Article

Extended dynamic clamp: controlling up to four neurons using a single desktop computer and interface

August 2001
Journal of Neuroscience Methods 108(1):39-48

August 2001
108(1):39-48

DOI:10.1016/S0165-0270(01)00368-5

Source
PubMed

Authors:

Robert Elson

Point Loma Nazarene University

Attila Szücs

Eötvös Loránd University

Mikhail israel Rabinovich

University of California, San Diego

Show all 6 authorsHide

The dynamic clamp protocol allows an experimenter to simulate the presence of membrane conductances in, and synaptic connections between, biological neurons. Existing protocols and commercial ADC/DAC boards provide ready control in and between < or =2 neurons. Control at >2 sites is desirable when studying neural circuits with serial or ring connectivity. Here, we describe how to extend dynamic clamp control to four neurons and their associated synaptic interactions, using a single IBM-compatible PC, an ADC/DAC interface with two analog outputs, and an additional demultiplexing circuit. A specific C++ program, DYNCLAMP4, implements these procedures in a Windows environment, allowing one to change parameters while the dynamic clamp is running. Computational efficiency is increased by varying the duration of the input-output cycle. The program simulates < or =8 Hodgkin-Huxley-type conductances and < or =18 (chemical and/or electrical) synapses in < or =4 neurons and runs at a minimum update rate of 5 kHz on a 450 MHz CPU. (Increased speed is possible in a two-neuron version that does not need auxiliary circuitry). Using identified neurons of the crustacean stomatogastric ganglion, we illustrate on-line parameter modification and the construction of three-member synaptic rings.

The dynamic clamp comes of age

Article

May 2004
TRENDS NEUROSCI

The dynamic clamp uses computer simulation to introduce artificial membrane or synaptic conductances into biological neurons and to create hybrid circuits of real and model neurons. In the ten years since it was first developed, the dynamic clamp has become a widely used tool for the study of neural systems at the cellular and circuit levels. This review describes recent state-of-the-art implementations of the dynamic clamp and summarizes insights gained through its use, ranging from the role of voltage-dependent conductances in shaping neuronal activity to the effects of synaptic dynamics on network behavior and the impact of in vivo-like input on neuronal information processing.

Neuromorphic neural interfaces: From neurophysiological inspiration to biohybrid coupling with nervous systems

Article

Full-text available

Aug 2017

Objective: Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach: This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results: Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance: Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.

EXAMINING THE NEURAL CODE AND SENSORY SIGNAL TRANSFER CONTROL MECHANISMS THROUGH HYBRID INTERFACES IN THE VISUAL SYSTEM

Article

May 2012

Sébastien Béhuret

Determining the neural code in the thalamus and cerebral cortex, especially in the primary visual area, is hindered by the complexity of the neural network which is based on an astonishing diversity of neuronal types exhibiting varying properties at the morphological, biochemical, electrical and synaptic levels. This diversity is amplified by the numerous functional properties of each neuron which are reflecting the highly recurrent synaptic connections in cortical circuits as well as the corticothalamocortical loop. In other words, the response specificity of each neuron is affected through thousands of excitatory and inhibitory synapses, by the overall computation performed in the thalamocortical network. In the first part, we developed a model of contextual synaptic bombardment reproducing the dynamics of thousands of excitatory and inhibitory synapses converging to a single cortical neuron. A major advantage of this model is the possibility to control the amount of synchronization among the afferent synapses contacting the cortical neuron. We show in the visual cortex of cats that the amount of synaptic synchronization is related to the sub-threshold neuronal activity correlation level. Classically used artificial stimulations such as drifting gratings led the cerebral cortex into a redundant and correlated state while natural stimulations produced a richer neural code with less correlations. These results indicate that the sub-threshold neuronal activity correlation level is an indicator of the functional state in which the cerebral cortex is engaged. In the second part, we further investigated the neural code by extending our study to the thalamus, the major gateway for the flow of sensory information from the periphery to the cerebral cortex. The thalamus receives a strong corticothalamic feedback which results from the overall computation performed by the cortical areas. In order to study the impact of the corticothalamic feedack, we modeled a retinothalamocortical pathway mixing artificial and biological neurons recorded in the slice and we mimicked in these neurons a synaptic bombardment of cortical origin through the injection of mixed excitatory and inhibitory stochastic inputs in dynamic-clamp. This approach allowed us to control independently every thalamic neurons involved in the artificial pathway. We show that the sensory information transfer from the retina to the primary visual cortex is regulated by both a stochastic facilitation process across the population and the classical gain control a the cellular level. The stochastic facilitation process which could not be seen at the single-cell level is governed by the level of inter-neuronal correlation of the neuronal activity in the thalamus. Unlike conventional views, -a highly decorrelated neuronal activity- optimizes the sensory information transfer from the retina to the cortex by promoting the synchronization of synaptic inputs. We suggest that a cortically-induced decorrelation could increase the transfer efficiency for specific cell assemblies in the thalamus, constituting an attentional mechanism at the level of the thalamocortical circuits. At the same time, we developed a method to extract synaptic conductance fluctuations from single-trial intracellular recordings. We expect this method will help refining our understanding of the synaptic contexts in which the neurons are immersed with potential benefits on the development of new synaptic bombardment models. To conclude, our work confirms the hypothesis of a neural code based on synaptic synchronization governed by the level of correlation of the neuronal activity. Our results are consistent with numerous studies on attentional processes and suggest that active correlation and decorrelation mechanisms as well as oscillatory activities may regulate the information transfer between sensory organs and cortical areas.

An embedded system for real-time feedback neuroscience experiments

Conference Paper

Full-text available

Nov 2014

A complete data acquisition and signal output control system for synchronous stimuli generation, geared towards in vivo neuroscience experiments, was developed using the Terasic DE2i-150 board. All emotions and thoughts are an emergent property of the chemical and electrical activity of neurons. Most of these cells are regarded as excitable cells (spiking neurons), which produce temporally localized electric patterns (spikes). Researchers usually consider that only the instant of occurrence (timestamp) of these spikes encodes information. Registering neural activity evoked by stimuli demands timing determinism and data storage capabilities that cannot be met without dedicated hardware and a hard real-time operational system (RTOS). Indeed, research in neuroscience usually requires dedicated electronic instrumentation for studies in neural coding, brain machine interfaces and closed loop in vivo or in vitro experiments. We developed a complete embedded system solution consisting of a hardware/software co-design with the Intel Atom processor running a free RTOS and a FPGA communicating via a PCIe-to-Avalon bridge. Our system is capable of registering input event timestamps with 1{\mu}s precision and digitally generating stimuli output in hard real-time. The whole system is controlled by a Linux-based Graphical User Interface (GUI). Collected results are simultaneously saved in a local file and broadcasted wirelessly to mobile device web-browsers in an user-friendly graphic format, enhanced by HTML5 technology. The developed system is low-cost and highly configurable, enabling various neuroscience experimental setups, while the commercial off-the-shelf systems have low availability and are less flexible to adapt to specific experimental configurations.

An embedded system for real-time feedback neuroscience experiments

Conference Paper

Full-text available

Nov 2014

A Modeling Approach on Why Simple Central Pattern Generators Are Built of Irregular Neurons

Article

Full-text available

Mar 2015
PLOS ONE

The crustacean pyloric Central Pattern Generator (CPG) is a nervous circuit that endogenously provides periodic motor patterns. Even after about 40 years of intensive studies, the rhythm genesis is still not rigorously understood in this CPG, mainly because it is made of neurons with irregular intrinsic activity. Using mathematical models we addressed the question of using a network of irregularly behaving elements to generate periodic oscillations, and we show some advantages of using non-periodic neurons with intrinsic behavior in the transition from bursting to tonic spiking (as found in biological pyloric CPGs) as building components. We studied two- and three-neuron model CPGs built either with Hindmarsh-Rose or with conductance-based Hodgkin-Huxley-like model neurons. By changing a model’s parameter we could span the neuron’s intrinsic dynamical behavior from slow periodic bursting to fast tonic spiking, passing through a transition where irregular bursting was observed. Two-neuron CPG, ha

The Past, Present, and Future of Real-Time Control in Cellular Electrophysiology

Article

Apr 2014
IEEE T BIO-MED ENG

For over 60 years, real-time control has been an important technique in the study of excitable cells. Two such control-based technologies are reviewed here. First, voltageclamp methods revolutionized the study of excitable cells. In this family of techniques, membrane potential is controlled, allowing one to parameterize a powerful class of models that describe the voltage-current relationship of cell membranes simply, flexibly, and accurately. Second, dynamic-clamp methods allow the addition of new, 'virtual' membrane mechanisms to living cells. Dynamic clamp allows researchers unprecedented ways of testing computationally based hypotheses in biological preparations. The review ends with predictions of how control-based technologies will be improved and adapted for new uses in the near future.

Generalization of the Dynamic Clamp Concept in Neurophysiology and Behavior

Article

Full-text available

Jul 2012
PLOS ONE

The idea of closed-loop interaction in in vitro and in vivo electrophysiology has been successfully implemented in the dynamic clamp concept strongly impacting the research of membrane and synaptic properties of neurons. In this paper we show that this concept can be easily generalized to build other kinds of closed-loop protocols beyond (or in addition to) electrical stimulation and recording in neurophysiology and behavioral studies for neuroethology. In particular, we illustrate three different examples of goal-driven real-time closed-loop interactions with drug microinjectors, mechanical devices and video event driven stimulation. Modern activity-dependent stimulation protocols can be used to reveal dynamics (otherwise hidden under traditional stimulation techniques), achieve control of natural and pathological states, induce learning, bridge between disparate levels of analysis and for a further automation of experiments. We argue that closed-loop interaction calls for novel real time analysis, prediction and control tools and a new perspective for designing stimulus-response experiments, which can have a large impact in neuroscience research.

Single Synapse Information Coding in Intraburst Spike Patterns of Central Pattern Generator Motor Neurons

Article

Full-text available

Aug 2011
J NEUROSCI

Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.

Decision-Making, Bias

Chapter

Jun 2022

Conventional measures of intrinsic excitability are poor estimators of neuronal activity under realistic synaptic inputs

Article

Full-text available

Sep 2021
PLOS COMPUT BIOL

Activity-dependent regulation of intrinsic excitability has been shown to greatly contribute to the overall plasticity of neuronal circuits. Such neuroadaptations are commonly investigated in patch clamp experiments using current step stimulation and the resulting input-output functions are analyzed to quantify alterations in intrinsic excitability. However, it is rarely addressed, how such changes translate to the function of neurons when they operate under natural synaptic inputs. Still, it is reasonable to expect that a strong correlation and near proportional relationship exist between static firing responses and those evoked by synaptic drive. We challenge this view by performing a high-yield electrophysiological analysis of cultured mouse hippocampal neurons using both standard protocols and simulated synaptic inputs via dynamic clamp. We find that under these conditions the neurons exhibit vastly different firing responses with surprisingly weak correlation between static and dynamic firing intensities. These contrasting responses are regulated by two intrinsic K-currents mediated by Kv1 and K ir channels, respectively. Pharmacological manipulation of the K-currents produces differential regulation of the firing output of neurons. Static firing responses are greatly increased in stuttering type neurons under blocking their Kv1 channels, while the synaptic responses of the same neurons are less affected. Pharmacological blocking of K ir -channels in delayed firing type neurons, on the other hand, exhibit the opposite effects. Our subsequent computational model simulations confirm the findings in the electrophysiological experiments and also show that adaptive changes in the kinetic properties of such currents can even produce paradoxical regulation of the firing output.

Automatic Adaptation of Model Neurons and Connections to Build Hybrid Circuits with Living Networks

Article

Full-text available

Jun 2020

Hybrid circuits built by creating mono- or bi-directional interactions among living cells and model neurons and synapses are an effective way to study neuron, synaptic and neural network dynamics. However, hybrid circuit technology has been largely underused in the context of neuroscience studies mainly because of the inherent difficulty in implementing and tuning this type of interactions. In this paper, we present a set of algorithms for the automatic adaptation of model neurons and connections in the creation of hybrid circuits with living neural networks. The algorithms perform model time and amplitude scaling, real-time drift adaptation, goal-driven synaptic and model tuning/calibration and also automatic parameter mapping. These algorithms have been implemented in RTHybrid, an open-source library that works with hard real-time constraints. We provide validation examples by building hybrid circuits in a central pattern generator. The results of the validation experiments show that the proposed dynamic adaptation facilitates closed-loop communication among living and artificial model neurons and connections, and contributes to characterize system dynamics, achieve control, automate experimental protocols and extend the lifespan of the preparations.

REVISTA Congreso Ciencia y Tecnologia 2015

Book

Full-text available

Sep 2015

RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience

Article

Full-text available

Mar 2019

Closed-loop technologies provide novel ways of online observation, control and bidirectional interaction with the nervous system, which help to study complex non-linear and partially observable neural dynamics. These protocols are often difficult to implement due to the temporal precision required when interacting with biological components, which in many cases can only be achieved using real-time technology. In this paper we introduce RTHybrid (www.github.com/GNB-UAM/RTHybrid), a free and open-source software that includes a neuron and synapse model library to build hybrid circuits with living neurons in a wide variety of experimental contexts. In an effort to encourage the standardization of real-time software technology in neuroscience research, we compared different open-source real-time operating system patches, RTAI, Xenomai 3 and Preempt-RT, according to their performance and usability. RTHybrid has been developed to run over Linux operating systems supporting both Xenomai 3 and Preempt-RT real-time patches, and thus allowing an easy implementation in any laboratory. We report a set of validation tests and latency benchmarks for the construction of hybrid circuits using this library. With this work we want to promote the dissemination of standardized, user-friendly and open-source software tools developed for open- and closed-loop experimental neuroscience.

Automatic adaptation of model neurons and connections to build hybrid circuits with living networks

Preprint

Full-text available

Sep 2018

Hybrid circuits built by creating mono- or bi-directional interactions among living cells and model neurons and synapses are an effective way to study neuron, synaptic and neural network dynamics. However, hybrid circuit technology has been largely underused in the context of neuroscience studies mainly because of the inherent difficulty in implementing and tuning this type of interactions. In this paper, we present a set of algorithms for the automatic adaptation of model neurons and connections in the creation of hybrid circuits with living neural networks. The algorithms perform model time and amplitude scaling, drift compensation, goal-driven synaptic and model tuning/calibration and also automatic parameter mapping. These algorithms have been implemented in RTHybrid, an open-source library that works with hard real-time constraints. We provide validation examples by building hybrid circuits in a central pattern generator. The results of the validation experiments show that the proposed dynamic adaptation facilitates building hybrid circuits and closed-loop communication among living and artificial model neurons and connections. Furthermore contributes to characterize system dynamics, achieve control, automate experimental protocols and extend the lifespan of the preparations.

Inhibitory Synchronization of Bursting in Biological Neurons: Dependence on Synaptic Time Constant

Article

Sep 2002

Using the dynamic clamp technique, we investigated the effects of varying the time constant of mutual synaptic inhibition on the synchronization of bursting biological neurons. For this purpose, we constructed artificial half-center circuits by inserting simulated reciprocal inhibitory synapses between identified neurons of the pyloric circuit in the lobster stomatogastric ganglion. With natural synaptic interactions blocked (but modulatory inputs retained), these neurons generated independent, repetitive bursts of spikes with cycle period durations of ∼1 s. After coupling the neurons with simulated reciprocal inhibition, we selectively varied the time constant governing the rate of synaptic activation and deactivation. At time constants ≤100 ms, bursting was coordinated in an alternating (anti-phase) rhythm. At longer time constants (>400 ms), bursts became phase-locked in a fully overlapping pattern with little or no phase lag and a shorter period. During the in-phase bursting, the higher-frequency spiking activity was not synchronized. If the circuit lacked a robust periodic burster, increasing the time constant evoked a sharp transition from out-of-phase oscillations to in-phase oscillations with associated intermittent phase-jumping. When a coupled periodic burster neuron was present (on one side of the half-center circuit), the transition was more gradual. We conclude that the magnitude and stability of phase differences between mutually inhibitory neurons varies with the ratio of burst cycle period duration to synaptic time constant and that cellular bursting (whether periodic or irregular) can adopt in-phase coordination when inhibitory synaptic currents are sufficiently slow.

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI

Article

Full-text available

Dec 2017

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin–Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

Frequency‐dependent regulation of intrinsic excitability by voltage‐activated membrane conductances, computational modeling and dynamic clamp

Article

Sep 2017
EUR J NEUROSCI

As one of the most unique properties of nerve cells, their intrinsic excitability allows them to transform synaptic inputs into action potentials. This process reflects a complex interplay between the synaptic inputs and the voltage-dependent membrane currents of the postsynaptic neuron. While neurons in natural conditions mostly fire under the action of intense synaptic bombardment and receive fluctuating patterns of excitation and inhibition, conventional techniques to characterize intrinsic excitability mainly utilize static means of stimulation. Recently we have shown that voltage-gated membrane currents regulate the firing responses under current step stimulation and under physiologically more realistic inputs in a differential manner. At the same time, a multitude of neuron types have been shown to exhibit some form of subthreshold resonance that potentially allows them to respond to synaptic inputs in a frequency-selective manner. In the present study we performed virtual experiments in computational models of neurons to examine how specific voltage-gated currents regulate their excitability under simulated frequency-modulated synaptic inputs. The model simulations and subsequent dynamic clamp experiments on mouse hippocampal pyramidal neurons revealed that the impact of voltage-gated currents in regulating the firing output is strongly frequency-dependent and mostly affecting the synaptic integration at theta-frequencies. Notably, robust frequency-dependent regulation of intrinsic excitability was observed even when conventional analysis of membrane impedance suggested no such tendency. Consequently, plastic or homeostatic regulation of intrinsic membrane properties can tune the frequency-selectivity of neuron populations in a way that is not readily expected from subthreshold impedance measurements. This article is protected by copyright. All rights reserved.

Efficient implementation of a real-time estimation system for thalamocortical hidden Parkinsonian properties OPEN

Article

Jan 2017

Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical properties of ion channels is extremely challenging experimentally and even impossible in clinical applications. This paper presents and evaluates a real-time estimation system for thalamocortical hidden properties. For the sake of efficiency, we use a field programmable gate array for strictly hardware-based computation and algorithm optimization. In the proposed system, the FPGA-based unscented Kalman filter is implemented into a conductance-based TC neuron model. Since the complexity of TC neuron model restrains its hardware implementation in parallel structure, a cost efficient model is proposed to reduce the resource cost while retaining the relevant ionic dynamics. Experimental results demonstrate the real-time capability to estimate thalamocortical hidden properties with high precision under both normal and Parkinsonian states. While it is applied to estimate the hidden properties of the thalamus and explore the mechanism of the Parkinsonian state, the proposed method can be useful in the dynamic clamp technique of the electrophysiological experiments, the neural control engineering and brain-machine interface studies.

Closed-Loop Methodologies for Cellular Electrophysiology

Chapter

Full-text available

Dec 2016

While the design of closed-loop experimental protocols in cellular electrophysiology dates back more than 60 years, recent developments promise to significantly advance the field. We review a selection of recent applications of closed-loop methods in neurobiology, focussing on the intracellular and extracellular access to cellular excitability, employed to dissect the biophysical bases of information processing. We cover relevant methodologies targeting different levels of description, ranging from single ion channels to large ensembles of neurons, and extending across different time scales, ranging from milliseconds to longer intervals characteristic of the variability in the firing rate. We conclude by mentioning future perspectives and developments.

Silicon central pattern generators for cardiac diseases

Article

Nov 2014
J PHYSIOL-LONDON

Cardiac rhythm management devices provide therapies for both arrhythmias and resynchronization but not heart failure, which affects millions of patients worldwide. This paper reviews recent advances in biophysics and mathematical engineering that provide a novel technological platform for addressing heart disease and enabling beat-to-beat adaptation of cardiac pacing in response to physiological feedback. The technology consists of silicon hardware central pattern generators (hCPG) that may be trained to emulate accurately the dynamical response of biological central pattern generators (bCPG). We discuss the limitations of present CPGs and appraise the advantages of analogue over digital circuits for application in bioelectronic medicine. To test the system, we have focused on the cardio-respiratory oscillators in the medulla oblongata that modulate heart rate in phase with respiration to induce respiratory sinus arrhythmia (RSA). We describe here a novel, scalable hCPG comprising physiologically realistic (Hodgkin-Huxley type) neurones and synapses. Our hCPG comprises two neurones that antagonise each other to provide rhythmic motor drive to the vagus nerve to slow the heart. We show how recent advances in modelling allow the motor output to adapt to physiological feedback such as respiration. In rats, we report on the restoration of RSA using an hCPG that receives diaphragmatic electromyography input and use it to stimulate the vagus nerve at specific time points of the respiratory cycle to slow the heart rate. We have validated the adaptation of stimulation to alterations in respiratory rate. We demonstrate that the hCPG is tuneable in terms of the depth and timing of the RSA relative to respiratory phase. These pioneering studies will now permit an analysis of the physiological role of RSA as well as its any potential therapeutic use in cardiac disease.This article is protected by copyright. All rights reserved

NEURONS TO NETWORKS AND BACK AGAIN: NEOCORTICAL CIRCUIT PROCESSING OF TRANSIENT SENSORY INPUT

Article

Full-text available

Automatic Realistic Real Time Stimulation/Recording in Weakly Electric Fish: Long Time Behavior Characterization in Freely Swimming Fish and Stimuli Discrimination

Article

Full-text available

Jan 2014
PLOS ONE

Weakly electric fish are unique model systems in neuroethology, that allow experimentalists to non-invasively, access, central nervous system generated spatio-temporal electric patterns of pulses with roles in at least 2 complex and incompletely understood abilities: electrocommunication and electrolocation. Pulse-type electric fish alter their inter pulse intervals (IPIs) according to different behavioral contexts as aggression, hiding and mating. Nevertheless, only a few behavioral studies comparing the influence of different stimuli IPIs in the fish electric response have been conducted. We developed an apparatus that allows real time automatic realistic stimulation and simultaneous recording of electric pulses in freely moving Gymnotus carapo for several days. We detected and recorded pulse timestamps independently of the fish's position for days. A stimulus fish was mimicked by a dipole electrode that reproduced the voltage time series of real conspecific according to previously recorded timestamp sequences. We characterized fish behavior and the eletrocommunication in 2 conditions: stimulated by IPIs pre-recorded from other fish and random IPI ones. All stimuli pulses had the exact Gymontus carapo waveform. All fish presented a surprisingly long transient exploratory behavior (more than 8 h) when exposed to a new environment in the absence of electrical stimuli. Further, we also show that fish are able to discriminate between real and random stimuli distributions by changing several characteristics of their IPI distribution.

Hippocampal CA1 pyramidal neurons exhibit Type 1 phase response curves and Type 1 excitability.

Article

Full-text available

Mar 2013
J NEUROPHYSIOL

Phase resetting properties of neurons determine their functionality as integrators (Type 1) versus resonators (Type 2), as well as their synchronization tendencies. We introduce a novel bias correction method to estimate the infinitesimal phase resetting curve (PRC), and confirm Type 1 excitability in hippocampal pyramidal CA1 neurons in vitro by two independent methods. First, PRCs evoked using depolarizing pulses consisted only of advances, consistent with Type 1. Second, the frequency/current (f/I) plots showed no minimum frequency, again consistent with Type 1. Type 1 excitability was also confirmed by the absence of a resonant peak in the interspike interval histograms derived from the f/I data. The PRC bias correction assumed that the distribution of noisy phase resetting is truncated because an input cannot advance a spike to a point in time before the input (the causal limit), and successfully removed the statistical bias for delays in the null PRC in response to zero magnitude input by computing the phase resetting as the mean of the untruncated distribution. The PRC for depolarization peaked at late phases and decreased to zero by the end of the cycle, whereas delays observed in response to hyperpolarization increased monotonically. The bias correction did not affect this difference in shape, which was due instead to the causal limit obscuring the infinitesimal PRC for depolarization but not hyperpolarization. Our results suggest that weak periodic hyperpolarizing drive can theoretically entrain CA1 pyramidal neurons at any phase, but that strong excitation will preferentially phase lock them with zero time lag.

Impact of Background Synaptic Activity on Neuronal Response Properties Revealed by Stepwise Replication of In Vivo-Like Conditions In Vitro

Chapter

Full-text available

Mar 2009

Neurons in the intact brain are bombarded by spontaneous synaptic input that causes increased membrane conductance (i.e. shunting), tonic depolarization, and noisy fluctuations in membrane potential. By comparison, neurons in acute brain slices experience little spontaneous synaptic input and are therefore less leaky, more hyperpolarized, and less noisy. Such differences can compromise the extrapolation of in vitro data to explain neuronal operation in vivo. Here, we replicated three effects of synaptic background activity in acute brain slices, using dynamic clamp to artificially increase membrane conductance, constant current injection to cause tonic depolarization, and time-varying current injection to introduce noise. These manipulations were applied separately and in different combinations in order to resolve their specific influence on neuronal activity. In addition to straightforward effects on passive membrane properties, shunting caused nonlinear effects on spiking. As a result, shunted neurons behaved more like coincidence detectors and less like integrators. Furthermore, shunting caused either divisive or subtractive modulation of firing rate depending on the presence or absence of background noise. These results demonstrate that even simplistic applications of dynamic clamp can reveal interesting phenomena and expand our ability to use in vitro experiments to help understand neuronal operation in vivo.

Using “Hard” Real-Time Dynamic Clamp to Study Cellular and Network Mechanisms of Synchronization in the Hippocampal Formation

Chapter

Mar 2009

We report on development and use of dynamic-clamp technology to understand how synchronous neuronal activity is generated in the hippocampus and entorhinal cortex. We find that “hard” real-time dynamic-clamp systems, characterized by very small maximal errors in timing of feedback, are necessary for cases in which fast voltage-gated channels are being mimicked in experiments. Using a hard real-time system to study cellular oscillations in entorhinal cortex, we demonstrate that the stochastic gating of persistent Na+ channels is necessary for cellular oscillations, and that cellular oscillations lead to dynamic changes in gain for conductance-based synaptic inputs. At the network level, we review experiments demonstrating that oscillating entorhinal stellate cells synchronize best via mutually excitatory interactions. Next, we show that cellular oscillations are volatile in the hypothesized “high-conductance” state, thought to occur in vivo, and suggest alternate means by which coherent activity can be generated in the absence of strong cellular oscillations. We close by discussing future developments that will increase the utility and widespread use of the dynamic-clamp method.

Functions of the Persistent Na+ Current in Cortical Neurons Revealed by Dynamic Clamp

Chapter

Full-text available

Mar 2009

Many cortical neurons and other vertebrate nerve cells are equipped with a persistent Na+ current, I NaP, which operates at membrane potentials near the action potential threshold. This current may strongly influence integration and transduction of synaptic input into spike patterns. However, due to the lack of pharmacological tools for selective blockade or enhancement of I NaP, its impact on spike generation has remained enigmatic. By using dynamic clamp to cancel or add I NaP during intracellular recordings in rat hippocampal pyramidal cells, we were able to circumvent this long-standing problem. Combined with computational modeling our dynamic-clamp experiments disclosed how I NaP strongly affects the transduction of excitatory current into action potentials in these neurons. First, we used computational model simulations to predict functional roles of I NaP, including unexpected effects on spike timing and current–frequency relations. We then used the dynamic-clamp technique to experimentally test and confirm our model predictions.

Single Neuron Firing Properties Impact Correlation-Based Population Coding

Article

Full-text available

Jan 2012
J NEUROSCI

Correlated spiking has been widely observed, but its impact on neural coding remains controversial. Correlation arising from comodulation of rates across neurons has been shown to vary with the firing rates of individual neurons. This translates into rate and correlation being equivalently tuned to the stimulus; under those conditions, correlated spiking does not provide information beyond that already available from individual neuron firing rates. Such correlations are irrelevant and can reduce coding efficiency by introducing redundancy. Using simulations and experiments in rat hippocampal neurons, we show here that pairs of neurons receiving correlated input also exhibit correlations arising from precise spike-time synchronization. Contrary to rate comodulation, spike-time synchronization is unaffected by firing rate, thus enabling synchrony- and rate-based coding to operate independently. The type of output correlation depends on whether intrinsic neuron properties promote integration or coincidence detection: "ideal" integrators (with spike generation sensitive to stimulus mean) exhibit rate comodulation, whereas ideal coincidence detectors (with spike generation sensitive to stimulus variance) exhibit precise spike-time synchronization. Pyramidal neurons are sensitive to both stimulus mean and variance, and thus exhibit both types of output correlation proportioned according to which operating mode is dominant. Our results explain how different types of correlations arise based on how individual neurons generate spikes, and why spike-time synchronization and rate comodulation can encode different stimulus properties. Our results also highlight the importance of neuronal properties for population-level coding insofar as neural networks can employ different coding schemes depending on the dominant operating mode of their constituent neurons.

Slow and Persistent Postinhibitory Rebound Acts as an Intrinsic Short-Term Memory Mechanism

Article

Full-text available

Mar 2010
J NEUROSCI

Many neurons exhibit postinhibitory rebound (PIR), in which neurons display enhanced excitability following inhibition. PIR can strongly influence the timing of spikes on rebound from an inhibitory input. We studied PIR in the lateral pyloric (LP) neuron of the stomatogastric ganglion of the crab Cancer borealis. The LP neuron is part of the pyloric network, a central pattern generator that normally oscillates with a period of approximately 1 s. We used the dynamic clamp to create artificial rhythmic synaptic inputs of various periods and duty cycles in the LP neuron. Surprisingly, we found that the strength of PIR increased slowly over multiple cycles of synaptic input. Moreover, this increased excitability persisted for 10-20 s after the rhythmic inhibition was removed. These effects are considerably slower than the rhythmic activity typically observed in LP. Thus this slow postinhibitory rebound allows the neuron to adjust its level of excitability to the average level of inhibition over many cycles, and is another example of an intrinsic "short-term memory" mechanism.

Coupling and synchrony in neuronal networks: electrophysiological experiments

Article

Full-text available

Amanda Preyer

There is a significant amount of computational literature on networks of neurons and their resulting behavior. This dissertation combines electrophysiology experiments with computational modeling to validate the assumptions and results found in this literature. First, we investigate the weak coupling assumption, which states that the phase response of a neuron to weak stimuli is separable from the stimulus waveform. For weak stimuli, there is an intrinsic neuronal property described by the infinitesimal phase response curve (IPRC) that will predict the phase response when convolved with the stimulus waveform. Here, we show that there is a linear relationship between the stimulus and phase response of the neuron, and that we are able to obtain IPRCs that successfully predict the neuronal phase response. Next, we use hybrid networks of neurons to study the phase locking behavior of networks as the synaptic time constant is changed. We verify that networks show anti-phase synchrony for fast time constants, and in-phase synchrony for slow time constants. We also show that phase models and phase response curves (PRCs) qualitatively predict phase locking observed in electrophysiology experiments. Finally, we investigate the stability of the dynamic clamp system. We determined that the maximal conductance of the current being simulated, the dynamic clamp sampling rate, the amount of electrode resistance compensation, and the amount of capacitance compensation all affect when the instability is present. There is a dramatic increase in stability when the electrode resistance and system capacitance are well compensated. Ph.D. Committee Chair: Butera, Robert; Committee Member: Canavier, Carmen; Committee Member: DeWeerth, Stephen; Committee Member: Hasler, Paul; Committee Member: Lanterman, Aaron; Committee Member: Prinz, Astrid

Causes of Transient Instabilities in the Dynamic Clamp

Article

Full-text available

Mar 2009
IEEE T NEUR SYS REH

The dynamic clamp is a widely used method for integrating mathematical models with electrophysiological experiments. This method involves measuring the membrane voltage of a cell, using it to solve computational models of ion channel dynamics in real-time, and injecting the calculated current(s) back into the cell. Limitations of this technique include those associated with single electrode current clamping and the sampling effects caused by the dynamic clamp. In this study, we show that the combination of these limitations causes transient instabilities under certain conditions. Through physical experiments and simulations, we show that dynamic clamp instability is directly related to the sampling delay and the maximum simulated conductance being injected. It is exaggerated by insufficient electrode series resistance and capacitance compensation. Increasing the sampling rate of the dynamic clamp system increases dynamic clamp stability; however, this improvement, is constrained by how well the electrode series resistance and capacitance are compensated. At present, dynamic clamp sampling rates are justified solely on the temporal dynamics of the models being simulated; here we show that faster rates increase the stable range of operation for the dynamic clamp system. In addition, we show that commonly accepted levels of resistance compensation nevertheless significantly compromise the stability of a dynamic clamp system.

Neuromorphic Neural Interfaces

Chapter

Feb 2023

Neuromorphic engineering aims at designing and building electronic systems that emulate the function and organization of nervous systems in very large-scale integration (VLSI) technology. Current neuromorphic VLSI hardware can now emulate large-scale neural network models with up to a million of silicon neurons, as well as various computational primitives involved in pattern recognition, learning, classification, and decision-making processes. These advances have spurred the development of closed-loop biohybrid circuits between populations of biological neurons and neural networks of silicon neurons. Biohybrid systems provide biological realism and relevance for investigating neuronal network functions and for fast prototyping of bidirectional neuromorphic neural interfaces and neuroprosthetic devices. This chapter describes the current efforts toward large-scale neuromorphic neural interfaces and their emerging applications in closed-loop neuroscience, for the study of neuronal networks at multiple timescales and levels of biological organization, and in neuroprosthetics, for the restoration of sensory, motor, and cognitive functions.

Dynamic Clamp Technique

Chapter

Jun 2022

Homeostatic plasticity and burst activity are mediated by hyperpolarization-activated cation currents and T-type calcium channels in neuronal cultures

Article

Full-text available

Feb 2021

Homeostatic plasticity stabilizes neuronal networks by adjusting the responsiveness of neurons according to their global activity and the intensity of the synaptic inputs. We investigated the homeostatic regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) and T-type calcium (CaV3) channels in dissociated and organotypic slice cultures. After 48 h blocking of neuronal activity by tetrodotoxin (TTX), our patch-clamp experiments revealed an increase in the depolarizing voltage sag and post-inhibitory rebound mediated by HCN and CaV3 channels, respectively. All HCN subunits (HCN1 to 4) and T-type Ca-channel subunits (CaV3.1, 3.2 and 3.3) were expressed in both control and activity-deprived hippocampal cultures. Elevated expression levels of CaV3.1 mRNA and a selective increase in the expression of TRIP8b exon 4 isoforms, known to regulate HCN channel localization, were also detected in TTX-treated cultured hippocampal neurons. Immunohistochemical staining in TTX-treated organotypic slices verified a more proximal translocation of HCN1 channels in CA1 pyramidal neurons. Computational modeling also implied that HCN and T-type calcium channels have important role in the regulation of synchronized bursting evoked by previous activity-deprivation. Thus, our findings indicate that HCN and T-type Ca-channels contribute to the homeostatic regulation of excitability and integrative properties of hippocampal neurons.

Alternative classifications of neurons based on physiological properties and synaptic responses, a computational study

Article

Full-text available

Sep 2019

One of the central goals of today's neuroscience is to achieve the conceivably most accurate classification of neuron types in the mammalian brain. As part of this research effort, electrophysiologists commonly utilize current clamp techniques to gain a detailed characterization of the neurons' physiological properties. While this approach has been useful, it is not well understood whether neurons that share physiological properties of a particular phenotype would also operate consistently under the action of natural synaptic inputs. We approached this problem by simulating a biophysically diverse population of model neurons based on 3 generic phenotypes. We exposed the model neurons to two types of stimulation to investigate their voltage responses under conventional current step protocols and under simulated synaptic bombardment. We extracted standard physiological parameters from the voltage responses elicited by current step stimulation and spike arrival times descriptive of the model's firing behavior under synaptic inputs. The biophysical phenotypes could be reliably identified using classification based on the 'static' physiological properties, but not the interspike interval-based parameters. However, the model neurons associated with the biophysically different phenotypes retained cell type specific features in the fine structure of their spike responses that allowed their accurate classification.

RTHybrid: a standardized and open-source real-time software model library for experimental neuroscience

Preprint

Full-text available

Sep 2018

Neuromorphic synapses with reconfigurable voltage-gated dynamics for biohybrid neural circuits

Conference Paper

Oct 2017

A Dynamic Clamp on Every Rig

Article

Full-text available

Sep 2017

The dynamic clamp should be a standard part of every cellular electrophysiologist’s toolbox. That it is not, even 25 years after its introduction, comes down to three issues: money, the disruption that adding dynamic clamp to an existing electrophysiology rig entails, and the technical prowess required of experimenters. These have been valid and limiting issues in the past, but no longer. Technological advances associated with the so-called “maker movement” render them moot. We demonstrate this by implementing a fast (~100 kHz) dynamic clamp system using an inexpensive microcontroller (Teensy 3.6). The overall cost of the system is less than USD$100, and assembling it requires no prior electronics experience. Modifying it – for example, to add Hodgkin-Huxley-style conductances – requires no prior programming experience. The system works together with existing electrophysiology data acquisition systems (for Macintosh, Windows, and Linux); it does not attempt to supplant them. Moreover, the process of assembling, modifying, and using the system constitutes a useful pedagogical exercise for students and researchers with no background but an interest in electronics and programming. We demonstrate the system’s utility by implementing conductances as fast as a transient sodium conductance and as complex as the Ornstein-Uhlenbeck conductances of the “point conductance” model of synaptic background activity.

Supplementary Material

Data

Full-text available

Oct 2012

Cell-specific Dynamic Clamp analysis of the role of funny If current in cardiac pacemaking

Article

Dec 2015

Dynamic Clamp in Biomimetic and Biohybrid Living-Hardware Systems

Article

Jun 2009

What is a Dynamic Clamp?Dynamic Clamp Performance and LimitationsExperimental Applications of Dynamic ClampDynamic Clamp System Implementations and FutureResourcesReferences

Fusion of real neuron and mathematical model by using dynamic clamp technique

Article

Jan 2009

The current clamp and voltage clamp techniques have been mainly used in intracellular recording. A third clamp technique recently receiving attention is the dynamic clamp; this technique enables a real-time interaction between a real neuron and a mathematical model. Here, we review our studies with the dynamic clamp techniques. First, we introduce the dynamic clamp that we recently developed. Next, we show an example of constructing a hybrid network of a real hippocampal CA1 pyramidal neuron and a model interneuron. Finally, we describe perturbation experiments for measuring the phase response curve performed on a real hippocampal CA1 pyramidal neuron. The dynamic clamp enables us to apply theoretical approaches to physiological experiments.

Hybrid Systems Analysis: Real-Time Systems for Design and Prototyping of Neural Interfaces and Prostheses

Article

Jun 2009

IntroductionTechnologyApplicationsHybrid Systems Analysis in the Leech Heart InterneuronDiscussionReferences

Dynamic Clamp Technique

Chapter

Feb 2014

DefinitionDynamic clamp is an electrophysiological technique for introducing simulated electrical components into biological cells using a real-time closed loop between the cell and a computer or another electronic device. Classic dynamic clamp protocols build a voltage-dependent current injection cycle to implement artificial membrane or synaptic conductances in the cell membrane of biological neurons. These protocols are employed to assess a large variety of neuronal computational properties and are widely applied for studying the physiology of neural systems at the cellular and circuit levels.Detailed DescriptionHistoryThe use of closed-loop feedback interactions with living neurons for observation and control purposes goes back to the beginnings of electrophysiology when the voltage clamp technique was developed (Marmont 1949; Cole 1955). The voltage clamp technique measures currents across the membrane of excitable cells while holding the membrane potential at a constant level. In ...

Modeling and Simulation of Ion Channels

Article

Oct 2012
CHEM REV

A study was conducted to demonstrate modeling and simulation of ion channels. Early phenomenological models of excitable membranes were discussed and the latest developments in this area were reviewed. Early work on phenomenological modeling of ion channels occurred before the existence of ion channels had been established. Researchers were making efforts to understand the mechanism of signal propagation in nerve cells. Early models described the axon as a 'cable', with a conductive core surrounded by a less conductive, capacitive sheath, which was later identified as a membrane in the Hodgkin-Huxley (HH) model. The HH model played a key role in understanding of nerve cells, and excitable membranes, while continuing to influence research work in the field. A team of researchers also demonstrated that millisecond all-atom molecular dynamic (MD) simulation of ion channels was performed by using Anton, a special-purpose hardware designed only for such MD simulations.

Modulation of respiratory sinus arrhythmia in rats with central pattern generator hardware

Article

Sep 2012

We report on the modulation of respiratory sinus arrhythmia in rats with central pattern generator (CPG) hardware made of silicon neurons. The neurons are made to compete through mutually inhibitory synapses to provide timed electrical oscillations that stimulate the peripheral end of vagus nerve at specific points of the respiratory cycle: the inspiratory phase (φ(1)), the early expiratory phase (φ(2)) and the late expiratory phase (φ(3)). In this way the CPG hardware mimics the neuron populations in the brainstem which through connections with cardiac vagal motoneurones control respiratory sinus arrhythmia (RSA). Here, we time the output of the CPG hardware from the phrenic nerve activity recorded from rats while monitoring heart rate changes evoked by vagal nerve stimulation (derived from ECG) controlled by the CPG. This neuroelectric stimulation has the effect of reducing the heart rate and increasing the arterial pressure. The artificially induced RSA strongly depends on the timing of pulses within the breathing cycle. It is strongest when the vagus nerve is stimulated during the inspiratory phase (φ(1)) or the early expiratory phase (φ(2)) in which case the heart rate slows by 50% of the normal rate. Heart rate modulation is less when the same exact stimulus is applied during the late expiratory phase (φ(3)). These trials show that neurostimulation by CPG hardware can augment respiratory sinus arrhythmia. The CPG hardware technology opens a new line of therapeutic possibilities for prosthetic devices that restore RSA in patients where respiratory-cardiac coupling has been lost.

Key Factors for Improving Dynamic-Clamp Performance

Chapter

Mar 2009

The dynamic-clamp technique has been recognized and used by electrophysiologists for over 15 years. Nevertheless, only a small number of papers have been written focusing on the performance and reliability of this protocol and how the accuracy of a dynamic-clamp system can be assessed. Here we review the published literature to date, focusing on how experimental, computational, and algorithmic factors contribute to the reliability of the dynamic-clamp protocol. Several of these papers point towards a common and technologically realizable solution – the need for dynamic-clamp systems that run at computational rates much faster (100–200kHz) than currently available. At present, dynamic-clamp rates are limited by the use of desktop computers and rationalized by the kinetics of the model simulated. Recent results show that faster and lower latency systems would result in a greater range of conductances that could be utilized, improved stability, and more accurate real-time model simulations.

Realistic Stimulation Through Advanced Dynamic-Clamp Protocols

Conference Paper

Full-text available

Jun 2005
Lect Notes Comput Sci

Traditional techniques to stimulate neurons in Neuroscience include current injection using several protocols. In most cases, although neurons are able to react to any stimulus in the physiological range, it is difficult to assess to what extent the response is a natural output to the processing of the input or just an awkward reaction to a foreign signal. In experiments that try to study the precise temporal relationships between the stimulus and the output pattern, it is crucial to use realistic stimulation protocols. Dynamic-clamp is a relatively recent method in electrophysiology to mimic the presence of ionic or synaptic conductances in a cell membrane through the injection of a controlled current waveform. Here we present a set of advanced dynamic-clamp protocols for realistic stimulation of cells that allow from the addition of single and multiple ionic or synaptic conductances, to the reconfiguration of circuits and bidirectional communication of living cells with model neurons including plasticity mechanisms.

Phase Resetting in an Asymptotically Phaseless System: On the Phase Response of Limit Cycles Verging on a Heteroclinic Orbit

Article

Full-text available

Mar 2011
SIAM J APPL DYN SYST

Rhythmic behaviors in neural systems often combine features of limit cycle dynamics (stability and periodicity) with features of near heteroclinic or near homoclinic cycle dynamics (extended dwell times in localized regions of phase space). Proximity of a limit cycle to one or more saddle equilibria can have a profound effect on the timing of trajectory components and response to both fast and slow perturbations, providing a possible mechanism for adaptive control of rhythmic motions. Reyn showed that for a planar dynamical system with a stable heteroclinic cycle (or separatrix polygon), small perturbations satisfying a net inflow condition will generically give rise to a stable limit cycle (Reyn, 1980; Guckenheimer and Holmes, 1983). Here we consider the asymptotic behavior of the infinitesimal phase response curve (iPRC) for examples of two systems satisfying Reyn's inflow criterion, (i) a smooth system with a chain of four hyperbolic saddle points and (ii) a piecewise linear system corresponding to local linearization of the smooth system about its saddle points. For system (ii), we obtain exact expressions for the limit cycle and the iPRC as a function of a parameter, mu>0, representing the distance from a heteroclinic bifurcation point. In the limit, as mu approaches zero, we find that perturbations parallel to the unstable eigenvector direction in a piecewise linear region lead to divergent phase response, as previously observed (Brown, Moehlis and Holmes (2004), Neural Computation). In contrast to previous work, we find that perturbations parallel to the stable eigenvector direction can lead to either divergent or convergent phase response, depending on the phase at which the perturbation occurs. In the smooth system (i), we show numerical evidence of qualitatively similar phase specific sensitivity to perturbation.

Dynamic clamp with StdpC software

Article

Full-text available

Feb 2011
NAT PROTOC

Dynamic clamp is a powerful method that allows the introduction of artificial electrical components into target cells to simulate ionic conductances and synaptic inputs. This method is based on a fast cycle of measuring the membrane potential of a cell, calculating the current of a desired simulated component using an appropriate model and injecting this current into the cell. Here we present a dynamic clamp protocol using free, fully integrated, open-source software (StdpC, for spike timing-dependent plasticity clamp). Use of this protocol does not require specialist hardware, costly commercial software, experience in real-time operating systems or a strong programming background. The software enables the configuration and operation of a wide range of complex and fully automated dynamic clamp experiments through an intuitive and powerful interface with a minimal initial lead time of a few hours. After initial configuration, experimental results can be generated within minutes of establishing cell recording.

In Vitro Analysis of Optimal Stimuli for Phase-Locking and Time-Delayed Modulation of Firing in Avian Nucleus Laminaris Neurons

Article

Full-text available

Mar 1996

Neurons of the avian nucleus laminaris (NL) provide a neural substrate for azimuthal sound localization. We examined the optimal stimuli for NL neurons to maintain high discharge rates, reliable phase-locking, and sensitivity to time-delayed stimuli. Whole-cell recordings were performed in chick [embryonic days 19-21 (E19-E21)] NL neurons using an in vitro slice preparation. Variation of membrane properties along the tonotopic axis was examined. Computer-controlled intracellular current injection was used to mimic postsynaptic currents or conductances (PSCs) generated in NL neurons by the firing of nucleus magnocellularis (NM) neurons during acoustic stimulation. At various stimulus frequencies, the effects of varying the number of NM cells and PSC amplitudes on firing rate and phase-locking were examined. During high-frequency stimulation, the greatest firing rate and phase-locking occurred when the protocol contained few NM cells that generated large PSCs. Because the stimulus-evoked unitary PSCs are small, we propose that NM cells fire in synchrony to generate large PSCs. To mimic the arrival of PSCs during binaural stimulation, two stimulus trains were summed at different delays before injection. The firing rate of NL neurons was greatest with zero delay. A delay of half the stimulus period evoked firing that was less than that evoked with a single train. Neurons lacking strong outward rectification exhibited neither reliable phase-locking during high-frequency stimulation nor sensitivity to stimulus delays. These findings suggest that the firing responses of NL neurons are determined primarily by their membrane properties.

All thalamocortical neurones possess a T‐type Ca2+‘window’ current that enables the expression of bistability‐mediated activities

Article

Full-text available

Sep 2004
J PHYSIOL-LONDON

• The existence of a non-negligible steady-state (‘window’) component of the low threshold, T-type Ca2+current (IT) and an appropriately large ratio of IT to ILeak conductance (i.e. gT/gLeak) have been shown to underlie a novel form of intrinsic bistability that is present in about 15 % of thalamocortical (TC) neurones. • In the present experiments, the dynamic clamp technique was used to introduce into mammalian TC neurones in vitro either an artificial, i.e. computer-generated, IT in order to enhance endogenous IT, or an artificial inward ILeak to decrease endogenous ILeak. Using this method, we were able to investigate directly whether the majority of TC neurones appear non-bistable because their intrinsic ionic membrane properties are essentially different (i.e. presence of a negligible IT‘window’ component), or simply because they possess a gT or gLeak conductance that is insufficiently large or small, respectively. • The validity of the dynamic clamp arrangement and the accuracy of artificial IT were confirmed by (i) recreating the low threshold calcium potential (LTCP) with artificial IT following its block by Ni2+ (0.5–1 mM), and (ii) blocking endogenous LTCPs with an artificial outward IT. • Augmentation of endogenous IT by an artificial analog or introduction of an artificial inward ILeak transformed all non-bistable TC neurones to bistable cells that expressed the full array of bistability-mediated behaviours, i.e. input signal amplification, slow oscillatory activity and membrane potential bistability. • These results demonstrate the existence of a non-negligible IT‘window’ component in all TC neurones and suggest that rather than being a novel group of neurones, bistable cells are merely representative of an interesting region of dynamical modes in the (gT, gLeak) parameter space that may be expressed under certain physiological or pathological conditions by all TC neurones and other types of excitable cells that possess an IT‘window’ component with similar biophysical properties.

Organization of the stomatogastric ganglion of the spiny lobster - I. Neurons driving the lateral teeth

Article

Full-text available

Mar 1974

The Stomatogastric ganglion ofPanulirus interruptus contains about 30 neurons, and controls the movements of the lobster's stomach. When experimentally isolated, the ganglion continues to generate complex rhythmic patterns of activity in its motor neurons which are similar to those seen in intact animals.In this paper, we describe the synaptic organization of a group of six neurons which drive the stomach's lateral teeth (Figs. 2, 6). This group includes four motor neurons and two interneurons, all but one of which were recorded and stimulated with intracellular microelectrodes.One pair of synergistic motor neurons, LGN and MGN, are electrotonically coupled and reciprocally inhibitory (Figs. 9, 12). A second pair of synergistic motor neurons, the LPGNs, are antagonists of LGN and MGN. The LPGNs are electrotonically coupled (Fig. 14), and are both inhibited by LGN and MGN (Figs. 8, 11). The LPGNs inhibit MGN (Fig. 15) but not LGN. One of the two interneurons in the ganglion, Int 1, reciprocally inhibits both LGN and MGN (Figs. 10, 13). The other interneuron, Int 2, excites Int 1 and inhibits the LPGNs (Fig. 16). The synaptic connections observed in the ganglion are reflected in the spontaneous activity recorded from the isolated ganglion and from intact animals.From the known synaptic organization and observations on the physiological properties of each of the neurons, we have formulated some hypotheses about the pattern-generating mechanism. We found no evidence that any of the neurons are endogenous bursters.

The pyloric central pattern generator in Crustacea: a set of conditional neural oscillators

Article

Full-text available

Nov 1988

In the stomatogastric nervous system of the Cape lobster,Jasus lalandii, all the neurons comprising the pyloric central pattern generator are cellular oscillators. This was shown by isolating in situ pyloric neurons from all other elements in the pyloric network. These neuronal oscillators are conditional and require modulatory inputs from anterior centers in order to express their oscillatory capabilities.1. Pyloric neurons were isolated from their counterparts in the network by photoinactivation of most of their presynaptic neurons (Miller and Selverston 1979, 1982a), and completed by pharmacological blockade of the remaining presynaptic influences. Under these conditions, all pyloric neurons display spontaneous bursting and underlying oscillations of their membrane potential. 2. Both period and amplitude of oscillation in all isolated pyloric neurons vary when their membrane potential is modified by current injection. Furthermore, in isolated constrictor neurons (LP, PY and IC) the duration of the rhythmic regenerative depolarizations is also dependent on membrane potential. 3. After isolation in situ, each type of pyloric neuron manifests a particular oscillatory behavior. The isolated interneuron AB has the fastest oscillation period with the shortest depolarizing phase. These oscillations closely resemble AB oscillations in the intact network. At the other extreme are the constrictor neurons (LP, PY and IC) which, when isolated, display spontaneous oscillations rather different from their oscillations in the intact network. Oscillations of isolated pyloric constrictor neurons are rhythmical plateaus whose duration and frequency are fairly irregular. 4. When axonal conduction is blocked in the single input nerve to the stomatogastric ganglion, none of the isolated pyloric neurons is able to oscillate whether at rest or when their membrane potential is modified by current injection. Under these conditions, electrical stimulation of the input nerve on the ganglionic side of the block restores oscillations in isolated pyloric neurons. 5. In conclusion, the pyloric network can be considered as a set of conditional oscillatory neurons, one of which, the interneuron AB, has a pacemaker function.

An Efficient Method for Computing Synaptic Conductances Based on a Kinetic Model of Receptor Binding

Article

Full-text available

Jul 1994

Past models of somatosensory cortex have successfully demonstrated map formation and subsequent map reorganization following localized repetitive stimuli or deafferentation. They provide an impressive demonstration that fairly simple assumptions about ...

From biophysics to models of network function

Article

Full-text available

Mar 1998

Eve Marder

Neurons and synapses display a rich range of time-dependent processes. Which of these are critical to understanding specific integrative functions in the brain? Computational methods of various kinds are used to understand how systems of neurons interact to produce behavior. However, these models often assume that neuronal dynamics and synaptic strengths are fixed. This review presents some recent models that illustrate that short-term synaptic plasticity mechanisms such as facilitation and depression can have important implications for network function. Other features of synaptic transmission such as multi-component synaptic potentials, cotransmission, and neuromodulation with obvious potential computational implications are presented. These examples illustrate that synaptic strength and intrinsic properties in networks are continuously varying on numerous time scales as a function of the temporal patterns of activity in the network. Thus, both firing frequency of the neurons in a circuit, and the modulatory environment determine the intrinsic and synaptic properties that produce behavior.

Modulation of Neural Networks for Behavior

Article

Full-text available

Feb 1991

Mechanisms underlying pattern generation in lobster stomatogastric ganglion as determined by selective inactivation of identified neurons. I. Pyloric system

Article

Full-text available

Jan 1981

1. Four factors contribute to pattern generation in the pyloric network of the lobster stomatogastric ganglion. These are: a) endogenously oscillating neurons; b) synaptic network properties; c) nonlinear cellular properties, including the generation of plateau potentials; and d) excitatory input from the commissural ganglia. The roles and relative importance of these factors were investigated with a new technique for inactivating single specific identified neurons. 2. In stomatogastric ganglia in which the excitatory input is left intact, a) pattern generation continues when any cell or pair of cells other than the endogenous bursters are inactivated, b) pattern generation also continues when the endogenous bursters are inactivated, c) pattern generation ceases when the endogenous bursters plus one other particular cell are inactivated. This cell, although not an endogenous burster, displays a strong tendency to generate plateau potentials. 3. In stomatogastric ganglia that have been isolated from excitatory input, a) pattern generation continues when any cell or pair of cells other than the endogenous bursters are inactivated, b) pattern generation ceases when the endogenous bursters are inactivated. 4. Some of the inputs to the stomatogastric ganglion normally fire in bursts. However, their potentiation and acceleration of the output pattern are also produced by tonic stimulation of the nerve. The effect of one of those inputs is mimicked by bath application of dopamine to the stomatogastric ganglion. 5. The roles and importance of the three most important factors were qualitatively summarized in a chart specifying the activity of the network as a function of its intactness.

Mechanisms underlying pattern generation in lobster stomatogastric ganglion as determined by selective inactivation of identified neurons. III. Synaptic connections of electrically coupled pyloric neurons

Article

Full-text available

Jan 1983

1. The pyloric dilator (PD) and anterior burster (AB) neurons in the pyloric system of the lobster stomatogastric ganglion are electrically coupled and synchronously active. We have used the lucifer yellow photoinactivation technique to separate the connections made by the PD motor neurons from those made by the AB interneuron. 2. Photoinactivation of either the two PD neurons or the single AB neuron allowed us to separate the compound inhibitory postsynaptic potentials (IPSPs) in the lateral pyloric (LP) and pyloric (PY) motor neurons resulting from synchronous PD and AB activity into AB-evoked and PD-evoked components. These IPSPs have different time courses, reversal potentials, ion selectivities, and pharmacological properties. 3. Photoinactivation and membrane-potential manipulations indicated that a readily observable IPSP recorded in the AB neuron and correlated with action potentials in the LP neuron is actually an electrotonic potential due to an LP-evoked IPSP in the PD neurons. 4. Selective inactivation of either the two PD neurons or the AB neuron revealed that the IPSP recorded in the ventricular dilator (VD) motor neuron is due solely to AB-released transmitter. 5. The electrical coupling potentials measurable between the AB, PD, and VD neuron somata are due to direct electrical coupling between all of these neurons. 6. Circuit analysis and transmitter identification may be complicated by electrical coupling. We suggest that the presence of electrical coupling between nonidentical neurons may provide a new mechanism that allows changes in synaptic characteristics among neurons within a "hard-wired" circuit.

Dynamic neuromodulation of synaptic strength intrinsic to a central pattern generator circuit

Article

Full-text available

Mar 1994

Motor circuits are often thought to be physically separate from their neuromodulatory systems. We report here a counter example, where neurons within a circuit appear to modulate synaptic properties of that same circuit during its normal operation. The dorsal swim interneurons (DSIs) are members of the central pattern generator circuit for escape swimming in the mollusc Tritonia diomedea. However, DSI stimulation also rapidly enhances the synaptic potentials evoked by another neuron in the same circuit onto its follower cells. This modulatory action appears to be mediated by serotonin (5-hydroxytryptamine); the DSIs are serotonin-immunoreactive, and bath-application of serotonin mimics and occludes the effect of DSIs. These results indicate that during the escape swim, circuit connection strengths are dynamically controlled by the activity of neurons within the circuit itself. This 'intrinsic neuromodulation' may be important for the animal's initial decision to swim, the generation of the swim motor programme itself, and certain types of learning.

The Role of K + Currents in Frequency-Dependent Spike Broadening in Aplysia R20 Neurons: A Dynamic-Clamp Analysis

Article

Full-text available

Aug 1996

The R20 neurons of Aplysia exhibit frequency-dependent spike broadening. Previously, we had used two-electrode voltage clamp to examine the mechanisms of this spike broadening (Ma and Koester, 1995). We identified three K ⁺ currents that mediate action-potential repolarization: a transient A-type K ⁺ current ( I Adepol ), a delayed rectifier current ( I K-V ), and a Ca ²⁺ -sensitive K ⁺ current ( I K-Ca ). A major constraint in that study was the lack of completely selective blockers for I Adepol and I K-V , resulting in an inability to assess directly the effects of their activation and inactivation on spike broadening. In the present study, the dynamic-clamp technique, which employs computer simulation to inject biologically realistic currents into a cell under current-clamp conditions (Sharp et al., 1993a,b), was used either to block I Adepol or I K-V or to modify their inactivation properties. The data in this paper, together with earlier results, lead to the following hypothesis for the mechanism of spike broadening in the R20 cells. As the spike train progresses, the primary responsibility for spike repolarization gradually shifts from I Adepol to I K-V to I K-Ca . This sequence can be explained on the basis of the relative rates of activation and inactivation of each current with respect to the constantly changing spike durations, the cumulative inactivation of I Adepol and I K-V , and the progressive potentiation of I K-Ca . Positive feedback interactions between spike broadening and inactivation contribute to the cumulative inactivation of both I Adepol and I K-V . The data also illustrate that when two or more currents have similar driving forces and partially overlapping activation characteristics, selectively blocking one current under current-clamp conditions can lead to a significant underestimate of its normal physiological importance.

Dopamine modulation of two subthreshold currents produces phase shifts in activity of an identified motoneuron

Article

Full-text available

Nov 1995

1. The lateral pyloric (LP) neuron is a component of the 14-neuron pyloric central pattern generator in the stomatogastric ganglion of the spiny lobster, Panulirus interruptus. In the pyloric rhythm, this neuron fires rhythmic bursts of action potentials whose phasing depends on the pattern of synaptic inhibition from other network neurons and on the intrinsic postinhibitory rebound properties of the LP cell itself. Bath-applied dopamine excites the LP cell and causes its activity to be phase advanced in the pyloric motor pattern. At least part of this modulatory effect is due to dopaminergic modulation of the intrinsic rate of postinhibitory rebound in the LP cell. 2. The LP neuron was isolated from all detectable synaptic input. We measured the rate of recovery after 1-s hyperpolarizing current injections of varying amplitudes, quantifying the latency to the first spike following the hyperpolarizing prepulse and the interval between the first and second action potentials. Dopamine reduced both the first spike latency and the first interspike interval (ISI) in the isolated LP neuron. During the hyperpolarizating pre-steps, the LP cell showed a slow depolarizing sag voltage that was enhanced by dopamine. 3. We used voltage clamp to analyze dopamine modulation of subthreshold ionic currents whose activity is affected by hyperpolarizing prepulses. Dopamine modulated the transient potassium current IA by reducing its maximal conductance and shifting its voltage dependence for activation and inactivation to more depolarized voltages. This outward current is normally transiently activated after hyperpolarization of the LP cell, and delays the rate of postinhibitory rebound; by reducing IA, dopamine thus accelerates the rate of rebound of the LP neuron. 4. Dopamine also modulated the hyperpolarization-activated inward current Ih by shifting its voltage dependence for activation 20 mV in the depolarizing direction and accelerating its rate of activation. This enhanced inward current helps accelerate the rate of rebound in the LP cell after inhibition. 5. The relative roles of Ih and IA in determining the first spike latency and first ISI were explored using pharmacological blockers of Ih (Cs+) and IA [4-aminopyridine (4-AP)]. Blockade of Ih prolonged the first spike latency and first ISI, but only slightly reduced the net effect of dopamine. In the continued presence of Cs+, blockade of IA with 4-AP greatly shortened the first spike latency and first ISI. Under conditions where both Ih and IA were blocked, dopamine had no additional effect on the LP cell. 6. We used the dynamic clamp technique to further study the relative roles of IA and Ih modulation in dopamine's phase advance of the LP cell. We blocked the endogenous Ih with Cs+ and replaced it with a simulated current generated by a computer model of Ih. The neuron with simulated Ih gave curves relating the hyperpolarizing prepulse amplitude to first spike latency that were the same as in the untreated cell. Changing the computer parameters of the simulated Ih to those induced by dopamine without changing IA caused only a slight reduction in first spike latency, which was approximately 20% of the total reduction caused by dopamine in an untreated cell. Bath application of dopamine in the presence of Cs+ and simulated Ih (with control parameters) allowed us to determine the effect of altering IA but not Ih: this caused a significant reduction in first spike latency, but it was still only approximately 70% of the effect of dopamine in the untreated cell. Finally, in the continued presence of dopamine, changing the parameters of the simulated Ih to those observed with dopamine reduced the first spike latency to that seen with dopamine in the untreated cell. 7. We generated a mathematical model of the lobster LP neuron, based on the model of Buchholtz et al. for the crab LP neuron.

Synaptic depression creates a switch that controls the frequency of an oscillatory circuit

Article

Full-text available

Aug 1999

Synaptic depression is a form of short-term plasticity exhibited by many synapses. Nonetheless, the functional significance of synaptic depression in oscillatory networks is not well understood. We show that, in a recurrent inhibitory network that includes an intrinsic oscillator, synaptic depression can give rise to two distinct modes of network operation. When the maximal conductance of the depressing synapse is small, the oscillation period is determined by the oscillator component. Increasing the maximal conductance beyond a threshold value activates a positive-feedback mechanism that greatly enhances the synaptic strength. In this mode, the oscillation period is determined by the strength and dynamics of the depressing synapse. Because of the regenerative nature of the feedback mechanism, the circuit can be switched from one mode of operation to another by a very small change in the maximal conductance of the depressing synapse. Our model was inspired by experimental work on the pyloric network of the lobster. The pyloric network produces a simple motor rhythm generated by a pacemaker neuron that receives feedback inhibition from a depressing synapse. In some preparations, elimination of the synapse had no effect on the period of the rhythm, whereas in other preparations, there was a significant decrease in the period. We propose that the pyloric network can operate in either of the two modes suggested by the model, depending on the maximal conductance of the depressing synapse.

Synaptic Control of Spiking in Cerebellar Purkinje Cells: Dynamic Current Clamp Based on Model Conductances

Article

Full-text available

Aug 1999
J NEUROSCI

Previous simulations using a realistic model of a cerebellar Purkinje cell suggested that synaptic control of somatic spiking in this cell type is mediated by voltage-gated intrinsic conductances and that inhibitory rather than excitatory synaptic inputs are more influential in controlling spike timing. In this paper, we have tested these predictions physiologically using dynamic current clamping to apply model-derived synaptic conductances to Purkinje cells in vitro. As predicted by the model, this input transformed the in vitro pattern of spiking into a different spike pattern typically observed in vivo. A net inhibitory synaptic current was required to achieve such spiking, indicating the presence of strong intrinsic depolarizing currents. Spike-triggered averaging confirmed that the length of individual intervals between spikes was correlated to the amplitude of the inhibitory conductance but was not influenced by excitatory inputs. Through repeated presentation of identical stimuli, we determined that the output spike rate was very sensitive to the relative balance of excitation and inhibition in the input conductances. In contrast, the accuracy of spike timing was dependent on input amplitude and was independent of spike rate. Thus, information could be encoded in Purkinje cell spiking in a precise spike time code and a rate code at the same time. We conclude that Purkinje cell responses to synaptic input are strongly dependent on active somatic and dendritic properties and that theories of cerebellar function likely need to incorporate single-cell dynamics to a greater degree than is customary.

Coordination of Fast and Slow Rhythmic Neuronal Circuits

Article

Full-text available

Sep 1999

Interactions among rhythmically active neuronal circuits that oscillate at different frequencies are important for generating complex behaviors, yet little is known about the underlying cellular mechanisms. We addressed this issue in the crab stomatogastric ganglion (STG), which contains two distinct but interacting circuits. These circuits generate the gastric mill rhythm (cycle period, approximately 10 sec) and the pyloric rhythm (cycle period, approximately 1 sec). When the identified modulatory projection neuron named modulatory commissural neuron 1 (MCN1) is activated, the gastric mill motor pattern is generated by interactions among MCN1 and two STG neurons [the lateral gastric (LG) neuron and interneuron 1]. We show that, during MCN1 stimulation, an identified synapse from the pyloric circuit onto the gastric mill circuit is pivotal for determining the gastric mill cycle period and the gastric-pyloric rhythm coordination. To examine the role of this intercircuit synapse, we replaced it with a computational equivalent via the dynamic-clamp technique. This enabled us to manipulate better the timing and strength of this synapse. We found this synapse to be necessary for production of the normal gastric mill cycle period. The synapse acts, during each LG neuron interburst, to boost rhythmically the influence of the modulatory input from MCN1 to LG and thereby to hasten LG neuron burst onset. The two rhythms become coordinated because LG burst onset occurs with a constant latency after the onset of the triggering pyloric input. These results indicate that intercircuit synapses can enable an oscillatory circuit to control the speed of a slower oscillatory circuit, as well as provide a mechanism for intercircuit coordination.

Neuromodulation of stomatogastric networks by identified neurons and transmitters

Article

Jan 1992

Dynamic Clamp - Computer-Generated Conductances in Real Neurons

Article

Apr 1993

1. We describe a new method, the dynamic clamp, that uses a computer as an interactive tool to introduce simulated voltage and ligand mediated conductances into real neurons. 2. We simulate a gamma-aminobutyric acid (GABA) response of a cultured stomatogastric ganglion neuron to illustrate that the dynamic clamp effectively introduces a conductance into the target neuron. 3. To demonstrate an artificial voltage-dependent conductance, we simulate the action of a voltage-dependent proctolin response on a neuron in the intact stomatogastric ganglion. We show that shifts in the activation curve and the maximal conductance of the response produce different effects on the target neuron. 4. The dynamic clamp is used to construct reciprocal inhibitory synapses between two stomatogastric ganglion neurons that are not coupled naturally, illustrating that this method can be used to form new networks at will.

A quantitative description of ion currents and its applications to conduction and excitation in nerve membranes

Article

Jan 1952

This article concludes a series of papers concerned with the flow of electric current through the surface membrane of a giant nerve fibre (Hodgkinet al., 1952,J. Physiol.116, 424–448; Hodgkin and Huxley, 1952,J. Physiol.116, 449–566). Its general object is to discuss the results of the preceding papers (Section 1), to put them into mathematical form (Section 2) and to show that they will account for conduction and excitation in quantitative terms (Sections 3–6).

Analysis of the Central Pattern Generator for Swimming in the Mollusk Clionea

Article

Nov 1998

: The pteropod mollusk Clione limacina swims by rhythmic movements of two wings. The central pattern generator (CPG) for swimming, located in the pedal ganglia, is formed by three groups of interneurons. The interneurons of the groups 7 and 8 are of crucial importance for rhythm generation. They are endogenous oscillators capable of generating rhythmic activity with a range of frequencies typical of swimming after extraction from the ganglia. This endogenous rhythmic activity is enhanced by serotonin. The interneurons 7 and 8 produce one prolonged action potential (about 100 ms in duration) per cycle. Prolonged action potentials contribute to determining the duration of the cycle phases. The interneurons of two groups inhibit one another determining their reciprocal activity. The putative transmitters of groups 7 and 8 interneurons are glutamate and acetylcholine, respectively. Transition from one phase to the other is facilitated by the plateau interneurons of group 12 that contribute to termination of one phase and to initiation of the next phase. Maintaining the rhythm generation and transition from one phase to the other is also promoted by postinhibitory rebound. The redundant organization of the swimming generator guarantees the high reliability of its operation. Generation of the swimming output persisted after the inhibitory input from interneurons 8 to 7 had been blocked by atropine. Activity of the swimming generator is controlled by a set of command neurons that activate, inhibit or modulate the operation of the swimming CPG in relation to a behaviorally relevant context.

A quantitative description of membrane current and its application to conduction and excitation in nerve

Article

Jan 1990

This article concludes a series of papers concerned with the flow of electric current through the surface membrane of a giant nerve fibre (Hodgkinet al., 1952,J. Physiol. 116, 424–448; Hodgkin and Huxley, 1952,J. Physiol. 116, 449–566). Its general object is to discuss the results of the preceding papers (Section 1), to put them into mathematical form (Section 2) and to show that they will account for conduction and excitation in quantitative terms (Sections 3–6).

Richmond, S.: Hard-wired central pattern generators for quadrupedal locomotion. Biol. Cybernet. 71, 375-385

Article

Sep 1994

Animal locomotion is generated and control- led, in part, by a central pattern generator (CPG), which is an intraspinal network of neurons capable of pro- ducing rhythmic output. In the present work, it is demon- strated that a hard-wired CPG model, made up of four coupled nonlinear oscillators, can produce multiple phase-locked oscillation patterns that correspond to three common quadrupedal gaits - the walk, trot, and bound. Transitions between the different gaits are gener- ated by varying the network's driving signal and/or by altering internal oscillator parameters. The above in numero results are obtained without changing the relative strengths or the polarities of the system's synap- tic interconnections, i.e., the network maintains an in- variant coupling architecture. It is also shown that the ability of the hard-wired CPG network to produce and switch between multiple gait patterns is a model-inde- pendent phenomenon, i.e., it does not depend upon the detailed dynamics of the component oscillators and/or the nature of the inter-oscillator coupling. Three different neuronal oscillator models - the Stein neuronal model, the Van der Pol oscillator, and the FitzHugh-Nagumo model - and two different coupling schemes are incorp- orated into the network without impeding its ability to produce the three quadrupedal gaits and the aforemen- tioned gait transitions.

Control of multistability in ring circuits of oscillators

Article

Feb 1999

The essential dynamics of some biological central pattern generators (CPGs) can be captured by a model consisting of N neurons connected in a ring. These circuits, like many oscillatory nonlinear circuits of sufficient complexity, are capable of multistability, that is, of generating different firing patterns distinguished by the phasic relationships between the firing in each circuit element (neuron). Moreover, a shift in firing pattern can be induced by a transient perturbation. A systematic approach, based on phase-response curve (PRC) theory, was used to determine the optimum timing for perturbations that induce a shift in the firing pattern. The first step was to visualize the solution space of the ring circuit, including the attractive basins for each stable firing pattern; this was possible using the relative phase of N-1 oscillators, with respect to an arbitrarily selected reference oscillator, as coordinate axes. The trajectories in this phase space were determined using an iterative mapping based only on the PRCs of the uncoupled component oscillators; this algorithm was called a circuit emulator. For an accurate mapping of the attractive basin of each pattern exhibited by the ring circuit, the emulator had to take into account the effect of a perturbation or input on the timing of two bursts following the onset of the perturbation, rather than just one. The visualization of the attractive basins for rings of two, three, and four oscillators enabled the accurate prediction of the amounts of phase resetting applied to up to N-1 oscillators within a cycle that would induce a transition from any pattern to any another pattern. Finally, the timing and synaptic characterization of an input called the switch signal was adjusted to produce the desired amount of phase resetting.

Rapid Killing of Single Neurons by Irradiation of Intracellularly Injected Dye

Article

Dec 1979

A simple technique for rapidly killing all or part of single neurons consists of filling the cell with Lucifer Yellow CH and irradiating all or part of it with intense blue light. Such treatment kills the irradiated part of the cell within a few minutes. Adjacent cells are not affected.

Mechanisms of gastric rhythm generation in the isolated stomatogastric ganglion of spiny lobsters: Bursting pacemaker potentials, synaptic interactions, and muscarinic modulation

Article

Oct 1992

1. The gastric central pattern generator (CPG), located in the stomatogastric ganglion (STG) of the spiny lobster (Panulirus interruptus), is nonrhythmic when deprived of neuromodulatory inputs from anterior ganglia. Leaving these inputs intact in vitro can sustain a gastric rhythm but also introduces numerous, uncontrolled and largely unknown modulatory and synaptic influences that greatly complicate analysis of this CPG. 2. Here we induced gastric rhythms in the isolated STG, by superfusing a specific modulator, the muscarinic agonist, pilocarpine. Muscarinic agents sustain vigorous gastric rhythms in the isolated STG. Our aim was to analyze the pattern-generating functions of the restricted gastric circuit, free of complicating influences from other ganglia, and under specific (muscarinic) modulation. 3. We used combinations of multiple cell hyperpolarizations, photodeletions, and synaptic blockade by picrotoxin to assess the pattern-generating role of individual gastric neurons and to study the activity of subcircuits. 4. Four identified gastric neurons [lateral gastric (LG), dorsal gastric (DG), 2 electrically coupled lateral posterior gastric (2LPGs)] acted as pattern-generating cells. They showed bursting pacemaker potentials (BPPs), i.e., plateau (or driver) potentials that underlay bursts of axonal spikes and slow, interburst depolarizing potentials that underlay repetitive burst activity. LG and DG, at least, became conditional bursters, able to burst repetitively because of intrinsic oscillations. The other gastric neurons behaved mainly as follower cells and derived their rhythmic bursting from synaptic coupling to the pattern-generator cells and from their own intrinsic (but nonoscillatory) properties. 5. The pattern-generating neurons form a novel "kernel" circuit that works by the cooperative interaction of cellular properties and synaptic connectivity. 6. This study constitutes the first complete and fully consistent analysis of pattern generation in the gastric network of the isolated STG. These mechanisms pertain to muscarinic rhythms in particular but also, we suggest, to gastric rhythm generation and CPG function in general. We suggest that 1) rhythmicity normally depends on the induction of bursty membrane properties in at least some component neurons; 2) different subcircuits can produce rhythmic patterns and may be activated by different modulators; and 3) the gastric network shares several important "building blocks" with CPGs that have been analyzed in other systems. 7. Muscarinic inputs are implicated as an important gastric regulator. We compare these responses with the reported modulatory actions of the anterior pyloric modulator (AMP), an identified, putatively cholinergic input interneuron that may act via muscarinic mechanisms.

Emerging Principles Governing The Operation Of Neural Networks

Article

Feb 1989

Peter A. Getting

ical, and computational techniques have provided the tools to begin uncovering concepts underlying neural network function. This review is a summary of insights into the organization and operation of neural circuits acquired through application of these techniques to invertebrate and vertebrate systems. This review is not a survey of the vast variety of known neural networks but rather concentrates on emerging concepts applicable to net works in general. The first section provides a brief historical perspective. The second and third sections summarize two emerging concepts about the operation and modulation of neural circuits. The first concept is that the operation of a neural network depends upon interactions among mul tiple nonlinear processes at the cellular, synaptic, and network levels. The second concept is that modulation of these underlying processes can alter network operation. The final section suggests potentially profitable research directions for the future.

Transmitter identification of pyloric neurons: Electrically coupled neurons use different transmitters

Article

Jul 1984

The neurotransmitters mediating the synaptic interactions among the neurons of the pyloric system of the stomatogastric ganglion (STG) of the lobster, Panulirus interruptus, were examined using a combination of electrophysiological, pharmacological, and biochemical techniques. Iontophoretically applied L-glutamate inhibited all motor neurons of the pyloric system. This inhibitory response was blocked by low concentrations of picrotoxin but unaffected by atropine. The anterior burster (AB) interneuron, pyloric dilator (PD) motor neurons, and ventricular dilator (VD) motor neuron were depolarized and excited by iontophoretically applied acetylcholine (ACh). The lateral pyloric (LP) and pyloric (PY) constrictor motor neurons were inhibited by ACh and by the cholinergic agonist, carbachol. These inhibitory cholinergic responses were blocked by atropine but not by picrotoxin. The inhibitory postsynaptic potentials (IPSPs) evoked by the constrictor motor neurons were blocked by picrotoxin but not by atropine. Taken together with previously published data (15, 18), this suggests that the constrictor motor neurons release glutamate at both their excitatory neuromuscular junctions and their inhibitory intraganglionic junctions. The lucifer yellow photoinactivation technique (27) was used to study separately the neurotransmitters released by the electrically coupled PD and AB neurons. The AB-evoked IPSPs were blocked by picrotoxin but not by atropine. The PD-evoked IPSPs were blocked by atropine and other muscarinic antagonists but not by picrotoxin. Somata of PD neurons contained choline acetyltransferase (CAT) activity, but somata of AB neurons contained no detectable CAT activity. On the basis of the data in this paper and previously published data (17, 18), we conclude that the PD neurons release ACh at both their excitatory neuromuscular junctions and their inhibitory intraganglionic connections. Although the AB neuron is electrically coupled to the PD neurons, the AB neuron is not cholinergic. Glutamate is a likely transmitter candidate for the AB neuron. These data show that electrically coupled neurons can release different transmitters. Furthermore, these data show that an IPSP can be the result of the combined actions of two different neurotransmitters, each released from a different neuron. The functional consequences of these conclusions are explored in the following papers (9, 22).

Pharmacological dissection of pyloric network of the lobster stomatogastric ganglion using picrotoxin J

Article

Jan 1981

M Bidaut

1. Picrotoxin (PTX) (10(-7)-10(-6) M) completely blocked most inhibitory synapses in the pyloric pattern generator of the lobster (Panulirus interruptus) stomatogastric ganglion. The sensitivity of synapses from most classes of identified neurons was examined. Blockade was at least partly reversible with prolonged washing. 2. The synapses from pyloric dilator (PD) neurons were the only inhibitory synapses that picrotoxin failed to block completely. 3. A correlation is derived that brief, fast-rise inhibitory postsynaptic potentials (IPSPs) are picrotoxin sensitive, whereas a slow rounded component of IPSPs from PD neurons is not picrotoxin sensitive. 4. Picrotoxin caused specific changes in the pattern of the motor rhythm produced by the 16-cell pyloric network. This sheds some light on the functional role of particular synapses in the pyloric generator. 5. The endogenously bursting neurons (PD and anterior burster (AB)), which drive the pyloric rhythm, kept a similar burst rate. 6. Under picrotoxin, the pyloric "follower" neurons all moved to later phase relative to the "driver" group. Some normally antagonistic cells, related by reciprocal inhibitor connections, became in-phase. These and other pattern changes could be related to blockade of particular synapses. 7. The pyloric rhythm was still quite recognizable under picrotoxin despite the drastically altered circuitry of the synaptic network. This supports the idea that periodic inhibition from the PD driver neurons plays a primary role in creating the pyloric pattern.

Generation and coordination of heartbeat timing oscillation in the medicinal leech. I. Oscillation in isolated ganglia

Article

Apr 1983

E L Peterson

1. The interactions among the four pairs of interneurons (HN(1)-HN(4)) of the heartbeat timing oscillator are confined to the third and fourth ganglia (G3 and G4). In isolation, G3 and G4 each produces a rhythm essentially the same as that shown when the two ganglia are linked together. 2. The local circuits in both ganglia have the same general form. In both the oscillation centers on a bilateral pair of HN cells that are linked by reciprocal inhibition (the HN(3) pair in G3 and the HN(4) pair in G4). In addition, there is reciprocal inhibition between an HN(3) or HN(4) cell and the intersegmental processes of the ipsilateral HN(1) and HN(2) cells. 3. These connections account for the phase relationships in an isolated G3 or G4, since cells linked by reciprocal inhibition produce bursts in alternation. 4. In isolated ganglia, reciprocal inhibition not only coordinates the activity of the HN cells but also appears to help generate their bursts. 5. Yet reciprocal inhibition alone cannot account for the activity of the network. An endogenous property of the HN(3) and HN(4) cells appears to create the instability necessary for oscillation.

The dynamic clamp: artificial conductances in biological neurons

Article

Nov 1993
TRENDS NEUROSCI

The dynamic clamp is a novel method that uses computer simulation to introduce conductances into biological neurons. This method can be used to study the role of various conductances in shaping the activity of single neurons, or neurons within networks. The dynamic clamp can also be used to form circuits from previously unconnected neurons. This approach makes computer simulation an interactive experimental tool, and will be useful in many applications where the role of synaptic strengths and intrinsic properties in neuronal and network dynamics is of interest.

Injection of Digitally Synthesized Synaptic Conductance Transients to Measure the Integrative Properties of Neurons

Article

Oct 1993
J NEUROSCI METH

A novel technique was developed for injecting a time-varying conductance into a neuron, to allow quantitative measurement of the processing of synaptic inputs. In current-clamp recording mode, the membrane potential was sampled continuously and used to calculate and update the level of injected current within 60 microseconds, using a real-time computer, so as to mimic the electrical effect of a given conductance transient. Cellular responses to synthetic conductance transients modelled on the fast (non-N-methyl-D-aspartate) phase of the glutamatergic postsynaptic potential were measured in cultured rat hippocampal neurons.

Switching in the activity state of an interneuron that controls coordination of the hearts in the medicinal leech (Hirudo medicinalis)

Article

Feb 1994

The rhythmically active heart interneuron HN(5) in the medicinal leech exhibits two distinct activity states, which have been associated with different coordination states of the two hearts. During the active state, it discharges high-frequency bursts of action potentials interrupted by rhythmic inhibitory input from other interneurons. In the inactive state, the same cell receives rhythmic inhibition but the membrane potential remains subthreshold between these volleys, producing few or no action potentials. We investigated differences in the membrane properties of the cell during the active and inactive states. The membrane potential in the active state oscillates on average between about -56 +/- 6 mV (S.D.) and -45 +/- 7 mV; the mean oscillation amplitude is 11 +/- 4 mV. In the inactive state, the membrane potential oscillates on average between -58 +/- 6 mV and -55 +/- 6 mV with a mean amplitude of 3 +/- 1 mV. The overall conductance of an HN(5) interneuron during the active state is approximately 10 nS lower than that during the inactive state, indicating that an outward current is turned off during the active state or turned on during the inactive state. This outward current is not voltage-dependent in the range -80 mV to -10 mV, as shown in voltage-clamp experiments by a linear current-voltage relationship. The reversal potential of this current is approximately -60 mV, indicating that chloride or potassium ions underlie the current. Using dynamic-clamp, we show that by adding an artificial current with a linear voltage-dependence (leak conductance) to an HN(5) interneuron (conductance 15 nS, reversal potential -60 mV), the cell can be transferred from its active to its inactive state.

Amine modulation of electrical coupling in the pyloric network of the lobster stomatogastric ganglion

Article

Jun 1993

1. The neurons of the pyloric network of the lobster (Panulirus interruptus) stomatogastric ganglion organize their rhythmic motor output using both chemical and electrical synapses. The 6 electrical synapses within this network help set the firing phases of the pyloric neurons during each rhythmic cycle. We examined the modulatory effects of the amines dopamine (DA), serotonin (5HT) and octopamine (Oct) on coupling at all the electrical synapses of the pyloric network. 2. Electrical coupling within the pacemaker group [anterior burster (AB) to pyloric dilator (PD), and PD-PD] was non-rectifying, while coupling at the other electrical synapses [AB to ventral dilator (VD), PD-VD, lateral pyloric (LP) to pyloric (PY), and PY-PY] was rectifying. 3. Dopamine decreased or increased the coupling strength of all the pyloric electrical synapses: the sign of the effect depended upon which neuron was the target of current injection. For example, DA decreased AB-->PD coupling (i.e., when current was injected into the AB) but increased coupling in the other direction, PD-->AB. Dopamine decreased AB to VD coupling when current was injected into either neuron. Serotonin also had mixed effects; it enhanced PD-->AB coupling but decreased AB to VD and PD to VD coupling in both directions. Octopamine's only effect was to reduce PD-->VD coupling. 4. Dopamine increased the input resistance of the AB neuron but decreased the input resistance of the PD and VD neurons. Serotonin reduced the input resistance of the VD and PY neurons, while Oct did not significantly change the input resistance of any pyloric neuron. 5. The characteristic modulation of electrical coupling by each amine may contribute to the unique motor pattern that DA, 5HT and Oct each elicit from the pyloric motor network.

Cellular short-term memory from a slow potassium conductance

Article

Mar 1996

1. We use the dynamic clamp to add the slowly inactivating and slowly recovering K+ conductance Kv1.3 to cultured stomatogastric ganglion neurons. 2. Introduction of Kv1.3 produced long delays to firing during depolarization. Additionally, the slow recovery from inactivation produced an increase in neuronal excitability after a depolarizing input that outlasted the input by many seconds. Finally, when introduced into bursting neurons, Kv1.3 produced a long-lasting depolarization-induced switch between tonic and burst firing. 3. These data demonstrate that the slow kinetics of a K+ conductance can produce a form of cellular short-term memory that is independent of any changes in synaptic efficacy.

Principles of rhythmic motor pattern generation

Article

Aug 1996

Rhythmic movements are produced by central pattern-generating networks whose output is shaped by sensory and neuromodulatory inputs to allow the animal to adapt its movements to changing needs. This review discusses cellular, circuit, and computational analyses of the mechanisms underlying the generation of rhythmic movements in both invertebrate and vertebrate nervous systems. Attention is paid to exploring the mechanisms by which synaptic and cellular processes interact to play specific roles in shaping motor patterns and, consequently, movement.

Mechanisms of oscillation in dynamic clamp constructed two-cell half- center circuits

Article

Sep 1996

1. The dynamic clamp was used to create reciprocally inhibitory two-cell circuits from pairs of pharmacologically isolated gastric mill neurons of the stomatogastric ganglion of the crab, Cancer borealis. 2. We used this system to study how systematic alterations in intrinsic and synaptic parameters affected the network behavior. This has previously only been possible in purely computational systems. 3. In the absence of additional hyperpolarization-activated inward current (IH), stable half-center oscillatory behavior was not observed. In the presence of additional IH, a variety of circuit dynamics, including stable half-center oscillatory activity, was produced. 4. Stable half-center behavior requires that the synaptic threshold lie within the voltage envelope of the slow wave oscillation. 5. Changes in the synaptic threshold produce dramatic changes in half-center period. As predicted by previous theoretical work, when the synaptic threshold is depolarized, the period first increases and then decreases in a characteristic inverted U-shaped relationship. Analysis of the currents responsible for the transition between the active and inhibited neurons shows that the mechanism of oscillation changes as the synaptic threshold is varied. 6. Increasing the time constant and the conductance of the inhibitory synaptic current increased the period of the half-center oscillator. 7. Increasing the conductance of IH or changing the voltage dependence of IH can either increase or decrease network period, depending on the initial mode of network oscillation. A depolarization of the activation curve causes the network to respond in a similar fashion as increasing the conductance of IH. 8. Many neuromodulatory substances are known to alter synaptic strength and the conductance and voltage dependence of IH, parameters we studied with the dynamic clamp. To understand the response of the network to modulation of a single parameter, it is necessary to understand the nature of the altered conductance and how it interacts with the other conductances in the system.

-Aminobutyric acid type B receptor-dependent burst-firing in thalamic neurons: A dynamic clamp study

Article

Nov 1996

Synchronized network responses in thalamus depend on phasic inhibition originating in the thalamic reticular nucleus (nRt) and are mediated by the neurotransmitter gamma-aminobutyric acid (GABA). A suggested role for intra-nRt connectivity in inhibitory phasing remains controversial. Recently, functional GABA type B (GABAB) receptors were demonstrated on nRt cells, and the slow time course of the GABAB synaptic response seems ideally suited to deinactivate low-threshold calcium channels. This promotes burst firing, a characteristic feature of synchronized responses. Here we investigate GABAB-mediated rebound burst firing in thalamic cells. Whole-cell current-clamp recordings were obtained from nRt cells and somatosensory thalamocortical relay cells in rat brain slices. Synthetic GABAB inhibitory postsynaptic potentials, generated by a hybrid computerneuron synapse (dynamic clamp), triggered rebound low-threshold calcium spikes in both cell types when peak inhibitory postsynaptic potential hyperpolarization was greater than -92 mV. The threshold inhibitory postsynaptic potential conductance for rebound burst generation was comparable in nRt (7 nS) and thalamocortical (5 nS) cells. However, burst onset in nRt (1 s) was considerably delayed compared with thalamocortical (0.6 s) cells. Thus, GABAB inhibitory postsynaptic potentials can elicit low-threshold calcium spikes in both relay and nRt neurons, but the resultant oscillation frequency would be faster for thalamocortical-nRt networks (3 Hz) than for nRt-nRt networks (1-2 Hz). We conclude, therefore, that fast (> 2 Hz) GABAB-dependent thalamic oscillations are maintained primarily by reciprocal connections between excitatory and inhibitory cells. These findings further indicate that when oscillatory neural networks contain both recurrent and reciprocal inhibition, then distinct population frequencies may result when one or the other type of inhibition is favored.

Model clamp and its application to synchronization of rabbit sinoatrial node cells

Article

Dec 1996
Am J Physiol

A method for coupling an isolated cardiac cell to a simulated cardiac cell, i.e., the real-time solution of a mathematical model of such cell, has been developed. With this "model clamp" technique, the real cell and the model cell are coupled by any desired value of intercellular coupling conductance, producing the effect of mutual interaction by electrical coupling through gap junctional channels. We implemented the model clamp technique with our previously published model of an isolated rabbit sinoatrial node cell. We used this model clamp system to study synchronization of sinoatrial node cells with regard to the critical value of intercellular coupling conductance required for frequency entrainment and the common interbeat interval during frequency entrainment. This common interbeat interval lay between the intrinsic intervals of the real cell and the model cell, but was closer to that of the intrinsically faster beating cell. Critical coupling conductance increased with increasing difference in intrinsic interbeat interval of the real cell and the model cell and ranged between 50 and 300 pS in 11 hybrid cell pairs.

From conductances to neural network properties: Analysis of simple circuits using the hybrid network method

Article

Feb 1995
PROG BIOPHYS MOL BIO

this article, we used a synaptic conductance controlledby a gating variable described by an equation similar to (3) above, a procedure which impartsseveral realistic properties to hybrid connections. First, because we are computing a drivingforce that depends on the postsynaptic neuron and a user-specified reversal potential,changing the postsynaptic membrane potential affects the intensity and sign of the artificialsynaptic current (shown in Fig. 3A, B). Second, the artificial current...

GABA A -Receptor-Mediated Rebound Burst Firing and Burst Shunting in Thalamus

Article

Sep 1997

The role of gamma-aminobutyric acid-A (GABA(A))-receptor-mediated inhibitory postsynaptic potentials (IPSPs) in 1) generating rebound burst firing and 2) burst inhibition in thalamocortical (TC) relay cells and inhibitory neurons of nucleus reticularis thalami (nRt) was investigated. Experimental data from previous studies were used to generate artificial synaptic responses in neurons via a computer-driven dynamic clamp. On average, in nRt neurons trains of six or more 10-nS GABA(A) IPSPs generated rebound bursts of action potentials with a mean delay of 605 +/- 32 (SE) ms. In contrast, 10 IPSPs were required for rebound bursts in relay cells, and these occurred with a significantly shorter delay of 327 +/- 35 ms. Ca2+-dependent burst responses could be shunted by single IPSPs. Half-maximal burst inhibition was obtained in nRt cells when IPSP conductance was 1.5 times the whole cell input conductance. Burst shunting in TC cells was less effective and required a synaptic- to input-conductance ratio of 3. The relative time window of IPSP burst shunting was broader in nRt (approximately 20 ms) than TC cells (approximately 10 ms). We conclude that in nRt cells GABA(A)-dependent rebound burst responses would occur with a latency that is incompatible with pacemaking of fast (>3-Hz) thalamic rhythm generation such as spindles, yet burst inhibition is powerful. Therefore a likely role for reciprocal intra-nRt connectivity is to mediate lateral inhibition between nRt cells.

Phase response characteristics of model neurons determine which patterns are expressed in a ring circuit model of gait generation

Article

Jan 1998

In order to assess the relative contributions to pattern-generation of the intrinsic properties of individual neurons and of their connectivity, we examined a ring circuit composed of four complex physiologically based oscillators. This circuit produced patterns that correspond to several quadrupedal gaits, including the walk, the bound, and the gallop. An analysis using the phase response curve (PRC) of an uncoupled oscillator accurately predicted all modes exhibited by this circuit and their phasic relationships--with the caveat that in certain parameter ranges, bistability in the individual oscillators added nongait patterns that were not amenable to PRC analysis, but further enriched the pattern-generating repertoire of the circuit. The key insights in the PRC analysis were that in a gait pattern, since all oscillators are entrained at the same frequency, the phase advance or delay caused by the action of each oscillator on its postsynaptic oscillator must be the same, and the sum of the normalized phase differences around the ring must equal to an integer. As suggested by several previous studies, our analysis showed that the capacity to exhibit a large number of patterns is inherent in the ring circuit configuration. In addition, our analysis revealed that the shape of the PRC for the individual oscillators determines which of the theoretically possible modes can be generated using these oscillators as circuit elements. PRCs that have a complex shape enable a circuit to produce a wider variety of patterns, and since complex neurons tend to have complex PRCs, enriching the repertoire of patterns exhibited by a circuit may be the function of some intrinsic neuronal complexity. Our analysis showed that gait transitions, or more generally, pattern transitions, in a ring circuit do not require rewiring the circuit or any changes in the strength of the connections. Instead, transitions can be achieved by using a control parameter, such as stimulus intensity, to sculpt the PRC so that it has the appropriate shape for the desired pattern(s). A transition can then be achieved simply by changing the value of the control parameter so that the first pattern either ceases to exist or loses stability, while a second pattern either comes into existence or gains stability. Our analysis illustrates the predictive value of PRCs in circuit analysis and can be extended to provide a design method for pattern-generating circuits.

Dynamic clamp study of I(h) modulation of burst firing and δ oscillations in thalamocortical neurons in vitro

Article

Jan 1999
NEUROSCIENCE

The dynamic clamp technique was used in thalamocortical neurons of the rat and cat dorsal lateral geniculate nucleus in vitro to investigate the effects of the hyperpolarization-activated cation current, Ih, and of its neuromodulation on burst firing and δ oscillations. Specific block of endogenous Ih using 4-(N-ethyl-N-phenylamino)-1,2-dimethyl-6-(methylamino)pyridinium chloride (ZD7288) (300 μM) abolished the depolarizing “sag” response to negative current steps, markedly increased the latency and shortened the duration of the low-threshold Ca²⁺ potentials, and decreased the number of action potentials in the burst evoked by the low-threshold Ca²⁺ potential. Subsequent introduction of artificial Ih using the dynamic clamp re-instated the “sag” and all the original properties of the low-threshold Ca²⁺ potential. In the absence of ZD7288, introduction of artificial outward Ih with the intention of abolishing endogenous Ih removed the depolarizing “sag” and produced similar effects on the low-threshold Ca²⁺ potentials as those observed during the pharmacological block of Ih. Application of ZD7288 to thalamocortical neurons displaying δ oscillations led to a reduction in the voltage range of their existence or to a complete cessation of this behaviour. A subsequent introduction of artificial Ih re-enabled the generation of δ oscillations. In the presence of ZD7288, physiologically relevant positive shifts in the voltage-dependence of artificial Ih increased the amplitude and duration of the low-threshold Ca²⁺ potential and increased the likelihood of δ oscillations while negative shifts had opposite effects.

Modulation of the Bursting Properties of Single Mouse Pancreatic ??-Cells by Artificial Conductances

Article

Mar 1999

Glucose triggers bursting activity in pancreatic islets, which mediates the Ca2+ uptake that triggers insulin secretion. Aside from the channel mechanism responsible for bursting, which remains unsettled, it is not clear whether bursting is an endogenous property of individual beta-cells or requires an electrically coupled islet. While many workers report stochastic firing or quasibursting in single cells, a few reports describe single-cell bursts much longer (minutes) than those of islets (15-60 s). We studied the behavior of single cells systematically to help resolve this issue. Perforated patch recordings were made from single mouse beta-cells or hamster insulinoma tumor cells in current clamp at 30-35 degrees C, using standard K+-rich pipette solution and external solutions containing 11.1 mM glucose. Dynamic clamp was used to apply artificial KATP and Ca2+ channel conductances to cells in current clamp to assess the role of Ca2+ and KATP channels in single cell firing. The electrical activity we observed in mouse beta-cells was heterogeneous, with three basic patterns encountered: 1) repetitive fast spiking; 2) fast spikes superimposed on brief (<5 s) plateaus; or 3) periodic plateaus of longer duration (10-20 s) with small spikes. Pattern 2 was most similar to islet bursting but was significantly faster. Burst plateaus lasting on the order of minutes were only observed when recordings were made from cell clusters. Adding gCa to cells increased the depolarizing drive of bursting and lengthened the plateaus, whereas adding gKATP hyperpolarized the cells and lengthened the silent phases. Adding gCa and gKATP together did not cancel out their individual effects but could induce robust bursts that resembled those of islets, and with increased period. These added currents had no slow components, indicating that the mechanisms of physiological bursting are likely to be endogenous to single beta-cells. It is unlikely that the fast bursting (class 2) was due to oscillations in gKATP because it persisted in 100 microM tolbutamide. The ability of small exogenous currents to modify beta-cell firing patterns supports the hypothesis that single cells contain the necessary mechanisms for bursting but often fail to exhibit this behavior because of heterogeneity of cell parameters.

Evolution and Analysis of Model CPGs for Walking: I. Dynamical Modules

Article

Apr 2000

Can one develop an abstract description of the dynamics of pattern generators that provides quantitative insight into their operation? We explored this question by examining the dynamics of a model central pattern generator that was created using an evolutionary algorithm. We propose an abstract description based on the concept of a dynamical module, a set of neurons that simultaneously make their transitions from one quasistable state to another while the synaptic inputs that they receive from other neurons remain essentially constant, thus temporarily reducing the dimensionality of the circuit dynamics. Using the mathematical tools of dynamical systems theory, we describe a method for identifying dynamical modules and demonstrate that this concept can be used to quantitatively characterize constraints on neural architecture, account for phase durations, and predict the effects of parameter changes. Moreover, this abstract description reveals coordinated parameter changes that leave the overall circuit dynamics essentially unchanged. In a companion article we employ this abstract description to examine the relationship between general principles and individual variability in large populations of evolved model pattern generators.

Interacting Biological and Electronic Neurons Generate Realistic Oscillatory Rhythms

Article

Mar 2000
NEUROREPORT

Small assemblies of neurons such as central pattern generators (CPG) are known to express regular oscillatory firing patterns comprising bursts of action potentials. In contrast, individual CPG neurons isolated from the remainder of the network can generate irregular firing patterns. In our study of cooperative behavior in CPGs we developed an analog electronic neuron (EN) that reproduces firing patterns observed in lobster pyloric CPG neurons. Using a tuneable artificial synapse we connected the EN bidirectionally to neurons of this CPG. We found that the periodic bursting oscillation of this mixed assembly depends on the strength and sign of the electrical coupling. Working with identified, isolated pyloric CPG neurons whose network rhythms were impaired, the EN/biological network restored the characteristic CPG rhythm both when the EN oscillations are regular and when they are irregular.

Synchronous Behavior of Two Coupled Electronic Neurons

Article

Sep 2000

We report on experimental studies of synchronization phenomena in a pair of analog electronic neurons (ENs). The ENs were designed to reproduce the observed membrane voltage oscillations of isolated biological neurons from the stomatogastric ganglion of the California spiny lobster Panulirus interruptus. The ENs are simple analog circuits which integrate four-dimensional differential equations representing fast and slow subcellular mechanisms that produce the characteristic regular/chaotic spiking-bursting behavior of these cells. In this paper we study their dynamical behavior as we couple them in the same configurations as we have done for their counterpart biological neurons. The interconnections we use for these neural oscillators are both direct electrical connections and excitatory and inhibitory chemical connections: each realized by analog circuitry and suggested by biological examples. We provide here quantitative evidence that the ENs and the biological neurons behave similarly when coupled in the same manner. They each display well defined bifurcations in their mutual synchronization and regularization. We report briefly on an experiment on coupled biological neurons and four-dimensional ENs, which provides further ground for testing the validity of our numerical and electronic models of individual neural behavior. Our experiments as a whole present interesting new examples of regularization and synchronization in coupled nonlinear oscillators.

A Quantitative Description Of Membrane Current And Its Application To Conduction And Excitation In Nerve

Article

Sep 1952

This article concludes a series of papers concerned with the flow of electric current through the surface membrane of a giant nerve fibre (Hodgkinet al., 1952,J. Physiol.116, 424–448; Hodgkin and Huxley, 1952,J. Physiol.116, 449–566). Its general object is to discuss the results of the preceding papers (Section 1), to put them into mathematical form (Section 2) and to whow that they will account for conduction and excitation in quantitative terms (Sections 3–6).

Amine modulation of electrical coupling in the pyloric network of the lobster stomato-gastric ganglion Dynamic neuromodulation of synaptic strength intrinsic to a central pattern generator circuit

715-32

Rr Johnson
Jh Peck
Harris
Warrick

Johnson RR, Peck JH, Harris-Warrick RM. Amine modulation of electrical coupling in the pyloric network of the lobster stomato-gastric ganglion. J Comp Physiol 1993;172:715–32. rR.D. Pinto et al. / Journal of Neuroscience Methods 108 (2001) 39–4848 Katz PS, Getting PA, Frost WN. Dynamic neuromodulation of synaptic strength intrinsic to a central pattern generator circuit. Nature 1994;367:729–31

Modulation of stom-atogastric networks by identified neurons and transmitters Dynamic Biological Net-works: The Stomatogastric Nervous System The Stomatogastric Nervous Sys-tem Dopamine modulation of two subthreshold currents produces phase shifts in activity of an identified motoneuron

Jan 1992
1404-20

Harris-Warrick Rm F Nagy
Nusbaum Mp Harris-Warrick Rm

Harris-Warrick RM, Nagy F, Nusbaum MP. Modulation of stom-atogastric networks by identified neurons and transmitters. In: Harris-Warrick RM, et al., editors. Dynamic Biological Net-works: The Stomatogastric Nervous System. Cambridge, MA: MIT Press, 1992a. Harris-Warrick RM, Marder E, Selverston AI, Moulins M, editors. Dynamic Biological Networks. The Stomatogastric Nervous Sys-tem. Cambridge, MA: MIT Press, 1992b. Harris-Warrick RM, Coniglio LM, Levini RM, Gueron S, Gucken-heimer J. Dopamine modulation of two subthreshold currents produces phase shifts in activity of an identified motoneuron. J Neurophysiol 1995;74:1404 – 20.

Hard-wired central pattern generators for quadripedal locomotion

Jan 1994
371-85

Richmond Sa

Collins JJ, Richmond SA. Hard-wired central pattern generators for quadripedal locomotion. Biol Cybern 1994;71:371 – 85.

Component for direct access to IO ports on Windows 95, 98 and Windows NT Selverston AI, Miller JP. Mechanisms underlying pattern generation in lobster stomatogastric ganglion as determined by selective inactivation of identified neurons. I. Pyloric system

Jan 1980
1102-21

E Salaj
Ioport

Salaj E. IOPort: Component for direct access to IO ports on Windows 95, 98 and Windows NT/2000. Winsoft Ltd. 2000; http:// www.cybermagic.co.nz/winsoft/ioport.htm. Selverston AI, Miller JP. Mechanisms underlying pattern generation in lobster stomatogastric ganglion as determined by selective inactivation of identified neurons. I. Pyloric system. J Neurophysiol 1980;44:1102 – 21.

Extended dynamic clamp: controlling up to four neurons using a single desktop computer and interface

Abstract

No full-text available

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