Understanding Neural Maps with Topographica

The biological function of neurons can often be understood only in the context of large, highly interconnected networks. These networks typically form two-dimensional topographic maps, such as the retinotopic maps in mammalian visual cortex. Computational simulations of these areas have led to valuable insights about how cortical topography develops and functions, but further progress has been hindered due to the lack of appropriate simulation tools. This paper introduces the freely available Topographica maplevel simulator, originally developed at the University of Texas at Austin and now maintained at the University of Edinburgh, UK. Topographica is designed to make large-scale, detailed models practical. The goal is to allow neuroscientists and computational scientists to work together to understand how topographic maps and their connections organize and operate. This understanding will be crucial for integrating experimental observations into a comprehensive theory of brain function.

Organization of hue selectivity in macaque V2 thin stripes.

V2 has long been recognized to contain functionally distinguishable compartments that are correlated with the stripelike pattern of cytochrome oxidase activity. Early electrophysiological studies suggested that color, direction/disparity, and orientation selectivity were largely segregated in the thin, thick, and interstripes, respectively. Subsequent studies revealed a greater degree of homogeneity in the distribution of response properties across stripes, yet color-selective cells were still found to be most prevalent in the thin stripes. Optical recording studies have demonstrated that thin stripes contain both color-preferring and luminance-preferring modules. These thin stripe color-preferring modules contain spatially organized hue maps, whereas the luminance-preferring modules contain spatially organized luminance-change maps. In this study, the neuronal basis of these hue maps was determined by characterizing the selectivity of neurons for isoluminant hues in multiple penetrations within previously characterized V2 thin stripe hue maps. The results indicate that neurons within the superficial layers of V2 thin stripe hue maps are organized into columns whose aggregated hue selectivity is closely related to the hue selectivity of the optically defined hue maps. These data suggest that thin stripes contain hue maps not simply because of their moderate percentage of hue-selective neurons, but because of the columnar and tangential organization of hue selectivity.

Recovery from monocular deprivation using binocular deprivation.

Ocular dominance (OD) plasticity is a robust paradigm for examining the functional consequences of synaptic plasticity. Previous experimental and theoretical results have shown that OD plasticity can be accounted for by known synaptic plasticity mechanisms, using the assumption that deprivation by lid suture eliminates spatial structure in the deprived channel. Here we show that in the mouse, recovery from monocular lid suture can be obtained by subsequent binocular lid suture but not by dark rearing. This poses a significant challenge to previous theoretical results. We therefore performed simulations with a natural input environment appropriate for mouse visual cortex. In contrast to previous work, we assume that lid suture causes degradation but not elimination of spatial structure, whereas dark rearing produces elimination of spatial structure. We present experimental evidence that supports this assumption, measuring responses through sutured lids in the mouse. The change in assumptions about the input environment is sufficient to account for new experimental observations, while still accounting for previous experimental results.

Modulation of orientation-selective neurons by motion: when additive, when multiplicative?

The recurrent interaction among orientation-selective neurons in the primary visual cortex (V1) is suited to enhance contours in a noisy visual scene. Motion is known to have a strong pop-up effect in perceiving contours, but how motion-sensitive neurons in V1 support contour detection remains vastly elusive. Here we suggest how the various types of motion-sensitive neurons observed in V1 should be wired together in a micro-circuitry to optimally extract contours in the visual scene. Motion-sensitive neurons can be selective about the direction of motion occurring at some spot or respond equally to all directions (pandirectional). We show that, in the light of figure-ground segregation, direction-selective motion neurons should additively modulate the corresponding orientation-selective neurons with preferred orientation orthogonal to the motion direction. In turn, to maximally enhance contours, pandirectional motion neurons should multiplicatively modulate all orientation-selective neurons with co-localized receptive fields. This multiplicative modulation amplifies the local V1-circuitry among co-aligned orientation-selective neurons for detecting elongated contours. We suggest that the additive modulation by direction-specific motion neurons is achieved through synaptic projections to the somatic region, and the multiplicative modulation by pandirectional motion neurons through projections to the apical region of orientation-specific pyramidal neurons. For the purpose of contour detection, the V1-intrinsic integration of motion information is advantageous over a downstream integration as it exploits the recurrent V1-circuitry designed for that task.

Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects

Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

Zazen meditation and no-task resting EEG compared with LORETA intracortical source localization

Meditation is a self-induced and willfully initiated practice that alters the state of consciousness. The meditation practice of Zazen, like many other meditation practices, aims at disregarding intrusive thoughts while controlling body posture. It is an open monitoring meditation characterized by detached moment-to-moment awareness and reduced conceptual thinking and self-reference. Which brain areas differ in electric activity during Zazen compared to task-free resting? Since scalp electroencephalography (EEG) waveforms are reference-dependent, conclusions about the localization of active brain areas are ambiguous. Computing intracerebral source models from the scalp EEG data solves this problem. In the present study, we applied source modeling using low resolution brain electromagnetic tomography (LORETA) to 58-channel scalp EEG data recorded from 15 experienced Zen meditators during Zazen and no-task resting. Zazen compared to no-task resting showed increased alpha-1 and alpha-2 frequency activity in an exclusively right-lateralized cluster extending from prefrontal areas including the insula to parts of the somatosensory and motor cortices and temporal areas. Zazen also showed decreased alpha and beta-2 activity in the left angular gyrus and decreased beta-1 and beta-2 activity in a large bilateral posterior cluster comprising the visual cortex, the posterior cingulate cortex and the parietal cortex. The results include parts of the default mode network and suggest enhanced automatic memory and emotion processing, reduced conceptual thinking and self-reference on a less judgmental, i.e., more detached moment-to-moment basis during Zazen compared to no-task resting.

Brain systems underlying encounter expectancy bias in spider phobia.

Spider-phobic individuals are characterized by exaggerated expectancies to be faced with spiders (so-called encounter expectancy bias). Whereas phobic responses have been linked to brain systems mediating fear, little is known about how the recruitment of these systems relates to exaggerated expectancies of threat. We used fMRI to examine spider-phobic and control participants while they imagined visiting different locations in a forest after having received background information about the likelihood of encountering different animals (spiders, snakes, and birds) at these locations. Critically, imagined encounter expectancies modulated brain responses differently in phobics as compared with controls. Phobics displayed stronger negative modulation of activity in the lateral prefrontal cortex, precuneus, and visual cortex by encounter expectancies for spiders, relative to snakes or birds (within-participants analysis); these effects were not seen in controls. Between-participants correlation analyses within the phobic group further corroborated the hypothesis that these phobia-specific modulations may underlie irrationality in encounter expectancies (deviations of encounter expectancies from objective background information) in spider phobia; the greater the negative modulation a phobic participant displayed in the lateral prefrontal cortex, precuneus, and visual cortex, the stronger was her bias in encounter expectancies for spiders. Interestingly, irrationality in expectancies reflected in frontal areas relied on right rather than left hemispheric deactivations. Our data accord with the idea that expectancy biases in spider phobia may reflect deficiencies in cognitive control and contextual integration that are mediated by right frontal and parietal areas.

Cathodal HD-tDCS on the right V5 improves motion perception in humans

Brain lesions in the visual associative cortex are known to impair visual perception, i.e., the capacity to correctly perceive different aspects of the visual world, such as motion, color, or shapes. Visual perception can be influenced by non-invasive brain stimulation such as transcranial direct current stimulation (tDCS). In a recently developed technique called high definition (HD) tDCS, small HD-electrodes are used instead of the sponge electrodes in the conventional approach. This is believed to achieve high focality and precision over the target area. In this paper we tested the effects of cathodal and anodal HD-tDCS over the right V5 on motion and shape perception in a single blind, within-subject, sham controlled, cross-over trial. The purpose of the study was to prove the high focality of the stimulation only over the target area. Twenty one healthy volunteers received 20 min of 2 mA cathodal, anodal and sham stimulation over the right V5 and their performance on a visual test was recorded. The results showed significant improvement in motion perception in the left hemifield after cathodal HD-tDCS, but not in shape perception. Sham and anodal HD-tDCS did not affect performance. The specific effect of influencing performance of visual tasks by modulating the excitability of the neurons in the visual cortex might be explained by the complexity of perceptual information needed for the tasks. This provokes a "noisy" activation state of the encoding neuronal patterns. We speculate that in this case cathodal HD-tDCS may focus the correct perception by decreasing global excitation and thus diminishing the "noise" below threshold.

POPULATION CODING IN LAMINAR CORTICAL CIRCUITS

One of the fundamental questions in neuroscience is to understand how encoding of sensory inputs is distributed across neuronal networks in cerebral cortex to influence sensory processing and behavioral performance. The fact that the structure of neuronal networks is organized according to cortical layers raises the possibility that sensory information could be processed differently in distinct layers. The goal of my thesis research is to understand how laminar circuits encode information in their population activity, how the properties of the population code adapt to changes in visual input, and how population coding influences behavioral performance. To this end, we performed a series of novel experiments to investigate how sensory information in the primary visual cortex (V1) emerges across laminar cortical circuits. First, it is commonly known that the amount of information encoded by cortical circuits depends critically on whether or not nearby neurons exhibit correlations. We examined correlated variability in V1 circuits from a laminar-specific perspective and observed that cells in the input layer, which have only local projections, encode incoming stimuli optimally by exhibiting low correlated variability. In contrast, output layers, which send projections to other cortical and subcortical areas, encode information suboptimally by exhibiting large correlations. These results argue that neuronal populations in different cortical layers play different roles in network computations. Secondly, a fundamental feature of cortical neurons is their ability to adapt to changes in incoming stimuli. Understanding how adaptation emerges across cortical layers to influence information processing is vital for understanding efficient sensory coding. We examined the effects of adaptation, on the time-scale of a visual fixation, on network synchronization across laminar circuits. Specific to the superficial layers, we observed an increase in gamma-band (30-80 Hz) synchronization after adaptation that was correlated with an improvement in neuronal orientation discrimination performance. Thus, synchronization enhances sensory coding to optimize network processing across laminar circuits. Finally, we tested the hypothesis that individual neurons and local populations synchronize their activity in real-time to communicate information about incoming stimuli, and that the degree of synchronization influences behavioral performance. These analyses assessed for the first time the relationship between changes in laminar cortical networks involved in stimulus processing and behavioral performance.

A new approach to a model of the mammalian retina with optically programmable logic cells

This paper reports a model of the mammalian retina as well as an interpretation of some functions of the visual cortex. Its main objective is to simulate some of the behaviors observed at the different retina cells depending on the characteristics of the light impinging onto the photoreceptors. This simulation is carried out with a simple structure employed previously as basic building block of some optical computer architectures. Its possibility to perform any type of Boolean function allows a wide range of behaviors.

Image processing based on a model of the mammalian retina

A first study in order to construct a simple model of the mammalian retina is reported. The basic elements for this model are Optical Programmable Logic Cells, OPLCs, previously employed as a functional element for Optical Computing. The same type of circuit simulates the five types of neurons present in the retina. Different responses are obtained by modifying either internal or external connections. Two types of behaviors are reported: symmetrical and non-symmetrical with respect to light position. Some other higher functions, as the possibility to differentiate between symmetric and non-symmetric light images, are performed by another simulation of the first layers of the visual cortex. The possibility to apply these models to image processing is reported.

A new method to analyse the perception of size

In living bodies, the correct perceptual representation of size constancy requires that an object's size appear the same when it changes its location with respect to the observer. At the same time, it is necessary that objects at different locations appear to be the same size if they are. In order to do that, the perceptual system must recover from the stimuli impinging on the individual, from the light falling on the retina, a representation of the relative sizes of objects in the environment. Moreover, at the same time, image perception is related to another type of phenomena. It corresponds to the well known perceptual illusions. To analyze this facts, we propose a system based on a particular arrays of receptive points composed by optical fibers and dummy fibers. The structure is based on the first layers of the mammalians primary visual cortex. At that part of the brain, the neurons located at certain columns, respond to particular directions. This orientation changes in a systematic way as one moves across the cortical surface. In our case, the signals from the above-mentioned array are analyzed and information concerning orientation and size of a particular line is obtained. With this system, the Muelle-Lyer illusion has been studied and some rules to interpret why equal length objects give rise to different interpretations are presented.

A model of ocular dominance column development by competition for trophic factor

Recent experimental evidence has shown that application of certain neurotrophic factors (NTs) to the developing primary visual cortex prevents the development of ocular dominance (OD) columns. One interpretation of this result is that afferents from the lateral geniculate nucleus compete for postsynaptic trophic factor in an activity-dependent manner. Application of excess trophic factor eliminates this competition, thereby preventing OD column formation. We present a model of OD column development, incorporating Hebbian synaptic modification and activity-driven competition for NT, which accounts for both normal OD column development as well as the prevention of that development when competition is removed. In the “control” situation, when available NT is below a critical amount, OD columns form normally. These columns form without weight normalization procedures and in the presence of positive inter-eye correlations. In the “experimental” case, OD column development is prevented in a local neighborhood in which excess NT has been added. Our model proposes a biologically plausible mechanism for competition between neural populations that is motivated by several pieces of experimental data, thereby accounting for both normal and experimentally perturbed conditions.

Subplate neuron ablation alters neurotrophin expression and ocular dominance column formation

Ocular dominance column formation in visual cortex depends on both the presence of subplate neurons and the endogenous expression of neurotrophins. Here we show that deletion of subplate neurons, which supply glutamatergic inputs to visual cortex, leads to a paradoxical increase in brain-derived neurotrophic factor mRNA in the same region of visual cortex in which ocular dominance columns are absent. Subplate neuron ablation also increases glutamic acid decarboxylase-67 levels, indicating an alteration in cortical inhibition. These observations imply a role for this special class of neurons in modulating activity-dependent competition by regulating levels of neurotrophins and excitability within a developing cortical circuit.

Perturbed dentate gyrus function in serotonin 5-HT2C receptor mutant mice

Serotonin systems have been implicated in the regulation of hippocampal function. Serotonin 5-HT2C receptors are widely expressed throughout the hippocampal formation, and these receptors have been proposed to modulate synaptic plasticity in the visual cortex. To assess the contribution of 5-HT2C receptors to the serotonergic regulation of hippocampal function, mice with a targeted 5-HT2C-receptor gene mutation were examined. An examination of long-term potentiation at each of four principal regions of the hippocampal formation revealed a selective impairment restricted to medial perforant path–dentate gyrus synapses of mutant mice. This deficit was accompanied by abnormal performance in behavioral assays associated with dentate gyrus function. 5-HT2C receptor mutants exhibited abnormal performance in the Morris water maze assay of spatial learning and reduced aversion to a novel environment. These deficits were selective and were not associated with a generalized learning deficit or with an impairment in the discrimination of spatial context. These results indicate that a genetic perturbation of serotonin receptor function can modulate dentate gyrus plasticity and that plasticity in this structure may contribute to neural mechanisms underlying hippocampus-dependent behaviors.