Biomedical subjects

John Rinzel

Publications and source records attributed to John Rinzel.

At least 19 recordsLinked to original sources

PubMed2006

Estimation of synaptic conductances.

In order to identify and understand mechanistically the cortical circuitry of sensory information processing estimates are needed of synaptic input fields that drive neurons. From intracellular in vivo recordings one would like to estimate net synaptic conductance time courses for excitation and inhibition, g(E)(t) and g(I)(t), during time-varying stimulus presentations. However, the intrinsic conductance transients associated with neuronal spiking can confound such estimates, and thereby jeopardize functional interpretations. Here, using a conductance-based pyramidal neuron model we illustrate errors in estimates when the influence of spike-generating conductances are not reduced or avoided. A typical estimation procedure involves approximating the current-voltage relation at each time point during repeated stimuli. The repeated presentations are done in a few sets, each with a different steady bias current. From the trial-averaged smoothed membrane potential one estimates total membrane conductance and then dissects out estimates for g(E)(t) and g(I)(t). Simulations show that estimates obtained during phases without spikes are good but those obtained from phases with spiking should be viewed with skeptism. For the simulations, we consider two different synaptic input scenarios, each corresponding to computational network models of orientation tuning in visual cortex. One input scenario mimics a push-pull arrangement for g(E)(t) and g(I)(t) and idealized as specified smooth time courses. The other is taken directly from a large-scale network simulation of stochastically spiking neurons in a slab of cortex with recurrent excitation and inhibition. For both, we show that spike-generating conductances cause serious errors in the estimates of g(E) and g(I). In some phases for the push-pull examples even the polarity of g(I) is mis-estimated, indicating significant increase when g(I) is actually decreased. Our primary message is to be cautious about forming interpretations based on estimates developed during spiking phases.

Adaptation, Physiological↗

PubMed2006

Dynamical characteristics common to neuronal competition models.

Models implementing neuronal competition by reciprocally inhibitory populations are widely used to characterize bistable phenomena such as binocular rivalry. We find common dynamical behavior in several models of this general type, which differ in their architecture in the form of their gain functions, and in how they implement the slow process that underlies alternating dominance. We focus on examining the effect of the input strength on the rate (and existence) of oscillations. In spite of their differences, all considered models possess similar qualitative features, some of which we report here for the first time. Experimentally, dominance durations have been reported to decrease monotonically with increasing stimulus strength (such as Levelt's "Proposition IV"). The models predict this behavior; however, they also predict that at a lower range of input strength dominance durations increase with increasing stimulus strength. The nonmonotonic dependency of duration on stimulus strength is common to both deterministic and stochastic models. We conclude that additional experimental tests of Levelt's Proposition IV are needed to reconcile models and perception.

Action Potentials↗

PubMed2006

Stochastic synchronization in finite size spiking networks.

We study a stochastic synchronization of spiking activity in feedforward networks of integrate-and-fire model neurons. A stochastic mean field analysis shows that synchronization occurs only when the network size is sufficiently small. This gives evidence that the dynamics, and hence processing, of finite size populations can be drastically different from that observed in the infinite size limit. Our results agree with experimentally observed synchrony in cortical networks, and further strengthen the link between synchrony and propagation in cortical systems.

Action Potentials↗

PubMed2006

Differential control of active and silent phases in relaxation models of neuronal rhythms.

Rhythmic bursting activity, found in many biological systems, serves a variety of important functions. Such activity is composed of episodes, or bursts (the active phase, AP) that are separated by quiescent periods (the silent phase, SP). Here, we use mean field, firing rate models of excitatory neural network activity to study how AP and SP durations depend on two critical network parameters that control network connectivity and cellular excitability. In these models, the AP and SP correspond to the network's underlying bistability on a fast time scale due to rapid recurrent excitatory connectivity. Activity switches between the AP and SP because of two types of slow negative feedback: synaptic depression-which has a divisive effect on the network input/output function, or cellular adaptation-a subtractive effect on the input/output function. We show that if a model incorporates the divisive process (regardless of the presence of the subtractive process), then increasing cellular excitability will speed up the activity, mostly by decreasing the silent phase. Reciprocally, if the subtractive process is present, increasing the excitatory connectivity will slow down the activity, mostly by lengthening the active phase. We also show that the model incorporating both slow processes is less sensitive to parameter variations than the models with only one process. Finally, we note that these network models are formally analogous to a type of cellular pacemaker and thus similar results apply to these cellular pacemakers.

Action Potentials↗

PubMed2006

An intracellular Ca2+ subsystem as a biologically plausible source of intrinsic conditional bistability in a network model of working memory.

We have developed a firing rate network model for working memory that combines Mexican-hat-like synaptic coupling with intrinsic or cellular dynamics that are conditionally bistable. While our approach is in the spirit of Camperi and Wang (1998) we include a specific and plausible mechanism for the cellular bistability. Modulatory neurotransmitters are known to activate second messenger signaling systems, and our model includes an intracellular Ca(2+) handling subsystem whose dynamics depend upon the level of the second messenger inositol 1,4,5 trisphosphate (IP3). This Ca(2+) subsystem endows individual units with conditional intrinsic bistability for a range of IP3. The full "hybrid" network sustains IP3-dependent persistent ("bump") activity in response to a brief transient stimulus. The bump response in our hybrid model, like that of Camperi-Wang, is resistant to noise-- its position does not drift with time.

Animals↗

PubMed2006

Enhanced neuronal response induced by fast inhibition.

We report a facilitatory role of inhibitory synaptic input that can enhance a neuron's firing rate, in contrast to the conventional belief that inhibition suppresses firing. We study this phenomenon using the Hodgkin-Huxley model of spike generation with random Poisson trains of subthreshold excitatory and inhibitory inputs. Enhancement occurs when, by chance, brief inhibition leads excitation with a favorable timing and counterintuitively induces a reduction of the spike threshold. The basic mechanism is also illustrated with the phase-plane analysis of a two variable model.

Animals↗

PubMed2006

A firing rate model of Parkinsonian deficits in interval timing.

To account for deficits in interval timing observed in Parkinson's Disease (PD) patients, we develop a model based on the accumulating firing rate of a neural population with recurrent excitation. This model naturally produces the curvilinear accumulation of neural activity introduced to timing psychophysics by Miall (Models of Neural Timing, Elsevier Science, 1996), and implicated in Parkinsonian timing by Malapani and Rakitin (Functional and Neural Mechanisms of Interval Timing, CRC Press, 2003). The parameters essential for our model are the strength of the net neural feedback and the mean rate of inputs to the population from external brain areas. Systematic variations in these parameters reproduce the PD migration effect, in which estimates of long and short intervals drift towards each other, as well as uniform slowing of time estimates observed under other experimental conditions. For example, our model suggests that dopamine depletion in PD patients increases the neural feedback parameter and decreases the effective input parameter for populations involved in the production of time estimates. The model also explains why the migration effect will be associated with a violation of the scalar property, the linear increase in the standard deviation of time estimates with the duration of the target interval that is ubiquitous in healthy participants. We also show that the effect of systematically decreasing the input rate parameter in our model is equivalent to increasing thresholds, so that either of these changes may be associated with the Parkinsonian state.

Humans↗

PubMed2006

Well-timed, brief inhibition can promote spiking: postinhibitory facilitation.

Brief synaptic inhibition can overwhelm a nearly coincident suprathreshold excitatory input to preclude spike generation. Surprisingly, a brief inhibitory event that occurs in a favorable time window preceding an otherwise subthreshold excitation can facilitate spiking. Such postinhibitory facilitation (PIF) requires that the inhibition has a short (decay) time constant tauinh. The timescale ranges of tauinh and of the window (width and timing) for PIF depend on the rates of neuronal subthreshold dynamics. The mechanism for PIF is general, involving reduction by hyperpolarization of some excitability-suppressing factor that is partially recruited at rest. Here we illustrate and analyze PIF, experimentally and theoretically, using brain stem auditory neurons and a conductance-based five-variable model. In this auditory case, PIF timescales are in the sub- to few millisecond range and the primary mechanistic factor is a low-threshold potassium conductance gKLT. Competing dynamic influences create the favorable time window: hyperpolarization that moves V away from threshold and hyperexcitability resulting from reduced gKLT. A two-variable reduced model that retains the dynamics only of V and gKLT displays a similar time window. We analyze this model in the phase plane; its geometry has generic features. Further generalizing, we show that PIF behavior may occur even in a very reduced model with linear subthreshold dynamics, by using an integrate-and-fire model with an accommodating voltage-dependent threshold. Our analyses of PIF provide insights for fast inhibition's facilitatory effects in longer trains. Periodic subthreshold excitatory inputs can lead to firing, even one for one, if brief inhibitory inputs are interleaved within a range of favorable phase lags. The temporal specificity of inhibition's facilitating effect could play a role in temporal processing, in sensitivity to inhibitory and excitatory temporal patterning, in the auditory and other neural systems.

Action Potentials↗

PubMed2005

Modeling spontaneous activity in the developing spinal cord using activity-dependent variations of intracellular chloride.

We investigated how spontaneous activity is generated in developing, hyperexcitable networks. We focused our study on the embryonic chick spinal cord, a preparation that exhibits rhythmic discharge on multiple timescales: slow episodes (lasting minutes) and faster intraepisode cycling (approximately 1 Hz frequency). For this purpose, we developed a mean field model of a recurrent network with slow chloride dynamics and a fast depression variable. We showed that the model, in addition to providing a biophysical mechanism for the slow dynamics, was able to account for the experimentally observed activity. The model made predictions on how interval and duration of episodes are affected when changing chloride-mediated synaptic transmission or chloride flux across cell membrane. These predictions guided experiments, and the model results were compared with experimental data obtained with electrophysiological recordings. We found agreement when transmission was affected through changes in synaptic conductance and good qualitative agreement when chloride flux was varied through changes in external chloride concentration or in the rate of the Na+-K+-2Cl- cotransporter. Furthermore, the model made predictions about the time course of intracellular chloride concentration and chloride reversal potential and how these are affected by changes in synaptic conductance. Based on the comparison between modeling and experimental results, we propose that chloride dynamics could be an important mechanism in rhythm generation in the developing chick spinal cord.

2-Amino-5-phosphonovalerate↗

PubMed2005

Background-activity-dependent properties of a network model for working memory that incorporates cellular bistability.

In models of working memory, transient stimuli are encoded by feature-selective persistent neural activity. Network models of working memory are also implicitly bistable. In the absence of a brief stimulus, only spontaneous, low-level, and presumably nonpatterned neural activity is seen. In many working-memory models, local recurrent excitation combined with long-range inhibition (Mexican hat coupling) can result in a network-induced, spatially localized persistent activity or "bump state" that coexists with a stable uniform state. There is now renewed interest in the concept that individual neurons might have some intrinsic ability to sustain persistent activity without recurrent network interactions. A recent visuospatial working-memory model (Camperi and Wang 1998) incorporates both intrinsic bistability of individual neurons within a firing rate network model and a single population of neurons on a ring with lateral inhibitory coupling. We have explored this model in more detail and have characterized the response properties with changes in background synaptic input I(o) and stimulus width. We find that only a small range of I(o) yields a working-memory-like coexistence of bump and uniform solutions that are both stable. There is a rather larger range where only the bump solution is stable that might correspond instead to a feature-selective long-term memory. Such a network therefore requires careful tuning to exhibit working-memory-like function. Interestingly, where bumps and uniform stable states coexist, we find a continuous family of stable bumps representing stimulus width. Thus, in the range of parameters corresponding to working memory, the model is capable of capturing a two-parameter family of stimulus features including both orientation and width.

Action Potentials↗

PubMed2005

Electrical coupling induces bistability of rhythms in networks of inhibitory spiking neurons.

Information processing in higher brain structures is thought to rely on the synchronization of spiking neurons. Increasing evidence indicates that, within these structures, inhibitory neurons are linked by both chemical and electrical synapses. However, how synchronized states may emerge from such circuits is not fully understood. Using snail neurons interconnected through a dynamic-clamp system, we show that networks of spiking neurons linked by both reciprocal inhibition and electrical coupling can express two coexisting coordination patterns of different rhythms. One of these patterns consists of antiphase firing of the network partners whereas, in the other, neurons fire synchronously. Switching between patterns may be evoked immediately by transient stimuli, demonstrating bistability of the network. Thus electrical coupling can provide a potent way for instantaneous reconfiguration of activity patterns in inhibitory spiking networks without alteration of intrinsic network properties by modulatory processes.

Algorithms↗

PubMed2004

Sodium along with low-threshold potassium currents enhance coincidence detection of subthreshold noisy signals in MSO neurons.

Voltage-dependent membrane conductances support specific neurophysiological properties. To investigate the mechanisms of coincidence detection, we activated gerbil medial superior olivary (MSO) neurons with dynamic current-clamp stimuli in vitro. Spike-triggered reverse-correlation analysis for injected current was used to evaluate the integration of subthreshold noisy signals. Consistent with previous reports, the partial blockade of low-threshold potassium channels (I(KLT)) reduced coincidence detection by slowing the rise of current needed on average to evoke a spike. However, two factors point toward the involvement of a second mechanism. First, the reverse correlation currents revealed that spike generation was associated with a preceding hyperpolarization. Second, rebound action potentials are 45% larger compared to depolarization-evoked spikes in the presence of an I(KLT) antagonist. These observations suggest that the sodium current (I(Na)) was substantially inactivated at rest. To test this idea, I(Na) was enhanced by increasing extracellular sodium concentration. This manipulation reduced coincidence detection, as reflected by slower spike-triggering current, and diminished the hyperpolarization phase in the reverse-correlation currents. As expected, a small outward bias current decreased the pre-spike hyperpolarization phase, and TTX blockade of I(Na) nearly eliminated the hyperpolarization phase in the reverse correlation current. A computer model including Hodgkin-Huxley type conductances for spike generation and for I(KLT) showed reduction in coincidence detection when I(KLT) was reduced or when I(Na) was increased. We hypothesize that desirable synaptic signals first remove some inactivation of I(Na) and reduce activation of I(KLT) to create a brief temporal window for coincidence detection of subthreshold noisy signals.

Action Potentials↗

PubMed2003

Subthreshold outward currents enhance temporal integration in auditory neurons.

Many auditory neurons possess low-threshold potassium currents ( I(KLT)) that enhance their responsiveness to rapid and coincident inputs. We present recordings from gerbil medial superior olivary (MSO) neurons in vitro and modeling results that illustrate how I(KLT) improves the detection of brief signals, of weak signals in noise, and of the coincidence of signals (as needed for sound localization). We quantify the enhancing effect of I(KLT) on temporal processing with several measures: signal-to-noise ratio (SNR), reverse correlation or spike-triggered averaging of input currents, and interaural time difference (ITD) tuning curves. To characterize how I(KLT), which activates below spike threshold, influences a neuron's voltage rise toward threshold, i.e., how it filters the inputs, we focus first on the response to weak and noisy signals. Cells and models were stimulated with a computer-generated steady barrage of random inputs, mimicking weak synaptic conductance transients (the "noise"), together with a larger but still subthreshold postsynaptic conductance, EPSG (the "signal"). Reduction of I(KLT) decreased the SNR, mainly due to an increase in spontaneous firing (more "false positive"). The spike-triggered reverse correlation indicated that I(KLT) shortened the integration time for spike generation. I(KLT) also heightened the model's timing selectivity for coincidence detection of simulated binaural inputs. Further, ITD tuning is shifted in favor of a slope code rather than a place code by precise and rapid inhibition onto MSO cells (Brand et al. 2002). In several ways, low-threshold outward currents are seen to shape integration of weak and strong signals in auditory neurons.

Animals↗

PubMed2003

Auditory system.

Explore the source record for details and available documents.

Animals↗

PubMed2003

Short duty cycle destabilizes a half-center oscillator, but gap junctions can restabilize the anti-phase pattern.

Mutually inhibitory pacemaker neurons with duty cycle close to 50% operate as a half-center oscillator (anti-phase coordination, i.e., 180 degrees out of phase), even in the presence of weak to modest gap junctional coupling. For electrical coupling strength above a critical value synchronization occurs. But, as shown here with modeling studies, the effects of electrical coupling depend critically on a cell's duty cycle. Instead of oscillating either in-phase or anti-phase, model cells with short duty cycle express additional rhythmic patterns, and different transitions between them, depending on electrical coupling strength. For weak or no electrical coupling, cells do not oscillate in anti-phase but instead exhibit almost in-phase activity. Strengthening this weak coupling leads to stable anti-phase activity. With yet stronger electrical coupling stable inphase (synchrony) emerges but it coexists with the anti-phase pattern. Thus the network shows bistability for an intermediate range of coupling strength. For sufficiently strong electrical coupling synchrony is the network's only attracting rhythmic state. Our results, numerical and analytical (phase plane analysis), are based on a minimal but biophysically motivated pacemaker model for the slowly oscillating envelope of bursting neurons. However, illustrations for an Hodgkin-Huxley model suggest that some of our results for short duty cycle may extend to patterning of repetitive spikes. In particular, electrical coupling of intermediate strength may promote anti-phase activity and provide bistability of anti-phase and in-phase spiking.

Biological Clocks↗

PubMed2003

Influence of subthreshold nonlinearities on signal-to-noise ratio and timing precision for small signals in neurons: minimal model analysis.

Subthreshold voltage- and time-dependent conductances can subserve different roles in signal integration and action potential generation. Here, we use minimal models to demonstrate how a non-inactivating low-threshold outward current (I(KLT)) can enhance the precision of small-signal integration. Our integrate-and-fire models have only a few biophysical parameters, enabling a parametric study of I(KLT) effects. I(KLT) increases the signal-to-noise ratio (SNR) for firing when a subthreshold 'signal' EPSP is delivered in the presence of weak random input. The increased SNR is due to the suppression of spontaneous firings to random input. In accordance, SNR grows as the EPSP amplitude increases. SNR also grows as the unitary synaptic current's time constant increases, leading to more effective suppression of spontaneous activity. Spike-triggered reverse correlation of the injected current indicates that, to reach spike threshold, a cell with I(KLT) requires a briefer time course of injected current. Consistent with this narrowed integration time window, I(KI.T) enhances phase-locking. measured as vector strength, to a weak noisy and periodically modulated stimulus. Thus subthreshold negative feedback mediated by I(KLT) enhances temporal processing. An alternative suppression mechanism is voltage- and time-dependent inactivation of a low-threshold inward current. This feature in an integrate-and-fire model also shows SNR enhancement, in comparison with a case when the inward current is non-inactivating. Small-signal detection can be significantly improved in noisy neuronal systems by subthreshold negative feedback, serving to suppress false positives.

Analysis of Variance↗

PubMed2002

Enhancement of signal-to-noise ratio and phase locking for small inputs by a low-threshold outward current in auditory neurons.

Neurons possess multiple voltage-dependent conductances specific for their function. To investigate how low-threshold outward currents improve the detection of small signals in a noisy background, we recorded from gerbil medial superior olivary (MSO) neurons in vitro. MSO neurons responded phasically, with a single spike to a step current injection. When bathed in dendrotoxin (DTX), most cells switched to tonic firing, suggesting that low-threshold potassium currents (I(KLT)) participated in shaping these phasic responses. Neurons were stimulated with a computer-generated steady barrage of random inputs, mimicking weak synaptic conductance transients (the "noise"), together with a larger but still subthreshold postsynaptic conductance, EPSG (the "signal"). DTX reduced the signal-to-noise ratio (SNR), defined as the ratio of probability to fire in response to the EPSG and the probability to fire spontaneously in response to noise. The reduction was mainly attributable to the increase of spontaneous firing in DTX. The spike-triggered reverse correlation indicated that, for spike generation, the neuron with I(KLT) required faster inward current transients. This narrow temporal integration window contributed to superior phase locking of firing to periodic stimuli before application of DTX. A computer model including Hodgkin-Huxley type conductances for spike generation and for I(KLT) (Rathouz and Trussell, 1998) showed similar response statistics. The dynamic low-threshold outward current increased SNR and the temporal precision of integration of weak subthreshold signals in auditory neurons by suppressing false positives.

Animals↗

PubMed2002

Thalamocortical bursts trigger recurrent activity in neocortical networks: layer 4 as a frequency-dependent gate.

Sensory information reaches the cortex via thalamocortical (TC) synapses in layer 4. Thalamic relay neurons that mediate information flow to cortex operate in two distinct modes, tonic and burst firing. Burst firing has been implicated in enhancing reliability of information flow between individual neurons. However, little is known about how local networks of neocortical neurons respond to different temporal patterns of TC activity. We studied cortical activity patterns evoked by stimulating TC afferents at different frequencies, using a combination of electrophysiology and calcium imaging in TC slices that allowed for the reconstruction of spatiotemporal activity with single-cell resolution. Stimulation of TC axons at low frequencies triggered action potentials in only a small number of layer 4 neurons. In contrast, brief high-frequency stimulus trains triggered widespread recurrent activity in populations of neurons in layer 4 and then spread into adjacent layers 2/3 and 5. Recurrent activity had a clear threshold, typically lasted 300 msec, and could be evoked repetitively at frequencies up to 0.5 Hz. Moreover, the spatial extent of recurrent activity was controlled by the TC pattern of activity. Recurrent activity triggered within the highly interconnected networks of layer 4 might act to selectively amplify and redistribute transient high-frequency TC inputs, filter out low-frequency inputs, and temporarily preserve a record of past sensory activity.

Action Potentials↗