Mikhail Katkov

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Analytical calculations show that two-alternative force-choice data are not always suitable for specifying the parameters of the underlying discrimination model. Experimentally, we show here that in the case of contrast discrimination in humans, a variety of models spanning a large range of parameters can explain the data within an experimental error.(More)
In serial recall experiments, human subjects are requested to retrieve a list of words in the same order as they were presented. In a classical study, participants were reported to recall more words from study lists composed of short words compared to lists of long words, the word length effect. The world length effect was also observed in free recall(More)
A basic problem in psychophysics is recovering the mean internal response and noise amplitude from sensory discrimination data. Since these components cannot be estimated independently, several indirect methods were suggested to resolve this issue. Here we analyze the two-alternative force-choice method (2AFC), using a signal detection theory approach, and(More)
Psychological studies indicate that human ability to keep information in readily accessible working memory is limited to four items for most people. This extremely low capacity severely limits execution of many cognitive tasks, but its neuronal underpinnings remain unclear. Here we show that in the framework of synaptic theory of working memory, capacity(More)
Klein [Klein, A. S. (2006). Separating transducer nonlinearities and multiplicative noise in contrast discrimination. Vision Research, 46, 4279–4293] questions the existence of intrinsic singularities in two-alternative force-choice (2AFC) Signal Detection Theory (SDT) models, suggesting that the singularities found in Katkov et al. [Katkov, M., Tsodyks,(More)
Human memory stores vast amounts of information. Yet recalling this information is often challenging when specific cues are lacking. Here we consider an associative model of retrieval where each recalled item triggers the recall of the next item based on the similarity between their long-term neuronal representations. The model predicts that different items(More)
Human memory can store large amount of information. Nevertheless, recalling is often a challenging task. In a classical free recall paradigm, where participants are asked to repeat a briefly presented list of words, people make mistakes for lists as short as 5 words. We present a model for memory retrieval based on a Hopfield neural network where transition(More)