Rethinking the taxonomy of visual neurons.
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Animals↗
Biomedical subjects
L F Abbott
Publications and source records attributed to L F Abbott.
Failure of averaging in the construction of a conductance-based neuron model.
Parameters for models of biological systems are often obtained by averaging over experimental results from a number of different preparations. To explore the validity of this procedure, we studied the behavior of a conductance-based model neuron with five voltage-dependent conductances. We randomly varied the maximal conductance of each of the active currents in the model and identified sets of maximal conductances that generate bursting neurons that fire a single action potential at the peak of a slow membrane potential depolarization. A model constructed using the means of the maximal conductances of this population is not itself a one-spike burster, but rather fires three action potentials per burst. Averaging fails because the maximal conductances of the population of one-spike bursters lie in a highly concave region of parameter space that does not contain its mean. This demonstrates that averages over multiple samples can fail to characterize a system whose behavior depends on interactions involving a number of highly variable components.
Action Potentials↗
Cortical development and remapping through spike timing-dependent plasticity.
Long-term modification of synaptic efficacy can depend on the timing of pre- and postsynaptic action potentials. In model studies, such spike timing-dependent plasticity (STDP) introduces the desirable features of competition among synapses and regulation of postsynaptic firing characteristics. STDP strengthens synapses that receive correlated input, which can lead to the formation of stimulus-selective columns and the development, refinement, and maintenance of selectivity maps in network models. The temporal asymmetry of STDP suppresses strong destabilizing self-excitatory loops and allows a group of neurons that become selective early in development to direct other neurons to become similarly selective. STDP, acting alone without further hypothetical global constraints or additional forms of plasticity, can also reproduce the remapping seen in adult cortex following afferent lesions.
Action Potentials↗
Global structure, robustness, and modulation of neuronal models.
The electrical characteristics of many neurons are remarkably robust in the face of changing internal and external conditions. At the same time, neurons can be highly sensitive to neuromodulators. We find correlates of this dual robustness and sensitivity in a global analysis of the structure of a conductance-based model neuron. We vary the maximal conductance parameters of the model neuron and, for each set of parameters tested, characterize the activity pattern generated by the cell as silent, tonically firing, or bursting. Within the parameter space of the five maximal conductances of the model, we find directions, representing concerted changes in multiple conductances, along which the basic pattern of neural activity does not change. In other directions, relatively small concurrent changes in a few conductances can induce transitions between these activity patterns. The global structure of the conductance-space maps implies that neuromodulators that alter a sensitive set of conductances will have powerful, and possibly state-dependent, effects. Other modulators that may have no direct impact on the activity of the neuron may nevertheless change the effects of such direct modulators via this state dependence. Some of the results and predictions arising from the model studies are replicated and verified in recordings of stomatogastric ganglion neurons using the dynamic clamp.
Action Potentials↗
Effects of synaptic noise and filtering on the frequency response of spiking neurons.
Noise can have a significant impact on the response dynamics of a nonlinear system. For neurons, the primary source of noise comes from background synaptic input activity. If this is approximated as white noise, the amplitude of the modulation of the firing rate in response to an input current oscillating at frequency omega decreases as 1/square root[omega] and lags the input by 45 degrees in phase. However, if filtering due to realistic synaptic dynamics is included, the firing rate is modulated by a finite amount even in the limit omega-->infinity and the phase lag is eliminated. Thus, through its effect on noise inputs, realistic synaptic dynamics can ensure unlagged neuronal responses to high-frequency inputs.
Action Potentials↗
Coordinate transformations in the visual system: how to generate gain fields and what to compute with them.
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Animals↗
The timing game.
In two publications presented as a contest, Hopfield and Brody propose a mechanism for detecting groups of neurons receiving similar levels of sensory input.
Models, Neurological↗
Activity-dependent modification of inhibitory synapses in models of rhythmic neural networks.
The faithful production of rhythms by many neural circuits depends critically on the strengths of inhibitory synaptic connections. We propose a model in which the strengths of inhibitory synapses in a central pattern-generating circuit are subject to activity-dependent plasticity. The strength of each synapse is modified as a function of the global activity of the postsynaptic neuron and by correlated activity of the pre- and postsynaptic neurons. This allows the self-assembly, from random initial synaptic strengths, of two cells into reciprocal oscillation and three cells into a rhythmic triphasic motor pattern. This self-assembly illustrates that complex oscillatory circuits that depend on multiple inhibitory synaptic connections can be tuned via simple activity-dependent rules.
Action Potentials↗
Integrating with action potentials.
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Action Potentials↗
Competitive Hebbian learning through spike-timing-dependent synaptic plasticity.
Hebbian models of development and learning require both activity-dependent synaptic plasticity and a mechanism that induces competition between different synapses. One form of experimentally observed long-term synaptic plasticity, which we call spike-timing-dependent plasticity (STDP), depends on the relative timing of pre- and postsynaptic action potentials. In modeling studies, we find that this form of synaptic modification can automatically balance synaptic strengths to make postsynaptic firing irregular but more sensitive to presynaptic spike timing. It has been argued that neurons in vivo operate in such a balanced regime. Synapses modifiable by STDP compete for control of the timing of postsynaptic action potentials. Inputs that fire the postsynaptic neuron with short latency or that act in correlated groups are able to compete most successfully and develop strong synapses, while synapses of longer-latency or less-effective inputs are weakened.
Action Potentials↗
Synaptic plasticity: taming the beast.
Synaptic plasticity provides the basis for most models of learning, memory and development in neural circuits. To generate realistic results, synapse-specific Hebbian forms of plasticity, such as long-term potentiation and depression, must be augmented by global processes that regulate overall levels of neuronal and network activity. Regulatory processes are often as important as the more intensively studied Hebbian processes in determining the consequences of synaptic plasticity for network function. Recent experimental results suggest several novel mechanisms for regulating levels of activity in conjunction with Hebbian synaptic modification. We review three of them-synaptic scaling, spike-timing dependent plasticity and synaptic redistribution-and discuss their functional implications.
Action Potentials↗
Do simple cells in primary visual cortex form a tight frame?
Sets of neuronal tuning curves, which describe the responses of neurons as functions of a stimulus, can serve as a basis for approximating other functions of stimulus parameters. In a function-approximating network, synaptic weights determined by a correlation-based Hebbian rule are closely related to the coefficients that result when a function is expanded in an orthogonal basis. Although neuronal tuning curves typically are not orthogonal functions, the relationship between function approximation and correlation-based synaptic weights can be retained if the tuning curves satisfy the conditions of a tight frame. We examine whether the spatial receptive fields of simple cells in cat and monkey primary visual cortex (V1) form a tight frame, allowing them to serve as a basis for constructing more complicated extrastriate receptive fields using correlation-based synaptic weights. Our calculations show that the set of V1 simple cell receptive fields is not tight enough to account for the acuity observed psychophysically.
Animals↗
Divisive inhibition in recurrent networks.
Models of visual cortex suggest that response selectivity can arise from recurrent networks operating at high gain. However, such networks have a number of problematic features: (i) they operate perilously close to a point of instability, (ii) small changes in synaptic strength can dramatically modify the degree of amplification, and (iii) they respond slowly to rapidly changing stimuli. Divisive inhibition, acting through interneurons that are themselves divisively inhibited, can solve these problems without degrading the selectivity of a recurrent network.
Animals↗
Activity-dependent regulation of potassium currents in an identified neuron of the stomatogastric ganglion of the crab Cancer borealis.
Identified neurons of the stomatogastric ganglion of the crab Cancer borealis were voltage-clamped, and the current densities of three K+ currents were measured. The current densities of each of the three K+ currents varied twofold to fivefold in inferior cardiac (IC) neurons from different animals. Conventionally, this degree of variability has been attributed to experimental artifacts. Instead, we suggest that it reflects a natural variability that may be related to an underlying process of plasticity. First, we found that there is no fixed ratio among the three K+ currents. Second, we found that several hours of stimulation with depolarizing current pulses (0.5 sec duration at 1 Hz) altered the current density of the Ca2+-dependent outward current, IK(Ca), and the transient outward current, IA. This stimulation paradigm mimics the normal pattern of activity for these neurons. The effect of stimulation on the IA current density was eliminated when Ca2+ influx was blocked by extracellular Cd2+. In contrast, the K+ current densities of the lateral pyloric (LP) neuron were unaffected by the same pattern of stimulation, and the currents expressed by both the IC and the LP neurons were insensitive to hyperpolarizing pulses at the same frequency. We conclude that the conductance densities expressed by neurons may vary continually depending on the recent history of electrical activity in the preparation, and that intracellular Ca2+ may play a role in the processes by which activity influences the regulation of current densities in neurons.
Animals↗
Network stability from activity-dependent regulation of neuronal conductances.
Activity-dependent plasticity appears to play an important role in the modification of neurons and neural circuits that occurs during development and learning. Plasticity is also essential for the maintenance of stable patterns of activity in the face of variable environmental and internal conditions. Previous theoretical and experimental results suggest that neurons stabilize their activity by altering the number or characteristics of ion channels to regulate their intrinsic electrical properties. We present both experimental and modeling evidence to show that activity-dependent regulation of conductances, operating at the level of individual neurons, can also stabilize network activity. These results indicate that the stomatogastric ganglion of the crab can generate a characteristic rhythmic pattern of activity in two fundamentally different modes of operation. In one mode, the rhythm is strictly conditional on the presence of neuromodulatory afferents from adjacent ganglia. In the other, it is independent of neuromodulatory input but relies on newly developed intrinsic properties of the component neurons.
Afferent Pathways↗
The effect of correlated variability on the accuracy of a population code.
We study the impact of correlated neuronal firing rate variability on the accuracy with which an encoded quantity can be extracted from a population of neurons. Contrary to widespread belief, correlations in the variabilities of neuronal firing rates do not, in general, limit the increase in coding accuracy provided by using large populations of encoding neurons. Furthermore, in some cases, but not all, correlations improve the accuracy of a population code.
Electrophysiology↗
Pointing the way toward target selection.
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Attention↗
Complex cells as cortically amplified simple cells.
The majority of synapses in primary visual cortex mediate excitation between nearby neurons, yet the role of local recurrent connections in visual processing remains unclear. We propose that these connections are responsible for the spatial-phase invariance of complex-cell responses. In a network model with selective cortical amplification, neurons exhibit simple-cell responses when recurrent connections are weak and complex-cell responses when they are strong, suggesting that simple and complex cells are the low- and high-gain limits of the same basic cortical circuit. Given the ubiquity of invariant responses in cognitive processing, the recurrent mechanism we propose for complex cells may be widely applicable.
Animals↗