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Edge detection is one of the most basic stages of image processing and have been used in many areas. Its purpose is to determine the pixels formed the objects. Many researchers have aimed to determine objects' edges correctly, like as they are determined by the human eye. In this study, a new edge detection technique based on spiking neural network is proposed. The proposed model has a different receptor structure than the ones found in literature and also does not use gray level values of the pixels in the receptive field directly. Instead, it takes the gray level differences between the pixel in the center of the receptive field and others as input. The model is tested by using BSDS train dataset. Besides, the obtained results are compared with the results calculated by Canny edge detection method. [ABSTRACT FROM AUTHOR]

The two paralogs of the calcium-dependent activator protein for secretion (CAPS) are priming factors for synaptic vesicles (SVs) and neuropeptide containing large dense-core vesicles (LDCVs). Yet, it is unclear whether CAPS1 and CAPS2 regulate exocytosis of these two vesicle types differentially in dorsal root ganglion (DRG) neurons, wherein synaptic transmission and neuropeptide release are of equal importance. These sensory neurons transfer information from the periphery to the spinal cord (SC), releasing glutamate as the primary neurotransmitter, with co-transmission via neuropeptides in a subset of so called peptidergic neurons. Neuropeptides are key components of the information-processing machinery of pain perception and neuropathic pain generation. Here, we compared the ability of CAPS1 and CAPS2 to support priming of both vesicle types in single and double knock-out mouse (DRG) neurons using a variety of high-resolution live cell imaging methods. While CAPS1 was localized to synapses of all DRG neurons and promoted synaptic transmission, CAPS2 was found exclusively in peptidergic neurons and mediated LDCV exocytosis. Intriguingly, ectopic expression of CAPS2 empowered non-peptidergic neurons to drive LDCV fusion, thereby identifying CAPS2 as an essential molecular determinant for peptidergic signaling. Our results reveal that these distinct functions of both CAPS paralogs are based on their differential subcellular localization in DRG neurons. Our data suggest a major role for CAPS2 in neuropathic pain via control of neuropeptide release. [ABSTRACT FROM AUTHOR]

The neurophysiological mechanisms underlying the central processing of incoming visual information is still a fundamental problem in the visual neuroscience. The response patterns of visually sensitive neurons in extrastriate area 21a of the cat cortex to the stationary and moving visual stimuli were studied in detail. The results of experiments show significant modulations of neuronal response patterns at the introduction of a moving visual stimulus, which could not be explained by the neuron receptive field (RF) stationary structure. The results of presented experiments have shown that neurons having homogenous stationary RFs structure may reveal multimodal patterns of responses to moving visual stimuli and such response profiles could be evoked from the isolated RF subfields too. Thus, with great probability, mutual interactions among simultaneously activated neighbouring neuron networks become to be of great importance in central processing of visual information, concerning the precise diversification and perception of visual images. [ABSTRACT FROM AUTHOR]

The cat perigeniculate nucleus (PGN) is a visual sector of the thalamic reticular nucleus that consists of GABAergic neurons. It receives excitatory axon-collateral input from relay neurons of the dorsal lateral geniculate nucleus (LGN) to which it provides inhibitory input. Thus, it is usually argued that the PGN works as feedback inhibition to the LGN. At the single neuron level, however, this circuit can also provide lateral inhibition. Which inhibition dominates in the visual circuit of the thalamus has yet to be well characterized. In this study, we conducted cross-correlation analysis of single spike trains simultaneously recorded from PGN and LGN neurons in anesthetized cats. For 12 pairs of functionally connected PGN and LGN neurons with overlapped receptive fields (RF), we quantitatively compared RF properties including the spatial frequency (SF) and temporal frequency (TF) tunings of each neuron. We found the SF and TF tunings of PGN neurons and LGN neurons were similar when there was only excitatory input from the LGN neuron to the PGN neuron, but different when the PGN neuron returned inhibitory inputs back, suggesting the circuit between PGN and LGN neurons works as lateral inhibition for these properties. [ABSTRACT FROM AUTHOR]

First-order tactile neurons have spatially complex receptive fields. Here we use machine-learning tools to show that such complexity arises for a wide range of training sets and network architectures. Moreover, we demonstrate that this complexity benefits network performance, especially on more difficult tasks and in the presence of noise. Our work suggests that spatially complex receptive fields are normatively good given the biological constraints of the tactile periphery. [ABSTRACT FROM AUTHOR]

Primates sample their visual environment actively through saccades and microsaccades (MSs). Saccadic eye movements not only modulate neural spike rates but might also affect temporal correlations (synchrony) among neurons. Neural synchrony plays a role in neural coding and modulates information transfer between cortical areas. The question arises of how eye movements shape neural synchrony within and across cortical areas and how it affects visual processing. Through local field recordings in macaque early visual cortex while monitoring eye position and through neural network simulations, we find 2 distinct synchrony regimes in early visual cortex that are embedded in a 3- to 4-Hz MS-related rhythm during visual fixation. In the period shortly after an MS (“transient period”), synchrony was high within and between cortical areas. In the subsequent period (“sustained period”), overall synchrony dropped and became selective to stimulus properties. Only mutually connected neurons with similar stimulus responses exhibited sustained narrow-band gamma synchrony (25–80 Hz), both within and across cortical areas. Recordings in macaque V1 and V2 matched the model predictions. Furthermore, our modeling provides predictions on how (micro)saccade-modulated gamma synchrony in V1 shapes V2 receptive fields (RFs). We suggest that the rhythmic alternation between synchronization regimes represents a basic repeating sampling strategy of the visual system. [ABSTRACT FROM AUTHOR]

Our eyes move constantly at a frequency of 3-5 times per second. These movements, called saccades, induce the sweeping of visual images on the retina, yet we perceive the world as stable. It has been suggested that the brain achieves this visual stability via predictive remapping of neuronal receptive field (RF). A recent experimental study disclosed details of this remapping process in the lateral intraparietal area (LIP), that is, about the time of the saccade, the neuronal RF expands along the saccadic trajectory temporally, covering the current RF (CRF), the future RF (FRF) and the region the eye will sweep through during the saccade. A cortical wave (CW) model was also proposed, which attributes the RF remapping as a consequence of neural activity propagating in the cortex, triggered jointly by a visual stimulus and the corollary discharge (CD) signal responsible for the saccade. In this study, we investigate how this CW model is learned naturally from visual experiences at the development of the brain. We build a two-layer network, with one layer consisting of LIP neurons and the other superior colliculus (SC) neurons. Initially, neuronal connections are random and non-selective. A saccade will cause a static visual image to sweep through the retina passively, creating the effect of the visual stimulus moving in the opposite direction of the saccade. According to the spiking-time-dependent-plasticity rule, the connection path in the opposite direction of the saccade between LIP neurons and the connection path fromSC to LIP are enhanced. Over many such visual experiences, the CW model is developed, which generates the peri-saccadic RF remapping in LIP as observed in the experiment. [ABSTRACT FROM AUTHOR]

The signal transformations that take place in high-level sensory regions of the brain remain enigmatic because of the many nonlinear transformations that separate responses of these neurons from the input stimuli. One would like to have dimensionality reduction methods that can describe responses of such neurons in terms of operations on a large but still manageable set of relevant input features. A number of methods have been developed for this purpose, but often these methods rely on the expansion of the input space to capture as many relevant stimulus components as statistically possible. This expansion leads to a lower effective sampling thereby reducing the accuracy of the estimated components. Alternatively, so-called low-rank methods explicitly search for a small number of components in the hope of achieving higher estimation accuracy. Even with these methods, however, noise in the neural responses can force the models to estimate more components than necessary, again reducing the methods' accuracy. Here we describe how a flexible regularization procedure, together with an explicit rank constraint, can strongly improve the estimation accuracy compared to previous methods suitable for characterizing neural responses to natural stimuli. Applying the proposed low-rank method to responses of auditory neurons in the songbird brain, we find multiple relevant components making up the receptive field for each neuron and characterize their computations in terms of logical OR and AND computations. The results highlight potential differences in how invariances are constructed in visual and auditory systems. [ABSTRACT FROM AUTHOR]

Summary Little is known about the internal circuitry of the primate lateral intraparietal area (LIP). During two versions of a delayed-saccade task, we found radically different network dynamics beneath similar population average firing patterns. When neurons are not influenced by stimuli outside their receptive fields (RFs), dynamics of the high-dimensional LIP network during slowly varying activity lie predominantly in one multi-neuronal dimension, as described previously. However, when activity is suppressed by stimuli outside the RF, slow LIP dynamics markedly deviate from a single dimension. The conflicting results can be reconciled if two LIP local networks, each underlying an RF location and dominated by a single multi-neuronal activity pattern, are suppressively coupled to each other. These results demonstrate the low dimensionality of slow LIP local dynamics, and suggest that LIP local networks encoding the attentional and movement priority of competing visual locations actively suppress one another. [ABSTRACT FROM AUTHOR]

High-level neurons processing complex, behaviorally relevant signals are sensitive to conjunctions of features. Characterizing the receptive fields of such neurons is difficult with standard statistical tools, however, and the principles governing their organization remain poorly understood. Here, we demonstrate multiple distinct receptivefield features in individual high-level auditory neurons in a songbird, European starling, in response to natural vocal signals (songs). We then show that receptive fields with similar characteristics can be reproduced by an unsupervised neural network trained to represent starling songs with a single learning rule that enforces sparseness and divisive normalization. We conclude that central auditory neurons have composite receptive fields that can arise through a combination of sparseness and normalization in neural circuits. Our results, along with descriptions of random, discontinuous receptive fields in the central olfactory neurons in mammals and insects, suggest general principles of neural computation across sensory systems and animal classes. [ABSTRACT FROM AUTHOR]

Theoretical arguments demonstrate that practical considerations, including the needs to limit physiological resources and to learn without interference with prior learning, severely constrain the anatomical architecture of the brain. These arguments identify the hippocampal system as the change manager for the cortex, with the role of selecting the most appropriate locations for cortical receptive field changes at each point in time and driving those changes. This role results in the hippocampal system recording the identities of groups of cortical receptive fields that changed at the same time. These types of records can also be used to reactivate the receptive fields active during individual unique past events, providing mechanisms for episodic memory retrieval. Our theoretical arguments identify the perirhinal cortex as one important focal point both for driving changes and for recording and retrieving episodic memories. The retrieval of episodic memories must not drive unnecessary receptive field changes, and this consideration places strong constraints on neuron properties and connectivity within and between the perirhinal cortex and regular cortex. Hence the model predicts a number of such properties and connectivity. Experimental test of these falsifiable predictions would clarify how change is managed in the cortex and how episodic memories are retrieved. [ABSTRACT FROM AUTHOR]

Neurons that respond to visual targets in a hand-centered frame of reference have been found within various areas of the primate brain. We investigate how hand-centered visual representations may develop in a neural network model of the primate visual system called VisNet, when the model is trained on images of the hand seen against natural visual scenes. The simulations show how such neurons may develop through a biologically plausible process of unsupervised competitive learning and self-organization. In an advance on our previous work, the visual scenes consisted of multiple targets presented simultaneously with respect to the hand. Three experiments are presented. First, VisNet was trained with computerized images consisting of a realistic image of a hand and a variety of natural objects, presented in different textured backgrounds during training. The network was then tested with just one textured object near the hand in order to verify if the output cells were capable of building hand-centered representations with a single localized receptive field. We explain the underlying principles of the statistical decoupling that allows the output cells of the network to develop single localized receptive fields even when the network is trained with multiple objects. In a second simulation we examined how some of the cells with hand-centered receptive fields decreased their shape selectivity and started responding to a localized region of hand-centered space as the number of objects presented in overlapping locations during training increases. Lastly, we explored the same learning principles training the network with natural visual scenes collected by volunteers. These results provide an important step in showing how single, localized, hand-centered receptive fields could emerge under more ecologically realistic visual training conditions. [ABSTRACT FROM AUTHOR]

Climbing fiber receptive fields are a physiological marker that have proven useful to delineate the details of the olivocerebellar circuitry. They have also proven useful as a point of reference to delineate the organization of other parts of the cerebellar circuitry. But what does the location of the climbing fiber receptive field imply and what is its relation to the presumed role of the cerebellum in coordination? Can we expect that all climbing fibers have a peripheral receptive field on the skin? In this short review, we aim to cover these issues. [ABSTRACT FROM AUTHOR]

In many insect species, photoreceptors of a small dorsal rim area of the eye are specialized for sensitivity to the oscillation plane of polarized skylight and, thus, serve a role in sky compass orientation. To further understand peripheral mechanisms of polarized-light processing in the optic lobe, we have studied the projections of photoreceptors and their receptive fields in the main eye and dorsal rim area of the desert locust, a model system for polarization vision analysis. In both eye regions, one photoreceptor per ommatidium, R7, has a long visual fiber projecting through the lamina to the medulla. Axonal fibers from R7 receptors of the dorsal rim area have short side branches throughout the depth of the dorsal lamina and maintain retinotopic projections to the dorsal medulla following the first optic chiasma. Receptive fields of dorsal rim photoreceptors are considerably larger (average acceptance angle 33°) than those of the main eye (average acceptance angle 2.04°) and, taken together, cover almost the entire sky. The data challenge previous reports of two long visual fibers per ommatidium in the main eye of the locust and provide data for future analysis of peripheral networks underlying polarization opponency in the locust brain. [ABSTRACT FROM AUTHOR]

The responses of neurons in primary visual cortex (V1) to stimulation of their receptive field (RF) are modulated by stimuli in the RF surround. This modulation is suppressive when the stimuli in the RF and surround are of similar orientation, but less suppressive or facilitatory when they are cross-oriented. Similarly, in human vision surround stimuli selectively suppress the perceived contrast of a central stimulus. Although the properties of surround modulation have been thoroughly characterized in many species, cortical areas and sensory modalities, its role in perception remains unknown. Here we argue that surround modulation in V1 consists of multiple components having different spatio-temporal and tuning properties, generated by different neural circuits and serving different visual functions. One component arises from LGN afferents, is fast, untuned for orientation, and spatially restricted to the surround region nearest to the RF (the near-surround); its function is to normalize V1 cell responses to local contrast. Intra-V1 horizontal connections contribute a slower, narrowly orientation-tuned component to near-surround modulation, whose function is to increase the coding efficiency of natural images in manner that leads to the extraction of object boundaries. The third component is generated by topdown feedback connections to V1, is fast, broadly orientation-tuned, and extends into the far-surround; its function is to enhance the salience of behaviorally relevant visual features. Far- and near-surround modulation, thus, act as parallel mechanisms: the former quickly detects and guides saccades/attention to salient visual scene locations, the latter segments object boundaries in the scene. [ABSTRACT FROM AUTHOR]

A recent model of intrinsic plasticity coupled to Hebbian synaptic plasticity proposes that adaptation of a neuron's threshold and gain in a sigmoidal response function to achieve a sparse, exponential output firing rate distribution facilitates the discovery of heavy-tailed or supergaussian sources in the neuron's inputs. We show that the exponential output distribution is irrelevant to these dynamics and that, furthermore, while sparseness is sufficient, it is not necessary. The intrinsic plasticity mechanism drives the neuron's threshold large and positive, and we prove that in such a regime, the neuron will find supergaussian sources; equally, however, if the threshold is large and negative (an antisparse regime), it will also find supergaussian sources. Away from such extremes, the neuron can also discover subgaussian sources. By examining a neuron with a fixed sigmoidal nonlinearity and considering the synaptic strength fixed-point structure in the two-dimensional parameter space defined by the neuron's threshold and gain, we show that this space is carved up into sub- and supergaussian-input-finding regimes, possibly with regimes of simultaneous stability of sub- and supergaussian sources or regimes of instability of all sources; a single gaussian source may also be stabilized by the presence of a nongaussian source. A neuron's operating point (essentially its threshold and gain coupled with its input statistics) therefore critically determines its computational repertoire. Intrinsic plasticity mechanisms induce trajectories in this parameter space but do not fundamentally modify it. Unless the trajectories cross critical boundaries in this space, intrinsic plasticity is irrelevant and the neuron's nonlinearity may be frozen with identical receptive field refinement dynamics. [ABSTRACT FROM AUTHOR]

In the primary visual cortex ( V1), the spike synchronization seen in neuron pairs with non-overlapping receptive fields can be explained by similarities in their preferred orientation ( PO). However, this is not true for pairs with overlapping receptive fields, as they can still exhibit spike synchronization even if their POs are only weakly correlated. Here, we investigated the relationship between spike synchronization and suppressive modulation derived from classical receptive-field surround (surround suppression). We found that layer 4 and layer 2/3 pairs exhibited mainly asymmetric spike synchronization that had non-zero time-lags and was dependent on both the similarity of the PO and the strength of surround suppression. In contrast, layer 2/3 and layer 2/3 pairs showed mainly symmetric spike synchronization that had zero time-lag and was dependent on the similarity of the strength of surround suppression but not on the similarity in POs. From these results, we propose that in cat V1 there exists a functional network that mainly depends on the similarity in surround suppression, and that in layer 2/3 neurons the network maintains surround suppression that is primarily inherited from layer 4 neurons. [ABSTRACT FROM AUTHOR]

Summary: It is widely assumed that mosaics of retinal ganglion cells establish the optimal representation of visual space. However, relay cells in the visual thalamus often receive convergent input from several retinal afferents and, in cat, outnumber ganglion cells. To explore how the thalamus transforms the retinal image, we built a model of the retinothalamic circuit using experimental data and simple wiring rules. The model shows how the thalamus might form a resampled map of visual space with the potential to facilitate detection of stimulus position in the presence of sensor noise. Bayesian decoding conducted with the model provides support for this scenario. Despite its benefits, however, resampling introduces image blur, thus impairing edge perception. Whole-cell recordings obtained in vivo suggest that this problem is mitigated by arrangements of excitation and inhibition within the receptive field that effectively boost contrast borders, much like strategies used in digital image processing. [Copyright &y& Elsevier]

We introduce a novel approach for a complete functional identification of biophysical spike-processing neural circuits. The circuits considered accept multidimensional spike trains as their input and comprise a multitude of temporal receptive fields and conductance-based models of action potential generation. Each temporal receptive field describes the spatio temporal contribution of all synapses between any two neurons and incorporates the (passive) processing carried out by the dendritic tree. The aggregate dendritic current produced by a multitude of temporal receptive fields is encoded into a sequence of action potentials by a spike generator modeled as a nonlinear dynamical system. Our approach builds on the observation that during any experiment, an entire neural circuit, including its receptive fields and biophysical spike generators, is projected onto the space of stimuli used to identify the circuit. Employing the reproducing kernel Hilbert space (RKHS) of trigonometric polynomials to describe input stimuli, we quantitatively describe the relationship between underlying circuit parameters and their projections. We also derive experimental conditions under which these projections converge to the true parameters. In doing so, we achieve the mathematical tractability needed to characterize the biophysical spike generator and identify the multitude of receptive fields. The algorithms obviate the need to repeat experiments in order to compute the neurons' rate of response, rendering our methodology of interest to both experimental and theoretical neuroscientists. [ABSTRACT FROM AUTHOR]

As the desire for biologically realistic spiking neural networks (SNNs) increases, tuning the enormous number of open parameters in these models becomes a difficult challenge. SNNs have been used to successfully model complex neural circuits that explore various neural phenomena such as neural plasticity, vision systems, auditory systems, neural oscillations, and many other important topics of neural function. Additionally, SNNs are particularly well-adapted to run on neuromorphic hardware that will support biological brain-scale architectures. Although the inclusion of realistic plasticity equations, neural dynamics, and recurrent topologies has increased the descriptive power of SNNs, it has also made the task of tuning these biologically realistic SNNs difficult. To meet this challenge, we present an automated parameter tuning framework capable of tuning SNNs quickly and efficiently using evolutionary algorithms (EA) and inexpensive, readily accessible graphics processing units (GPUs). A sample SNN with 4104 neurons was tuned to give V1 simple cell-like tuning curve responses and produce self-organizing receptive fields (SORFs) when presented with a random sequence of counterphase sinusoidal grating stimuli. A performance analysis comparing the GPU-accelerated implementation to a single-threaded central processing unit (CPU) implementation was carried out and showed a speedup of 65× of the GPU implementation over the CPU implementation, or 0.35 h per generation for GPU vs. 23.5 h per generation for CPU. Additionally, the parameter value solutions found in the tuned SNN were studied and found to be stable and repeatable. The automated parameter tuning framework presented here will be of use to both the computational neuroscience and neuromorphic engineering communities, making the process of constructing and tuning large-scale SNNs much quicker and easier. [ABSTRACT FROM AUTHOR]

Many mossy fiber pathways to the neurons of the deep cerebellar nucleus (DCN) originate from the spinal motor circuitry. For cutaneously activated spinal neurons, the receptive field is a tag indicating the specific motor function the spinal neuron has. Similarly, the climbing fiber receptive field of the DCN neuron reflects the specific motor output function of the DCN neuron. To explore the relationship between the motor information the DCN neuron receives and the output it issues, we made patch clamp recordings of DCN cell responses to tactile skin stimulation in the forelimb region of the anterior interposed nucleus in vivo. The excitatory responses were organized according to a general principle, in which the DCN cell responses became stronger the closer the skin site was located to its climbing fiber receptive field. The findings represent a novel functional principle of cerebellar connectivity, with crucial importance for our understanding of the function of the cerebellum in movement coordination. [ABSTRACT FROM AUTHOR]

Tree shrew primary visual cortex (VI) exhibits a pronounced laminar segregation of inputs from different classes of relay neurons in the lateral geniculate nucleus (LGN). We examined how several receptive field (RF) properties were transformed from LGN to VI layer 4 to VI layer 2/3. The progression of RF properties across these stages differed markedly from that found in the cat. VI layer 4 cells are largely similar to the the LGN cells that provide their input, being dominated by a single sign (ON or OFF) and being strongly modulated by sinusoidal gratings. Some layer 4 neurons, notably those near the edges of layer 4, exhibited increased orientation selectivity, and most layer 4 neurons exhibited a preference for lower temporal frequencies. Neurons in cortical layer 2/3 differ significantly from those in the LGN; most exhibited strong orientation tuning and both ON and OFF responses. The strength of orientation selectivity exhibited a notable sublaminar organization, with the strongest orientation tuned neurons in the most superficial parts of layer 2/3. Modulation indexes provide evidence for simple and complex cells in both layer 4 and layer 2/3. However, neurons with high modulation indexes were heterogenous in the spatial organization of ON and OFF responses, with many of them exhibiting unbalanced ON and OFF responses rather than well-segregated ON and OFF subunits. When compared to the laminar organization of VI in other mammals, these data show that the process of natural selection can result in significantly altered structure/function relationships in homologous cortical circuits. [ABSTRACT FROM AUTHOR]

In many animals, a fast and reliable circuit for discriminating between predator-sized objects and edible (prey-sized) objects is necessary for survival. How are receptive fields (RFs) in visual brain areas organized to extract information about size? Recent studies from the zebrafish optic tectum and the mouse visual cortex suggest de novo shaping of RFs by subtypes of inhibitory neurons. Del Bene etal. (2010) describe a population of GABAergic neurons in the zebrafish optic tectum (superficial interneurons, SINs) that are necessary for size filtering during prey capture. Adesnik etal. (2012) describe a somatostatin-expressing interneuron population (SOMs) that confers surround suppression on layer II/III pyramidal cells in mouse V1. Strikingly both the SINs and the SOMs, display size-dependent response properties. Increasing visual stimulus size increases excitatory input to these neurons. Dampening SIN or SOM activity alters tuning of neighboring circuits such that they lose preference for small objects. Both results provide exciting evidence for mechanisms of size filtering in visual circuits. Here we review the roles of the SINs and the SOMs and speculate on the similarity of such spatial filters across species. [ABSTRACT FROM AUTHOR]

Neurons in primary visual cortex, V1, very often have extraclassical receptive fields (eCRFs). The eCRF is defined as the region of visual space where stimuli cannot elicit a spiking response but can modulate the response of a stimulus in the classical receptive field (CRF). We investigated the dependence of the eCRF on stimulus contrast and orientation in macaque V1 cells for which the laminar location was determined. The eCRF was more sensitive to contrast than the CRF across the whole population of V1 cells with the greatest contrast differential in layer 2/3. We confirmed that many V1 cells experience stronger suppression for collinear than orthogonal stimuli in the eCRF. Laminar analysis revealed that the predominant bias for collinear suppression was found in layers 2/3 and 4b. The laminar pattern of contrast and orientation dependence suggests that eCRF suppression may derive from different neural circuits in different layers, and may be comprised of two distinct components: orientation-tuned and untuned suppression. On average tuned suppression was delayed by ∼25 ms compared with the onset of untuned suppression. Therefore, response modulation by the eCRF develops dynamically and rapidly in time. [ABSTRACT FROM AUTHOR]

Abstract: The broad region outside the classical receptive field (CRF) of a vision neuron, known as the non-classical receptive field (nCRF), exerts a robust modulatory effect on the responses to visual stimuli presented within the CRF, and plays an important role in visual information processing. One possible role for the nCRF is the extract object contours from disorderly background textures. In this study, a multi-scale integration based contour extraction model, inspired by the inhibitory and disinhibitory interactions between the CRF and the nCRF is presented. Unlike previous models, our model not only includes both the simple and complex cell mechanisms but also introduces pre-processing of the external information by the retinal ganglion cells at an early stage. The multi-scale representation of a physical scene acquired through such pre-processing was filtered through Gabor filters, and then inhibited or disinhibited at different spatial locations on different scales until a final response was obtained. Our results show that by introducing this kind of mechanism into the model, numbers of non-meaningful texture elements can be removed significantly, while at the same time, the object contours can be detected effectively. In addition to the superior contour detection performance in comparison to other contour detection models, our model provides a better understanding of the role of the nCRF and a novel approach for computer vision and pattern recognition. [Copyright &y& Elsevier]

Local field potentials (LFPs) recorded in the auditory cortex of mammals are known to reveal weakly selective and often multimodal spectrotemporal receptive fields in contrast to spiking activity. This may in part reflect the wider “listening sphere” of LFPs relative to spikes due to the greater current spread at low than high frequencies. We recorded LFPs and spikes from auditory cortex of guinea pigs using 16-channel electrode arrays. LFPs were processed by a component analysis technique that produces optimally tuned linear combinations of electrode signals. Linear combinations of LFPs were found to have sharply tuned responses, closer to spike-related tuning. The existence of a sharply tuned component implies that a cortical neuron (or group of neurons) capable of forming a linear combination of its inputs has access to that information. Linear combinations of signals from electrode arrays reveal information latent in the subspace spanned by multichannel LFP recordings and are justified by the fact that the observations themselves are linear combinations of neural sources. [ABSTRACT FROM AUTHOR]

Neural activity plays an important role in development and maturation of visual circuits in the brain. Activity can be instructive in refining visual projections by directly mediating formation and elimination of specific synaptic contacts through competition-based mechanisms. Alternatively, activity could be permissive-regulating production of factors that create a favorable environment for circuit refinement. Here we used the Xenopus laevL· tadpole visual system to test whether activity is instructive or permissive for shaping development of the retinotectal circuit. In vivo spike output was dampened in a small subgroup of tectal neurons, starting from developmental stages 44-46, by overexpressing Shaker-like Xenopus Kv1.1 potassium channels using electroporation. Tadpoles were then reared until stage 49, a time period when significant refinement of the retinotectal map occurs. Kv1.1-expressing neurons had significantly decreased spike output in response to both current injection and visual stimuli compared to untransfected controls, with spiking occurring during a more limited time interval. We found that Kv1.1-expressing neurons had larger visual receptive fields, decreased receptive field sharpness, and more persistent recurrent excitation than control neurons, all of which are characteristics of immature neurons. Transfected cells, however, had normal spontaneous excitatory synaptic currents and dendritic arbors. These results suggest that spike output of a tectal neuron plays an important instructive role in development of its receptive field properties and refinement of local circuits. However, other activity-dependent processes, such as synaptogenesis and dendritic growth, remain unaffected due to the permissive environment created by otherwise normal network activity. [ABSTRACT FROM AUTHOR]

Summary: Dendrites of the same neuron usually avoid each other. Some neurons also repel similar neurons through dendrite-dendrite interaction to tile the receptive field. Nonoverlapping coverage based on such contact-dependent repulsion requires dendrites to compete for limited space. Here we show that Drosophila class IV dendritic arborization (da) neurons, which tile the larval body wall, grow their dendrites mainly in a 2D space on the extracellular matrix (ECM) secreted by the epidermis. Removing neuronal integrins or blocking epidermal laminin production causes dendrites to grow into the epidermis, suggesting that integrin-laminin interaction attaches dendrites to the ECM. We further show that some of the previously identified tiling mutants fail to confine dendrites in a 2D plane. Expansion of these mutant dendrites in three dimensions results in overlap of dendritic fields. Moreover, overexpression of integrins in these mutant neurons effectively reduces dendritic crossing and restores tiling, revealing an additional mechanism for tiling. [ABSTRACT FROM AUTHOR]

In macaque primary visual cortex (V1), neuronal responses to stimuli inside the receptive field (RF) are modulated by stimuli in the RF surround. This modulation is orientation specific. Previous studies suggested that, for some cells, this specificity may not be fixed but changes with the stimulus orientation presented to the RF. We demonstrate, in recording studies, that this tuning behavior is instead highly prevalent in V1 and, in theoretical work, that it arises only if V1 operates in a regime of strong local recurrence. Strongest surround suppression occurs when the stimuli in the RF and the surround are iso-oriented, and strongest facilitation when the stimuli are cross-oriented. This is the case even when the RF is suboptimally activated by a stimulus of nonpreferred orientation but only if this stimulus can activate the cell when presented alone. This tuning behavior emerges from the interaction of lateral inhibition (via the surround pathways), which is tuned to the preferred orientation of the RF, with weakly tuned, but strong, local recurrent connections, causing maximal withdrawal of recurrent excitation at the feedforward input orientation. Thus, horizontal and feedback modulation of strong recurrent circuits allows the tuning of contextual effects to change with changing feedforward inputs. [ABSTRACT FROM AUTHOR]

Extracellular recording has shown that dorsal horn neurons can have an inhibitory surround outside their excitatory receptive field, but cannot reveal inhibitory inputs within the excitatory field, or show the underlying excitatory and inhibitory synaptic inputs that determine net output. To study the underlying components of receptive field organization, in vivo patch-clamp recording was used to compare the size and distribution of subthreshold, suprathreshold, and inhibitory fields, in neurons in the mouse superficial medullary dorsal horn that were characterized by their responses to noxious and innocuous mechanical facial stimulation. Subthreshold excitatory fields typically extended some distance beyond the borders of the suprathreshold field, and also commonly exhibited broader stimulus selectivity, in that the majority of nociceptive-specific neurons exhibited subthreshold responses to brush. Separate voltage-clamp recording of excitatory and inhibitory inputs using different holding potentials revealed that inhibition could be evoked from both within and outside the excitatory field. In nociceptive neurons, inhibition tended to be maximal at the excitatory receptive field center, and was usually greater for pinch than brush, although the selectivity for pinch versus brush was not as great as with excitatory responses. Based on current data on dorsal horn organization, we propose that the localized peak of inhibition at the excitatory field center could be mediated by local interneurons, while the more widespread surrounding inhibition may depend on supraspinal circuitry. [ABSTRACT FROM AUTHOR]

Neurons in the hand representation of primary somatosensory cortex (area 3b) are known to have discretely localized receptive fields; and these neurons form modules that can be visualized histologically as distinct digit and palm representations. Despite these indicators of the importance of local processing in area 3b, widespread interactions between stimuli presented to locations across the hand have been reported. We investigated the relationship of neuron firing rate with distance from the site of maximum activation in cortex by recording from a 100-electrode array with electrodes spaced 400 μm apart, implanted into the area 3b hand representation in anesthetized owl monkeys. For each stimulated location on the hand, the electrode site where neurons had the highest peak firing rate was defined as the peak activation site. The lesser firing rates of neurons at all other electrode sites in the grid were compared with the firing rates of neurons at the peak activation site. On average, peak firing rates of neurons decreased rapidly with distance away from the peak activation site. The effect of distance on the variance of firing rates was highly significant (P < 0.0001). However, individual neurons retained high firing rates for distances over 3 mm. The clear decline in firing rate with distance from the most activated location indicates that local processing is emphasized in area 3b, while the distance of neurons with reduced but maintained firing rates ≤3–4 mm from the site of best activation demonstrated widespread activation in primary somatosensory cortex. [ABSTRACT FROM AUTHOR]

People can find objects in a visual scene fast and effortlessly. It is thought that this may be accomplished by creating a map of the outside world that incorporates bottom-up sensory and top-down cognitive inputs—a priority map. Eye movements are made toward the location represented by the highest activity on the priority map. We hypothesized that the lateral intraparietal area (LIP) of posterior parietal cortex acts as such a map. To test this, we performed low current microstimulation on animals trained to perform a foraging task and asked whether we could bias the animals to make a saccade to a particular stimulus, by creating an artificial peak of activity at the location representing that stimulus on the map. We found that microstimulation slightly biased the animals to make saccades to visual stimuli at the stimulated location, without actively generating saccades. The magnitude of this effect was small, but it appeared to be similar for all visual stimuli. We interpret these results to mean that microstimulation slightly biased saccade goal selection to the object represented at the stimulated location in LIP. [ABSTRACT FROM AUTHOR]

Processing of sensory information in neural circuits is modulated by an animal's behavioral state, but the underlying cellular mechanisms are not well understood. Focusing on the mouse visual cortex, here we analyze the role of GABAergic interneurons that are located in layer 1 and express Ndnf (L1 NDNF INs) in the state-dependent control over sensory processing. We find that the ongoing and sensory-evoked activity of L1 NDNF INs is strongly enhanced when an animal is aroused and that L1 NDNF INs gain-modulate local excitatory neurons selectively during high-arousal states by inhibiting their apical dendrites while disinhibiting their somata via Parvalbumin -expressing interneurons. Because active NDNF INs are evenly spread in L1 and can affect excitatory neurons across all cortical layers, this indicates that the state-dependent activation of L1 NDNF INs and the subsequent shift of inhibition in excitatory neurons toward their apical dendrites gain-modulate sensory processing in whole cortical columns. [Display omitted] • Arousal strongly enhances the activity and sensory-evoked responses of L1 NDNF INs • L1 NDNF INs gain-modulate local EXC neurons selectively during high-arousal states • L1 NDNF INs inhibit the apical dendrites of EXC neurons and disinhibit their somata • Active NDNF INs are evenly spread across L1 and can affect EXC neurons in all layers Cohen-Kashi Malina et al. show that visual cortex L1 NDNF INs are strongly driven by arousal. Active NDNF INs are evenly spread in L1 and gain-modulate local excitatory neurons in all cortical layers during high-arousal states by directly inhibiting their apical dendrites while disinhibiting their somata via Parvalbumin -expressing interneurons. [ABSTRACT FROM AUTHOR]

When navigating the environment, animals need to prioritize responses to the most relevant stimuli. Although a theoretical framework for selective visual attention exists, its circuit implementation has remained obscure. Here we investigated how larval zebrafish select between simultaneously presented visual stimuli. We found that a mix of winner-take-all (WTA) and averaging strategies best simulates behavioral responses. We identified two circuits whose activity patterns predict the relative saliencies of competing visual objects. Stimuli presented to only one eye are selected by WTA computation in the inner retina. Binocularly presented stimuli, on the other hand, are processed by reciprocal, bilateral connections between the nucleus isthmi (NI) and the tectum. This interhemispheric computation leads to WTA or averaging responses. Optogenetic stimulation and laser ablation of NI neurons disrupt stimulus selection and behavioral action selection. Thus, depending on the relative locations of competing stimuli, a combination of retinotectal and isthmotectal circuits enables selective visual attention. • Zebrafish respond to competing stimuli using winner-take-all and averaging strategies • Retinotectal and isthmotectal circuits enable context-dependent stimulus selection • Perturbing nucleus isthmi function disrupts behavioral action selection • Isthmotectal circuit layout is consistent with local enhancement and global suppression Fernandes et al. investigate how zebrafish larvae respond selectively to one of two stimuli competing for the animal's attention. Two strategies for stimulus selection are used: winner-take-all or averaging. The corresponding neuronal computations are implemented in an intricate system of feedback loops between tectum and nucleus isthmi. [ABSTRACT FROM AUTHOR]

Summary Many animals guide their movements using optic flow, the displacement of stationary objects across the retina caused by self-motion. How do animals selectively synthesize a global motion pattern from its local motion components? To what extent does this feature selectivity rely on circuit mechanisms versus dendritic processing? Here we used in vivo calcium imaging to identify pre- and postsynaptic mechanisms for processing local motion signals in global motion detection circuits in Drosophila. Lobula plate tangential cells (LPTCs) detect global motion by pooling input from local motion detectors, T4/T5 neurons. We show that T4/T5 neurons suppress responses to adjacent local motion signals whereas LPTC dendrites selectively amplify spatiotemporal sequences of local motion signals consistent with preferred global patterns. We propose that sequential nonlinear suppression and amplification operations allow optic flow circuitry to simultaneously prevent saturating responses to local signals while creating selectivity for global motion patterns critical to behavior. Highlights • Global motion circuits in Drosophila exhibit nonlinear summation of local signals • Neurons that detect local motion suppress spatially adjacent signals • Dendrites that pool local motion inputs align with a preferred direction of motion • Oriented dendrites amplify responses to specific spatiotemporal input sequences Barnhart et al. show that sequential nonlinear summation of local motion cues shapes feature selectivity in the Drosophila visual system. In global motion circuits, adjacent local signals are suppressed presynaptically, whereas specific spatiotemporal sequences of local signals are amplified postsynaptically. [ABSTRACT FROM AUTHOR]

Summary Visual perception is affected by spatial context. In visual cortex, neuronal responses to stimuli inside the receptive field (RF) are suppressed by stimuli in the RF surround. To understand the circuits and cortical layers processing spatial context, we simultaneously recorded across all layers of macaque primary visual cortex while presenting stimuli at increasing distances from the recorded cells' RF. We find that near versus far-surround stimuli activate distinct layers, thus revealing unique laminar contributions to the processing of local and global spatial context. Stimuli in the near-surround evoke the earliest subthreshold responses in superficial and upper-deep layers, and earliest suppression of spiking responses in superficial layers. Conversely, far-surround stimuli evoke the earliest subthreshold responses in feedback-recipient layer 1 and lower-deep layers, and earliest suppression of spiking responses almost simultaneously in all layers, except 4C, where suppression emerges last. Our results suggest distinct circuits for local and global signal integration. Graphical Abstract Highlights • Local and global visuo-spatial context engage V1 laminae in selective ways • Processing of local information is faster and begins in superficial and deep layers • Processing of global information is slower and begins in layers 1 and 6 • Local information engages multiple circuits, and global information engages feedback Visual perception is affected by spatial context. Here Bijanzadeh et al. examine the role of V1 layers in the processing of contextual information. They find layer-specific differences in the processing of local and global visuo-spatial context suggestive of distinct underlying neural circuits. [ABSTRACT FROM AUTHOR]

Summary Substantial evidence at the subcellular level indicates that the spatial arrangement of synaptic inputs onto dendrites could play a significant role in cortical computations, but how synapses of functionally defined cortical networks are arranged within the dendrites of individual neurons remains unclear. Here we assessed one-dimensional spatial receptive fields of individual dendritic spines within individual layer 2/3 neuron dendrites. Spatial receptive field properties of dendritic spines were strikingly diverse, with no evidence of large-scale topographic organization. At a fine scale, organization was evident: neighboring spines separated by less than 10 μm shared similar spatial receptive field properties and exhibited a distance-dependent correlation in sensory-driven and spontaneous activity patterns. Fine-scale dendritic organization was supported by the fact that functional groups of spines defined by dimensionality reduction of receptive field properties exhibited non-random dendritic clustering. Our results demonstrate that functional synaptic clustering is a robust feature existing at a local spatial scale. Video Abstract [ABSTRACT FROM AUTHOR]

Life is preserved and enhanced by coordinated selectivity in local neural circuits. Narrow receptive-field selectivity is necessary to avoid the curse-of-dimensionality, but local activities can be made coherent and relevant by guiding learning and processing using broad coordinating contextual gain-controlling interactions. Better understanding of the functions and mechanisms of those interactions is therefore crucial to the issues Clark examines. [ABSTRACT FROM AUTHOR]

Summary: Females of many species, once mated, undergo a rapid change in reproductive physiology and behavior, shifting from a sexually receptive state to one devoted to the rearing of offspring. Two recent reports shed light on the neural circuitry governing the female post-mating response in the fruit fly Drosophila, providing insight into the neurobiological processes governing a complex behavior. [Copyright &y& Elsevier]

Advances in experimental techniques, including behavioral paradigms using rich stimuli under closed loop conditions and the interfacing of neural systems with external inputs and outputs, reveal complex dynamics in the neural code and require a revisiting of standard concepts of representation. High-throughput recording and imaging methods along with the ability to observe and control neuronal subpopulations allow increasingly detailed access to the neural circuitry that subserves neural representations and the computations they support. How do we harness theory to build biologically grounded models of complex neural function? [ABSTRACT FROM AUTHOR]