Biomedical subjects

Brent Doiron

Publications and source records attributed to Brent Doiron.

15 recordsLinked to original sources

PubMed2006

Towards blueprints for network architecture, biophysical dynamics and signal transduction.

We review mathematical aspects of biophysical dynamics, signal transduction and network architecture that have been used to uncover functionally significant relations between the dynamics of single neurons and the networks they compose. We focus on examples that combine insights from these three areas to expand our understanding of systems neuroscience. These range from single neuron coding to models of decision making and electrosensory discrimination by networks and populations and also coincidence detection in pairs of dendrites and dynamics of large networks of excitable dendritic spines. We conclude by describing some of the challenges that lie ahead as the applied mathematics community seeks to provide the tools which will ultimately underpin systems neuroscience.

Animals↗

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.

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PubMed2005

Theory of oscillatory firing induced by spatially correlated noise and delayed inhibitory feedback.

A network of leaky integrate-and-fire neurons with global inhibitory feedback and under the influence of spatially correlated noise is studied. We calculate the spectral statistics of the network (power spectrum of the population activity, cross spectrum between spike trains of different neurons) as well as of a single neuron (power spectrum of spike train, cross spectrum between external noise and spike train) within the network. As shown by comparison with numerical simulations, our theory works well for arbitrary network size if the feedback is weak and the amount of external noise does not exceed that of the internal noise. By means of our analytical results we discuss the quality of the correlation-induced oscillation in a large network as a function of the transmission delay and the internal noise intensity. It is shown that the strongest oscillation is obtained in a system with zero internal noise and adiabatically long delay (i.e., the delay period is longer than any other time scale in the system). For a neuron with a strong intrinsic frequency, the oscillation becomes strongly anharmonic in the case of a long delay time. We also discuss briefly the kind of synchrony introduced by the feedback-induced oscillation.

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PubMed2005

Deterministic multiplicative gain control with active dendrites.

Multiplicative gain control is a vital component of many theoretical analyses of neural computations, conferring the ability to scale neuronal firing rate in response to synaptic inputs. Many theories of gain control in single cells have used precisely balanced noisy inputs. Such noisy inputs can degrade signal processing. We demonstrate a deterministic method for the control of gain without the use of noise. We show that a depolarizing afterpotential (DAP), arising from active dendritic spike backpropagation, leads to a multiplicative increase in gain. Reduction of DAP amplitude by dendritic inhibition dilutes the multiplicative effect, allowing for divisive scaling of the firing rate. In contrast, somatic inhibition acts in a subtractive manner, allowing spatially distinct inhibitory inputs to perform distinct computations. The simplicity of this mechanism and the ubiquity of its elementary components suggest that many cell types have the potential to display a dendritic division of neuronal output.

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PubMed2005

Coding of temporally varying signals in networks of spiking neurons with global delayed feedback.

Oscillatory and synchronized neural activities are commonly found in the brain, and evidence suggests that many of them are caused by global feedback. Their mechanisms and roles in information processing have been discussed often using purely feedforward networks or recurrent networks with constant inputs. On the other hand, real recurrent neural networks are abundant and continually receive information-rich inputs from the outside environment or other parts of the brain. We examine how feedforward networks of spiking neurons with delayed global feedback process information about temporally changing inputs. We show that the network behavior is more synchronous as well as more correlated with and phase-locked to the stimulus when the stimulus frequency is resonant with the inherent frequency of the neuron or that of the network oscillation generated by the feedback architecture. The two eigenmodes have distinct dynamical characteristics, which are supported by numerical simulations and by analytical arguments based on frequency response and bifurcation theory. This distinction is similar to the class I versus class II classification of single neurons according to the bifurcation from quiescence to periodic firing, and the two modes depend differently on system parameters. These two mechanisms may be associated with different types of information processing.

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PubMed2004

Oscillatory activity in electrosensory neurons increases with the spatial correlation of the stochastic input stimulus.

We present results from a novel experimental paradigm to investigate the influence of spatial correlations of stimuli on electrosensory neural network dynamics. Further, a new theoretical analysis for the dynamics of a model network of stochastic leaky integrate-and-fire neurons with delayed feedback is proposed. Experiment and theory for this system both establish that spatial correlations induce a network oscillation, the strength of which is proportional to the degree of stimulus correlation at constant total stimulus power.

Animals↗

PubMed2004

Parallel processing of sensory input by bursts and isolated spikes.

Burst firing is commonly observed in many sensory systems and is proposed to transmit information reliably. Although a number of biophysical burst mechanisms have been identified, the relationship between burst dynamics and information transfer is uncertain. Electrosensory pyramidal cells have a well defined backpropagation-dependent burst mechanism. We used in vivo, in vitro, and modeling approaches to investigate pyramidal cell responses to mimics of behaviorally relevant sensory input. We found that within a given spike train, bursts are biased toward low-frequency events while isolated spikes simultaneously code for the entire frequency range. We also demonstrated that burst dynamics are essential for optimal feature detection but are not required for stimulus estimation. We conclude that burst and spike dynamics can segregate a single spike train into two parallel and complementary streams of information transfer.

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PubMed2003

Non-classical receptive field mediates switch in a sensory neuron's frequency tuning.

Animals have developed stereotyped communication calls to which specific sensory neurons are well tuned. These communication calls must be discriminated from environmental signals such as those produced by prey. Sensory systems might have evolved neural circuitry to encode both categories. In weakly electric fish, prey and communication signals differ in their spatial extent and frequency content. Here we show that stimuli of different spatial extents mimicking prey and communication signals cause a switch in the frequency tuning and spike-timing precision of electrosensory pyramidal neurons, resulting in the selective and optimal encoding of both stimulus categories. As in other sensory systems, pyramidal neurons respond only to stimuli located within a restricted region of space known as the classical receptive field (CRF). In some systems, stimulation outside the CRF but within a non-classical receptive field (nCRF) can modulate the neural response to CRF stimulation even though nCRF stimulation alone fails to elicit responses. We show that pyramidal neurons possess a nCRF and that it can modulate the response to CRF stimuli to induce this neurobiological switch in frequency tuning.

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PubMed2003

A dynamic dendritic refractory period regulates burst discharge in the electrosensory lobe of weakly electric fish.

Na+-dependent spikes initiate in the soma or axon hillock region and actively backpropagate into the dendritic arbor of many central neurons. Inward currents underlying spike discharge are offset by outward K+ currents that repolarize a spike and establish a refractory period to temporarily prevent spike discharge. We show in a sensory neuron that somatic and dendritic K+ channels differentially control burst discharge by regulating the extent to which backpropagating dendritic spikes can re-excite the soma. During repetitive discharge a progressive broadening of dendritic spikes promotes a dynamic increase in dendritic spike refractory period. A leaky integrate-and-fire model shows that spike bursts are terminated when a decreasing somatic interspike interval and an increasing dendritic spike refractory period synergistically act to block backpropagation. The time required for the somatic interspike interval to intersect with dendritic refractory period determines burst frequency, a time that is regulated by somatic and dendritic spike repolarization. Thus, K+ channels involved in spike repolarization can efficiently control the pattern of spike output by establishing a soma-dendritic interaction that invokes dynamic shifts in dendritic spike properties.

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PubMed2003

Inhibitory feedback required for network oscillatory responses to communication but not prey stimuli.

Stimulus-induced oscillations occur in visual, olfactory and somatosensory systems. Several experimental and theoretical studies have shown how such oscillations can be generated by inhibitory connections between neurons. But the effects of realistic spatiotemporal sensory input on oscillatory network dynamics and the overall functional roles of such oscillations in sensory processing are poorly understood. Weakly electric fish must detect electric field modulations produced by both prey (spatially localized) and communication (spatially diffuse) signals. Here we show, through in vivo recordings, that sensory pyramidal neurons in these animals produce an oscillatory response to communication-like stimuli, but not to prey-like stimuli. On the basis of well-characterized circuitry, we construct a network model of pyramidal neurons that predicts that diffuse delayed inhibitory feedback is required to achieve oscillatory behaviour only in response to communication-like stimuli. This prediction is experimentally verified by reversible blockade of feedback inhibition that removes oscillatory behaviour in the presence of communication-like stimuli. Our results show that a sensory system can use inhibitory feedback as a mechanism to 'toggle' between oscillatory and non-oscillatory firing states, each associated with a naturalistic stimulus.

Acoustic Stimulation↗

PubMed2003

Persistent Na+ current modifies burst discharge by regulating conditional backpropagation of dendritic spikes.

The estimation and detection of stimuli by sensory neurons is affected by factors that govern a transition from tonic to burst mode and the frequency characteristics of burst output. Pyramidal cells in the electrosensory lobe of weakly electric fish generate spike bursts for the purpose of stimulus detection. Spike bursts are generated during repetitive discharge when a frequency-dependent broadening of dendritic spikes increases current flow from dendrite to soma to potentiate a somatic depolarizing afterpotential (DAP). The DAP eventually triggers a somatic spike doublet with an interspike interval that falls inside the dendritic refractory period, blocking spike backpropagiation and the DAP. Repetition of this process gives rise to a rhythmic dendritic spike failure, termed conditional backpropagation, that converts cell output from tonic to burst discharge. Through in vitro recordings and compartmental modeling we show that burst frequency is regulated by the rate of DAP potentiation during a burst, which determines the time required to discharge the spike doublet that blocks backpropagation. DAP potentiation is magnified through a positive feedback process when an increase in dendritic spike duration activates persistent sodium current (I(NaP)). I(NaP) further promotes a slow depolarization that induces a shift from tonic to burst discharge over time. The results are consistent with a dynamical systems analysis that shows that the threshold separating tonic and burst discharge can be represented as a saddle-node bifurcation. The interaction between dendritic K(+) current and I(NaP) provides a physiological explanation for a variable time scale of bursting dynamics characteristic of such a bifurcation.

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PubMedDate not supplied

Noise-induced divisive gain control in neuron models.

A recent computational study of gain control via shunting inhibition has shown that the slope of the frequency-versus-input (f-I) characteristic of a neuron can be decreased by increasing the noise associated with the inhibitory input (Neural Comput. 13, 227-248). This novel noise-induced divisive gain control relies on the concommittant increase of the noise variance with the mean of the total inhibitory conductance. Here we investigate this effect using different neuronal models. The effect is shown to occur in the standard leaky integrate-and-fire (LIF) model with additive Gaussian white noise, and in the LIF with multiplicative noise acting on the inhibitory conductance. The noisy scaling of input currents is also shown to occur in the one-dimensional theta-neuron model, which has firing dynamics, as well as a large scale compartmental model of a pyramidal cell in the electrosensory lateral line lobe of a weakly electric fish. In this latter case, both the inhibition and the excitatory input have Poisson statistics; noise-induced divisive inhibition is thus seen in f-I curves for which the noise increases along with the input I. We discuss how the variation of the noise intensity along with inputs is constrained by the physiological context and the class of model used, and further provide a comparison of the divisive effect across models.

Computational Biology↗

PubMedDate not supplied

Oscillatory burst discharge generated through conditional backpropagation of dendritic spikes.

Gamma frequencies of burst discharge (>40 Hz) have become recognized in select cortical and non-cortical regions as being important in feature extraction, neural synchrony and oscillatory discharge. Pyramidal cells of the electrosensory lateral line lobe (ELL) of Apteronotus leptorhynchus generate burst discharge in relation to specific features of sensory input in vivo that resemble those recognized as gamma frequency discharge when examined in vitro. We have shown that these bursts are generated by an entirely novel mechanism termed conditional backpropagation that involves an intermittent failure of dendritic Na+ spike conduction. Conditional backpropagation arises from a frequency-dependent broadening of dendritic spikes during repetitive discharge, and a mismatch between the refractory periods of somatic and dendritic spikes. A high threshold class of K+ channel, AptKv3.3, is expressed at high levels and distributed over the entire soma-dendritic axis of pyramidal cells. AptKv3.3 channels are shown to contribute to the repolarization of both somatic and dendritic spikes, with pharmacological blockade of dendritic Kv3 channels revealing an important role in controlling the threshold for burst discharge. The entire process of conditional back-propagation and burst output is successfully simulated using a new compartmental model of pyramidal cells that incorporates a cumulative inactivation of dendritic K+ channels during repetitive discharge. This work is important in demonstrating how the success of spike backpropagation can control the output of a principle sensory neuron, and how this process is regulated by the distribution and properties of voltage-dependent K+ channels.

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PubMedDate not supplied

Ghostbursting: a novel neuronal burst mechanism.

Pyramidal cells in the electrosensory lateral line lobe (ELL) of weakly electric fish have been observed to produce high-frequency burst discharge with constant depolarizing current (Turner et al., 1994). We present a two-compartment model of an ELL pyramidal cell that produces burst discharges similar to those seen in experiments. The burst mechanism involves a slowly changing interaction between the somatic and dendritic action potentials. Burst termination occurs when the trajectory of the system is reinjected in phase space near the "ghost" of a saddle-node bifurcation of fixed points. The burst trajectory reinjection is studied using quasi-static bifurcation theory, that shows a period doubling transition in the fast subsystem as the cause of burst termination. As the applied depolarization is increased, the model exhibits first resting, then tonic firing, and finally chaotic bursting behavior, in contrast with many other burst models. The transition between tonic firing and burst firing is due to a saddle-node bifurcation of limit cycles. Analysis of this bifurcation shows that the route to chaos in these neurons is type I intermittency, and we present experimental analysis of ELL pyramidal cell burst trains that support this model prediction. By varying parameters in a way that changes the positions of both saddle-node bifurcations in parameter space, we produce a wide gallery of burst patterns, which span a significant range of burst time scales.

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PubMedDate not supplied

Type I burst excitability.

We introduce the concept of "type I burst excitability", which is a generalization of the "normal" excitability that is well-known in cardiac and neural systems. We demonstrate this type of burst excitability in a specific model system, a pyramidal cell from the electrosensory lateral line lobe of the weakly electric fish Apteronotus leptorhynchus. As depolarizing current is increased, a saddle-node bifurcation of periodic orbits occurs, which separates tonic and burst activity. This bifurcation is responsible for the excitable nature of the system, and is the basis for the "type I" designation. We verify the existence of this transition from in vitro recordings of a number of actual pyramidal cells. A scaling relationship between the magnitude and duration of a current pulse required to induce a burst is derived. We also observe this type of burst excitability and the scaling relationships in a multicompartmental model that is driven by realistic stochastic synaptic inputs mimicking sensory input. We conclude by discussing the relevance of burst excitability to communication between weakly electric fish.

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