Biomedical subjects

Patrick D Roberts

Publications and source records attributed to Patrick D Roberts.

10 recordsLinked to original sources

PubMed2007

Stability of complex spike timing-dependent plasticity in cerebellar learning.

Dynamics of spike-timing dependent synaptic plasticity are analyzed for excitatory and inhibitory synapses onto cerebellar Purkinje cells. The purpose of this study is to place theoretical constraints on candidate synaptic learning rules that determine the changes in synaptic efficacy due to pairing complex spikes with presynaptic spikes in parallel fibers and inhibitory interneurons. Constraints are derived for the timing between complex spikes and presynaptic spikes, constraints that result from the stability of the learning dynamics of the learning rule. Potential instabilities in the parallel fiber synaptic learning rule are found to be stabilized by synaptic plasticity at inhibitory synapses if the inhibitory learning rules are stable, and conditions for stability of inhibitory plasticity are given. Combining excitatory with inhibitory plasticity provides a mechanism for minimizing the overall synaptic input. Stable learning rules are shown to be able to sculpt simple-spike patterns by regulating the excitability of neurons in the inferior olive that give rise to climbing fibers.

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PubMed2006

Effects of sensing behavior on a latency code.

Sensory information is often acquired through active exploration, yet relatively little is known about how neurons encode sensory stimuli in the context of natural patterns of sensing behavior. We examined the effects of sensing behavior on a spike latency code in the active electrosensory system of mormyrid fish. These fish actively probe their environment by emitting brief electric organ discharge (EOD) pulses. Nearby objects alter the spatial pattern of current flowing through the skin. These changes are encoded by small shifts in the latency of individual electroreceptor afferent spikes after the EOD. In nature, the temporal pattern of EOD intervals is highly structured and varies depending on the behavioral context. We performed experiments in which we varied both the EOD amplitude and the intervals between EODs to understand how sensing behavior affects afferent latency coding. We use white-noise stimuli and linear filter estimation methods to develop simple models characterizing the dependence of afferent spike latency on the preceding sequence of EOD intervals and amplitudes. Comparing the predictions of these models with actual afferent responses for natural patterns of EOD intervals and amplitudes reveals an unexpectedly rich interplay between sensing behavior and stimulus encoding. Implications of our results for how afferent spike latency is decoded at central stages of electrosensory processing are discussed.

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PubMed2004

Random walks for spike-timing-dependent plasticity.

Random walk methods are used to calculate the moments of negative image equilibrium distributions in synaptic weight dynamics governed by spike-timing-dependent plasticity. The neural architecture of the model is based on the electrosensory lateral line lobe of mormyrid electric fish, which forms a negative image of the reafferent signal from the fish's own electric discharge to optimize detection of sensory electric fields. Of particular behavioral importance to the fish is the variance of the equilibrium postsynaptic potential in the presence of noise, which is determined by the variance of the equilibrium weight distribution. Recurrence relations are derived for the moments of the equilibrium weight distribution, for arbitrary postsynaptic potential functions and arbitrary learning rules. For the case of homogeneous network parameters, explicit closed form solutions are developed for the covariances of the synaptic weight and postsynaptic potential distributions.

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PubMed2004

Recurrent biological neural networks: the weak and noisy limit.

A perturbative method is developed for calculating the effects of recurrent synaptic interactions between neurons embedded in a network. A series expansion is constructed that converges for networks with noisy membrane potential and weak synaptic connectivity. The terms of the series can be interpreted as loops of interactions between neurons, so the technique is called a loop expansion. A diagrammatic method is introduced that allows for construction of analytic expressions for the parameter dependencies of the spike-probability function and correlation functions. An analytic expression is obtained to predict the effect of the surrounding network on a neuron during an intracellular current injection. The analytic results are compared with simulations to test the range of their validity and significant effects of the the recurrent connections in network are accurately predicted by the loop expansion.

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PubMed2004

Dynamics of everyday life: rigorous modular modeling in neurobiology based on Bloch's dynamical theorem.

Natural, everyday sensorimotor behaviors, such as rising from sitting, typically have an intrinsic organization of several levels of analysis. Taking this intrinsic organization as key to understanding neural dynamics is neither a top-down nor a bottom-up approach, but rather a meshing of multiple centers and levels of analysis. Motor control requires body dynamics that are consistent with physical dynamics, besides the more microscopic levels of neural dynamics. The dynamics of separate movements have been investigated as if the ends can be capped off, separated from the rest of the individual's life. Is this dynamically correct? Even chaotic behavior is deterministic. However, the mathematics of nonlinear oscillations is not all of dynamics. This paper relates Bloch's dynamical theorem to the modular, conditional approach to sensorimotor and other neural functioning. Bloch's dynamical theorem lays a foundation for the piecewise study of structurally accurate dynamics in theoretical neurobiology. Piecewise studies can be used as a modeling option complementary to the methods of nonlinear oscillator dynamics. By applying Bloch's theorem, dynamics of movements analyzed piecewise can be extended into a smooth flow on any manifold, either as a whole or conditionally. Conditional dynamics makes dynamical modeling options explicit, often depending on what variables the organism can control, and allows one to take different modeling options at different junctures in analyzing the same phenomenon. For example, this approach allows the study of complex motor control problems to be reduced to modular constructions using singularities and flow lines. Dynamical contingencies are expressed using the mathematics of ordered structures. This paper presents Bloch's dynamical theorem and its relevance to model construction in theoretical neurobiology. Specific examples, integrated into physiological and behavioral context, are cited from the literature.

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PubMed2003

Stability of negative-image equilibria in spike-timing-dependent plasticity.

We investigate the stability of negative image equilibria in mean synaptic weight dynamics governed by spike-timing-dependent plasticity (STDP). The model architecture closely follows the anatomy and physiology of the electrosensory lateral line lobe (ELL) of mormyrid electric fish. The ELL uses a spike-timing-dependent learning rule to form a negative image of the reafferent signal from the fish's own electric discharge, thus improving detectability of external electric fields. We derive sufficient conditions for existence of the negative image and necessary and sufficient conditions for stability, for arbitrary postsynaptic potential functions and arbitrary learning rules. This significantly generalizes earlier investigations. We then apply the general result to several examples of biological interest, including a class of learning rules consistent with the rule observed experimentally in the mormyrid ELL.

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PubMed2003

The mormyromast region of the mormyrid electrosensory lobe. I. Responses to corollary discharge and electrosensory stimuli.

This is the first of two papers on the electrosensory lobe (ELL) of mormyrid electric fish. The ELL is the first stage in the central processing of electrosensory information from electroreceptors. Cells of the mormyrid ELL are affected at the time of the electric organ discharge (EOD) by two different inputs, EOD-evoked reafferent input from electroreceptors and corollary discharge input associated with the motor command that elicits the EOD. This first paper examines the intracellular responses of ELL cells to these two different inputs in the region of ELL that receives primary afferent fibers from mormyromast electroreceptors. Mormyromast electroreceptors are responsible for active electrolocation. The paper extends previous studies of the mormyrid ELL by describing the physiological responses of cell types, which had been previously identified only morphologically, including: the two types of Purkinje-like medium ganglionic cells, MG1 and MG2; the thick smooth dendrite cells; and the medium fusiform cells. In addition, two previously unrecognized cell types, the large thick smooth dendrite cell and the interzonal cell, are described both morphologically and physiologically for the first time. Finally, new information is provided on the two types of ELL efferent cells, the large ganglionic and large fusiform cells. All cell types, except for the medium fusiform cell, show nonlinear interactions between electrosensory and corollary discharge inputs. All cell types, except for the medium fusiform cell and the interzonal cell, also show plasticity of the corollary discharge response after pairing with electrosensory stimuli.

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PubMed2003

The mormyromast region of the mormyrid electrosensory lobe. II. Responses to input from central sources.

This is the second in a series of two papers on the mormyromast regions of the electrosensory lobe (ELL) of mormyrid electric fish. In this study, we examined the effects of artificial stimulation of two of the three major central inputs to ELL on different morphologically identified cell types of ELL. The three major central inputs to ELL are the eminentia granularis posterior, the juxtalobar nucleus, and the preeminential nucleus. We stimulated the juxtalobar and preeminential nuclei. We compared the effects of such stimulation with effects of the electric organ corollary discharge (EOCD) on the same cells to understand the origins of EOCD effects in ELL. Responses to juxtalobar stimulation were different in different cell types and remarkably similar to corollary discharge responses in the same cells. In addition, responses to juxtalobar stimulation were consistently depressed when the stimulus was delivered immediately after the naturally occurring EOCD response. These findings indicate that the juxtalobar nucleus is a major source of the EOCD responses of ELL cells. In contrast, preeminential stimulation evoked similar responses in medium ganglionic cells, and the two types of efferent cells that were quite different from the EOCD responses of these cells, suggesting that the preeminential nucleus is less important than the juxtalobar nucleus in determining the EOCD responses of ELL cells. Preeminential responses of medium ganglionic and efferent cells consisted of a short-latency excitatory postsynaptic potential (EPSP) followed by a long-lasting inhibitory postsynaptic potential (IPSP). Both the EPSPs and IPSPs were facilitated when brief bursts of closely spaced stimuli were delivered.

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PubMed2002

Spike timing dependent synaptic plasticity in biological systems.

Association of a presynaptic spike with a postsynaptic spike can lead to changes in synaptic efficacy that are highly dependent on the relative timing of the pre- and postsynaptic spikes. Different synapses show varying forms of such spike-timing dependent learning rules. This review describes these different rules, the cellular mechanisms that may be responsible for them, and the computational consequences of these rules for information processing and storage in the nervous system.

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PubMedDate not supplied

Active control of spike-timing dependent synaptic plasticity in an electrosensory system.

A spike timing dependent learning rule is present at the synapse between parallel fibers and Purkinje-like medium ganglion cells in the electrosensory lobe of mormyrid electric fish. The synapse is depressed when a postsynaptic dendritic spike occurs within 50 ms of the onset of a parallel fiber excitatory postsynaptic potential, but is enhanced at all other timing relations. Operation of this learning rule results in the cancellation of predictable membrane potential changes, driving the cell towards a constant output frequency. But medium ganglion cells show a strong and predictable response to corollary discharge signals associated with the motor command that initiates the electric organ discharge. The modeling study presented here resolves this conflict by proposing an active control of dendritic spike threshold during the brief period of medium ganglion cell response.

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