 channels in rescuing cardiac action potential conduction: an in silico study. Am J Physiol Heart Circ Physiol 2023; 325:H1178-H1192. [PMID: 37737736 PMCID: PMC10908372 DOI: 10.1152/ajpheart.00287.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 09/14/2023] [Accepted: 09/18/2023] [Indexed: 09/23/2023]
Abstract
Methods to augment Na+ current in cardiomyocytes hold potential for the treatment of various cardiac arrhythmias involving conduction slowing. Because the gene coding cardiac Na+ channel (Nav1.5) is too large to fit in a single adeno-associated virus (AAV) vector, new gene therapies are being developed to enhance endogenous Nav1.5 current (by overexpression of chaperon molecules or use of multiple AAV vectors) or to exogenously introduce prokaryotic voltage-gated Na+ channels (BacNav) whose gene size is significantly smaller than that of the Nav1.5. In this study, based on experimental measurements in heterologous expression systems, we developed an improved computational model of the BacNav channel, NavSheP D60A. We then compared in silico how NavSheP D60A expression vs. Nav1.5 augmentation affects the electrophysiology of cardiac tissue. We found that the incorporation of BacNav channels in both adult guinea pig and human cardiomyocyte models increased their excitability and reduced action potential duration. When compared with equivalent augmentation of Nav1.5 current in simulated settings of reduced tissue excitability, the addition of the BacNav current was superior in improving the safety of conduction under conditions of current source-load mismatch, reducing the vulnerability to unidirectional conduction block during premature pacing, preventing the instability and breakup of spiral waves, and normalizing the conduction and ECG in Brugada syndrome tissues with mutated Nav1.5. Overall, our studies show that compared with a potential enhancement of the endogenous Nav1.5 current, expression of the BacNav channels with their slower inactivation kinetics can provide greater anti-arrhythmic benefits in hearts with compromised action potential conduction.NEW & NOTEWORTHY Slow action potential conduction is a common cause of various cardiac arrhythmias; yet, current pharmacotherapies cannot augment cardiac conduction. This in silico study compared the efficacy of recently proposed antiarrhythmic gene therapy approaches that increase peak sodium current in cardiomyocytes. When compared with the augmentation of endogenous sodium current, expression of slower-inactivating bacterial sodium channels was superior in preventing conduction block and arrhythmia induction. These results further the promise of antiarrhythmic gene therapies targeting sodium channels.
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Affiliation(s)
- Daniel Needs
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States
| | - Tianyu Wu
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States
| | - Hung X Nguyen
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States
| | - Craig S Henriquez
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States
| | - Nenad Bursac
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States
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6
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Marder E. Individual Variability, Statistics, and the Resilience of Nervous Systems of Crabs and Humans to Temperature and Other Perturbations. eNeuro 2023; 10:ENEURO.0425-23.2023. [PMID: 37963654 PMCID: PMC10646886 DOI: 10.1523/eneuro.0425-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 10/23/2023] [Indexed: 11/16/2023] Open
Affiliation(s)
- Eve Marder
- Volen Center and Biology Department, Brandeis University, Waltham, MA 02454
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Marom S, Marder E. A biophysical perspective on the resilience of neuronal excitability across timescales. Nat Rev Neurosci 2023; 24:640-652. [PMID: 37620600 DOI: 10.1038/s41583-023-00730-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/27/2023] [Indexed: 08/26/2023]
Abstract
Neuronal membrane excitability must be resilient to perturbations that can take place over timescales from milliseconds to months (or even years in long-lived animals). A great deal of attention has been paid to classes of homeostatic mechanisms that contribute to long-term maintenance of neuronal excitability through processes that alter a key structural parameter: the number of ion channel proteins present at the neuronal membrane. However, less attention has been paid to the self-regulating 'automatic' mechanisms that contribute to neuronal resilience by virtue of the kinetic properties of ion channels themselves. Here, we propose that these two sets of mechanisms are complementary instantiations of feedback control, together enabling resilience on a wide range of temporal scales. We further point to several methodological and conceptual challenges entailed in studying these processes - both of which involve enmeshed feedback control loops - and consider the consequences of these mechanisms of resilience.
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Affiliation(s)
- Shimon Marom
- Faculty of Medicine, Technion - Institute of Technology, Haifa, Israel.
| | - Eve Marder
- Biology Department, Brandeis University, Waltham, MA, USA.
- Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA.
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8
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Jin H, Verma P, Jiang F, Nagarajan SS, Raj A. Bayesian inference of a spectral graph model for brain oscillations. Neuroimage 2023; 279:120278. [PMID: 37516373 PMCID: PMC10840584 DOI: 10.1016/j.neuroimage.2023.120278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/22/2023] [Accepted: 07/12/2023] [Indexed: 07/31/2023] Open
Abstract
The relationship between brain functional connectivity and structural connectivity has caught extensive attention of the neuroscience community, commonly inferred using mathematical modeling. Among many modeling approaches, spectral graph model (SGM) is distinctive as it has a closed-form solution of the wide-band frequency spectra of brain oscillations, requiring only global biophysically interpretable parameters. While SGM is parsimonious in parameters, the determination of SGM parameters is non-trivial. Prior works on SGM determine the parameters through a computational intensive annealing algorithm, which only provides a point estimate with no confidence intervals for parameter estimates. To fill this gap, we incorporate the simulation-based inference (SBI) algorithm and develop a Bayesian procedure for inferring the posterior distribution of the SGM parameters. Furthermore, using SBI dramatically reduces the computational burden for inferring the SGM parameters. We evaluate the proposed SBI-SGM framework on the resting-state magnetoencephalography recordings from healthy subjects and show that the proposed procedure has similar performance to the annealing algorithm in recovering power spectra and the spatial distribution of the alpha frequency band. In addition, we also analyze the correlations among the parameters and their uncertainty with the posterior distribution which cannot be done with annealing inference. These analyses provide a richer understanding of the interactions among biophysical parameters of the SGM. In general, the use of simulation-based Bayesian inference enables robust and efficient computations of generative model parameter uncertainties and may pave the way for the use of generative models in clinical translation applications.
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Affiliation(s)
- Huaqing Jin
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA
| | - Parul Verma
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA
| | - Fei Jiang
- Department of Epidemiology and Biostatistics University of California San Francisco, San Francisco, CA, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA.
| | - Ashish Raj
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA.
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9
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Jaquette J, Kedia S, Sander E, Touboul JD. Reliability and robustness of oscillations in some slow-fast chaotic systems. CHAOS (WOODBURY, N.Y.) 2023; 33:103135. [PMID: 37874881 PMCID: PMC10599791 DOI: 10.1063/5.0166846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 09/26/2023] [Indexed: 10/26/2023]
Abstract
A variety of nonlinear models of biological systems generate complex chaotic behaviors that contrast with biological homeostasis, the observation that many biological systems prove remarkably robust in the face of changing external or internal conditions. Motivated by the subtle dynamics of cell activity in a crustacean central pattern generator (CPG), this paper proposes a refinement of the notion of chaos that reconciles homeostasis and chaos in systems with multiple timescales. We show that systems displaying relaxation cycles while going through chaotic attractors generate chaotic dynamics that are regular at macroscopic timescales and are, thus, consistent with physiological function. We further show that this relative regularity may break down through global bifurcations of chaotic attractors such as crises, beyond which the system may also generate erratic activity at slow timescales. We analyze these phenomena in detail in the chaotic Rulkov map, a classical neuron model known to exhibit a variety of chaotic spike patterns. This leads us to propose that the passage of slow relaxation cycles through a chaotic attractor crisis is a robust, general mechanism for the transition between such dynamics. We validate this numerically in three other models: a simple model of the crustacean CPG neural network, a discrete cubic map, and a continuous flow.
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Affiliation(s)
| | | | - Evelyn Sander
- Department of Mathematical Sciences, George Mason University, Fairfax, Virginia 22030, USA
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10
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Borges FS, Protachevicz PR, Souza DLM, Bittencourt CF, Gabrick EC, Bentivoglio LE, Szezech JD, Batista AM, Caldas IL, Dura-Bernal S, Pena RFO. The Roles of Potassium and Calcium Currents in the Bistable Firing Transition. Brain Sci 2023; 13:1347. [PMID: 37759949 PMCID: PMC10527161 DOI: 10.3390/brainsci13091347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/13/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
Healthy brains display a wide range of firing patterns, from synchronized oscillations during slow-wave sleep to desynchronized firing during movement. These physiological activities coexist with periods of pathological hyperactivity in the epileptic brain, where neurons can fire in synchronized bursts. Most cortical neurons are pyramidal regular spiking (RS) cells with frequency adaptation and do not exhibit bursts in current-clamp experiments (in vitro). In this work, we investigate the transition mechanism of spike-to-burst patterns due to slow potassium and calcium currents, considering a conductance-based model of a cortical RS cell. The joint influence of potassium and calcium ion channels on high synchronous patterns is investigated for different synaptic couplings (gsyn) and external current inputs (I). Our results suggest that slow potassium currents play an important role in the emergence of high-synchronous activities, as well as in the spike-to-burst firing pattern transitions. This transition is related to the bistable dynamics of the neuronal network, where physiological asynchronous states coexist with pathological burst synchronization. The hysteresis curve of the coefficient of variation of the inter-spike interval demonstrates that a burst can be initiated by firing states with neuronal synchronization. Furthermore, we notice that high-threshold (IL) and low-threshold (IT) ion channels play a role in increasing and decreasing the parameter conditions (gsyn and I) in which bistable dynamics occur, respectively. For high values of IL conductance, a synchronous burst appears when neurons are weakly coupled and receive more external input. On the other hand, when the conductance IT increases, higher coupling and lower I are necessary to produce burst synchronization. In light of our results, we suggest that channel subtype-specific pharmacological interactions can be useful to induce transitions from pathological high bursting states to healthy states.
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Affiliation(s)
- Fernando S. Borges
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY 11203, USA
- Center for Mathematics, Computation and Cognition, Federal University of ABC, São Bernardo do Campo 09606-045, Brazil
| | | | - Diogo L. M. Souza
- Graduate Program in Science, State University of Ponta Grossa, Ponta Grossa 84010-330, Brazil
| | - Conrado F. Bittencourt
- Graduate Program in Science, State University of Ponta Grossa, Ponta Grossa 84010-330, Brazil
| | - Enrique C. Gabrick
- Graduate Program in Science, State University of Ponta Grossa, Ponta Grossa 84010-330, Brazil
| | - Lucas E. Bentivoglio
- Graduate Program in Science, State University of Ponta Grossa, Ponta Grossa 84010-330, Brazil
| | - José D. Szezech
- Graduate Program in Science, State University of Ponta Grossa, Ponta Grossa 84010-330, Brazil
- Department of Mathematics and Statistics, State University of Ponta Grossa, Ponta Grossa 84030-900, Brazil
| | - Antonio M. Batista
- Graduate Program in Science, State University of Ponta Grossa, Ponta Grossa 84010-330, Brazil
- Department of Mathematics and Statistics, State University of Ponta Grossa, Ponta Grossa 84030-900, Brazil
| | - Iberê L. Caldas
- Institute of Physics, University of São Paulo, São Paulo 05508-090, Brazil
| | - Salvador Dura-Bernal
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY 11203, USA
- Center for Biomedical Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Rodrigo F. O. Pena
- Department of Biological Sciences, Florida Atlantic University, Jupiter, FL 33458, USA
- Stiles-Nicholson Brain Institute, Florida Atlantic University, Jupiter, FL 33458, USA
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11
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Inibhunu H, Moradi Chameh H, Skinner F, Rich S, Valiante TA. Hyperpolarization-Activated Cation Channels Shape the Spiking Frequency Preference of Human Cortical Layer 5 Pyramidal Neurons. eNeuro 2023; 10:ENEURO.0215-23.2023. [PMID: 37567768 PMCID: PMC10467019 DOI: 10.1523/eneuro.0215-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/19/2023] [Accepted: 07/20/2023] [Indexed: 08/13/2023] Open
Abstract
Discerning the contribution of specific ionic currents to complex neuronal dynamics is a difficult, but important, task. This challenge is exacerbated in the human setting, although the widely characterized uniqueness of the human brain compared with preclinical models necessitates the direct study of human neurons. Neuronal spiking frequency preference is of particular interest given its role in rhythm generation and signal transmission in cortical circuits. Here, we combine the frequency-dependent gain (FDG), a measure of spiking frequency preference, and novel in silico analyses to dissect the contributions of individual ionic currents to the suprathreshold features of human layer 5 (L5) neurons captured by the FDG. We confirm that a contemporary model of such a neuron, primarily constrained to capture subthreshold activity driven by the hyperpolarization-activated cyclic nucleotide gated (h-) current, replicates key features of the in vitro FDG both with and without h-current activity. With the model confirmed as a viable approximation of the biophysical features of interest, we applied new analysis techniques to quantify the activity of each modeled ionic current in the moments before spiking, revealing unique dynamics of the h-current. These findings motivated patch-clamp recordings in analogous rodent neurons to characterize their FDG, which confirmed that a biophysically detailed model of these neurons captures key interspecies differences in the FDG. These differences are correlated with distinct contributions of the h-current to neuronal activity. Together, this interdisciplinary and multispecies study provides new insights directly relating the dynamics of the h-current to suprathreshold spiking frequency preference in human L5 neurons.
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Affiliation(s)
- Happy Inibhunu
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
| | - Homeira Moradi Chameh
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
| | - Frances Skinner
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
- Departments of Medicine, Neurology and Physiology, University of Toronto, Toronto, Ontario M5S 3H2, Canada
| | - Scott Rich
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
| | - Taufik A Valiante
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 1M8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3E2, Canada
- Electrical and Computer Engineering, University of Toronto, Toronto, Ontario M5S 3G4, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario M5T 1P5, Canada
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12
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Schneider M, Bird AD, Gidon A, Triesch J, Jedlicka P, Cuntz H. Biological complexity facilitates tuning of the neuronal parameter space. PLoS Comput Biol 2023; 19:e1011212. [PMID: 37399220 DOI: 10.1371/journal.pcbi.1011212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 05/24/2023] [Indexed: 07/05/2023] Open
Abstract
The electrical and computational properties of neurons in our brains are determined by a rich repertoire of membrane-spanning ion channels and elaborate dendritic trees. However, the precise reason for this inherent complexity remains unknown, given that simpler models with fewer ion channels are also able to functionally reproduce the behaviour of some neurons. Here, we stochastically varied the ion channel densities of a biophysically detailed dentate gyrus granule cell model to produce a large population of putative granule cells, comparing those with all 15 original ion channels to their reduced but functional counterparts containing only 5 ion channels. Strikingly, valid parameter combinations in the full models were dramatically more frequent at -6% vs. -1% in the simpler model. The full models were also more stable in the face of perturbations to channel expression levels. Scaling up the numbers of ion channels artificially in the reduced models recovered these advantages confirming the key contribution of the actual number of ion channel types. We conclude that the diversity of ion channels gives a neuron greater flexibility and robustness to achieve a target excitability.
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Affiliation(s)
- Marius Schneider
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in cooperation with the Max Planck Society, Frankfurt am Main, Germany
- ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany
- Faculty of Physics, Goethe University, Frankfurt/Main, Frankfurt am Main, Germany
| | - Alexander D Bird
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in cooperation with the Max Planck Society, Frankfurt am Main, Germany
- ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany
| | - Albert Gidon
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jochen Triesch
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
- Faculty of Physics, Goethe University, Frankfurt/Main, Frankfurt am Main, Germany
- Faculty of Computer Science and Mathematics, Goethe University, Frankfurt am Main, Germany
| | - Peter Jedlicka
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
- ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany
- Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University, Frankfurt am Main, Germany
| | - Hermann Cuntz
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in cooperation with the Max Planck Society, Frankfurt am Main, Germany
- ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany
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13
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Alonso LM, Rue MCP, Marder E. Gating of homeostatic regulation of intrinsic excitability produces cryptic long-term storage of prior perturbations. Proc Natl Acad Sci U S A 2023; 120:e2222016120. [PMID: 37339223 PMCID: PMC10293857 DOI: 10.1073/pnas.2222016120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 05/16/2023] [Indexed: 06/22/2023] Open
Abstract
Neurons and neuronal circuits must maintain their function throughout the life of the organism despite changing environments. Previous theoretical and experimental work suggests that neurons monitor their activity using intracellular calcium concentrations to regulate their intrinsic excitability. Models with multiple sensors can distinguish among different patterns of activity, but previous work using models with multiple sensors produced instabilities that lead the models' conductances to oscillate and then to grow without bound and diverge. We now introduce a nonlinear degradation term that explicitly prevents the maximal conductances to grow beyond a bound. We combine the sensors' signals into a master feedback signal that can be used to modulate the timescale of conductance evolution. Effectively, this means that the negative feedback can be gated on and off according to how far the neuron is from its target. The modified model recovers from multiple perturbations. Interestingly, depolarizing the models to the same membrane potential with current injection or with simulated high extracellular K+ produces different changes in conductances, arguing that caution must be used in interpreting manipulations that serve as a proxy for increased neuronal activity. Finally, these models accrue traces of prior perturbations that are not visible in their control activity after perturbation but that shape their responses to subsequent perturbations. These cryptic or hidden changes may provide insight into disorders such as posttraumatic stress disorder that only become visible in response to specific perturbations.
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Affiliation(s)
- Leandro M. Alonso
- Volen Center and Biology Department, Brandeis University, Waltham, MA02454
| | - Mara C. P. Rue
- Volen Center and Biology Department, Brandeis University, Waltham, MA02454
| | - Eve Marder
- Volen Center and Biology Department, Brandeis University, Waltham, MA02454
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14
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Hull JM, Denomme N, Yuan Y, Booth V, Isom LL. Heterogeneity of voltage gated sodium current density between neurons decorrelates spiking and suppresses network synchronization in Scn1b null mouse models. Sci Rep 2023; 13:8887. [PMID: 37264112 PMCID: PMC10235421 DOI: 10.1038/s41598-023-36036-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 05/28/2023] [Indexed: 06/03/2023] Open
Abstract
Voltage gated sodium channels (VGSCs) are required for action potential initiation and propagation in mammalian neurons. As with other ion channel families, VGSC density varies between neurons. Importantly, sodium current (INa) density variability is reduced in pyramidal neurons of Scn1b null mice. Scn1b encodes the VGSC β1/ β1B subunits, which regulate channel expression, trafficking, and voltage dependent properties. Here, we investigate how variable INa density in cortical layer 6 and subicular pyramidal neurons affects spike patterning and network synchronization. Constitutive or inducible Scn1b deletion enhances spike timing correlations between pyramidal neurons in response to fluctuating stimuli and impairs spike-triggered average current pattern diversity while preserving spike reliability. Inhibiting INa with a low concentration of tetrodotoxin similarly alters patterning without impairing reliability, with modest effects on firing rate. Computational modeling shows that broad INa density ranges confer a similarly broad spectrum of spike patterning in response to fluctuating synaptic conductances. Network coupling of neurons with high INa density variability displaces the coupling requirements for synchronization and broadens the dynamic range of activity when varying synaptic strength and network topology. Our results show that INa heterogeneity between neurons potently regulates spike pattern diversity and network synchronization, expanding VGSC roles in the nervous system.
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Affiliation(s)
- Jacob M Hull
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Nicholas Denomme
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yukun Yuan
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Victoria Booth
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Mathematics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lori L Isom
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA.
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15
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Glasgow NG, Chen Y, Korngreen A, Kass RE, Urban NN. A biophysical and statistical modeling paradigm for connecting neural physiology and function. J Comput Neurosci 2023; 51:263-282. [PMID: 37140691 PMCID: PMC10182162 DOI: 10.1007/s10827-023-00847-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 02/10/2023] [Accepted: 02/16/2023] [Indexed: 05/05/2023]
Abstract
To understand single neuron computation, it is necessary to know how specific physiological parameters affect neural spiking patterns that emerge in response to specific stimuli. Here we present a computational pipeline combining biophysical and statistical models that provides a link between variation in functional ion channel expression and changes in single neuron stimulus encoding. More specifically, we create a mapping from biophysical model parameters to stimulus encoding statistical model parameters. Biophysical models provide mechanistic insight, whereas statistical models can identify associations between spiking patterns and the stimuli they encode. We used public biophysical models of two morphologically and functionally distinct projection neuron cell types: mitral cells (MCs) of the main olfactory bulb, and layer V cortical pyramidal cells (PCs). We first simulated sequences of action potentials according to certain stimuli while scaling individual ion channel conductances. We then fitted point process generalized linear models (PP-GLMs), and we constructed a mapping between the parameters in the two types of models. This framework lets us detect effects on stimulus encoding of changing an ion channel conductance. The computational pipeline combines models across scales and can be applied as a screen of channels, in any cell type of interest, to identify ways that channel properties influence single neuron computation.
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Affiliation(s)
- Nathan G Glasgow
- Department of Neurobiology and Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Yu Chen
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alon Korngreen
- The Leslie and Susan Gonda Interdisciplinary Brain Research Centre, Bar-Ilan University, Ramat Gan, Israel
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
| | - Robert E Kass
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA.
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Nathan N Urban
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
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16
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Naudin L. Different parameter solutions of a conductance-based model that behave identically are not necessarily degenerate. J Comput Neurosci 2023; 51:201-206. [PMID: 36905484 DOI: 10.1007/s10827-023-00848-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 02/13/2023] [Accepted: 02/22/2023] [Indexed: 03/12/2023]
Affiliation(s)
- Loïs Naudin
- Laboratoire Lorrain de Recherche en Informatique et ses Applications, CNRS, Université de Lorraine, Nancy, France. .,Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, F-75012, France.
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17
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Jin H, Verma P, Jiang F, Nagarajan S, Raj A. Bayesian Inference of a Spectral Graph Model for Brain Oscillations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.01.530704. [PMID: 36909647 PMCID: PMC10002745 DOI: 10.1101/2023.03.01.530704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
Abstract
The relationship between brain functional connectivity and structural connectivity has caught extensive attention of the neuroscience community, commonly inferred using mathematical modeling. Among many modeling approaches, spectral graph model (SGM) is distinctive as it has a closed-form solution of the wide-band frequency spectra of brain oscillations, requiring only global biophysically interpretable parameters. While SGM is parsimonious in parameters, the determination of SGM parameters is non-trivial. Prior works on SGM determine the parameters through a computational intensive annealing algorithm, which only provides a point estimate with no confidence intervals for parameter estimates. To fill this gap, we incorporate the simulation-based inference (SBI) algorithm and develop a Bayesian procedure for inferring the posterior distribution of the SGM parameters. Furthermore, using SBI dramatically reduces the computational burden for inferring the SGM parameters. We evaluate the proposed SBI-SGM framework on the resting-state magnetoencephalography recordings from healthy subjects and show that the proposed procedure has similar performance to the annealing algorithm in recovering power spectra and the spatial distribution of the alpha frequency band. In addition, we also analyze the correlations among the parameters and their uncertainty with the posterior distribution which can not be done with annealing inference. These analyses provide a richer understanding of the interactions among biophysical parameters of the SGM. In general, the use of simulation-based Bayesian inference enables robust and efficient computations of generative model parameter uncertainties and may pave the way for the use of generative models in clinical translation applications.
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Affiliation(s)
- Huaqing Jin
- Department of Radiology and Biomedical Imaging, University of California San Francisco, USA San Francisco, CA
| | - Parul Verma
- Department of Radiology and Biomedical Imaging, University of California San Francisco, USA San Francisco, CA
| | - Fei Jiang
- Department of Epidemiology and Biostatistics, University of California San Francisco, USA San Francisco, CA
| | - Srikantan Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, USA San Francisco, CA
| | - Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California San Francisco, USA San Francisco, CA
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18
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Zang Y, Marder E. Neuronal morphology enhances robustness to perturbations of channel densities. Proc Natl Acad Sci U S A 2023; 120:e2219049120. [PMID: 36787352 PMCID: PMC9974411 DOI: 10.1073/pnas.2219049120] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/14/2023] [Indexed: 02/15/2023] Open
Abstract
Biological neurons show significant cell-to-cell variability but have the striking ability to maintain their key firing properties in the face of unpredictable perturbations and stochastic noise. Using a population of multi-compartment models consisting of soma, neurites, and axon for the lateral pyloric neuron in the crab stomatogastric ganglion, we explore how rebound bursting is preserved when the 14 channel conductances in each model are all randomly varied. The coupling between the axon and other compartments is critical for the ability of the axon to spike during bursts and consequently determines the set of successful solutions. When the coupling deviates from a biologically realistic range, the neuronal tolerance of conductance variations is lessened. Thus, the gross morphological features of these neurons enhance their robustness to perturbations of channel densities and expand the space of individual variability that can maintain a desired output pattern.
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Affiliation(s)
- Yunliang Zang
- Volen Center, Brandeis University, Waltham, MA02454
- Department of Biology, Brandeis University, Waltham, MA02454
| | - Eve Marder
- Volen Center, Brandeis University, Waltham, MA02454
- Department of Biology, Brandeis University, Waltham, MA02454
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19
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Naudin L, Raison-Aubry L, Buhry L. A general pattern of non-spiking neuron dynamics under the effect of potassium and calcium channel modifications. J Comput Neurosci 2023; 51:173-186. [PMID: 36371576 DOI: 10.1007/s10827-022-00840-w] [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: 07/04/2022] [Revised: 10/08/2022] [Accepted: 11/02/2022] [Indexed: 11/13/2022]
Abstract
Electrical activity of excitable cells results from ion exchanges through cell membranes, so that genetic or epigenetic changes in genes encoding ion channels are likely to affect neuronal electrical signaling throughout the brain. There is a large literature on the effect of variations in ion channels on the dynamics of spiking neurons that represent the main type of neurons found in the vertebrate nervous systems. Nevertheless, non-spiking neurons are also ubiquitous in many nervous tissues and play a critical role in the processing of some sensory systems. To our knowledge, however, how conductance variations affect the dynamics of non-spiking neurons has never been assessed. Based on experimental observations reported in the biological literature and on mathematical considerations, we first propose a phenotypic classification of non-spiking neurons. Then, we determine a general pattern of the phenotypic evolution of non-spiking neurons as a function of changes in calcium and potassium conductances. Furthermore, we study the homeostatic compensatory mechanisms of ion channels in a well-posed non-spiking retinal cone model. We show that there is a restricted range of ion conductance values for which the behavior and phenotype of the neuron are maintained. Finally, we discuss the implications of the phenotypic changes of individual cells at the level of neuronal network functioning of the C. elegans worm and the retina, which are two non-spiking nervous tissues composed of neurons with various phenotypes.
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Affiliation(s)
- Loïs Naudin
- Laboratoire Lorrain de Recherche en Informatique et ses Applications, CNRS, Université de Lorraine, Nancy, France.
| | - Laetitia Raison-Aubry
- Laboratoire Lorrain de Recherche en Informatique et ses Applications, CNRS, Université de Lorraine, Nancy, France
| | - Laure Buhry
- Laboratoire Lorrain de Recherche en Informatique et ses Applications, CNRS, Université de Lorraine, Nancy, France.
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20
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Energy-efficient network activity from disparate circuit parameters. Proc Natl Acad Sci U S A 2022; 119:e2207632119. [PMID: 36279461 PMCID: PMC9636970 DOI: 10.1073/pnas.2207632119] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Neural circuits can produce similar activity patterns from vastly different combinations of channel and synaptic conductances. These conductances are tuned for specific activity patterns but might also reflect additional constraints, such as metabolic cost or robustness to perturbations. How do such constraints influence the range of permissible conductances? Here we investigate how metabolic cost affects the parameters of neural circuits with similar activity in a model of the pyloric network of the crab
Cancer borealis
. We present a machine learning method that can identify a range of network models that generate activity patterns matching experimental data and find that neural circuits can consume largely different amounts of energy despite similar circuit activity. Furthermore, a reduced but still significant range of circuit parameters gives rise to energy-efficient circuits. We then examine the space of parameters of energy-efficient circuits and identify potential tuning strategies for low metabolic cost. Finally, we investigate the interaction between metabolic cost and temperature robustness. We show that metabolic cost can vary across temperatures but that robustness to temperature changes does not necessarily incur an increased metabolic cost. Our analyses show that despite metabolic efficiency and temperature robustness constraining circuit parameters, neural systems can generate functional, efficient, and robust network activity with widely disparate sets of conductances.
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21
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Wang YC, Rudi J, Velasco J, Sinha N, Idumah G, Powers RK, Heckman CJ, Chardon MK. Multimodal parameter spaces of a complex multi-channel neuron model. Front Syst Neurosci 2022; 16:999531. [PMID: 36341477 PMCID: PMC9632740 DOI: 10.3389/fnsys.2022.999531] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/28/2022] [Indexed: 08/21/2023] Open
Abstract
One of the most common types of models that helps us to understand neuron behavior is based on the Hodgkin-Huxley ion channel formulation (HH model). A major challenge with inferring parameters in HH models is non-uniqueness: many different sets of ion channel parameter values produce similar outputs for the same input stimulus. Such phenomena result in an objective function that exhibits multiple modes (i.e., multiple local minima). This non-uniqueness of local optimality poses challenges for parameter estimation with many algorithmic optimization techniques. HH models additionally have severe non-linearities resulting in further challenges for inferring parameters in an algorithmic fashion. To address these challenges with a tractable method in high-dimensional parameter spaces, we propose using a particular Markov chain Monte Carlo (MCMC) algorithm, which has the advantage of inferring parameters in a Bayesian framework. The Bayesian approach is designed to be suitable for multimodal solutions to inverse problems. We introduce and demonstrate the method using a three-channel HH model. We then focus on the inference of nine parameters in an eight-channel HH model, which we analyze in detail. We explore how the MCMC algorithm can uncover complex relationships between inferred parameters using five injected current levels. The MCMC method provides as a result a nine-dimensional posterior distribution, which we analyze visually with solution maps or landscapes of the possible parameter sets. The visualized solution maps show new complex structures of the multimodal posteriors, and they allow for selection of locally and globally optimal value sets, and they visually expose parameter sensitivities and regions of higher model robustness. We envision these solution maps as enabling experimentalists to improve the design of future experiments, increase scientific productivity and improve on model structure and ideation when the MCMC algorithm is applied to experimental data.
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Affiliation(s)
- Y. Curtis Wang
- Department of Electrical and Computer Engineering, California State University, Los Angeles, Los Angeles, CA, United States
| | - Johann Rudi
- Department of Mathematics, Virginia Tech, Blacksburg, VA, United States
| | - James Velasco
- Department of Electrical and Computer Engineering, California State University, Los Angeles, Los Angeles, CA, United States
| | - Nirvik Sinha
- Interdepartmental Neuroscience, Northwestern University, Chicago, IL, United States
| | - Gideon Idumah
- Department of Mathematics, Case Western Reserve University, Cleveland, OH, United States
| | - Randall K. Powers
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, United States
| | - Charles J. Heckman
- Department of Neuroscience, Northwestern University, Chicago, IL, United States
- Physical Medicine and Rehabilitation, Shirley Ryan Ability Lab, Chicago, IL, United States
- Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States
| | - Matthieu K. Chardon
- Department of Neuroscience, Northwestern University, Chicago, IL, United States
- Northwestern-Argonne Institute of Science and Engineering, Evanston, IL, United States
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22
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Marder E, Kedia S, Morozova EO. New insights from small rhythmic circuits. Curr Opin Neurobiol 2022; 76:102610. [PMID: 35986971 DOI: 10.1016/j.conb.2022.102610] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/20/2022] [Accepted: 06/28/2022] [Indexed: 11/30/2022]
Abstract
Small rhythmic circuits, such as those found in invertebrates, have provided fundamental insights into how circuit dynamics depend on individual neuronal and synaptic properties. Degenerate circuits are those with different network parameters and similar behavior. New work on degenerate circuits and their modulation illustrates some of the rules that help maintain stable and robust circuit function despite environmental perturbations. Advances in neuropeptide isolation and identification provide enhanced understanding of the neuromodulation of circuits for behavior. The advent of molecular studies of mRNA expression provides new insight into animal-to-animal variability and the homeostatic regulation of excitability in neurons and networks.
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Affiliation(s)
- Eve Marder
- Volen Center and Biology Department, Brandeis University, Waltham, MA 02454, USA
| | - Sonal Kedia
- Volen Center and Biology Department, Brandeis University, Waltham, MA 02454, USA. https://twitter.com/Sonal_Kedia
| | - Ekaterina O Morozova
- Volen Center and Biology Department, Brandeis University, Waltham, MA 02454, USA.
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23
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Rue MC, Alonso LM, Marder E. Repeated applications of high potassium elicit long-term changes in a motor circuit from the crab, Cancer borealis. iScience 2022; 25:104919. [PMID: 36060056 PMCID: PMC9436765 DOI: 10.1016/j.isci.2022.104919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 07/12/2022] [Accepted: 08/08/2022] [Indexed: 12/04/2022] Open
Abstract
We examined the effects of altered extracellular potassium concentration on the output of the well-studied pyloric circuit in the crab, Cancer borealis. Pyloric neurons initially become quiescent, then recover spiking and bursting activity in high potassium saline (2.5x[K+]). These changes in circuit robustness are maintained after the perturbation is removed; pyloric neurons are more robust to subsequent potassium perturbations even after several hours of wash in control saline. Despite this long-term "memory" of the stimulus history, we found no differences in neuronal activity in control saline. The circuit's adaptation is erased by both low potassium saline (0.4x[K+]) and direct hyperpolarizing current. Initial sensitivity of PD neurons to high potassium saline also varies seasonally, indicating that changes in robustness may reflect natural changes in circuit states. Thus, perturbation, followed by recovery of normal activity, can hide cryptic changes in neuronal properties that are only revealed by subsequent challenges.
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Affiliation(s)
- Mara C.P. Rue
- Biology Department and Volen Center, Brandeis University, Waltham, MA 02454, USA
| | - Leandro M. Alonso
- Biology Department and Volen Center, Brandeis University, Waltham, MA 02454, USA
| | - Eve Marder
- Biology Department and Volen Center, Brandeis University, Waltham, MA 02454, USA,Corresponding author
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24
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Huygens synchronization of medial septal pacemaker neurons generates hippocampal theta oscillation. Cell Rep 2022; 40:111149. [PMID: 35926456 DOI: 10.1016/j.celrep.2022.111149] [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: 01/22/2021] [Revised: 05/06/2022] [Accepted: 07/07/2022] [Indexed: 11/21/2022] Open
Abstract
Episodic learning and memory retrieval are dependent on hippocampal theta oscillation, thought to rely on the GABAergic network of the medial septum (MS). To test how this network achieves theta synchrony, we recorded MS neurons and hippocampal local field potential simultaneously in anesthetized and awake mice and rats. We show that MS pacemakers synchronize their individual rhythmicity frequencies, akin to coupled pendulum clocks as observed by Huygens. We optogenetically identified them as parvalbumin-expressing GABAergic neurons, while MS glutamatergic neurons provide tonic excitation sufficient to induce theta. In accordance, waxing and waning tonic excitation is sufficient to toggle between theta and non-theta states in a network model of single-compartment inhibitory pacemaker neurons. These results provide experimental and theoretical support to a frequency-synchronization mechanism for pacing hippocampal theta, which may serve as an inspirational prototype for synchronization processes in the central nervous system from Nematoda to Arthropoda to Chordate and Vertebrate phyla.
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25
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Linaro D, Levy MJ, Hunt DL. Cell type-specific mechanisms of information transfer in data-driven biophysical models of hippocampal CA3 principal neurons. PLoS Comput Biol 2022; 18:e1010071. [PMID: 35452457 PMCID: PMC9089861 DOI: 10.1371/journal.pcbi.1010071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 05/10/2022] [Accepted: 03/31/2022] [Indexed: 11/19/2022] Open
Abstract
The transformation of synaptic input into action potential output is a fundamental single-cell computation resulting from the complex interaction of distinct cellular morphology and the unique expression profile of ion channels that define the cellular phenotype. Experimental studies aimed at uncovering the mechanisms of the transfer function have led to important insights, yet are limited in scope by technical feasibility, making biophysical simulations an attractive complementary approach to push the boundaries in our understanding of cellular computation. Here we take a data-driven approach by utilizing high-resolution morphological reconstructions and patch-clamp electrophysiology data together with a multi-objective optimization algorithm to build two populations of biophysically detailed models of murine hippocampal CA3 pyramidal neurons based on the two principal cell types that comprise this region. We evaluated the performance of these models and find that our approach quantitatively matches the cell type-specific firing phenotypes and recapitulate the intrinsic population-level variability in the data. Moreover, we confirm that the conductance values found by the optimization algorithm are consistent with differentially expressed ion channel genes in single-cell transcriptomic data for the two cell types. We then use these models to investigate the cell type-specific biophysical properties involved in the generation of complex-spiking output driven by synaptic input through an information-theoretic treatment of their respective transfer functions. Our simulations identify a host of cell type-specific biophysical mechanisms that define the morpho-functional phenotype to shape the cellular transfer function and place these findings in the context of a role for bursting in CA3 recurrent network synchronization dynamics. The hippocampus is comprised of numerous types of neurons, which constitute the cellular substrate for its rich repertoire of network dynamics. Among these are sharp waves, sequential activations of ensembles of neurons that have been shown to be crucially involved in learning and memory. In the CA3 area of the hippocampus, two types of excitatory cells, thorny and a-thorny neurons, are preferentially active during distinct phases of a sharp wave, suggesting a differential role for these cell types in phenomena such as memory consolidation. Using a strictly data-driven approach, we built biophysically realistic models of both thorny and a-thorny cells and used them to investigate the integrative differences between these two cell types. We found that both neuron classes have the capability of integrating incoming synaptic inputs in a supralinear fashion, although only a-thorny cells respond with bursts of action potentials to spatially and temporally clustered synaptic inputs. Additionally, by using a computational approach based on information theory, we show that, owing to this propensity for bursting, a-thorny cells can encode more information in their spiking output than their thorny counterpart. These results shed new light on the computational capabilities of two types of excitatory neurons and suggest that thorny and a-thorny cells may play distinct roles in the generation of hippocampal network synchronization.
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Affiliation(s)
- Daniele Linaro
- Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy
- * E-mail: (DL); (DLH)
| | - Matthew J. Levy
- Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, United State of America
| | - David L. Hunt
- Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, United State of America
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, United State of America
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, United State of America
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, United State of America
- * E-mail: (DL); (DLH)
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26
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Gorur-Shandilya S, Cronin EM, Schneider AC, Haddad SA, Rosenbaum P, Bucher D, Nadim F, Marder E. Mapping circuit dynamics during function and dysfunction. eLife 2022; 11:e76579. [PMID: 35302489 PMCID: PMC9000962 DOI: 10.7554/elife.76579] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
Neural circuits can generate many spike patterns, but only some are functional. The study of how circuits generate and maintain functional dynamics is hindered by a poverty of description of circuit dynamics across functional and dysfunctional states. For example, although the regular oscillation of a central pattern generator is well characterized by its frequency and the phase relationships between its neurons, these metrics are ineffective descriptors of the irregular and aperiodic dynamics that circuits can generate under perturbation or in disease states. By recording the circuit dynamics of the well-studied pyloric circuit in Cancer borealis, we used statistical features of spike times from neurons in the circuit to visualize the spike patterns generated by this circuit under a variety of conditions. This approach captures both the variability of functional rhythms and the diversity of atypical dynamics in a single map. Clusters in the map identify qualitatively different spike patterns hinting at different dynamic states in the circuit. State probability and the statistics of the transitions between states varied with environmental perturbations, removal of descending neuromodulatory inputs, and the addition of exogenous neuromodulators. This analysis reveals strong mechanistically interpretable links between complex changes in the collective behavior of a neural circuit and specific experimental manipulations, and can constrain hypotheses of how circuits generate functional dynamics despite variability in circuit architecture and environmental perturbations.
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Affiliation(s)
| | - Elizabeth M Cronin
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers UniversityNewarkUnited States
| | - Anna C Schneider
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers UniversityNewarkUnited States
| | - Sara Ann Haddad
- Volen Center and Biology Department, Brandeis UniversityWalthamUnited States
| | - Philipp Rosenbaum
- Volen Center and Biology Department, Brandeis UniversityWalthamUnited States
| | - Dirk Bucher
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers UniversityNewarkUnited States
| | - Farzan Nadim
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers UniversityNewarkUnited States
| | - Eve Marder
- Volen Center and Biology Department, Brandeis UniversityWalthamUnited States
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27
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Abstract
A hallmark of adaptation in humans and other animals is our ability to control how we think and behave across different settings. Research has characterized the various forms cognitive control can take-including enhancement of goal-relevant information, suppression of goal-irrelevant information, and overall inhibition of potential responses-and has identified computations and neural circuits that underpin this multitude of control types. Studies have also identified a wide range of situations that elicit adjustments in control allocation (e.g., those eliciting signals indicating an error or increased processing conflict), but the rules governing when a given situation will give rise to a given control adjustment remain poorly understood. Significant progress has recently been made on this front by casting the allocation of control as a decision-making problem. This approach has developed unifying and normative models that prescribe when and how a change in incentives and task demands will result in changes in a given form of control. Despite their successes, these models, and the experiments that have been developed to test them, have yet to face their greatest challenge: deciding how to select among the multiplicity of configurations that control can take at any given time. Here, we will lay out the complexities of the inverse problem inherent to cognitive control allocation, and their close parallels to inverse problems within motor control (e.g., choosing between redundant limb movements). We discuss existing solutions to motor control's inverse problems drawn from optimal control theory, which have proposed that effort costs act to regularize actions and transform motor planning into a well-posed problem. These same principles may help shed light on how our brains optimize over complex control configuration, while providing a new normative perspective on the origins of mental effort.
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28
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A design principle of spindle oscillations in mammalian sleep. iScience 2022; 25:103873. [PMID: 35243235 PMCID: PMC8861656 DOI: 10.1016/j.isci.2022.103873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 01/07/2022] [Accepted: 02/01/2022] [Indexed: 11/22/2022] Open
Abstract
Neural oscillations are mainly regulated by molecular mechanisms and network connectivity of neurons. Large-scale simulations of neuronal networks have driven the population-level understanding of neural oscillations. However, cell-intrinsic mechanisms, especially a design principle, of neural oscillations remain largely elusive. Herein, we developed a minimal, Hodgkin-Huxley-type model of groups of neurons to investigate molecular mechanisms underlying spindle oscillation, which is synchronized oscillatory activity predominantly observed during mammalian sleep. We discovered that slowly inactivating potassium channels played an essential role in characterizing the firing pattern. The detailed analysis of the minimal model revealed that leak sodium and potassium channels, which controlled passive properties of the fast variable (i.e., membrane potential), competitively regulated the base value and time constant of the slow variable (i.e., cytosolic calcium concentration). Consequently, we propose a theoretical design principle of spindle oscillations that may explain intracellular mechanisms behind the flexible control over oscillation density and calcium setpoint. A minimal, Hodgkin-Huxley-type model of spindle oscillations is developed The property of delayed rectifier K+ channels characterizes spindle oscillations The combination of bifurcations specifies spindle oscillations Spindle oscillations are controlled by the balance of inward and outward currents
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29
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Elmasri M, Hunter DW, Winchester G, Bates EE, Aziz W, Van Der Does DM, Karachaliou E, Sakimura K, Penn AC. Common synaptic phenotypes arising from diverse mutations in the human NMDA receptor subunit GluN2A. Commun Biol 2022; 5:174. [PMID: 35228668 PMCID: PMC8885697 DOI: 10.1038/s42003-022-03115-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 01/31/2022] [Indexed: 02/06/2023] Open
Abstract
Dominant mutations in the human gene GRIN2A, encoding NMDA receptor (NMDAR) subunit GluN2A, make a significant and growing contribution to the catalogue of published single-gene epilepsies. Understanding the disease mechanism in these epilepsy patients is complicated by the surprising diversity of effects that the mutations have on NMDARs. Here we have examined the cell-autonomous effect of five GluN2A mutations, 3 loss-of-function and 2 gain-of-function, on evoked NMDAR-mediated synaptic currents (NMDA-EPSCs) in CA1 pyramidal neurons in cultured hippocampal slices. Despite the mutants differing in their functional incorporation at synapses, prolonged NMDA-EPSC current decays (with only marginal changes in charge transfer) were a common effect for both gain- and loss-of-function mutants. Modelling NMDA-EPSCs with mutant properties in a CA1 neuron revealed that the effect of GRIN2A mutations can lead to abnormal temporal integration and spine calcium dynamics during trains of concerted synaptic activity. Investigations beyond establishing the molecular defects of GluN2A mutants are much needed to understand their impact on synaptic transmission. The cell-autonomous effect of five severe loss- or gain-of-function GluN2A (NMDA receptor) mutations is assessed on evoked NMDAR-mediated synaptic currents in CA1 pyramidal neurons in cultured mouse hippocampal slices. Data and modelling suggest that mutant-like NMDA-EPSCs can lead to abnormal temporal summation and spine calcium dynamics.
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Affiliation(s)
- Marwa Elmasri
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK
| | - Daniel William Hunter
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK
| | - Giles Winchester
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK
| | - Ella Emine Bates
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK
| | - Wajeeha Aziz
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK
| | | | - Eirini Karachaliou
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK
| | - Kenji Sakimura
- Department of Cellular Neurobiology, Brain Research Institute, Niigata University, Niigata, 951-8585, Japan
| | - Andrew Charles Penn
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK.
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30
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Ben-Shalom R, Ladd A, Artherya NS, Cross C, Kim KG, Sanghevi H, Korngreen A, Bouchard KE, Bender KJ. NeuroGPU: Accelerating multi-compartment, biophysically detailed neuron simulations on GPUs. J Neurosci Methods 2022; 366:109400. [PMID: 34728257 PMCID: PMC9887806 DOI: 10.1016/j.jneumeth.2021.109400] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 10/09/2021] [Accepted: 10/27/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND The membrane potential of individual neurons depends on a large number of interacting biophysical processes operating on spatial-temporal scales spanning several orders of magnitude. The multi-scale nature of these processes dictates that accurate prediction of membrane potentials in specific neurons requires the utilization of detailed simulations. Unfortunately, constraining parameters within biologically detailed neuron models can be difficult, leading to poor model fits. This obstacle can be overcome partially by numerical optimization or detailed exploration of parameter space. However, these processes, which currently rely on central processing unit (CPU) computation, often incur orders of magnitude increases in computing time for marginal improvements in model behavior. As a result, model quality is often compromised to accommodate compute resources. NEW METHOD Here, we present a simulation environment, NeuroGPU, that takes advantage of the inherent parallelized structure of the graphics processing unit (GPU) to accelerate neuronal simulation. RESULTS & COMPARISON WITH EXISTING METHODS NeuroGPU can simulate most biologically detailed models 10-200 times faster than NEURON simulation running on a single core and 5 times faster than GPU simulators (CoreNEURON). NeuroGPU is designed for model parameter tuning and best performs when the GPU is fully utilized by running multiple (> 100) instances of the same model with different parameters. When using multiple GPUs, NeuroGPU can reach to a speed-up of 800 fold compared to single core simulations, especially when simulating the same model morphology with different parameters. We demonstrate the power of NeuoGPU through large-scale parameter exploration to reveal the response landscape of a neuron. Finally, we accelerate numerical optimization of biophysically detailed neuron models to achieve highly accurate fitting of models to simulation and experimental data. CONCLUSIONS Thus, NeuroGPU is the fastest available platform that enables rapid simulation of multi-compartment, biophysically detailed neuron models on commonly used computing systems accessible by many scientists.
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Affiliation(s)
- Roy Ben-Shalom
- Weill Institute for Neurosciences, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States,Department of Neurology, University of California, San Francisco, San Francisco, CA, United States,MIND Institute University of California, Davis, CA, United States,Computational Research Division, Lawrence Berkeley National Lab, Berkeley, CA, United States,Correspondence to: University of California, Davis MIND Institute Wet Lab 2805 50th Street, Room 2460 Sacramento, CA 95817, United States., (R. Ben-Shalom), (K.J. Bender)
| | - Alexander Ladd
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, United States
| | - Nikhil S. Artherya
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, United States
| | - Christopher Cross
- Weill Institute for Neurosciences, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Kyung Geun Kim
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, United States
| | - Hersh Sanghevi
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, United States
| | - Alon Korngreen
- The Leslie and Susan Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel,The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel
| | - Kristofer E. Bouchard
- Computational Research Division, Lawrence Berkeley National Lab, Berkeley, CA, United States,Hellen Wills Neuroscience Institute & Redwood Center for Theoretical Neuroscience, University of California, Berkeley, Berkeley, CA, United States,Biological Systems and Engineering Division, Lawrence Berkeley National Lab, Berkeley, CA, United States
| | - Kevin J. Bender
- Weill Institute for Neurosciences, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States,Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
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31
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Marder E, Rue MCP. From the Neuroscience of Individual Variability to Climate Change. J Neurosci 2021; 41:10213-10221. [PMID: 34753741 PMCID: PMC8672684 DOI: 10.1523/jneurosci.1261-21.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/28/2021] [Accepted: 11/01/2021] [Indexed: 11/21/2022] Open
Abstract
Years of basic neuroscience on the modulation of the small circuits found in the crustacean stomatogastric ganglion have led us to study the effects of temperature on the motor patterns produced by the stomatogastric ganglion. While the impetus for this work was the study of individual variability in the parameters determining intrinsic and synaptic conductances, we are confronting substantial fluctuations in the stability of the networks to extreme temperature; these may correlate with changes in ocean temperature. Interestingly, when studied under control conditions, these wild-caught animals appear to be unchanged, but it is only when challenged by extreme temperatures that we reveal the consequences of warming oceans.
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Affiliation(s)
- Eve Marder
- Volen Center and Biology Department, Brandeis University, Waltham, Massachusetts 02454
| | - Mara C P Rue
- Volen Center and Biology Department, Brandeis University, Waltham, Massachusetts 02454
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32
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Kamaleddin MA. Degeneracy in the nervous system: from neuronal excitability to neural coding. Bioessays 2021; 44:e2100148. [PMID: 34791666 DOI: 10.1002/bies.202100148] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 09/26/2021] [Accepted: 09/28/2021] [Indexed: 02/04/2023]
Abstract
Degeneracy is ubiquitous across biological systems where structurally different elements can yield a similar outcome. Degeneracy is of particular interest in neuroscience too. On the one hand, degeneracy confers robustness to the nervous system and facilitates evolvability: Different elements provide a backup plan for the system in response to any perturbation or disturbance. On the other, a difficulty in the treatment of some neurological disorders such as chronic pain is explained in light of different elements all of which contribute to the pathological behavior of the system. Under these circumstances, targeting a specific element is ineffective because other elements can compensate for this modulation. Understanding degeneracy in the physiological context explains its beneficial role in the robustness of neural circuits. Likewise, understanding degeneracy in the pathological context opens new avenues of discovery to find more effective therapies.
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Affiliation(s)
- Mohammad Amin Kamaleddin
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.,Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
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33
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Powell DJ, Marder E, Nusbaum MP. Perturbation-specific responses by two neural circuits generating similar activity patterns. Curr Biol 2021; 31:4831-4838.e4. [PMID: 34506730 DOI: 10.1016/j.cub.2021.08.042] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/07/2021] [Accepted: 08/13/2021] [Indexed: 01/30/2023]
Abstract
A fundamental question in neuroscience is whether neuronal circuits with variable circuit parameters that produce similar outputs respond comparably to equivalent perturbations.1-4 Work on the pyloric rhythm of the crustacean stomatogastric ganglion (STG) showed that highly variable sets of intrinsic and synaptic conductances can generate similar circuit activity patterns.5-9 Importantly, in response to physiologically relevant perturbations, these disparate circuit solutions can respond robustly and reliably,10-12 but when exposed to extreme perturbations the underlying circuit parameter differences produce diverse patterns of disrupted activity.7,12,13 In this example, the pyloric circuit is unchanged; only the conductance values vary. In contrast, the gastric mill rhythm in the STG can be generated by distinct circuits when activated by different modulatory neurons and/or neuropeptides.14-21 Generally, these distinct circuits produce different gastric mill rhythms. However, the rhythms driven by stimulating modulatory commissural neuron 1 (MCN1) and bath-applying CabPK (Cancer borealis pyrokinin) peptide generate comparable output patterns, despite having distinct circuits that use separate cellular and synaptic mechanisms.22-25 Here, we use these two gastric mill circuits to determine whether such circuits respond comparably when challenged with persisting (hormonal: CCAP) or acute (sensory: GPR neuron) metabotropic influences. Surprisingly, the hormone-mediated action separates these two rhythms despite activating the same ionic current in the same circuit neuron during both rhythms, whereas the sensory neuron evokes comparable responses despite acting via different synapses during each rhythm. These results highlight the need for caution when inferring the circuit response to a perturbation when that circuit is not well defined physiologically.
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Affiliation(s)
- Daniel J Powell
- Volen Center for Complex Systems and Department of Biology, Brandeis University, 415 South Street, Waltham, MA 02454, USA
| | - Eve Marder
- Volen Center for Complex Systems and Department of Biology, Brandeis University, 415 South Street, Waltham, MA 02454, USA
| | - Michael P Nusbaum
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, 211 CRB, 415 Curie Boulevard, Philadelphia, PA 19104, USA.
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34
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de Bournonville C, Mendoza KR, Remage-Healey L. Aromatase and nonaromatase neurons in the zebra finch secondary auditory forebrain are indistinct in their song-driven gene induction and intrinsic electrophysiological properties. Eur J Neurosci 2021; 54:7072-7091. [PMID: 34535925 DOI: 10.1111/ejn.15463] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 08/16/2021] [Accepted: 09/15/2021] [Indexed: 01/29/2023]
Abstract
Estrogens support major brain functions including cognition, reproduction, neuroprotection and sensory processing. Neuroestrogens are synthesized within some brain areas by the enzyme aromatase and can rapidly modulate local circuit functions, yet the cellular physiology and sensory-response profiles of aromatase neurons are essentially unknown. In songbirds, social and acoustic stimuli drive neuroestrogen elevations in the auditory forebrain caudomedial nidopallium (NCM). In both males and females, neuroestrogens rapidly enhance NCM auditory processing and auditory learning. Estrogen-producing neurons in NCM may therefore exhibit distinguishing profiles for sensory-activation and intrinsic electrophysiology. Here, we explored these questions using both immunocyctochemistry and electrophysiological recordings. Immunoreactivity for aromatase and the immediate early gene EGR1, a marker of activity and plasticity, were quantified in NCM of song-exposed animals versus silence-exposed controls. Using whole-cell patch clamp recordings from NCM slices, we also documented the intrinsic excitability profiles of aromatase-positive and aromatase-negative neurons. We observed that a subset of aromatase neurons were significantly activated during song playback, in both males and females, and in both hemispheres. A comparable population of non-aromatase-expressing neurons were also similarly driven by song stimulation. Membrane properties (i.e., resting membrane potential, rheobase, input resistance and multiple action potential parameters) were similarly indistinguishable between NCM aromatase and non-aromatase neurons. Together, these findings demonstrate that aromatase and non-aromatase neurons in NCM are indistinct in terms of their intrinsic electrophysiology and responses to song. Nevertheless, such similarities in response properties may belie more subtle differences in underlying conductances and/or computational roles that may be crucial to their function.
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Affiliation(s)
| | - Kyssia Ruth Mendoza
- Center for Neuroendocrine Studies, University of Massachusetts, Amherst, Massachusetts, USA
| | - Luke Remage-Healey
- Center for Neuroendocrine Studies, University of Massachusetts, Amherst, Massachusetts, USA
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35
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Guet-McCreight A, Skinner FK. Deciphering how interneuron specific 3 cells control oriens lacunosum-moleculare cells to contribute to circuit function. J Neurophysiol 2021; 126:997-1014. [PMID: 34379493 DOI: 10.1152/jn.00204.2021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The wide diversity of inhibitory cells across the brain makes them suitable to contribute to network dynamics in specialized fashions. However, the contributions of a particular inhibitory cell type in a behaving animal are challenging to untangle as one needs to both record cellular activities and identify the cell type being recorded. Thus, using computational modeling and theory to predict and hypothesize cell-specific contributions is desirable. Here, we examine potential contributions of interneuron-specific 3 (I-S3) cells - an inhibitory interneuron found in CA1 hippocampus that only targets other inhibitory interneurons - during simulated theta rhythms. We use previously developed multi-compartment models of oriens lacunosum-moleculare (OLM) cells, the main target of I-S3 cells, and explore how I-S3 cell inputs during in vitro and in vivo scenarios contribute to theta. We find that I-S3 cells suppress OLM cell spiking, rather than engender its spiking via post-inhibitory rebound mechanisms, and contribute to theta frequency spike resonance during simulated in vivo scenarios. To elicit recruitment similar to in vitro experiments, inclusion of disinhibited pyramidal cell inputs is necessary, implying that I-S3 cell firing broadens the window for pyramidal cell disinhibition. Using in vivo virtual networks, we show that I-S3 cells contribute to a sharpening of OLM cell recruitment at theta frequencies. Further, shifting the timing of I-S3 cell spiking due to external modulation shifts the timing of the OLM cell firing and thus disinhibitory windows. We propose a specialized contribution of I-S3 cells to create temporally precise coordination of modulation pathways.
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Affiliation(s)
- Alexandre Guet-McCreight
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Frances K Skinner
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Departments of Medicine (Neurology) and Physiology, University of Toronto, Toronto, Ontario, Canada
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36
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Mishra P, Narayanan R. Ion-channel degeneracy: Multiple ion channels heterogeneously regulate intrinsic physiology of rat hippocampal granule cells. Physiol Rep 2021; 9:e14963. [PMID: 34342171 PMCID: PMC8329439 DOI: 10.14814/phy2.14963] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 06/13/2021] [Accepted: 06/21/2021] [Indexed: 01/09/2023] Open
Abstract
Degeneracy, the ability of multiple structural components to elicit the same characteristic functional properties, constitutes an elegant mechanism for achieving biological robustness. In this study, we sought electrophysiological signatures for the expression of ion-channel degeneracy in the emergence of intrinsic properties of rat hippocampal granule cells. We measured the impact of four different ion-channel subtypes-hyperpolarization-activated cyclic-nucleotide-gated (HCN), barium-sensitive inward rectifier potassium (Kir ), tertiapin-Q-sensitive inward rectifier potassium, and persistent sodium (NaP) channels-on 21 functional measurements employing pharmacological agents, and report electrophysiological data on two characteristic signatures for the expression of ion-channel degeneracy in granule cells. First, the blockade of a specific ion-channel subtype altered several, but not all, functional measurements. Furthermore, any given functional measurement was altered by the blockade of many, but not all, ion-channel subtypes. Second, the impact of blocking each ion-channel subtype manifested neuron-to-neuron variability in the quantum of changes in the electrophysiological measurements. Specifically, we found that blocking HCN or Ba-sensitive Kir channels enhanced action potential firing rate, but blockade of NaP channels reduced firing rate of granule cells. Subthreshold measures of granule cell intrinsic excitability (input resistance, temporal summation, and impedance amplitude) were enhanced by blockade of HCN or Ba-sensitive Kir channels, but were not significantly altered by NaP channel blockade. We confirmed that the HCN and Ba-sensitive Kir channels independently altered sub- and suprathreshold properties of granule cells through sequential application of pharmacological agents that blocked these channels. Finally, we found that none of the sub- or suprathreshold measurements of granule cells were significantly altered upon treatment with tertiapin-Q. Together, the heterogeneous many-to-many mapping between ion channels and single-neuron intrinsic properties emphasizes the need to account for ion-channel degeneracy in cellular- and network-scale physiology.
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Affiliation(s)
- Poonam Mishra
- Cellular Neurophysiology LaboratoryMolecular Biophysics UnitIndian Institute of ScienceBangaloreIndia
| | - Rishikesh Narayanan
- Cellular Neurophysiology LaboratoryMolecular Biophysics UnitIndian Institute of ScienceBangaloreIndia
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37
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Bittner SR, Palmigiano A, Piet AT, Duan CA, Brody CD, Miller KD, Cunningham J. Interrogating theoretical models of neural computation with emergent property inference. eLife 2021; 10:e56265. [PMID: 34323690 PMCID: PMC8321557 DOI: 10.7554/elife.56265] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 06/30/2021] [Indexed: 11/13/2022] Open
Abstract
A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or a pattern of neural activity -- and thus can offer insights into neural computation. The operation of these circuits, like all models, critically depends on the choice of model parameters. A key step is then to identify the model parameters consistent with observed phenomena: to solve the inverse problem. In this work, we present a novel technique, emergent property inference (EPI), that brings the modern probabilistic modeling toolkit to theoretical neuroscience. When theorizing circuit models, theoreticians predominantly focus on reproducing computational properties rather than a particular dataset. Our method uses deep neural networks to learn parameter distributions with these computational properties. This methodology is introduced through a motivational example of parameter inference in the stomatogastric ganglion. EPI is then shown to allow precise control over the behavior of inferred parameters and to scale in parameter dimension better than alternative techniques. In the remainder of this work, we present novel theoretical findings in models of primary visual cortex and superior colliculus, which were gained through the examination of complex parametric structure captured by EPI. Beyond its scientific contribution, this work illustrates the variety of analyses possible once deep learning is harnessed towards solving theoretical inverse problems.
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Affiliation(s)
- Sean R Bittner
- Department of Neuroscience, Columbia UniversityNew YorkUnited States
| | | | - Alex T Piet
- Princeton Neuroscience InstitutePrincetonUnited States
- Princeton UniversityPrincetonUnited States
- Allen Institute for Brain ScienceSeattleUnited States
| | - Chunyu A Duan
- Institute of Neuroscience, Chinese Academy of SciencesShanghaiChina
| | - Carlos D Brody
- Princeton Neuroscience InstitutePrincetonUnited States
- Princeton UniversityPrincetonUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
| | - Kenneth D Miller
- Department of Neuroscience, Columbia UniversityNew YorkUnited States
| | - John Cunningham
- Department of Statistics, Columbia UniversityNew YorkUnited States
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38
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Reed JD, Blackwell KT. Prediction of Neural Diameter From Morphology to Enable Accurate Simulation. Front Neuroinform 2021; 15:666695. [PMID: 34149388 PMCID: PMC8209307 DOI: 10.3389/fninf.2021.666695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 05/10/2021] [Indexed: 11/29/2022] Open
Abstract
Accurate neuron morphologies are paramount for computational model simulations of realistic neural responses. Over the last decade, the online repository NeuroMorpho.Org has collected over 140,000 available neuron morphologies to understand brain function and promote interaction between experimental and computational research. Neuron morphologies describe spatial aspects of neural structure; however, many of the available morphologies do not contain accurate diameters that are essential for computational simulations of electrical activity. To best utilize available neuron morphologies, we present a set of equations that predict dendritic diameter from other morphological features. To derive the equations, we used a set of NeuroMorpho.org archives with realistic neuron diameters, representing hippocampal pyramidal, cerebellar Purkinje, and striatal spiny projection neurons. Each morphology is separated into initial, branching children, and continuing nodes. Our analysis reveals that the diameter of preceding nodes, Parent Diameter, is correlated to diameter of subsequent nodes for all cell types. Branching children and initial nodes each required additional morphological features to predict diameter, such as path length to soma, total dendritic length, and longest path to terminal end. Model simulations reveal that membrane potential response with predicted diameters is similar to the original response for several tested morphologies. We provide our open source software to extend the utility of available NeuroMorpho.org morphologies, and suggest predictive equations may supplement morphologies that lack dendritic diameter and improve model simulations with realistic dendritic diameter.
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Affiliation(s)
- Jonathan D Reed
- Krasnow Institute of Advanced Study, George Mason University, Fairfax, VA, United States.,Department of Biology, George Mason University, Fairfax, VA, United States
| | - Kim T Blackwell
- Krasnow Institute of Advanced Study, George Mason University, Fairfax, VA, United States.,Department of Bioengineering, Volgenau School of Engineering, George Mason University, Fairfax, VA, United States
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39
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Tang Y, An L, Wang Q, Liu JK. Regulating synchronous oscillations of cerebellar granule cells by different types of inhibition. PLoS Comput Biol 2021; 17:e1009163. [PMID: 34181653 PMCID: PMC8270418 DOI: 10.1371/journal.pcbi.1009163] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 07/09/2021] [Accepted: 06/08/2021] [Indexed: 11/18/2022] Open
Abstract
Synchronous oscillations in neural populations are considered being controlled by inhibitory neurons. In the granular layer of the cerebellum, two major types of cells are excitatory granular cells (GCs) and inhibitory Golgi cells (GoCs). GC spatiotemporal dynamics, as the output of the granular layer, is highly regulated by GoCs. However, there are various types of inhibition implemented by GoCs. With inputs from mossy fibers, GCs and GoCs are reciprocally connected to exhibit different network motifs of synaptic connections. From the view of GCs, feedforward inhibition is expressed as the direct input from GoCs excited by mossy fibers, whereas feedback inhibition is from GoCs via GCs themselves. In addition, there are abundant gap junctions between GoCs showing another form of inhibition. It remains unclear how these diverse copies of inhibition regulate neural population oscillation changes. Leveraging a computational model of the granular layer network, we addressed this question to examine the emergence and modulation of network oscillation using different types of inhibition. We show that at the network level, feedback inhibition is crucial to generate neural oscillation. When short-term plasticity was equipped on GoC-GC synapses, oscillations were largely diminished. Robust oscillations can only appear with additional gap junctions. Moreover, there was a substantial level of cross-frequency coupling in oscillation dynamics. Such a coupling was adjusted and strengthened by GoCs through feedback inhibition. Taken together, our results suggest that the cooperation of distinct types of GoC inhibition plays an essential role in regulating synchronous oscillations of the GC population. With GCs as the sole output of the granular network, their oscillation dynamics could potentially enhance the computational capability of downstream neurons.
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Affiliation(s)
- Yuanhong Tang
- School of Computer Science and Technology, Xidian University, Xi’an, China
| | - Lingling An
- School of Computer Science and Technology, Xidian University, Xi’an, China
- Guangzhou institute of technology, Xidian University, Guangzhou, China
| | - Quan Wang
- School of Computer Science and Technology, Xidian University, Xi’an, China
| | - Jian K. Liu
- Centre for Systems Neuroscience, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, United Kingdom
- School of Computing, University of Leeds, Leeds, United Kingdom
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40
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Jacquerie K, Drion G. Robust switches in thalamic network activity require a timescale separation between sodium and T-type calcium channel activations. PLoS Comput Biol 2021; 17:e1008997. [PMID: 34003841 PMCID: PMC8162675 DOI: 10.1371/journal.pcbi.1008997] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 05/28/2021] [Accepted: 04/23/2021] [Indexed: 11/18/2022] Open
Abstract
Switches in brain states, synaptic plasticity and neuromodulation are fundamental processes in our brain that take place concomitantly across several spatial and timescales. All these processes target neuron intrinsic properties and connectivity to achieve specific physiological goals, raising the question of how they can operate without interfering with each other. Here, we highlight the central importance of a timescale separation in the activation of sodium and T-type calcium channels to sustain robust switches in brain states in thalamic neurons that are compatible with synaptic plasticity and neuromodulation. We quantify the role of this timescale separation by comparing the robustness of rhythms of six published conductance-based models at the cellular, circuit and network levels. We show that robust rhythm generation requires a T-type calcium channel activation whose kinetics are situated between sodium channel activation and T-type calcium channel inactivation in all models despite their quantitative differences. Our brain is constantly processing information either from the environment to quickly react to incoming events or learning from experience to shape our memory. These brain states translate a collective activity of neurons interconnected via synaptic connections. Here, we focus on the thalamic network showing a transition from an active to an oscillatory mode at the population level, reverberating a switch from tonic to bursting mode at the cellular level. We are questioning how these activity fluctuations can be robustly modeled despite synaptic plasticity affecting the network configuration and the presence of neuromodulators affecting neuron intrinsic properties. To do so, we investigate six conductance-based models and their ability to reproduce activity switches at the cellular, circuit and population levels. We highlight that the robustness requires the timescale separation between the fast activation of sodium channels compared to the slow activation of T-type calcium channels. Our results show that this kinetics difference is not a computational detail but rather makes a model suitable and robust to study the interaction between switches in brain states, synaptic plasticity and neuromodulation.
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Affiliation(s)
- Kathleen Jacquerie
- Department of Electrical Engineering and Computer Science, University of Liege, Liege, Belgium
- * E-mail:
| | - Guillaume Drion
- Department of Electrical Engineering and Computer Science, University of Liege, Liege, Belgium
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41
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Boeri J, Meunier C, Le Corronc H, Branchereau P, Timofeeva Y, Lejeune FX, Mouffle C, Arulkandarajah H, Mangin JM, Legendre P, Czarnecki A. Two opposite voltage-dependent currents control the unusual early development pattern of embryonic Renshaw cell electrical activity. eLife 2021; 10:62639. [PMID: 33899737 PMCID: PMC8139835 DOI: 10.7554/elife.62639] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 04/24/2021] [Indexed: 11/25/2022] Open
Abstract
Renshaw cells (V1R) are excitable as soon as they reach their final location next to the spinal motoneurons and are functionally heterogeneous. Using multiple experimental approaches, in combination with biophysical modeling and dynamical systems theory, we analyzed, for the first time, the mechanisms underlying the electrophysiological properties of V1R during early embryonic development of the mouse spinal cord locomotor networks (E11.5–E16.5). We found that these interneurons are subdivided into several functional clusters from E11.5 and then display an unexpected transitory involution process during which they lose their ability to sustain tonic firing. We demonstrated that the essential factor controlling the diversity of the discharge pattern of embryonic V1R is the ratio of a persistent sodium conductance to a delayed rectifier potassium conductance. Taken together, our results reveal how a simple mechanism, based on the synergy of two voltage-dependent conductances that are ubiquitous in neurons, can produce functional diversity in embryonic V1R and control their early developmental trajectory.
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Affiliation(s)
- Juliette Boeri
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Claude Meunier
- Centre de Neurosciences Intégratives et Cognition, CNRS UMR 8002, Institut Neurosciences et Cognition, Université de Paris, Paris, France
| | - Hervé Le Corronc
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France.,Univ Angers, Angers, France
| | | | - Yulia Timofeeva
- Department of Computer Science and Centre for Complexity Science, University of Warwick, Coventry, United Kingdom.,Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - François-Xavier Lejeune
- Institut du Cerveau et de la Moelle Epinière, Centre de Recherche CHU Pitié-Salpétrière, INSERM, U975, CNRS, UMR 7225, Sorbonne Univ, Paris, France
| | - Christine Mouffle
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Hervé Arulkandarajah
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Jean Marie Mangin
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Pascal Legendre
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France
| | - Antonny Czarnecki
- INSERM, UMR_S 1130, CNRS, UMR 8246, Neuroscience Paris Seine, Institute of Biology Paris Seine, Sorbonne Univ, Paris, France.,Univ. Bordeaux, CNRS, EPHE, INCIA, Bordeaux, France
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42
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Goaillard JM, Marder E. Ion Channel Degeneracy, Variability, and Covariation in Neuron and Circuit Resilience. Annu Rev Neurosci 2021; 44:335-357. [PMID: 33770451 DOI: 10.1146/annurev-neuro-092920-121538] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The large number of ion channels found in all nervous systems poses fundamental questions concerning how the characteristic intrinsic properties of single neurons are determined by the specific subsets of channels they express. All neurons display many different ion channels with overlapping voltage- and time-dependent properties. We speculate that these overlapping properties promote resilience in neuronal function. Individual neurons of the same cell type show variability in ion channel conductance densities even though they can generate reliable and similar behavior. This complicates a simple assignment of function to any conductance and is associated with variable responses of neurons of the same cell type to perturbations, deletions, and pharmacological manipulation. Ion channel genes often show strong positively correlated expression, which may result from the molecular and developmental rules that determine which ion channels are expressed in a given cell type.
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Affiliation(s)
| | - Eve Marder
- Volen Center and Department of Biology, Brandeis University, Waltham, Massachusetts 02454, USA;
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43
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Ratliff J, Franci A, Marder E, O'Leary T. Neuronal oscillator robustness to multiple global perturbations. Biophys J 2021; 120:1454-1468. [PMID: 33610580 PMCID: PMC8105708 DOI: 10.1016/j.bpj.2021.01.038] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/07/2020] [Accepted: 01/07/2021] [Indexed: 11/29/2022] Open
Abstract
Neuronal activity depends on ion channels and biophysical processes that are strongly and differentially sensitive to physical variables such as temperature and pH. Nonetheless, neuronal oscillators can be surprisingly resilient to perturbations in these variables. We study a three-neuron pacemaker ensemble that drives the pyloric rhythm of the crab, Cancer borealis. These crabs routinely experience a number of global perturbations, including changes in temperature and pH. Although pyloric oscillations are robust to such changes, for sufficiently large deviations the rhythm reversibly breaks down. As temperature increases beyond a tipping point, oscillators transition to silence. Acidic pH deviations also show tipping points, with a reliable transition first to tonic spiking, then to silence. Surprisingly, robustness to perturbations in pH only moderately affects temperature robustness. Consistent with high animal-to-animal variability in biophysical circuit parameters, tipping points in temperature and pH vary across animals. However, the ordering and discrete classes of transitions at critical points are conserved. This implies that qualitative oscillator dynamics are preserved across animals despite high quantitative parameter variability. A universal model of bursting dynamics predicts the existence of these transition types and the order in which they occur.
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Affiliation(s)
- Jacob Ratliff
- Dominick P Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York
| | - Alessio Franci
- Department of Mathematics, National Autonomous University of Mexico, Mexico City, Mexico
| | - Eve Marder
- Biology Department, Volen Center, Brandeis University, Waltham, Massachusetts.
| | - Timothy O'Leary
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
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44
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Oesterle J, Behrens C, Schröder C, Hermann T, Euler T, Franke K, Smith RG, Zeck G, Berens P. Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics. eLife 2020; 9:e54997. [PMID: 33107821 PMCID: PMC7673784 DOI: 10.7554/elife.54997] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 10/26/2020] [Indexed: 01/02/2023] Open
Abstract
While multicompartment models have long been used to study the biophysics of neurons, it is still challenging to infer the parameters of such models from data including uncertainty estimates. Here, we performed Bayesian inference for the parameters of detailed neuron models of a photoreceptor and an OFF- and an ON-cone bipolar cell from the mouse retina based on two-photon imaging data. We obtained multivariate posterior distributions specifying plausible parameter ranges consistent with the data and allowing to identify parameters poorly constrained by the data. To demonstrate the potential of such mechanistic data-driven neuron models, we created a simulation environment for external electrical stimulation of the retina and optimized stimulus waveforms to target OFF- and ON-cone bipolar cells, a current major problem of retinal neuroprosthetics.
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Affiliation(s)
- Jonathan Oesterle
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
| | - Christian Behrens
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
| | - Cornelius Schröder
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
| | - Thoralf Hermann
- Naturwissenschaftliches und Medizinisches Institut an der Universität TübingenReutlingenGermany
| | - Thomas Euler
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
- Center for Integrative Neuroscience, University of TübingenTübingenGermany
- Bernstein Center for Computational Neuroscience, University of TübingenTübingenGermany
| | - Katrin Franke
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
- Bernstein Center for Computational Neuroscience, University of TübingenTübingenGermany
| | - Robert G Smith
- Department of Neuroscience, University of PennsylvaniaPhiladelphiaUnited States
| | - Günther Zeck
- Naturwissenschaftliches und Medizinisches Institut an der Universität TübingenReutlingenGermany
| | - Philipp Berens
- Institute for Ophthalmic Research, University of TübingenTübingenGermany
- Center for Integrative Neuroscience, University of TübingenTübingenGermany
- Bernstein Center for Computational Neuroscience, University of TübingenTübingenGermany
- Institute for Bioinformatics and Medical Informatics, University of TübingenTübingenGermany
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45
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Sekulić V, Yi F, Garrett T, Guet-McCreight A, Lawrence JJ, Skinner FK. Integration of Within-Cell Experimental Data With Multi-Compartmental Modeling Predicts H-Channel Densities and Distributions in Hippocampal OLM Cells. Front Cell Neurosci 2020; 14:277. [PMID: 33093823 PMCID: PMC7527636 DOI: 10.3389/fncel.2020.00277] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 08/05/2020] [Indexed: 12/13/2022] Open
Abstract
Determining biophysical details of spatially extended neurons is a challenge that needs to be overcome if we are to understand the dynamics of brain function from cellular perspectives. Moreover, we now know that we should not average across recordings from many cells of a given cell type to obtain quantitative measures such as conductance since measures can vary multiple-fold for a given cell type. In this work we examine whether a tight combination of experimental and computational work can address this challenge. The oriens-lacunosum/moleculare (OLM) interneuron operates as a “gate” that controls incoming sensory and ongoing contextual information in the CA1 of the hippocampus, making it essential to understand how its biophysical properties contribute to memory function. OLM cells fire phase-locked to the prominent hippocampal theta rhythms, and we previously used computational models to show that OLM cells exhibit high or low theta spiking resonance frequencies that depend respectively on whether their dendrites have hyperpolarization-activated cation channels (h-channels) or not. However, whether OLM cells actually possess dendritic h-channels is unknown at present. We performed a set of whole-cell recordings of OLM cells from mouse hippocampus and constructed three multi-compartment models using morphological and electrophysiological parameters extracted from the same OLM cell, including per-cell pharmacologically isolated h-channel currents. We found that the models best matched experiments when h-channels were present in the dendrites of each of the three model cells created. This strongly suggests that h-channels must be present in OLM cell dendrites and are not localized to their somata. Importantly, this work shows that a tight integration of model and experiment can help tackle the challenge of characterizing biophysical details and distributions in spatially extended neurons. Full spiking models were built for two of the OLM cells, matching their current clamp cell-specific electrophysiological recordings. Overall, our work presents a technical advancement in modeling OLM cells. Our models are available to the community to use to gain insight into cellular dynamics underlying hippocampal function.
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Affiliation(s)
- Vladislav Sekulić
- Krembil Research Institute, University Health Network, Toronto, ON, Canada.,Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Feng Yi
- Department of Biomedical and Pharmaceutical Sciences, Center for Biomolecular Structure and Dynamics, Center for Structural and Functional Neuroscience, University of Montana, Missoula, MT, United States
| | - Tavita Garrett
- Neuroscience Graduate Program and Vollum Institute, Oregon Health & Science University, Portland, OR, United States
| | - Alexandre Guet-McCreight
- Krembil Research Institute, University Health Network, Toronto, ON, Canada.,Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - J Josh Lawrence
- Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, United States.,Center for Translational Neuroscience and Therapeutics, Texas Tech University Health Sciences Center, Lubbock, TX, United States.,Garrison Institute on Aging, Texas Tech University Health Sciences Center, Lubbock, TX, United States
| | - Frances K Skinner
- Krembil Research Institute, University Health Network, Toronto, ON, Canada.,Departments of Medicine (Neurology) and Physiology, University of Toronto, Toronto, ON, Canada
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46
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Gonçalves PJ, Lueckmann JM, Deistler M, Nonnenmacher M, Öcal K, Bassetto G, Chintaluri C, Podlaski WF, Haddad SA, Vogels TP, Greenberg DS, Macke JH. Training deep neural density estimators to identify mechanistic models of neural dynamics. eLife 2020; 9:e56261. [PMID: 32940606 PMCID: PMC7581433 DOI: 10.7554/elife.56261] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 09/16/2020] [Indexed: 01/27/2023] Open
Abstract
Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators-trained using model simulations-to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin-Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics.
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Affiliation(s)
- Pedro J Gonçalves
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
| | - Jan-Matthis Lueckmann
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
| | - Michael Deistler
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Machine Learning in Science, Excellence Cluster Machine Learning, Tübingen UniversityTübingenGermany
| | - Marcel Nonnenmacher
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
- Model-Driven Machine Learning, Institute of Coastal Research, Helmholtz Centre GeesthachtGeesthachtGermany
| | - Kaan Öcal
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
- Mathematical Institute, University of BonnBonnGermany
| | - Giacomo Bassetto
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
| | - Chaitanya Chintaluri
- Centre for Neural Circuits and Behaviour, University of OxfordOxfordUnited Kingdom
- Institute of Science and Technology AustriaKlosterneuburgAustria
| | - William F Podlaski
- Centre for Neural Circuits and Behaviour, University of OxfordOxfordUnited Kingdom
| | - Sara A Haddad
- Max Planck Institute for Brain ResearchFrankfurtGermany
| | - Tim P Vogels
- Centre for Neural Circuits and Behaviour, University of OxfordOxfordUnited Kingdom
- Institute of Science and Technology AustriaKlosterneuburgAustria
| | - David S Greenberg
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Model-Driven Machine Learning, Institute of Coastal Research, Helmholtz Centre GeesthachtGeesthachtGermany
| | - Jakob H Macke
- Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of MunichMunichGermany
- Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar)BonnGermany
- Machine Learning in Science, Excellence Cluster Machine Learning, Tübingen UniversityTübingenGermany
- Max Planck Institute for Intelligent SystemsTübingenGermany
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47
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Alonso LM, Marder E. Temperature compensation in a small rhythmic circuit. eLife 2020; 9:e55470. [PMID: 32484437 PMCID: PMC7332291 DOI: 10.7554/elife.55470] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 05/31/2020] [Indexed: 12/28/2022] Open
Abstract
Temperature affects the conductances and kinetics of the ionic channels that underlie neuronal activity. Each membrane conductance has a different characteristic temperature sensitivity, which raises the question of how neurons and neuronal circuits can operate robustly over wide temperature ranges. To address this, we employed computational models of the pyloric network of crabs and lobsters. We produced multiple different models that exhibit a triphasic pyloric rhythm over a range of temperatures and explored the dynamics of their currents and how they change with temperature. Temperature can produce smooth changes in the relative contributions of the currents to neural activity so that neurons and networks undergo graceful transitions in the mechanisms that give rise to their activity patterns. Moreover, responses of the models to deletions of a current can be different at high and low temperatures, indicating that even a well-defined genetic or pharmacological manipulation may produce qualitatively distinct effects depending on the temperature.
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Affiliation(s)
- Leandro M Alonso
- Volen Center and Biology Department, Brandeis UniversityWalthamUnited States
| | - Eve Marder
- Volen Center and Biology Department, Brandeis UniversityWalthamUnited States
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48
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He LS, Rue MCP, Morozova EO, Powell DJ, James EJ, Kar M, Marder E. Rapid adaptation to elevated extracellular potassium in the pyloric circuit of the crab, Cancer borealis. J Neurophysiol 2020; 123:2075-2089. [PMID: 32319837 DOI: 10.1152/jn.00135.2020] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Elevated potassium concentration ([K+]) is often used to alter excitability in neurons and networks by shifting the potassium equilibrium potential (EK) and, consequently, the resting membrane potential. We studied the effects of increased extracellular [K+] on the well-described pyloric circuit of the crab Cancer borealis. A 2.5-fold increase in extracellular [K+] (2.5×[K+]) depolarized pyloric dilator (PD) neurons and resulted in short-term loss of their normal bursting activity. This period of silence was followed within 5-10 min by the recovery of spiking and/or bursting activity during continued superfusion of 2.5×[K+] saline. In contrast, when PD neurons were pharmacologically isolated from pyloric presynaptic inputs, they exhibited no transient loss of spiking activity in 2.5×[K+], suggesting the presence of an acute inhibitory effect mediated by circuit interactions. Action potential threshold in PD neurons hyperpolarized during an hour-long exposure to 2.5×[K+] concurrent with the recovery of spiking and/or bursting activity. Thus the initial loss of activity appears to be mediated by synaptic interactions within the network, but the secondary adaptation depends on changes in the intrinsic excitability of the pacemaker neurons. The complex sequence of events in the responses of pyloric neurons to elevated [K+] demonstrates that electrophysiological recordings are necessary to determine both the transient and longer term effects of even modest alterations of K+ concentrations on neuronal activity.NEW & NOTEWORTHY Solutions with elevated extracellular potassium are commonly used as a depolarizing stimulus. We studied the effects of high potassium concentration ([K+]) on the pyloric circuit of the crab stomatogastric ganglion. A 2.5-fold increase in extracellular [K+] caused a transient loss of activity that was not due to depolarization block, followed by a rapid increase in excitability and recovery of spiking within minutes. This suggests that changing extracellular potassium can have complex and nonstationary effects on neuronal circuits.
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Affiliation(s)
- Lily S He
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Mara C P Rue
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Ekaterina O Morozova
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Daniel J Powell
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
| | - Eric J James
- Biology Department, Adelphi University, Garden City, New York
| | - Manaswini Kar
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Eve Marder
- Biology Department and Volen Center, Brandeis University, Waltham, Massachusetts
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49
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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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50
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Circuit Stability to Perturbations Reveals Hidden Variability in the Balance of Intrinsic and Synaptic Conductances. J Neurosci 2020; 40:3186-3202. [PMID: 32179572 PMCID: PMC7159886 DOI: 10.1523/jneurosci.0985-19.2020] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 02/06/2020] [Accepted: 02/10/2020] [Indexed: 11/29/2022] Open
Abstract
Neurons and circuits each with a distinct balance of intrinsic and synaptic conductances can generate similar behavior but sometimes respond very differently to perturbation. Examining a large family of circuit models with non-identical neurons and synapses underlying rhythmic behavior, we analyzed the circuits' response to modifications in single and multiple intrinsic conductances in the individual neurons. To summarize these changes over the entire range of perturbed parameters, we quantified circuit output by defining a global stability measure. Using this measure, we identified specific subsets of conductances that when perturbed generate similar behavior in diverse individuals of the population. Our unbiased clustering analysis enabled us to quantify circuit stability when simultaneously perturbing multiple conductances as a nonlinear combination of single conductance perturbations. This revealed surprising conductance combinations that can predict the response to specific perturbations, even when the remaining intrinsic and synaptic conductances are unknown. Therefore, our approach can expose hidden variability in the balance of intrinsic and synaptic conductances of the same neurons across different versions of the same circuit solely from the circuit response to perturbations. Developed for a specific family of model circuits, our quantitative approach to characterizing high-dimensional degenerate systems provides a conceptual and analytic framework to guide future theoretical and experimental studies on degeneracy and robustness. SIGNIFICANCE STATEMENT Neural circuits can generate nearly identical behavior despite neuronal and synaptic parameters varying several-fold between individual instantiations. Yet, when these parameters are perturbed through channel deletions and mutations or environmental disturbances, seemingly identical circuits can respond very differently. What distinguishes inconsequential perturbations that barely alter circuit behavior from disruptive perturbations that drastically disturb circuit output remains unclear. Focusing on a family of rhythmic circuits, we propose a computational approach to reveal hidden variability in the intrinsic and synaptic conductances in seemingly identical circuits based solely on circuit output to different perturbations. We uncover specific conductance combinations that work similarly to maintain stability and predict the effect of changing multiple conductances simultaneously, which often results from neuromodulation or injury.
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