Attractive and repulsive serial dependence: The role of task relevance, the passage of time, and the number of stimuli
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Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...
Decisions about a current visual stimulus are systematically biased by recently encountered stimuli, a phenomenon known as serial dependence. In human vision, for instance, we tend to report the features of current images as more similar â i.e., an attra ...
Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...
Recent work suggests that the individual alpha peak frequency (IAPF) reflects the temporal resolution of visual processing: individuals with higher IAPF can segregate stimuli at shorter intervals compared to those with lower IAPF. However, this evidence ma ...
To fully comprehend visual perception, we need to necessarily understand its temporal dimension. Our visual environment is highly dynamic, requiring the processing and integration of temporal signals in order to make sense of it. Many processes, such as th ...
In the last few years, stroke ranked as the second most common cause of death and is the third most significant condition affecting disability-adjusted life years (DALYs) worldwide. Being the most prevalent and quality of life impacting post-stroke symptom ...
Recent work suggests that serial dependence, where perceptual decisions are biased toward previous stimuli, arises from the prior that sensory input is temporally correlated. However, existing studies have mostly used random stimulus sequences that do not ...
Recent work indicates that visual features are processed in a serially dependent manner: The decision about a stimulus feature in the present is influenced by the features of stimuli seen in the past, leading to serial dependence. It remains unclear, howev ...
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...
Aversively-motivated associative learning allows animals to avoid harm and thus ensures survival. Aversive learning can be studied by the fear learning paradigm, in which an innocuous sensory stimulus like a tone (conditioned stimulus, CS), acquires a nega ...