PubMed Health⌕ Search

Biomedical subjects

L F Abbott

Publications and source records attributed to L F Abbott.

At least 19 recordsLinked to original sources
PubMed1998

A model neuron with activity-dependent conductances regulated by multiple calcium sensors.

Membrane channels are subject to a wide variety of regulatory mechanisms that can be affected by activity. We present a model of a stomatogastric ganglion (STG) neuron in which several Ca2+-dependent pathways are used to regulate the maximal conductances of membrane currents in an activity-dependent manner. Unlike previous models of this type, the regulation and modification of maximal conductances by electrical activity is unconstrained. The model has seven voltage-dependent membrane currents and uses three Ca2+ sensors acting on different time scales. Starting from random initial conditions over a given range, the model sets the maximal conductances for its active membrane currents to values that produce a predefined target pattern of activity approximately 90% of the time. In these models, the same pattern of electrical activity can be produced by a range of maximal conductances, and this range is compared with voltage-clamp data from the lateral pyloric neuron of the STG. If the electrical activity of the model neuron is perturbed, the maximal conductances adjust to restore the original pattern of activity. When the perturbation is removed, the activity pattern is again restored after a transient adjustment period, but the conductances may not return to their initial values. The model suggests that neurons may regulate their conductances to maintain fixed patterns of electrical activity, rather than fixed maximal conductances, and that the regulation process requires feedback systems capable of reacting to changes of electrical activity on a number of different time scales.

Action Potentials↗
PubMed1997

Responses of neurons in primary and inferior temporal visual cortices to natural scenes.

The primary visual cortex (V1) is the first cortical area to receive visual input, and inferior temporal (IT) areas are among the last along the ventral visual pathway. We recorded, in area V1 of anaesthetized cats and area IT of awake macaque monkeys, responses of neurons to videos of natural scenes. Responses were analysed to test various hypotheses concerning the nature of neural coding in these two regions. A variety of spike-train statistics were measured including spike-count distributions, interspike interval distributions, coefficients of variation, power spectra, Fano factors and different sparseness measures. All statistics showed non-Poisson characteristics and several revealed self-similarity of the spike trains. Spike-count distributions were approximately exponential in both visual areas for eight different videos and for counting windows ranging from 50 ms to 5 seconds. The results suggest that the neurons maximize their information carrying capacity while maintaining a fixed long-term-average firing rate, or equivalently, minimize their average firing rate for a fixed information carrying capacity.

Animals↗
PubMed1997

A quantitative description of short-term plasticity at excitatory synapses in layer 2/3 of rat primary visual cortex.

Cortical synapses exhibit several forms of short-term plasticity, but the contribution of this plasticity to visual response dynamics is unknown. In part, this is because the simple patterns of stimulation used to probe plasticity in vitro do not correspond to patterns of activity that occur in vivo. We have developed a method of quantitatively characterizing short-term plasticity at cortical synapses that permits prediction of responses to arbitrary patterns of stimulation. Synaptic responses were recorded intracellularly as EPSCs and extracellularly as local field potentials in layer 2/3 of rat primary visual cortical slices during stimulation of layer 4 with trains of electrical stimuli containing random mixtures of frequencies. Responses exhibited complex dynamics that were well described by a simple three-component model consisting of facilitation and two forms of depression, a stronger form that decayed exponentially with a time constant of several hundred milliseconds and a weaker, but more persistent, form that decayed with a time constant of several seconds. Parameters obtained from fits to one train were used to predict accurately responses to other random and constant frequency trains. Control experiments revealed that depression was not caused by a decrease in the effectiveness of extracellular stimulation or by a buildup of inhibition. Pharmacological manipulations of transmitter release and postsynaptic sensitivity suggested that both forms of depression are mediated presynaptically. These results indicate that firing evoked by visual stimuli is likely to cause significant depression at cortical synapses. Hence synaptic depression may be an important determinant of the temporal features of visual cortical responses.

Animals↗
PubMed1997

Temporal dynamics of graded synaptic transmission in the lobster stomatogastric ganglion.

Synaptic transmission between neurons in the stomatogastric ganglion of the lobster Panulirus interruptus is a graded function of membrane potential, with a threshold for transmitter release in the range of -50 to -60 mV. We studied the dynamics of graded transmission between the lateral pyloric (LP) neuron and the pyloric dilator (PD) neurons after blocking action potential-mediated transmission with 0.1 microM tetrodotoxin. We compared the graded IPSPs (gIPSPs) from LP to PD neurons evoked by square pulse presynaptic depolarizations with those potentials evoked by realistic presynaptic waveforms of variable frequency, amplitude, and duty cycle. The gIPSP shows frequency-dependent synaptic depression. The recovery from depression is slow, and as a result, the gIPSP is depressed at normal pyloric network frequencies. Changes in the duration of the presynaptic depolarization produce nonintuitive changes in the amplitude and time course of the postsynaptic responses, which are again frequency-dependent. Taken together, these data demonstrate that the measurements of synaptic efficacy that are used to understand neural network function are best made using presynaptic waveforms and patterns of activity that mimic those in the functional network.

Animals↗
PubMed1997

Synaptic depression and cortical gain control.

Cortical neurons receive synaptic inputs from thousands of afferents that fire action potentials at rates ranging from less than 1 hertz to more than 200 hertz. Both the number of afferents and their large dynamic range can mask changes in the spatial and temporal pattern of synaptic activity, limiting the ability of a cortical neuron to respond to its inputs. Modeling work based on experimental measurements indicates that short-term depression of intracortical synapses provides a dynamic gain-control mechanism that allows equal percentage rate changes on rapidly and slowly firing afferents to produce equal postsynaptic responses. Unlike inhibitory and adaptive mechanisms that reduce responsiveness to all inputs, synaptic depression is input-specific, leading to a dramatic increase in the sensitivity of a neuron to subtle changes in the firing patterns of its afferents.

Action Potentials↗
PubMed1997

Learning navigational maps through potentiation and modulation of hippocampal place cells.

We analyze a model of navigational map formation based on correlation-based, temporally asymmetric potentiation and depression of synapses between hippocampal place cells. We show that synaptic modification during random exploration of an environment shifts the location encoded by place cell activity in such a way that it indicates the direction from any location to a fixed target avoiding walls and other obstacles. Multiple maps to different targets can be simultaneously stored if we introduce target-dependent modulation of place cell activity. Once maps to a number of target locations in a given environment have been stored, novel maps to previously unknown target locations are automatically constructed by interpolation between existing maps.

Animals↗
PubMed1997

Invariant visual responses from attentional gain fields.

Inferotemporal (IT) neurons exhibit a substantial degree of invariance with respect to translation of images used as visual stimuli. Through theoretical and computer-modeling methods, we show how translation-invariant receptive fields, like those of IT neurons, can be generated from the responses of V4 neurons if the effects of attention are taken into account. The model incorporates a recently reported form of attention-dependent gain modulation in V4 and produces IT receptive fields that shift so they are centered at the point where attention is directed. Receptive fields of variable, attention-controlled spatial scale are obtained when the mechanism is extended to scale-dependent attentional gain fields. The results indicate that gain modulation may play analogous roles in the dorsal and ventral visual pathways, generating transformations from retinal coordinates to body- and object-centered systems, respectively.

Animals↗
PubMed1996

Memory from the dynamics of intrinsic membrane currents.

Almost all theoretical and experimental studies of the mechanisms underlying learning and memory focus on synaptic efficacy and make the implicit assumption that changes in synaptic efficacy are both necessary and sufficient to account for learning and memory. However, network dynamics depends on the complex interaction between intrinsic membrane properties and synaptic strengths and time courses. Furthermore, neuronal activity itself modifies not only synaptic efficacy but also the intrinsic membrane properties of neurons. This paper presents examples demonstrating that neurons with complex temporal dynamics can provide short-term "memory" mechanisms that rely solely on intrinsic neuronal properties. Additionally, we discuss the potential role that activity may play in long-term modification of intrinsic neuronal properties. While not replacing synaptic plasticity as a powerful learning mechanism, these examples suggest that memory in networks results from an ongoing interplay between changes in synaptic efficacy and intrinsic membrane properties.

Animals↗
PubMed1996

A model of multiplicative neural responses in parietal cortex.

Visual responses of neurons in parietal area 7a are modulated by a combined eye and head position signal in a multiplicative manner. Neurons with multiplicative responses can act as powerful computational elements in neural networks. In the case of parietal cortex, multiplicative gain modulation appears to play a crucial role in the transformation of object locations from retinal to body-centered coordinates. It has proven difficult to uncover single-neuron mechanisms that account for neuronal multiplication. Here we show that multiplicative responses can arise in a network model through population effects. Specifically, neurons in a recurrently connected network with excitatory connections between similarly tuned neurons and inhibitory connections between differently tuned neurons can perform a product operation on additive synaptic inputs. The results suggest that parietal responses may be based on this architecture.

Animals↗
PubMed1996

Decoding synapses.

The strength of many synapses is modified by various use and time-dependent processes, including facilitation and depression. A general description of synaptic transfer characteristics must account for the history-dependence of synaptic efficacy and should be able to predict the postsynaptic response to any temporal pattern of presynaptic activity. To generate such a description, we use an approach similar to the decoding method used to reconstruct a sensory input from a neuronal firing pattern. Specifically, a mathematical fit of the postsynaptic response to an isolated action potential is multiplied by an amplitude factor that depends on a time-dependent function summed over all previous presynaptic spikes. The amplitude factor is, in general, a nonlinear function of this sum. Approximate forms of the time-dependent function and the nonlinearity are extracted from the data, and then both functions are constructed more precisely by a learning algorithm. This approach, which should be applicable to a wide variety of synapses, is applied here to several crustacean neuromuscular junctions. After training on data from random spike sequences, the method predicts the postsynaptic response to an arbitrary train of presynaptic action potentials. Using a model synapse, we relate the functions used in the fit to underlying biophysical processes. Fitting different neuromuscular junctions allows us to compare their responses to sequences of action potentials and to contrast the time course and degree of facilitation or depression that they exhibit.

Action Potentials↗
PubMed1996

Cellular short-term memory from a slow potassium conductance.

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.

Action Potentials↗
PubMed1996

A model of spatial map formation in the hippocampus of the rat.

Using experimental facts about long-term potentiation (LTP) and hippocampal place cells, we model how a spatial map of the environment can be created in the rat hippocampus. Sequential firing of place cells during exploration induces, in the model, a pattern of LTP between place cells that shifts the location coded by their ensemble activity away from the actual location of the animal. These shifts provide a navigational map that, in a simulation of the Morris maze, can guide the animal toward its goal. The model demonstrates how behaviorally generated modifications of synaptic strengths can be read out to affect subsequent behavior. Our results also suggest a way that navigational maps can be constructed from experimental recordings of hippocampal place cells.

Action Potentials↗
PubMed1995

Theory in motion.

Modeling studies are now a significant part of mainstream research in motor control. Novel and classical modeling techniques used in recent work on small and large motor systems illustrate the different roles that models play in furthering our understanding of motor systems. The models presented reveal single neuron short-term memory, unexpected effects of reciprocal inhibition and methods for decoding activity in large populations of neurons.

Animals↗
PubMed1995

Transfer of coded information from sensory to motor networks.

During sensory-guided motor tasks, information must be transferred from arrays of neurons coding target location to motor networks that generate and control movement. We address two basic questions about this information transfer. First, what mechanisms assure that the different neural representations align properly so that activity in the sensory network representing target location evokes a motor response generating accurate movement toward the target? Coordinate transformations may be needed to put the sensory data into a form appropriate for use by the motor system. For example, in visually guided reaching the location of a target relative to the body is determined by a combination of the position of its image on the retina and the direction of gaze. What assures that the motor network responds to the appropriate combination of sensory inputs corresponding to target position in body- or arm-centered coordinates? To answer these questions, we model a sensory network coding target position and use it to drive a similarly modeled motor network. To determine the actual motor response we use decoding methods that have been developed and verified in experimental work. We derive a general set of conditions on the sensory-to-motor synaptic connections that assure a properly aligned and transformed response. The accuracy of the response for different numbers of coding cells is computed. We show that development of the synaptic weights needed to generate the correct motor response can occur spontaneously through the observation of random movements and correlation-based synaptic modification. No error signal or external teaching is needed during this process. We also discuss nonlinear coordinate transformations and the presence of both shifting and nonshifting receptive fields in sensory/motor systems.

Animals↗
PubMed1994

Activity-dependent current distributions in model neurons.

The electrical activity of a neuron can affect its intrinsic physiological characteristics through a wide range of processes. We study a computer-simulated multicompartment model neuron in which channel density depends on local Ca2+ concentrations. This has three interesting consequences for the spatial distribution of conductances and the physiological behavior of the neuron: (i) the model neuron spontaneously develops a realistic, nonuniform distribution of conductances that is linked both to the morphology of the neuron and to the pattern of synaptic input that it receives, (ii) the response to synaptic input reveals a form of intrinsic localized plasticity that balances the synaptic contribution from dendritic regions receiving unequal stimulation, and (iii) intrinsic plasticity establishes a biophysical gain control that restores the neuron to its optimal firing range after synapses are strengthened by "Hebbian" long-term potentiation.

Calcium↗
PubMed1994

Activity-dependent changes in the intrinsic properties of cultured neurons.

Learning and memory arise through activity-dependent modifications of neural circuits. Although the activity dependence of synaptic efficacy has been studied extensively, less is known about how activity shapes the intrinsic electrical properties of neurons. Lobster stomatogastric ganglion neurons fire in bursts when receiving synaptic and modulatory input but fire tonically when pharmacologically isolated. Long-term isolation in culture changed their intrinsic activity from tonic firing to burst firing. Rhythmic stimulation reversed this transition through a mechanism that was mediated by a rise in intracellular calcium concentration. These data suggest that neurons regulate their conductances to maintain stable activity patterns and that the intrinsic properties of a neuron depend on its recent history of activation.

Animals↗
PubMed1994

When inhibition not excitation synchronizes neural firing.

Excitatory and inhibitory synaptic coupling can have counter-intuitive effects on the synchronization of neuronal firing. While it might appear that excitatory coupling would lead to synchronization, we show that frequently inhibition rather than excitation synchronizes firing. We study two identical neurons described by integrate-and-fire models, general phase-coupled models or the Hodgkin-Huxley model with mutual, non-instantaneous excitatory or inhibitory synapses between them. We find that if the rise time of the synapse is longer than the duration of an action potential, inhibition not excitation leads to synchronized firing.

Action Potentials↗