Responses of Leaky Integrate-and-Fire Neurons to a Plurality of Stimuli in Their Receptive Fields

A fundamental question concerning the way the visual world is represented in our brain is how a cortical cell responds when its classical receptive field contains a plurality of stimuli. Two opposing models have been proposed. In the response-averaging model, the neuron responds with a weighted average of all individual stimuli. By contrast, in the probability-mixing model, the cell responds to a plurality of stimuli as if only one of the stimuli were present. Here we apply the probability-mixing and the response-averaging model to leaky integrate-and-fire neurons, to describe neuronal behavior based on observed spike trains. We first estimate the parameters of either model using numerical methods, and then test which model is most likely to have generated the observed data. Results show that the parameters can be successfully estimated and the two models are distinguishable using model selection

Visuel genkendelse ved template matching

A computational model of human visual recognition by comparison of stimulus patterns against memory representations is developed. Recognition is achieved by template matching (cross correlation). Invariance with respect to spatial position, size and orientation is obtained by coordinate transformations, and sensitivity to noise is reduced by Gaussian filtering.Themodel is implemented as a self-learning algorithm which is currently being tested with a sample of handwritten letters.Der udvikles en beregningsmæssig model for visuel genkendelse ved sammenligning af synsindtryk med hukommelsesbilleder. I modellen antages genkendelse at være baseret på template matching i form af krydskorrelation. Positions-, størrelses- og orienteringsinvarians opnås ved aksetransformationer, mens støjproblemet tackles ved gaussisk filtrering. Modellen er implementeret som et computerprogram, hvis anvendelsesområde for øjeblikket omfatter genkendelse af enkeltvis præsenterede todimensionale mønstre såsom håndskrevne bogstaver

Automatic Attraction of Visual Attention by Supraletter Features of Former Target Strings

Observers were trained to search for a particular horizontal string of 3 capital letters presented among similar strings consisting of exactly the same letters in different orders. The training was followed by a test in which the observers searched for a new target that was identical to one of the former distractors. The new distractor set consisted of the remaining former distractors plus the former target. On each trial, three letter-strings were displayed, which included the target string with a probability of .5. In Experiment 1, the strings were centered at different locations on the circumference of an imaginary circle around the fixation point. The training phase of Experiment 2 was similar, but in the test phase of the experiment, the strings were located in a vertical array centered on fixation, and in target-present arrays, the target always appeared at fixation. In both experiments, performance (d’) degraded on trials in which former targets were present, suggesting that the former targets automatically drew processing resources away from the current targets. Apparently, the two experiments showed automatic attraction of visual attention by supraletter features of former target strings

Neurons in Primate Visual Cortex Alternate between Responses to Multiple Stimuli in Their Receptive Field

A fundamental question concerning representation of the visual world in our brain is how a cortical cell responds when presented with more than a single stimulus. We find supportive evidence that most cells presented with a pair of stimuli respond predominantly to one stimulus at a time, rather than a weighted average response. Traditionally, the firing rate is assumed to be a weighted average of the firing rates to the individual stimuli (response-averaging model) (Bundesen et al., 2005). Here, we also evaluate a probability-mixing model (Bundesen et al., 2005), where neurons temporally multiplex the responses to the individual stimuli. This provides a mechanism by which the representational identity of multiple stimuli in complex visual scenes can be maintained despite the large receptive fields in higher extrastriate visual cortex in primates. We compare the two models through analysis of data from single cells in the middle temporal visual area (MT) of rhesus monkeys when presented with two separate stimuli inside their receptive field with attention directed to one of the two stimuli or outside the receptive field. The spike trains were modeled by stochastic point processes, including memory effects of past spikes and attentional effects, and statistical model selection between the two models was performed by information theoretic measures as well as the predictive accuracy of the models. As an auxiliary measure, we also tested for uni- or multimodality in interspike interval distributions, and performed a correlation analysis of simultaneously recorded pairs of neurons, to evaluate population behavior