Zero-crossing detectors in primary visual cortex?

David Marr and others have hypothesized that the visual system processes complex scene information in stages, the first of which involves the detection of light intensity edges or zero-crossings (Marr, 1982). Ideal zero-crossing detector mechanisms have been described and modeled in terms of their possible physiological implementation (Marr and Hildreth, 1980; Poggio, 1983). We now present evidence of visual cortical receptive fields which resemble in spatial organizational terms the requirements of zero-crossing analysis. The linear and nonlinear summation within and between the receptive field subunits are described and compared with predicted processes. The relative subunit sizes and separations are analyzed in these terms. Our findings support the notion that receptive fields may correspond with zero-crossing filters rather than zero-crossing detector gates.     

“Irregular” visual receptive fields of neurons of the cat lateral geniculate body

Using point-to-point testing, the spatial organization of receptive fields (RF) of the neurons of the lateral geniculate body (LGB) was studied in cats with pretrigeminally transected brainstcm (without general anesthesia). In 60% of studied neurons (96 units of 160 examined), configuration of their RF considerably differed from round or ellipsoid. The shape of such RF was frequently rather complex, and they were qualified as irregular receptive fields (IRF). Presentation of the stable flickering spot throughout the entire surface of 60 IRF (63%) evoked qualitatively similar responses of a neuron, i.e., these IRF were homogeneous. In 29 cells the responses were of theon-off type, 22 neurons generatedoff responses, andon responses were observed in 9 cells. In the rest of the IRF (37%), it was possible to differentiate the subfields, whose stimulation evoked generation of different types of responses, i.e., these IRF were heterogeneous. In the case of moving stimuli, the neurons with homogeneous IRF showed no directional selectivity, while such selectivity was observed in most units with heterogeneous IRF.Neirofiziologiya/Neurophysiology, Vol. 28, No. 1, pp. 7–16, January–February, 1996.     

Spatiotemporal organization of simple-cell receptive fields in area 18 of cat’s cortex

Spatiotemporal structures of receptive-fields (RF) have been studied for simple cells in area 18 of eat by measuring the temporal transfer function (TTF) over different locations (subregions) within the RF. The temporal characteristics of different subregions differed from each other in the absolute phase shift (APS) to visual stimuli. Two types of relationships can be seen: (i)The APS varied continuously from one subregion to the next: (ii) A 180°-phase jump was seen as the stimulus position changed somewhere within the receptive field. Spatiotemporal receptive field profiles have been determined by applying reverse Fourier analysis to responses in the frequency domain. For the continuous type, spatial and temporal characteristics cannot be dissociated (space time inseparable) and the spatiotemporal structure is oriented. On the contrary, the spatial and temporal characteristics for the jumping type can be dissociated (space-time separable) and the structure is not oriented in the space-time plane. Based on the APSs measured at different subregions, the optimal direction of motion and optimal spatial frequency of neurons can be predicted.     

Is slowness a learning principle of the visual cortex?

Slow feature analysis is an algorithm for extracting slowly varying features from a quickly varying signal. It has been shown in network simulations on one-dimensional stimuli that visual invariances to shift and other transformations can be learned in an unsupervised fashion based on slow feature analysis. More recently, we have shown that slow feature analysis applied to image sequences generated from natural images using a range of spatial transformations results in units that share many properties with complex and hypercomplex cells of the primary visual cortex. We find cells responsive to Gabor stimuli with phase invariance, sharpened or widened orientation or frequency tuning, secondary response lobes, end-stopping, and cells selective for direction of motion. These results indicate that slowness may be an important principle of self-organization in the visual cortex.     

‘Vector white noise’: a technique for mapping the motion receptive fields of direction-selective visual neurons

A technique is described and tested for mapping the sensitivities and preferred directions of motion at different locations within the receptive fields of direction-selective motion-detecting visual neurons. The procedure is to record the responses to a number of visual stimuli, each stimulus presentation consisting of a set of short, randomly-oriented, moving bars arranged in a square grid. Each bar moves perpendicularly to its long axis. The vector describing the sensitivity and preferred direction of motion at each grid location is obtained as a sum of the unit vectors defining the directions of motion of the bars in each of the stimuli at that location, weighted by the strengths of the corresponding responses. The resulting vector field specifies the optimum flow field for the neuron. The advantage of this technique over the conventional approach of probing the receptive field sequentially at each grid location is that the parallel nature of the stimulus is sensitive to nonlinear interactions (such as shunting inhibition for mutual facilitation) between different regions of the visual field. The technique is used to determine accurately the motion receptive fields of direction-selective motion detecting neurons in the optic lobes of insects. It is potentially applicable to motion-sensitive neurons with highly structured receptive fields, such as those in the optic tectum of the pigeon or in area MST of the monkey.     

Why do olfactory neurons have unspecific receptive fields?

Biological olfactory neurons are deployed as a population, most responding to a large variety of chemical compounds, that is, they possess unspecific receptive fields. The question of whether this unspecificity results from some physical constraint placed upon chemical transduction, or on the other hand, is beneficial to system performance is unclear. In this paper we employ the notion of Fisher information to address this question by quantifying how both the distribution and the tunings of the receptive fields within olfactory receptor populations affect the optimal estimation performance of the system. Our results show that overlapping sensory neuron tunings that respond to common chemical compounds have better estimation performance than perfectly specific tunings. Our results suggest two phenomena that might represent general principles of organization within biological sensory systems responding to multiple stimuli: maximization of the diversity of tunings and homogeneity in the distribution of these different receptive fields across the stimulus space (independent of the statistics of the input stimuli). Our model predicts that a local randomized mechanism controlling receptor specificities generates optimal multidimensional stimulus estimation, for which there is some experimental evidence from the biology.     

How does the cerebral cortex work? Learning, attention, and grouping by the laminar circuits of visual cortex

The organization of neocortex into layers is one of its most salient anatomical features. These layers include circuits that form functional columns in cortical maps. A major unsolved problem concerns how bottom-up, top-down, and horizontal interactions are organized within cortical layers to generate adaptive behaviors. This article models how these interactions help visual cortex to realize: (i) the binding process whereby cortex groups distributed data into coherent object representations; (ii) the attentional process whereby cortex selectively processes important events; and (iii) the developmental and learning processes whereby cortex shapes its circuits to match environmental constraints. New computational ideas about feedback systems suggest how neocortex develops and learns in a stable way, and why top-down attention requires converging bottom-up inputs to fully activate cortical cells, whereas perceptual groupings do not.     

Effect of the spatial context along the invasion process: “Hierarchical spatial” or “Host-switching spatial” hypotheses?

Very little is known about how spatial effects influence invasive species throughout the invasion sequence. We propose here two mechanisms to explain the changes in spatial effects throughout the stages of invasion, using the soybean aphid (Aphis glycines) as a model. First, the “hierarchical spatial effect” hypothesis, based on a change in the relative importance of the spatial scales throughout the invasion process, with main effect at broad scale during the first years of invasion, and main effect at local scale during the subsequent years. Second, the “host-switching spatial effect” hypothesis, stating that the spatial effect is driven by a switch in the effect of the host/habitat throughout the invasion process, from effect of main summer host/habitat during the first years of invasion to effect of overwintering host/habitat during the subsequent years. Data from governmental archives and field samplings enabled to investigate the spatial effects on aphid density at three scales (regional, landscape, local) during a 7 year period (2006–2012). Our results demonstrate that the hierarchical spatial effect hypothesis is not an adequate model for the soybean aphid, aphid density being more affected by landscape-scale factors irrespective of years. In contrast, our results are in accordance with the host-switching spatial hypothesis, with positive effect of the main summer host/habitat (soybean) during the first steps of invasion (2006–2008), followed by a positive effect of overwintering habitats (buckthorn, woodland) during the subsequent years (2010–2012). Overall, investigating these hypotheses in other systems would determine whether the same tendency is observed for other invasive species.     

Nonlinear cross-frequency interactions in primary auditory cortex spectrotemporal receptive fields: a Wiener–Volterra analysis

The effects of nonlinear interactions between different sound frequencies on the responses of neurons in primary auditory cortex (AI) have only been investigated using two-tone paradigms. Here we stimulated with relatively dense, Poisson-distributed trains of tone pips (with frequency ranges spanning five octaves, 16 frequencies /octave, and mean rates of 20 or 120 pips /s), and examined within-frequency (or auto-frequency) and cross-frequency interactions in three types of AI unit responses by computing second-order “Poisson-Wiener” auto- and cross-kernels. Units were classified on the basis of their spectrotemporal receptive fields (STRFs) as “double-peaked”, “single-peaked” or “peak-valley”. Second-order interactions were investigated between the two bands of excitatory frequencies on double-peaked STRFs, between an excitatory band and various non-excitatory bands on single-peaked STRFs, and between an excitatory band and an inhibitory sideband on peak-valley STRFs. We found that auto-frequency interactions (i.e., those within a single excitatory band) were always characterized by a strong depression of (first-order) excitation that decayed with the interstimulus lag up to ～200 ms. That depression was weaker in cross-frequency compared to auto-frequency interactions for ～25% of dual-peaked STRFs, evidence of “combination sensitivity” for the two bands. Non-excitatory and inhibitory frequencies (on single-peaked and peak-valley STRFs, respectively) typically weakly depressed the excitatory response at short interstimulus lags (<50 ms), but weakly facilitated it at longer lags (～50–200 ms). Both the depression and especially the facilitation were stronger for interactions with inhibitory frequencies rather than just non-excitatory ones. Finally, facilitation in single-peaked and peak-valley units decreased with increasing stimulus density. Our results indicate that the strong combination sensitivity and cross-frequency facilitation suggested by previous two-tone-paradigm studies are much less pronounced when using more temporally-dense stimuli.     

Are any functionally mature cells of medullary phenotype located in the thymus cortex?

Experiments were undertaken to test if thymocytes of "mature" or "medullary" phenotype were restricted to the medullary area of the thymus. A calculation based on direct cell counts on serial sections indicated that 11.5% of adult male CBA thymic lymphoid cells were within the medullary zone. Since only 3-4% of thymocytes were cortisone resistant, the majority of thymocytes within the medulla were, like cortical thymocytes, cortisone sensitive. A series of cell surface antigenic markers, used alone or in pairs, suggested that 13-15% of thymocytes were of medullary phenotype, somewhat more than the number of thymocytes actually present in the medulla. However, much of this discrepancy could be explained by differential death of cortical cells during isolation and staining, and by the existence in the cortex of a subpopulation of early blast cells which shared some, but not all markers with medullary thymocytes. A direct test for mature or medullary phenotype cells in the cortex involved selective transcapsular labeling of outer-cortical cells with fluorescent dyes, followed by multiparameter immunofluorescent analysis of the 10% labeled population. Outer-cortical thymocytes included some cells (mainly early blasts) sharing some markers with medullary thymocytes, but very few (less than 1%) of these cells expressed all the characteristic "mature" markers. Limit-dilution precursor frequency studies showed the level of functional cells in the outer cortex was extremely low. The overall conclusion was that the vast majority of cells of complete "mature" phenotype are confined to the thymic medulla. These findings favor the view that thymus migrants originate from the thymic medulla, but do not exclude a cortical origin. The results also illustrate the need for multiparameter analysis to distinguish medullary thymocytes from early blast cells.     

Chance or design? Some specific considerations concerning synaptic boutons in cat visual cortex

To understand the rules by which axons lay down their synaptic boutons we analyzed the linear bouton distributions in 39 neurons (23 spiny, 13 smooth) and 3 thalamic axons, which were filled intracellularly with horseradish peroxidase (HRP) during in vivo experiments in cat area 17. The variation of the total number of boutons and the total axonal length was large (789–7912 boutons, 12–126 mm). The overall linear bouton density for smooth cells was higher than that of spiny cells and thalamic afferents (mean ± sd, 110 ± 21 and 78 ± 27 boutons per mm of axonal length). The distribution of boutons varied according to their location on the tree. Distal axon collaterals (first and second order segments in Horton-Strahler ordering) of smooth neurons had a 3.5 times higher, spiny cells and thalamic afferents a 2 times higher bouton density compared to the higher order (more proximal) segments. The distribution of interbouton intervals was positively skewed and similar for cells of the same type. In most cases a γ-distribution fitted well, but the distributions had a tendency to have a heavier tail. To a first approximation these bouton distributions are consistent with both diffuse and specific models of interneuronal connections. Quite simple rules can explain these distributions and the connections between the different classes of neurons.     

Are environmental electromagnetic fields genotoxic?

Long-term exposure to extremely-low-frequency electromagnetic fields (ELF EMFs) greater than 0.4 microT has been linked, by epidemiological studies, to a small elevated risk of childhood leukaemia. Laboratory-based experiments have been claimed to show that ELF EMFs induce a variety of biological responses, although these claims are controversial. Recent experiments by Ivancsits et al. [Mutat. Res. 519 (2002) 1; Int. Arch. Occup. Environ. Health 76 (2003) 431; Mech. Age. Dev. 124 (2003) 847; H.W. Rüdiger, S. Ivancsits, E. Diem, O. Jahn, Genotoxic effects of ELF-EMF on human cells in vitro, Bioelectromagnetics Society 25th Annual Meeting, Maui, USA, 2003] suggest that ELF EMFs are genotoxic, on the basis of observations that intermittent exposures induce single-strand breaks (SSB) and double-strand DNA breaks (DSB) in the DNA of cultured human fibroblasts. The implications of these findings are discussed.     

Playing the electric light orchestra—how electrical stimulation of visual cortex elucidates the neural basis of perception

Vision research has the potential to reveal fundamental mechanisms underlying sensory experience. Causal experimental approaches, such as electrical microstimulation, provide a unique opportunity to test the direct contributions of visual cortical neurons to perception and behaviour. But in spite of their importance, causal methods constitute a minority of the experiments used to investigate the visual cortex to date. We reconsider the function and organization of visual cortex according to results obtained from stimulation techniques, with a special emphasis on electrical stimulation of small groups of cells in awake subjects who can report their visual experience. We compare findings from humans and monkeys, striate and extrastriate cortex, and superficial versus deep cortical layers, and identify a number of revealing gaps in the ‘causal map′ of visual cortex. Integrating results from different methods and species, we provide a critical overview of the ways in which causal approaches have been used to further our understanding of circuitry, plasticity and information integration in visual cortex. Electrical stimulation not only elucidates the contributions of different visual areas to perception, but also contributes to our understanding of neuronal mechanisms underlying memory, attention and decision-making.     

Synchronized oscillations in the visual cortex — a synergetic model

 We present an oscillator network model for the synchronization of oscillatory neuronal activity underlying visual processing. The single neuron is modeled by means of a limit cycle oscillator with an eigenfrequency corresponding to visual stimulation. The eigenfrequency may be time dependent. The mutual coupling strengths are unsymmetrical and activity dependent, and they scatter within the network. Synchronized clusters (groups) of neurons emerge in the network due to the visual stimulation. The different clusters correspond to different visual stimuli. There is no limitation of the number of stimuli. Distinct clusters do not perturb each other, although the coupling strength between all model neurons is of the same order of magnitude. Our analysis is not restricted to weak coupling strength. The scatter of the couplings causes shifts of the cluster frequencies. The model’s behavior is compared with the experimental findings. The coupling mechanism is extended in order to model the influence of bicucullin upon the neural network. We additionally investigate repulsive couplings, which lead to constant phase differences between clusters of the same frequency. Finally, we consider the problem of selective attention from the viewpoint of our model. Received: 15 February 1995/Accepted in revised form: 18 July 1995