scholarly journals Image statistics at the point of gaze during human navigation

2009 ◽  
Vol 26 (1) ◽  
pp. 81-92 ◽  
Author(s):  
CONSTANTIN A. ROTHKOPF ◽  
DANA H. BALLARD
Keyword(s):  
Visual System ◽  
Selection Process ◽  
Human Subjects ◽  
Image Features ◽  
Complex Cells ◽  
Cell Responses ◽  
Active Selection ◽  
Active Nature ◽  
Simple And Complex Cells ◽  
Distinct Features

AbstractTheories of efficient sensory processing have considered the regularities of image properties due to the structure of the environment in order to explain properties of neuronal representations of the visual world. The regularities imposed on the input to the visual system due to the regularities of the active selection process mediated by the voluntary movements of the eyes have been considered to a much lesser degree. This is surprising, given that the active nature of vision is well established. The present article investigates statistics of image features at the center of gaze of human subjects navigating through a virtual environment and avoiding and approaching different objects. The analysis shows that contrast can be significantly higher or lower at fixation location compared to random locations, depending on whether subjects avoid or approach targets. Similarly, significant differences in the distribution of responses of model simple and complex cells between horizontal and vertical orientations are found over timescales of tens of seconds. By clustering the model simple cell responses, it is established that gaze was directed toward three distinct features of intermediate complexity the vast majority of time. Thus, this study demonstrates and quantifies how the visuomotor tasks of approaching and avoiding objects during navigation determine feature statistics of the input to the visual system through the combined influence on body and eye movements.

Complex Cells Increase Their Phase Sensitivity at Low Contrasts and Following Adaptation

2007 ◽  
Vol 98 (3) ◽  
pp. 1155-1166 ◽  
Author(s):  
N. A. Crowder ◽  
J. van Kleef ◽  
B. Dreher ◽  
M. R. Ibbotson
Keyword(s):  
Receptive Fields ◽  
Phase Sensitivity ◽  
Complex Cells ◽  
Spike Threshold ◽  
Cell Responses ◽  
Layer 4 ◽  
A Cell ◽  
Phase Sensitive ◽  
Simple And Complex Cells ◽  
Mean Time

One of the best-known dichotomies in neuroscience is the division of neurons in the mammalian primary visual cortex into simple and complex cells. Simple cells have receptive fields with separate on and off subregions and give phase-sensitive responses to moving gratings, whereas complex cells have uniform receptive fields and are phase invariant. The phase sensitivity of a cell is calculated as the ratio of the first Fourier coefficient ( F1) to the mean time-average ( F0) of the response to moving sinusoidal gratings at 100% contrast. Cells are then classified as simple ( F1/ F0>1) or complex ( F1/ F0<1). We manipulated cell responses by changing the stimulus contrast or through adaptation. The F1/ F0ratios of cells defined as complex at 100% contrast increased at low contrasts and following adaptation. Conversely, the F1/ F0ratios remained constant for cells defined as simple at 100% contrast. The latter cell type was primarily located in thalamorecipient layers 4 and 6. Many cells initially classified as complex exhibit F1/ F0>1 at low contrasts and after adaptation (particularly in layer 4). The results are consistent with the spike-threshold hypothesis, which suggests that the division of cells into two types arises from the nonlinear interaction of spike threshold with membrane potential responses.

Quantum-like signal-tuned approach to V1 modeling

2019 ◽  
Vol 30 (05) ◽  
pp. 1950032
Author(s):  
José R. A. Torreão ◽  
Marcos S. Amaral
Keyword(s):  
Receptive Fields ◽  
Spatial Summation ◽  
Cortical Cells ◽  
Complex Cells ◽  
Cell Responses ◽  
Gabor Functions ◽  
Half Wave ◽  
Plausible Model ◽  
Simple And Complex Cells ◽  
Carry Over

Signal-tuned Gabor functions — Gaussian-modulated sinusoids whose parameters are determined by a spatial or spectral “tuning signal” — have previously been shown to provide a plausible model for the stimulus-dependent receptive fields and responses of the simple and complex cells of the primary visual cortex (V1). The signal-tuned responses obey Schrödinger equations, which has led to the proposal of a quantum-like model for V1 cells: by considering the squared magnitude of a particular signal-tuned wave function as a probability density, one arrives at a Poisson spiking process which appears consistent with the neurophysiological findings. Here, by incorporating Hermite-polynomial factors to the signal-tuned Gabor functions, we obtain a generalized quantum-like signal-tuned model for which further relevant properties are demonstrated, such as receptive-field coding of the stimulus and its derivatives, saturating spatial summation curves and half-wave rectification of the simple cell responses. Although only a one-dimensional approach is considered here, such properties will carry over to a two-dimensional model, in which case, as our preliminary analysis indicates, end-stopping — another important feature of cortical cells — can also be accommodated.

scholarly journals A Model of the Early Visual System Based on Parallel Spike-Sequence Detection, Showing Orientation Selectivity

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 801
Author(s):  
Alejandro Santos-Mayo ◽  
Stephan Moratti ◽  
Javier de Echegaray ◽  
Gianluca Susi
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Human Subjects ◽  
Basic Feature ◽  
Image Features ◽  
Orientation Selectivity ◽  
Model Parameters ◽  
Sequence Detection ◽  
Model Response ◽  
Evoked Activity

Since the first half of the twentieth century, numerous studies have been conducted on how the visual cortex encodes basic image features. One of the hallmarks of basic feature extraction is the phenomenon of orientation selectivity, of which the underlying neuronal-level computational mechanisms remain partially unclear despite being intensively investigated. In this work we present a reduced visual system model (RVSM) of the first level of scene analysis, involving the retina, the lateral geniculate nucleus and the primary visual cortex (V1), showing orientation selectivity. The detection core of the RVSM is the neuromorphic spike-decoding structure MNSD, which is able to learn and recognize parallel spike sequences and considerably resembles the neuronal microcircuits of V1 in both topology and operation. This structure is equipped with plasticity of intrinsic excitability to embed recent findings about V1 operation. The RVSM, which embeds 81 groups of MNSD arranged in 4 oriented columns, is tested using sets of rotated Gabor patches as input. Finally, synthetic visual evoked activity generated by the RVSM is compared with real neurophysiological signal from V1 area: (1) postsynaptic activity of human subjects obtained by magnetoencephalography and (2) spiking activity of macaques obtained by multi-tetrode arrays. The system is implemented using the NEST simulator. The results attest to a good level of resemblance between the model response and real neurophysiological recordings. As the RVSM is available online, and the model parameters can be customized by the user, we propose it as a tool to elucidate the computational mechanisms underlying orientation selectivity.

Computing relative motion with complex cells

2005 ◽  
Vol 22 (2) ◽  
pp. 225-236 ◽  
Author(s):  
BABETTE K. DELLEN ◽  
JOHN W. CLARK ◽  
RALF WESSEL
Keyword(s):  
Relative Motion ◽  
Cell Model ◽  
Neural Representation ◽  
Complex Cell ◽  
Contextual Influences ◽  
Complex Cells ◽  
Cell Responses ◽  
Motion Computation ◽  
Model Tuning ◽  
Simple And Complex Cells

Contextual influences shape our perception of local visual stimuli. Relative-motion stimuli represent an important contextual influence, yet the mechanism subserving relative-motion computation remains largely unknown. In the present work, we investigated the responses of an established model for simple and complex cells to relative-motion stimuli. A straightforward mathematical analysis showed that relative-motion computation is inherent in the nonlinear transformation of the complex-cell model. Tuning to relative velocity is achieved by applying a temporal filter to the complex-cell response. The mathematical inference is supported by simulations that quantitatively reproduce measured complex-cell responses in both cat and monkey to a variety of relative-motion stimuli. Importantly, the posited mechanism for cortical computation of relative motion does not require an intermediate neural representation of local velocities and does not require lateral or feedback interactions within a network.

scholarly journals Selection of visual information for lightness judgements by eye movements

2013 ◽  
Vol 368 (1628) ◽  
pp. 20130056 ◽  
Author(s):  
Matteo Toscani ◽  
Matteo Valsecchi ◽  
Karl R. Gegenfurtner
Keyword(s):  
Eye Movements ◽  
Visual System ◽  
Visual Information ◽  
Selection Process ◽  
Sampling Strategy ◽  
Selection Strategy ◽  
Eye Fixations ◽  
Target Layer ◽  
Highly Correlated ◽  
Selection Of

When judging the lightness of objects, the visual system has to take into account many factors such as shading, scene geometry, occlusions or transparency. The problem then is to estimate global lightness based on a number of local samples that differ in luminance. Here, we show that eye fixations play a prominent role in this selection process. We explored a special case of transparency for which the visual system separates surface reflectance from interfering conditions to generate a layered image representation. Eye movements were recorded while the observers matched the lightness of the layered stimulus. We found that observers did focus their fixations on the target layer, and this sampling strategy affected their lightness perception. The effect of image segmentation on perceived lightness was highly correlated with the fixation strategy and was strongly affected when we manipulated it using a gaze-contingent display. Finally, we disrupted the segmentation process showing that it causally drives the selection strategy. Selection through eye fixations can so serve as a simple heuristic to estimate the target reflectance.

scholarly journals MicroRNA-203 represses selection and expansion of oncogenic Hras transformed tumor initiating cells

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Kent Riemondy ◽  
Xiao-jing Wang ◽  
Enrique C Torchia ◽  
Dennis R Roop ◽  
Rui Yi
Keyword(s):  
Cell Division ◽  
Skin Cancer ◽  
Mouse Model ◽  
Mouse Models ◽  
Knockout Mouse ◽  
Selection Process ◽  
Tumor Initiating Cells ◽  
Knockout Mouse Model ◽  
Active Selection ◽  
The Impact

In many mouse models of skin cancer, only a few tumors typically form even though many cells competent for tumorigenesis receive the same oncogenic stimuli. These observations suggest an active selection process for tumor-initiating cells. Here, we use quantitative mRNA- and miR-Seq to determine the impact of HrasG12V on the transcriptome of keratinocytes. We discover that microRNA-203 is downregulated by HrasG12V. Using a knockout mouse model, we demonstrate that loss of microRNA-203 promotes selection and expansion of tumor-initiating cells. Conversely, restoration of microRNA-203 using an inducible model potently inhibits proliferation of these cells. We comprehensively identify microRNA-203 targets required for Hras-initiated tumorigenesis. These targets include critical regulators of the Ras pathway and essential genes required for cell division. This study establishes a role for the loss of microRNA-203 in promoting selection and expansion of Hras mutated cells and identifies a mechanism through which microRNA-203 antagonizes Hras-mediated tumorigenesis.

Selective effects of aging on simple and complex cells in primary visual cortex of rhesus monkeys

2012 ◽  
Vol 1470 ◽  
pp. 17-23 ◽  
Author(s):  
Zhen Liang ◽  
Hongxin Li ◽  
Yun Yang ◽  
Guangxing Li ◽  
Yong Tang ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Rhesus Monkeys ◽  
Complex Cells ◽  
Simple And Complex Cells ◽  
Effects Of Aging ◽  
Selective Effects

A Method of Image Affective Semantic Classification Based on Attribution Reduction

2014 ◽  
Vol 556-562 ◽  
pp. 4820-4824
Author(s):  
Ying Xia ◽  
Le Mi ◽  
Hae Young Bae
Keyword(s):  
Feature Selection ◽  
Rough Set ◽  
Classification Accuracy ◽  
Selection Process ◽  
Attribute Reduction ◽  
Image Features ◽  
Decision Table ◽  
Reduction Algorithm ◽  
Semantic Classification ◽  
Low Level

In study of image affective semantic classification, one problem is the low classification accuracy caused by low-level redundant features. To eliminate the redundancy, a novel image affective classification method based on attributes reduction is proposed. In this method, a decision table is built from the extraction of image features first. And then valid low-level features are determined through the feature selection process using the rough set attribute reduction algorithm. Finally, the semantic recognition is done using SVM. Experiment results show that the proposed method improves the accuracy in image affective semantic classification significantly.

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