Determination of the fraction of active inputs required by a neuron to fire

What fraction of the inputs to a neuron in the primary visual cortex (V1) need to be active for that neuron to reach its firing threshold? The paper describes a numerical method for estimating the selectivity of visual neurons, in terms of the required fraction of active excitatory inputs, from standard data produced by intracellular electro-physiological recordings. The method also provides an estimate of the relative strength of the feedforward inhibition in a push-pull model of the inputs to V1 simple cells. The method is tested on two V1 cells described in Carandini and Ferster [Carandini, M., Ferster, D., 2000. Membrane potential and firing rate in cat primary visual cortex. J. Neurosci. 20, 470-484]. The results indicate that the maximum strength of feedforward inhibition is around 30% of the maximum strength of feedforward excitation. The two V1 neurons investigated fire if more than around 40% of their excitatory LGN inputs are active.     

Multiplication and stimulus invariance in a looming-sensitive neuron.

Multiplicative operations and invariance of neuronal responses are thought to play important roles in the processing of neural information in many sensory systems. Yet the biophysical mechanisms that underlie both multiplication and invariance of neuronal responses in vivo, either at the single cell or at the network level, remain to a large extent unknown. Recent work on an identified neuron in the locust visual system (the LGMD neuron) that responds well to objects looming on a collision course towards the animal suggests that this cell represents a good model to investigate the biophysical basis of multiplication and invariance at the single neuron level. Experimental and theoretical results are consistent with multiplication being implemented by subtraction of two logarithmic terms followed by exponentiation via active membrane conductances, according to a x 1/b = exp(log(a) - log(b)). Invariance appears to be in part due to non-linear integration of synaptic inputs within the dendritic tree of this neuron.     

A look into the cockpit of the developing locust: Looming detectors and predator avoidance

For many animals, the visual detection of looming stimuli is crucial at any stage of their lives. For example, human babies of only 6 days old display evasive responses to looming stimuli (Bower et al. [1971]: Percept Psychophys 9: 193–196). This means the neuronal pathways involved in looming detection should mature early in life. Locusts have been used extensively to examine the neural circuits and mechanisms involved in sensing looming stimuli and triggering visually evoked evasive actions, making them ideal subjects in which to investigate the development of looming sensitivity. Two lobula giant movement detectors (LGMD) neurons have been identified in the lobula region of the locust visual system: the LGMD1 neuron responds selectively to looming stimuli and provides information that contributes to evasive responses such as jumping and emergency glides. The LGMD2 responds to looming stimuli and shares many response properties with the LGMD1. Both neurons have only been described in the adult. In this study, we describe a practical method combining classical staining techniques and 3D neuronal reconstructions that can be used, even in small insects, to reveal detailed anatomy of individual neurons. We have used it to analyze the anatomy of the fan‐shaped dendritic tree of the LGMD1 and the LGMD2 neurons in all stages of the post‐embryonic development of Locusta migratoria. We also analyze changes seen during the ontogeny of escape behaviors triggered by looming stimuli, specially the hiding response. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 74: 1078–1095, 2014     

Collision avoidance and a looming sensitive neuron: size matters but biggest is not necessarily best

Locusts possess visual neurons that can be uniquely identified in each locust and that respond selectively to looming stimuli, giving the animal a warning of impending collision. It has been suggested that one such neuron, the lobula giant movement detector (LGMD), issues this warning by generating a peak in its response that occurs ca. 25 ms after a looming object reaches a subtense of 17 degrees on the eye. This peak is proposed to be a trigger for escape behaviour. We use both modelling and electrophysiological techniques to show that this early peak in LGMD response is not the 'essential functional variable' used naturally by the locust to trigger escape, but rather results from the unnaturally large stimulus used in the previous experimental work. The natural predators of Locusta in Africa, where the locust evolved, are small birds such as the fiscal shrike Lanius collaris humeralis and the carmine bee-eater Merops nubicus, with pectoral diameters of 40-45 mm (measurements from museum specimens). Locusta in flight are less than 100 mm wing tip to wing tip. When a locust views small approaching objects, the response of the LGMD continues to increase throughout the object's approach and the locust is able to trigger escape behaviours without the LGMD response peaking prior to collision.     

Close encounters: how cortical neurons find and connect to their correct synaptic partners depends on the cell type

In this issue of Neuron, Stepanyants et al. embark on quantitative analyses of the axonal and dendritic arbors of cortical neurons. They test whether the paths taken by axons actually bring them closer to their true synaptic partners than they would have gotten by chance encounters based on the same axon trajectories. The results depend on the type of presynaptic neuron. Inhibitory cells take paths that explicitly link them to their actual partners while excitatory axons are as likely to have close encounters with actual partners as with other neurons. These results suggest that the mechanisms for selectivity depend on the type of presynaptic neuron.     

Dynamics of orientation selectivity in the primary visual cortex and the importance of cortical inhibition

To test theories of orientation selectivity in primary visual cortex (V1), we have done experiments to measure the dynamics of orientation tuning of single neurons in the V1 cortex of macaque monkeys. Based on our dynamics results, we propose that a V1 cell's orientation selectivity is generated mainly by both tuned enhancement and global suppression. Enhancement near the preferred orientation is probably caused by feed-forward input from LGN (plus amplification by cortical-cortical interaction). Global suppression could be supplied by cortical inhibition. Additionally, in about 1/3 of V1 neurons (usually the most sharply tuned) there is tuned suppression, centered near the cell's preferred orientation but broader than tuned enhancement. These mechanisms also can explain important features of steady-state selectivity in the V1 neuron population. Furthermore, similar neuronal mechanisms may be used generally throughout the cerebral cortex.     

A multi-stage model for fundamental functional properties in primary visual cortex

Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. We here define a model that accounts for many of the empirical observations concerning direction selectivity. The model describes a single column of cat primary visual cortex and comprises a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small (～4 ms) interval, and it is this difference that confers direction selectivity on model neurons. We show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex.     

Contralateral input modulates the excitability of dorsal horn neurons involved in noxious signal processes. Potential role in neuronal sensitization

Wide Dynamic Range (WDR) neurons in the spinal cord receive inputs from the contralateral side that, under normal conditions, are ineffective in generating an active response. These inputs are effective when the target WDRs change their excitability conditions. To further reveal the mechanisms supporting this effectiveness shift, we investigated the weight of the excitation of the contralateral neurons on the target WDR responses. In the circuit of presynaptic (sending) and postsynaptic (receiving) neurons in crossed spinal connections the fibres that form the presynaptic neurons impinge on postsynaptic neurons can be considered the final relay of this contralateral pathway. The enhancement of the presynaptic neuron excitability may thus modify the efficacy of the contralateral input. Pairs of neurons each on a side of the spinal cord, at the L5-L6 lumbar level were simultaneously recorded in intact, anaesthetized, paralysed rats. The excitatory aminoacid NMDA and strychnine, the antagonist of the inhibitory aminoacid glycine, were iontophoretically administrated to presynaptic neurons to increase their excitability. Before and during the drug administration, spontaneous and noxious-evoked activities of the neurons were analysed. During the iontophoresis of the two substances we found that noxious stimuli applied to the receptive field of presynaptic neurons activated up to 50% of the previously unresponsive postsynaptic neurons on the opposite side. Furthermore, the neurons on both sides of the spinal cord showed significantly increased spontaneous activity and amplified responses to ipsilateral noxious stimulation. These findings indicate that the contralateral input participates in the circuit dynamics of spinal nociceptive transmission, by modulating the excitability of the postsynaptic neurons. A possible functional role of such a nociceptive transmission circuit in neuronal sensitization following unilateral nerve injury is hypothesized.     

Contralateral input modulates the excitability of dorsal horn neurons involved in noxious signal processes. Potential role in neuronal sensitization

Wide Dynamic Range (WDR) neurons in the spinal cord receive inputs from the contralateral side that, under normal conditions, are ineffective in generating an active response. These inputs are effective when the target WDRs change their excitability conditions. To further reveal the mechanisms supporting this effectiveness shift, we investigated the weight of the excitation of the contralateral neurons on the target WDR responses. In the circuit of presynaptic (sending) and postsynaptic (receiving) neurons in crossed spinal connections the fibres that form the presynaptic neurons impinge on postsynaptic neurons can be considered the final relay of this contralateral pathway. The enhancement of the presynaptic neuron excitability may thus modify the efficacy of the contralateral input. Pairs of neurons each on a side of the spinal cord, at the L5–L6 lumbar level were simultaneously recorded in intact, anaesthetized, paralysed rats. The excitatory aminoacid NMDA and strychnine, the antagonist of the inhibitory aminoacid glycine, were iontophoretically administrated to presynaptic neurons to increase their excitability. Before and during the drug administration, spontaneous and noxious-evoked activities of the neurons were analysed. During the iontophoresis of the two substances we found that noxious stimuli applied to the receptive field of presynaptic neurons activated up to 50% of the previously unresponsive postsynaptic neurons on the opposite side. Furthermore, the neurons on both sides of the spinal cord showed significantly increased spontaneous activity and amplified responses to ipsilateral noxious stimulation. These findings indicate that the contralateral input participates in the circuit dynamics of spinal nociceptive transmission, by modulating the excitability of the postsynaptic neurons. A possible functional role of such a nociceptive transmission circuit in neuronal sensitization following unilateral nerve injury is hypothesized.     

Maturation of GABAergic Inhibition Promotes Strengthening of Temporally Coherent Inputs among Convergent Pathways

Spike-timing-dependent plasticity (STDP), a form of Hebbian plasticity, is inherently stabilizing. Whether and how GABAergic inhibition influences STDP is not well understood. Using a model neuron driven by converging inputs modifiable by STDP, we determined that a sufficient level of inhibition was critical to ensure that temporal coherence (correlation among presynaptic spike times) of synaptic inputs, rather than initial strength or number of inputs within a pathway, controlled postsynaptic spike timing. Inhibition exerted this effect by preferentially reducing synaptic efficacy, the ability of inputs to evoke postsynaptic action potentials, of the less coherent inputs. In visual cortical slices, inhibition potently reduced synaptic efficacy at ages during but not before the critical period of ocular dominance (OD) plasticity. Whole-cell recordings revealed that the amplitude of unitary IPSCs from parvalbumin positive (Pv+) interneurons to pyramidal neurons increased during the critical period, while the synaptic decay time-constant decreased. In addition, intrinsic properties of Pv+ interneurons matured, resulting in an increase in instantaneous firing rate. Our results suggest that maturation of inhibition in visual cortex ensures that the temporally coherent inputs (e.g. those from the open eye during monocular deprivation) control postsynaptic spike times of binocular neurons, a prerequisite for Hebbian mechanisms to induce OD plasticity.     

Responses of descending neurons to looming stimuli in the praying mantis <Emphasis Type="Italic">Tenodera aridifolia</Emphasis>

Responses to visual stimuli of some neurons that descend the nerve cord from the brain were recorded extracellularly in the mantis Tenodera aridifolia. Most of the recorded neurons showed their largest responses to looming stimuli that simulated a black circle approaching towards the mantis. The neurons showed a transient excitatory response to a gradually darkening or receding circle. The neurons showed sustained excitation to the linearly expanding stimuli, but the spike frequency decreased rapidly. The responses of the neurons were affected by both the diameter and the speed of looming stimuli. Faster or smaller looming stimuli elicited a higher peak frequency. These responses were observed in both recordings from the connective between suboesophageal and prothoracic ganglia and the connective between prothoracic and mesothoracic ganglia. There was a one-to-one correspondence of spike firing between these two recordings with a fixed delay. The neurons had the receptive field on ipsilateral side to its axon at the cervical connective. These results suggest that there is a looming-sensitive descending neuron, with an axon projecting over prothoracic ganglion, in the mantis nervous system.     

Modeling convergent ON and OFF pathways in the early visual system

For understanding the computation and function of single neurons in sensory systems, one needs to investigate how sensory stimuli are related to a neuron’s response and which biological mechanisms underlie this relationship. Mathematical models of the stimulus–response relationship have proved very useful in approaching these issues in a systematic, quantitative way. A starting point for many such analyses has been provided by phenomenological “linear–nonlinear” (LN) models, which comprise a linear filter followed by a static nonlinear transformation. The linear filter is often associated with the neuron’s receptive field. However, the structure of the receptive field is generally a result of inputs from many presynaptic neurons, which may form parallel signal processing pathways. In the retina, for example, certain ganglion cells receive excitatory inputs from ON-type as well as OFF-type bipolar cells. Recent experiments have shown that the convergence of these pathways leads to intriguing response characteristics that cannot be captured by a single linear filter. One approach to adjust the LN model to the biological circuit structure is to use multiple parallel filters that capture ON and OFF bipolar inputs. Here, we review these new developments in modeling neuronal responses in the early visual system and provide details about one particular technique for obtaining the required sets of parallel filters from experimental data.     

A neuronal network model of primary visual cortex explains spatial frequency selectivity

We address how spatial frequency selectivity arises in Macaque primary visual cortex (V1) by simulating V1 with a large-scale network model consisting of O(10⁴) excitatory and inhibitory integrate-and-fire neurons with realistic synaptic conductances. The new model introduces variability of the widths of subregions in V1 neuron receptive fields. As a consequence different model V1 neurons prefer different spatial frequencies. The model cortex has distributions of spatial frequency selectivity and of preference that resemble experimental findings from the real V1. Two main sources of spatial frequency selectivity in the model are the spatial arrangement of feedforward excitation, and cortical nonlinear suppression, a result of cortical inhibition. Action Editor: Jonathan D. Victor     

Sharpening of directional selectivity from neural output of rabbit retina

The estimation of motion direction from time varying retinal images is a fundamental task of visual systems. Neurons that selectively respond to directional visual motion are found in almost all species. In many of them already in the retina direction selective neurons signal their preferred direction of movement. Scientific evidences suggest that direction selectivity is carried from the retina to higher brain areas. Here we adopt a simple integrate-and-fire neuron model, inspired by recent work of Casti et al. (2008), to investigate how directional selectivity changes in cells postsynaptic to directional selective retinal ganglion cells (DSRGC). Our model analysis shows that directional selectivity in the postsynaptic cells increases over a wide parameter range. The degree of directional selectivity positively correlates with the probability of burst-like firing of presynaptic DSRGCs. Postsynaptic potentials summation and spike threshold act together as a temporal filter upon the input spike train. Prior to the intricacy of neural circuitry between retina and higher brain areas, we suggest that sharpening is a straightforward result of the intrinsic spiking pattern of the DSRGCs combined with the summation of excitatory postsynaptic potentials and the spike threshold in postsynaptic neurons.     

Identifying and Tracking Simulated Synaptic Inputs from Neuronal Firing: Insights from In Vitro Experiments

Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes.     

The chandelier neuron in schizophrenia

Markers of GABA neurotransmission between chandelier neurons and their synaptic targets, the axon initial segment (AIS) of pyramidal neurons, are altered in the dorsolateral prefrontal cortex (DLPFC) of subjects with schizophrenia. For example, immunoreactivity for the GABA membrane transporter (GAT1) is decreased in presynaptic chandelier neuron axon terminals, whereas immunoreactivity for the GABA(A) receptor α2 subunit is increased in postsynaptic AIS. These alterations are most marked in cortical layers 2-3. In addition, other determinants of the function of chandelier cell-pyramidal neuron synapses, such as ankyrin-G (which regulates the recruitment of sodium channels to the AIS), are also selectively altered in superficial layer pyramidal neurons in subjects with schizophrenia. Each of these components of chandelier cell-pyramidal neuron connectivity exhibits distinctive developmental trajectories in the primate DLPFC, suggesting that disturbances in these trajectories could contribute to the pathogenesis of schizophrenia. Recent findings that inputs from neocortical chandelier neurons are excitatory provide new ideas about the role of this circuitry in the pathophysiology of cortical dysfunction in schizophrenia.     

Functional multimodality of axonal tree in invertebrate neurons.

This review, based on invertebrate neuron examples, aims at highlighting the functional consequences of axonal tree organization. The axonal organization of invertebrate neurons is very complex both morphologically and physiologically. The first part shows how the transfer of information along sensory axons is modified by presynaptic inhibition mechanisms. In primary afferents, presynaptic inhibition is involved in: 1) increasing the dynamic range of the sensory response; 2) processing the sensory information such as increasing spatial and/or temporal selectivity; 3) discriminating environmental information from sensory activities generated by the animal's own movement; and 4) modulating the gain of negative feedback (resistance reflex) during active rhythmic movements such as locomotion. In a second part, the whole organization of other types of neurons is considered, and evidence is given that a neuron may not work as a unit, but rather as a mosaic of disconnected 'integrate-and-fire' units. Examples of invertebrate neurons are presented in which several spike initiating zones exist, such as in some stomatogastric neurons. The separation of a neuron into two functionally distinct entities may be almost total with distinct arborizations existing in different ganglia. However, this functional separation is not definitive and depends on the state of the neuron. In conclusion, the classical integrate-and-fire representation of the neuron, with its dendritic arborization, its spike initiating zone, its axon and axonal tree seems to be no more applicable to invertebrate neurons. A better knowledge of the function of vertebrate neurons would probably demonstrate that it is the case for a large number of them, as suggested by the complex architecture of some reticular interneurons in vertebrates.     

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1’s function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.