Divisive Gain Modulation with Dynamic Stimuli in Integrate-and-Fire Neurons

The modulation of the sensitivity, or gain, of neural responses to input is an important component of neural computation. It has been shown that divisive gain modulation of neural responses can result from a stochastic shunting from balanced (mixed excitation and inhibition) background activity. This gain control scheme was developed and explored with static inputs, where the membrane and spike train statistics were stationary in time. However, input statistics, such as the firing rates of pre-synaptic neurons, are often dynamic, varying on timescales comparable to typical membrane time constants. Using a population density approach for integrate-and-fire neurons with dynamic and temporally rich inputs, we find that the same fluctuation-induced divisive gain modulation is operative for dynamic inputs driving nonequilibrium responses. Moreover, the degree of divisive scaling of the dynamic response is quantitatively the same as the steady-state responses—thus, gain modulation via balanced conductance fluctuations generalizes in a straight-forward way to a dynamic setting.     

Fechner-Benham subjective colors do not induce McCollough after-effects

Fechner-Benham subjective color is widely believed to be governed by local interactions in early (probably retinal) mechanisms. Here we report three lines of phenomenological evidence that suggest otherwise: subjective colors seen in spatially extended stimuli (a) are dependent on global aspects of the stimuli; (b) can become multistable in position; and (c) even after being stabilized do not support the creation of McCollough's colored after-effects--a cortically based phenomenon generally thought to be more central than Fechner-Benham color. These phenomena suggest a central locus that controls perception of subjective color, characterized by pattern dependent interactions among cortical mechanisms that draw their inputs from peripheral units.     

Identifying mechanisms that structure ecological communities by snapping model parameters to empirically observed tradeoffs

Theory predicts that interspecific tradeoffs are primary determinants of coexistence and community composition. Using information from empirically observed tradeoffs to augment the parametrisation of mechanism‐based models should therefore improve model predictions, provided that tradeoffs and mechanisms are chosen correctly. We developed and tested such a model for 35 grassland plant species using monoculture measurements of three species characteristics related to nitrogen uptake and retention, which previous experiments indicate as important at our site. Matching classical theoretical expectations, these characteristics defined a distinct tradeoff surface, and models parameterised with these characteristics closely matched observations from experimental multi‐species mixtures. Importantly, predictions improved significantly when we incorporated information from tradeoffs by ‘snapping’ characteristics to the nearest location on the tradeoff surface, suggesting that the tradeoffs and mechanisms we identify are important determinants of local community structure. This ‘snapping’ method could therefore constitute a broadly applicable test for identifying influential tradeoffs and mechanisms.     

Cell cycle control: many ways to skin a cat

Thirty exponential cell divisions after fertilization would produce the number of cells in a baby mouse, but would not make a mouse. Sophisticated controls govern the cell cycle during development. These controls appear to play a central role in sculpting biological form. Rapid advances in our understanding of the machinery that drives the cell cycle provide a foundation for investigation of the molecular nature of cell cycle control in development. In this article, I emphasize that the design of the cell cycle machinery provides numerous inputs for regulation. I hope that the emphasis I have chosen will avert a tendency towards a narrow perception of cell cycle control.     

Retinal circadian clocks and control of retinal physiology

Retinas of all classes of vertebrates contain endogenous circadian clocks that control many aspects of retinal physiology, including retinal sensitivity to light, neurohormone synthesis, and cellular events such as rod disk shedding, intracellular signaling pathways, and gene expression. The vertebrate retina is an example of a "peripheral" oscillator that is particularly amenable to study because this tissue is well characterized, the relationships between the various cell types are extensively studied, and many local clock-controlled rhythms are known. Although the existence of a photoreceptor clock is well established in several species, emerging data are consistent with multiple or dual oscillators within the retina that interact to control local physiology. A prominent example is the antiphasic regulation of melaton in and dopamine in photoreceptors and inner retina, respectively. This review focuses on the similarities and differences in the molecular mechanisms of the retinal versus the SCN oscillators, as well as on the expression of core components of the circadian clockwork in retina. Finally, the interactions between the retinal clock(s) and the master clock in the SCN are examined.     

Sensory gain control (amplification) as a mechanism of selective attention: electrophysiological and neuroimaging evidence.

Both physiological and behavioral studies have suggested that stimulus-driven neural activity in the sensory pathways can be modulated in amplitude during selective attention. Recordings of event-related brain potentials indicate that such sensory gain control or amplification processes play an important role in visual-spatial attention. Combined event-related brain potential and neuroimaging experiments provide strong evidence that attentional gain control operates at an early stage of visual processing in extrastriate cortical areas. These data support early selection theories of attention and provide a basis for distinguishing between separate mechanisms of attentional suppression (of unattended inputs) and attentional facilitation (of attended inputs).     

Synaptic integration in motoneurons with hyper-excitable dendrites

Motoneurons have extensive dendritic trees that receive the numerous inputs required to produce movement. These dendrites are highly active, containing voltage-sensitive channels that generate persistent inward currents (PICs) that can enhance synaptic input 5-fold or more. However, this enhancement is proportional to the level of activity of monoaminergic inputs from the brainstem that release serotonin and noradrenalin. The higher this activity, the larger the dendritic PIC and the higher the firing rate evoked by a given amount of excitatory synaptic input. This brainstem control of motoneuron input-output gain translates directly into control of system gain of a motor pool and its muscle. Because large dendritic PICs are probably necessary for motoneurons to have sufficient gain to generate large forces, it is possible that descending monoaminergic inputs scale in proportion to voluntary force. Inhibition from sensory inputs has a strong suppressive effect on dendritic PICs: the stronger the inhibition, the smaller the PIC. Thus, local inhibitory inputs within the cord may oppose the descending monoaminergic control of PICs. Most motor behaviors evoke a mixture of excitation and inhibition (e.g., the reciprocal inhibition between antagonists). Therefore, normal joint movements may involve constant adjustment of PIC amplitude.     

Presynaptic cGMP sets synaptic strength in the striatum and is important for motor learning

The striatum is a subcortical brain region responsible for the initiation and termination of voluntary movements. Striatal spiny projection neurons receive major excitatory synaptic input from neocortex and thalamus, and cyclic nucleotides have long been known to play important roles in striatal function. Yet, the precise mechanism of action is unclear. Here, we combine optogenetic stimulation, 2‐photon imaging, and genetically encoded scavengers to dissect the regulation of striatal synapses in mice. Our data show that excitatory striatal inputs are tonically depressed by phosphodiesterases (PDEs), in particular PDE1. Blocking PDE activity boosts presynaptic calcium entry and glutamate release, leading to strongly increased synaptic transmission. Although PDE1 degrades both cAMP and cGMP, we uncover that the concentration of cGMP, not cAMP, controls the gain of striatal inputs. Disturbing this gain control mechanism in vivo impairs motor skill learning in mice. The tight dependence of striatal excitatory synapses on PDE1 and cGMP offers a new perspective on the molecular mechanisms regulating striatal activity.     

A general model of local competition for space

Local competition for space across a wide array of taxa typically involves three mechanisms that we denote here as expansion (spreading into unoccupied habitat), lottery (replacing dead competitors), and overgrowth (encroaching on competitors along zones of contact). By formulating and analysing a simple, general model incorporating these features, we identify ecological conditions and life‐history features that lead to stable coexistence or competitive exclusion (with or without initial‐condition dependence) and gain insight by linking these to case studies in the literature. We demonstrate the importance of contact inhibition, a little‐studied feature of overgrowth, and we show how life‐history tradeoffs may influence and be influenced by local competition for space. The general model we present can help indicate whether local interactions are sufficient to explain patterns of coexistence or exclusion and can serve as the foundation for more specific, realistic models of spatial competition.     

Mechanism of gain modulation at single neuron and network levels

Gain modulation, in which the sensitivity of a neural response to one input is modified by a second input, is studied at single-neuron and network levels. At the single neuron level, gain modulation can arise if the two inputs are subject to a direct multiplicative interaction. Alternatively, these inputs can be summed in a linear manner by the neuron and gain modulation can arise, instead, from a nonlinear input–output relationship. We derive a mathematical constraint that can distinguish these two mechanisms even though they can look very similar, provided sufficient data of the appropriate type are available. Previously, it has been shown in coordinate transformation studies that artificial neurons with sigmoid transfer functions can acquire a nonlinear additive form of gain modulation through learning-driven adjustment of synaptic weights. We use the constraint derived for single-neuron studies to compare responses in this network with those of another network model based on a biologically inspired transfer function that can support approximately multiplicative interactions.     

EEG simulation: variation of spectral envelope, pulse synchrony and ≈40 Hz oscillation

 Macroscopic EEG travelling wave phenomena and cortical pulse synchronisation effects are related within a single simple simulation. Non-specific activation acts to control the transfer function of the simulated cortex, and thus determines the relative amplitude of macroscopic EEG waves generated by rhythmic inputs. When concurrent asynchronous excitatory inputs to separate, local, cortical sites are introduced, the simulation reproduces both gamma-band (40 Hz) electrocorticogram (ECoG) activity and synchronous oscillation of action potential pulse density at the separate sites. The gamma-band ECoG and pulse synchrony effects depend on different mechanisms: the former upon local excitatory/inhibitory interactions, and the latter on cortico-cortical interactions. The pattern of synchronous activity depends upon both structural and dynamic aspects of gain, and is sustained by linearised versions of the simulation’s state equations. Dynamic properties of the simulation, which are independent of scale, describe both microscopic and macroscopic phenomena, all in accord with physiological findings. Received: 25 June 1996 / Accepted in revised form: 29 November 1996     

A neural computation for visual acuity in the presence of eye movements

Humans can distinguish visual stimuli that differ by features the size of only a few photoreceptors. This is possible despite the incessant image motion due to fixational eye movements, which can be many times larger than the features to be distinguished. To perform well, the brain must identify the retinal firing patterns induced by the stimulus while discounting similar patterns caused by spontaneous retinal activity. This is a challenge since the trajectory of the eye movements, and consequently, the stimulus position, are unknown. We derive a decision rule for using retinal spike trains to discriminate between two stimuli, given that their retinal image moves with an unknown random walk trajectory. This algorithm dynamically estimates the probability of the stimulus at different retinal locations, and uses this to modulate the influence of retinal spikes acquired later. Applied to a simple orientation-discrimination task, the algorithm performance is consistent with human acuity, whereas naive strategies that neglect eye movements perform much worse. We then show how a simple, biologically plausible neural network could implement this algorithm using a local, activity-dependent gain and lateral interactions approximately matched to the statistics of eye movements. Finally, we discuss evidence that such a network could be operating in the primary visual cortex.     

New clues to organ size control in plants

Plant growth has unparalleled importance for human civilization, yet we are only starting to gain an understanding of its mechanisms. The growth rate and final size of plant organs is determined by both genetic constraints and environmental factors. Regulatory inputs act at two control points: on proliferation; and on the transition between proliferation and differentiation. Cell-autonomous and short-range growth signals act within meristematic domains, whereas diffusible signals from differentiated parts to proliferating cells provide measures of geometry and size and channel environmental inputs.     

Mechanisms of pathogenesis and the evolution of parasite virulence

When studying how much a parasite harms its host, evolutionary biologists turn to the evolutionary theory of virulence. That theory has been successful in predicting how parasite virulence evolves in response to changes in epidemiological conditions of parasite transmission or to perturbations induced by drug treatments. The evolutionary theory of virulence is, however, nearly silent about the expected differences in virulence between different species of parasite. Why, for example, is anthrax so virulent, whereas closely related bacterial species cause little harm? The evolutionary theory might address such comparisons by analysing differences in tradeoffs between parasite fitness components: transmission as a measure of parasite fecundity, clearance as a measure of parasite lifespan and virulence as another measure that delimits parasite survival within a host. However, even crude quantitative estimates of such tradeoffs remain beyond reach in all but the most controlled of experimental conditions. Here, we argue that the great recent advances in the molecular study of pathogenesis provide a way forward. In light of those mechanistic studies, we analyse the relative sensitivity of tradeoffs between components of parasite fitness. We argue that pathogenic mechanisms that manipulate host immunity or escape from host defences have particularly high sensitivity to parasite fitness and thus dominate as causes of parasite virulence. The high sensitivity of immunomodulation and immune escape arise because those mechanisms affect parasite survival within the host, the most sensitive of fitness components. In our view, relating the sensitivity of pathogenic mechanisms to fitness components will provide a way to build a much richer and more general theory of parasite virulence.     

Shunting inhibition controls the gain modulation mediated by asynchronous neurotransmitter release in early development

The sensitivity of a neuron to its input can be modulated in several ways. Changes in the slope of the neuronal input-output curve depend on factors such as shunting inhibition, background noise, frequency-dependent synaptic excitation, and balanced excitation and inhibition. However, in early development GABAergic interneurons are excitatory and other mechanisms such as asynchronous transmitter release might contribute to regulating neuronal sensitivity. We modeled both phasic and asynchronous synaptic transmission in early development to study the impact of activity-dependent noise and short-term plasticity on the synaptic gain. Asynchronous release decreased or increased the gain depending on the membrane conductance. In the high shunt regime, excitatory input due to asynchronous release was divisive, whereas in the low shunt regime it had a nearly multiplicative effect on the firing rate. In addition, sensitivity to correlated inputs was influenced by shunting and asynchronous release in opposite ways. Thus, asynchronous release can regulate the information flow at synapses and its impact can be flexibly modulated by the membrane conductance.     

Lateral Inhibition in the Human Visual System in Patients with Glaucoma and Healthy Subjects: A Case-Control Study

In glaucoma, the density of retinal ganglion cells is reduced. It is largely unknown how this influences retinal information processing. An increase in spatial summation and a decrease in contrast gain control and contrast adaptation have been reported. A decrease in lateral inhibition might also arise. This could result in a larger than expected response to some stimuli, which could mask ganglion cell loss on functional testing (structure-function discrepancy). The aim of this study was to compare lateral inhibition between glaucoma patients and healthy subjects; we used a case-control design. Cases (n = 18) were selected to have advanced visual field loss in combination with a normal visual acuity. Controls (n = 50) were not allowed to have symptoms or signs of any eye disease. Lateral inhibition was measured psychophysically on a computer screen, with (1) a modified illusory movement experiment and (2) a contrast sensitivity (CS) test. Illusory movement was quantified by nulling it with a real movement; measure of lateral inhibition was the amount of illusory movement. CS was measured at 1 and 4 cycles per degree (cpd); measure of lateral inhibition was the difference between log CS at 4 and 1 cpd. Both measures were compared between cases and controls; analyses were adjusted for age and gender. There was no difference between cases and controls for these two measures of lateral inhibition (p = 0.58 for illusory movement; p = 0.20 for CS). The movement threshold was higher in cases than in controls (p = 0.008) and log CS was lower, at both 1 (-0.20; p = 0.008) and 4 (-0.28; p = 0.001) cpd. Our results indicate that spatially antagonistic mechanisms are not specifically affected in glaucoma, at least not in the intact center of a severely damaged visual field. This suggests that the structure-function discrepancy in glaucoma is not related to a decrease in lateral inhibition.     

Location-dependent excitatory synaptic interactions in pyramidal neuron dendrites

Neocortical pyramidal neurons (PNs) receive thousands of excitatory synaptic contacts on their basal dendrites. Some act as classical driver inputs while others are thought to modulate PN responses based on sensory or behavioral context, but the biophysical mechanisms that mediate classical-contextual interactions in these dendrites remain poorly understood. We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs. distal ends of the basal branches, the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry. Supporting this possibility, we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric. Distal excitation lowers the local spike threshold for more proximal inputs, while having little effect on peak responses at the soma. In contrast, proximal excitation lowers the threshold, but also substantially increases the gain of distally-driven responses. Our findings support the view that PN basal dendrites possess significant analog computing capabilities, and suggest that the diverse forms of nonlinear response modulation seen in the neocortex, including uni-modal, cross-modal, and attentional effects, could depend in part on pathway-specific biases in the spatial distribution of excitatory synaptic contacts onto PN basal dendritic arbors.     

A simple model of retina-LGN transmission

To gain a deeper understanding of the transmission of visual signals from retina through the lateral geniculate nucleus (LGN), we have used a simple leaky integrate and-fire model to simulate a relay cell in the LGN. The simplicity of the model was motivated by two questions: (1) Can an LGN model that is driven by a retinal spike train recorded as synaptic (‘S’) potentials, but does not include a diverse array of ion channels, nor feedback inputs from the cortex, brainstem, and thalamic reticular nucleus, accurately simulate the LGN discharge on a spike-for-spike basis? (2) Are any special synaptic mechanisms, beyond simple summation of currents, necessary to model experimental recordings? We recorded cat relay cell responses to spatially homogeneous small or large spots, with luminance that was rapidly modulated in a pseudo-random fashion. Model parameters for each cell were optimized with a Simplex algorithm using a short segment of the recording. The model was then tested on a much longer, distinct data set consisting of responses to numerous repetitions of the noisy stimulus. For LGN cells that spiked in response to a sufficiently large fraction of retinal inputs, we found that this simplified model accurately predicted the firing times of LGN discharges. This suggests that modulations of the efficacy of the retino-geniculate synapse by pre-synaptic facilitation or depression are not necessary in order to account for the LGN responses generated by our stimuli, and that post-synaptic summation is sufficient.     

Evolution of color vision.

Color vision is achieved by comparing the inputs from retinal photoreceptor neurons that differ in their wavelength sensitivity. Recent studies have elucidated the distribution and phylogeny of opsins, the family of light-sensitive molecules involved in this process. Interesting new findings suggest that animals have evolved a strategy to achieve specific sensitivity through the mutually exclusive expression of different opsin genes in photoreceptors.