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Biomedical subjects

Ernst Niebur

Publications and source records attributed to Ernst Niebur.

12 recordsLinked to original sources

A novel method for visualizing functional connectivity using principal component analysis.

Functional connectivity is a useful measure of voxel-wise functional magnetic resonance imaging signals that allows for the identification of functionally related brain areas and distributed networks. However, the high dimensionality of functional connectivity makes it difficult to visualize. In most studies, a small percentage of the total functional connectivity is visualized through diagrams that are constructed using individual seed voxels. In the present study describes a new method for visualizing most of the functional connectivity through a single diagram. This method does not rely on seed voxels, but rather employs a reduction of the high-dimensionality of the functional connectivity via a projection onto a three-dimensional color space using principal components analysis. With this new method, most of the information contained in a functional connectivity matrix can be represented through a single color-coded functional connectivity map, thereby facilitating a greater visual appreciation of functional connectivity.

Brain↗

Phase transitions in multiplicative competitive processes.

We introduce a discrete multiplicative process as a generic model of competition. Players with different abilities successively join the game and compete for finite resources. Emergence of dominant players and evolutionary development occur as a phase transition. The competitive dynamics underlying this transition is understood from a formal analogy to statistical mechanics. The theory is applicable to bacterial competition, predicting novel population dynamics near criticality.

Animals↗

Rate and synchrony in feedforward networks of coincidence detectors: analytical solution.

We provide an analytical recurrent solution for the firing rates and cross-correlations of feedforward networks with arbitrary connectivity, excitatory or inhibitory, in response to steady-state spiking input to all neurons in the first network layer. Connections can go between any two layers as long as no loops are produced. Mean firing rates and pairwise cross-correlations of all input neurons can be chosen individually. We apply this method to study the propagation of rate and synchrony information through sample networks to address the current debate regarding the efficacy of rate codes versus temporal codes. Our results from applying the network solution to several examples support the following conclusions: (1) differential propagation efficacy of rate and synchrony to higher layers of a feedforward network is dependent on both network and input parameters, and (2) previous modeling and simulation studies exclusively supporting either rate or temporal coding must be reconsidered within the limited range of network and input parameters used. Our exact, analytical solution for feedforward networks of coincidence detectors should prove useful for further elucidating the efficacy and differential roles of rate and temporal codes in terms of different network and input parameter ranges.

Action Potentials↗

Correlated inhibitory and excitatory inputs to the coincidence detector: analytical solution.

We present a solution for the steady-state output rate of an ideal coincidence detector receiving an arbitrary number of excitatory and inhibitory inputspike trains. All excitatory spike trains have identical binomial count distributions (which includes Poisson statistics as a special case) and arbitrary pairwise cross correlations between them. The same applies to the inhibitory inputs, and the rates and correlation functions of excitatory and inhibitory populations may be the same or different from each other. Thus, for each population independently, the correlation may range from complete independence to perfect correlation (identical processes). We find that inhibition, if made sufficiently strong, will result in an inverted U-shaped curve for the output rate of a coincidence detector as a function of input rates for the case of identical inhibitory and excitory input rates. This leads to the prediction that higher presynaptic (input) rates may lead to lower postsynaptic (output) rates where the output rate may fall faster than the inverse of the input rate, and shows some qualitative similarities to the case of purely excitatory inputs with synaptic depression. In general, we find that including inhibition invariably and significantly increases the behavioral repertoire of the coincidence detector over the case of pure excitatory input.

Action Potentials↗

Texture contrast attracts overt visual attention in natural scenes.

In natural vision, the central nervous system actively selects information for detailed processing through mechanisms of visual attention. It is widely held that simple stimulus features such as color, orientation and intensity contribute to the determination of visual salience and thus can act to guide the selection process in a bottom-up fashion. Contrary to this view, Einhäuser, W. & König, P. [(2003) Eur. J. Neurosci., 17, 1089-1097] conclude from their study of human eye movements that luminance contrast does not contribute to the calculation of stimulus salience and that top-down, rather than bottom-up, factors therefore determine attentional allocation in natural scenes. In this article, we dispute their conclusion and argue that the Einhäuser and König study has a number of methodological problems, the most prominent of which is the unintentional introduction of changes in texture contrast. We hypothesize that texture contrast, like luminance contrast, can contribute to the guidance of attention in a bottom-up fashion, and that an appeal to top-down factors is not necessary. To test this hypothesis, we implement a purely bottom-up model of visual selective attention where salience is derived from both luminance and texture contrast. We find that the model can quantitatively account for Einhäuser and König's results and that texture contrast strongly influences attentional guidance in this particular paradigm. The significance of this result for attentional guidance in other paradigms is discussed.

Attention↗

The effects of input rate and synchrony on a coincidence detector: analytical solution.

We derive analytically the solution for the output rate of the ideal coincidence detector. The solution is for an arbitrary number of input spike trains with identical binomial count distributions (which includes Poisson statistics as a special case) and identical arbitrary pairwise cross-correlations, from zero correlation (independent processes) to complete correlation (identical processes).

Afferent Pathways↗

Synaptic depression leads to nonmonotonic frequency dependence in the coincidence detector.

In this letter, we extend our previous analytical results (Mikula & Niebur, 2003) for the coincidence detector by taking into account probabilistic frequency-dependent synaptic depression. We present a solution for the steady-state output rate of an ideal coincidence detector receiving an arbitrary number of input spike trains with identical binomial count distributions (which includes Poisson statistics as a special case) and identical arbitrary pairwise cross-correlations, from zero correlation (independent processes) to perfect correlation (identical processes). Synapses vary their efficacy probabilistically according to the observed depression mechanisms. Our results show that synaptic depression, if made sufficiently strong, will result in an inverted U-shaped curve for the output rate of a coincidence detector as a function of input rate. This leads to the counterintuitive prediction that higher presynaptic (input) rates may lead to lower postsynaptic (output) rates where the output rate may fall faster than the inverse of the input rate.

Action Potentials↗

Scene content selected by active vision.

The primate visual system actively selects visual information from the environment for detailed processing through mechanisms of visual attention and saccadic eye movements. This study examines the statistical properties of the scene content selected by active vision. Eye movements were recorded while participants free-viewed digitized images of natural and artificial scenes. Fixation locations were determined for each image and image patches were extracted around the observed fixation locations. Measures of local contrast, local spatial correlation and spatial frequency content were calculated on the extracted image patches. Replicating previous results, local contrast was found to be greater at the points of fixation when compared to either the contrast for image patches extracted at random locations or at the observed fixation locations using an image-shuffled database. Contrary to some results and in agreement with other results in the literature, a significant decorrelation of image intensity is observed between the locations of fixation and other neighboring locations. A discussion and analysis of methodological techniques is given that provides an explanation for the discrepancy in results. The results of our analyses indicate that both the local contrast and correlation at the points of fixation are a function of image type and, furthermore, that the magnitude of these effects depend on the levels of contrast and correlation present overall in the images. Finally, the largest effect sizes in local contrast and correlation are found at distances of approximately 1 deg of visual angle, which agrees well with measures of optimal spatial scale selectivity in the visual periphery where visual information for potential saccade targets is processed.

Attention↗

Modeling the role of salience in the allocation of overt visual attention.

A biologically motivated computational model of bottom-up visual selective attention was used to examine the degree to which stimulus salience guides the allocation of attention. Human eye movements were recorded while participants viewed a series of digitized images of complex natural and artificial scenes. Stimulus dependence of attention, as measured by the correlation between computed stimulus salience and fixation locations, was found to be significantly greater than that expected by chance alone and furthermore was greatest for eye movements that immediately follow stimulus onset. The ability to guide attention of three modeled stimulus features (color, intensity and orientation) was examined and found to vary with image type. Additionally, the effect of the drop in visual sensitivity as a function of eccentricity on stimulus salience was examined, modeled, and shown to be an important determiner of attentional allocation. Overall, the results indicate that stimulus-driven, bottom-up mechanisms contribute significantly to attentional guidance under natural viewing conditions.

Analysis of Variance↗

Synchrony: a neuronal mechanism for attentional selection?

Attentional selection involves brain processes that select and control the flow of information into the mechanisms that underlie perception and consciousness. One theory proposes that the neural activity that represents the stimuli or events to be attended to is selected through modification of its synchrony. Recent experimental evidence supports this theory, by showing that changes in attentional focus increase the synchrony of neural firing in some neuron pairs and decrease it in others.

Animals↗

Variable-resolution displays: a theoretical, practical, and behavioral evaluation.

Variable-resolution display techniques present visual information in a display using more than one resolution. For example, gaze-contingent variable-resolution displays allocate computational resources for image generation preferentially to the area around the center of gaze, where visual sensitivity to detail is the greatest. Using such displays reduces the amount of computational resources required as compared with traditional uniform-resolution displays. The theoretical benefits, implementational issues, and behavioral consequences of variable-resolution displays are reviewed. A mathematical analysis of computational efficiency for a two-region variable-resolution display is conducted. The results are discussed in relation to applications that are limited by computational resources, such as virtual reality, and applications that are limited by bandwidth, such as internet image transmission. The potential for variable-resolution display techniques as a viable future technology is discussed.

Attention↗

Electrophysiological correlates of synchronous neural activity and attention: a short review.

Attentional selection implies preferential treatment of some sensory stimuli over others. This requires differential representation of attended and unattended stimuli. Most previous research has focused on pure rate codes for this representation but recent evidence indicates that a mixed code, involving both mean firing rate and temporal codes, may be employed. Of particular interest is a distinction of attended from unattended stimuli based on synchrony within neural populations. I review electrophysiological evidence at macroscopic, mesoscopic and microscopic spatial scales showing that the degree of synchronous activity varies with the attentional state of the perceiving organism.

Animals↗