On nonlinearity in neural encoding models applied to the primary visual cortex

Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansions of the input variables (enlarging the number of inputs) or train a simple but different model for each area of the data domain. Spline-based models are popular within the first category. Kernel smoothing methods fall into the second category. Whereas the first choice is useful for globally characterizing complex functions, the second is very handy for temporal data and is able to include inner-state subject variations. Also, interactions among stimuli are considered. We compare state-of-the-art firing rate prediction methods with some more sophisticated spline-based nonlinear methods: multivariate adaptive regression splines and sparse additive models. We also study the impact of kernel smoothing. Finally, we explore the combination of various local models in an incremental learning procedure. Our goal is to demonstrate that appropriate nonlinearity treatment can greatly improve the results. We test our hypothesis on both synthetic data and real neuronal recordings in cat primary visual cortex, giving a plausible explanation of the results from a biological perspective.

A model of the mammalian retina and the visual cortex. Disorders of vision

A model of the mammalian retina and the behavior of the first layers in the visual cortex is reported. The building blocks are optically programmable logic cells. A model of the retina, similar to the one reported by Dowling (1987) is presented. From the model of the visual cortex obtained, some types of symmetries and asymmetries are possible to be detected

Image characterisation based on the mammalian visual cortex

A proposal for a model of the primary visual cortex is reported. It is structured with the basis of a simple unit cell able to perform fourteen pairs of different boolean functions corresponding to the two possible inputs. As a first step, a model of the retina is presented. Different types of responses, according to the different possibilities of interconnecting the building blocks, have been obtained. These responses constitute the basis for an initial configuration of the mammalian primary visual cortex. Some qualitative functions, as symmetry or size of an optical input, have been obtained. A proposal to extend this model to some higher functions, concludes the paper.

An approach to visual cortex operation: optical neuron model

Several works have been published in the last years concerning the modelling and implementation of the visual cortex operation. Most of them present simple neurons with just two different responses, namely inhibitory and excitatory. Some of the different types of visual cortex cells are simulated in these configurations.

An approach to a model of the visual cortex: disorders of vision

One of the most challenging problems that must be solved by any theoretical model purporting to explain the competence of the human brain for relational tasks is the one related with the analysis and representation of the internal structure in an extended spatial layout of múltiple objects. In this way, some of the problems are related with specific aims as how can we extract and represent spatial relationships among objects, how can we represent the movement of a selected object and so on. The main objective of this paper is the study of some plausible brain structures that can provide answers in these problems. Moreover, in order to achieve a more concrete knowledge, our study will be focused on the response of the retinal layers for optical information processing and how this information can be processed in the first cortex layers. The model to be reported is just a first trial and some major additions are needed to complete the whole vision process.

Photonic processing subsystem based on visual cortex architecture

Optical signal processing in any living being is more complex than the one obtained in artificial systems. Cortex architecture, although only partly known, gives some useful ideas to be employed in communications. To analyze some of these structures is the objective of this paper. One of the main possibilities reported is handling signals in a parallel way. As it is shown, according to the signal characteristics each signal impinging onto a single input may be routed to a different output. At the same time, identical signals, coming to different inputs, may be routed to the same output without internal conflicts. This is due to the change of some of their characteristics in the way out when going through the intermediate levels. The simulation of this architecture is based on simple logic cells. The basis for the proposed architecture is the five layers of the mammalian retina and the first levels of the visual cortex.

Dynamic gamma frequency feedback coupling between higher and lower order visual cortices underlies perceptual completion in humans

To perceive a coherent environment, incomplete or overlapping visual forms must be integrated into meaningful coherent percepts, a process referred to as ?Gestalt? formation or perceptual completion. Increasing evidence suggests that this process engages oscillatory neuronal activity in a distributed neuronal assembly. A separate line of evidence suggests that Gestalt formation requires top-down feedback from higher order brain regions to early visual cortex. Here we combine magnetoencephalography (MEG) and effective connectivity analysis in the frequency domain to specifically address the effective coupling between sources of oscillatory brain activity during Gestalt formation. We demonstrate that perceptual completion of two-tone ?Mooney? faces induces increased gamma frequency band power (55?71 Hz) in human early visual, fusiform and parietal cortices. Within this distributed neuronal assembly fusiform and parietal gamma oscillators are coupled by forward and backward connectivity during Mooney face perception, indicating reciprocal influences of gamma activity between these higher order visual brain regions. Critically, gamma band oscillations in early visual cortex are modulated by top-down feedback connectivity from both fusiform and parietal cortices. Thus, we provide a mechanistic account of Gestalt perception in which gamma oscillations in feature sensitive and spatial attention-relevant brain regions reciprocally drive one another and convey global stimulus aspects to local processing units at low levels of the sensory hierarchy by top-down feedback. Our data therefore support the notion of inverse hierarchical processing within the visual system underlying awareness of coherent percepts.

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.

Lateral orbitofrontal cortex involvement in initial negative aesthetic impression formation

It is well established that aesthetic appreciation is related with activity in several different brain regions. The identification of the neural correlates of beauty or liking ratings has been the focus of most prior studies. Not much attention has been directed towards the fact that humans are surrounded by objects that lead them to experience aesthetic indifference or leave them with a negative aesthetic impression. Here we explore the neural substrate of such experiences. Given the neuroimaging techniques that have been used, little is known about the temporal features of such brain activity. By means of magnetoencephalography we registered the moment at which brain activity differed while participants viewed images they considered to be beautiful or not. Results show that the first differential activity appears between 300 and 400 ms after stimulus onset. During this period activity in right lateral orbitofrontal cortex (lOFC) was greater while participants rated visual stimuli as not beautiful than when they rated them as beautiful. We argue that this activity is associated with an initial negative aesthetic impression formation, driven by the relative hedonic value of stimuli regarded as not beautiful. Additionally, our results contribute to the understanding of the nature of the functional roles of the lOFC.