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Mert, B.

Publications and source records attributed to Mert, B..

2 recordsLinked to original sources

More is better: Improved visual discrimination through local feature diversity in naturalistic objects

Visual discrimination is traditionally studied with highly controlled, artificial stimuli such as gratings. Yet real-world object discrimination relies on many interacting image dimensions. Here we compared human discrimination performance of oriented gratings with that of natural object morphs, and then asked which stimulus dimensions are most important for morph discrimination. In Experiment 1, participants discriminated between two artificial gratings, two natural grating-like textures, and two natural, morphed stimuli. Morph stimuli were discriminated faster and over a larger stimulus range. In Experiment 2, we separated the contribution of distinct image features, specifically colour, texture, and shape, to the discriminability of the morph stimuli. To this end, we varied two feature dimensions at a time while keeping the third dimension constant. Discrimination was best when colour and texture varied together, resulting in steeper psychometric functions and faster responses than when shape changed. Together, these results suggest a discriminative advantage for natural-object morphs over gratings, driven primarily by local colour and texture information rather than global shape.

neuroscience↗

Thoughtful faces: inferring internal states across species using facial features

Animal behaviour is shaped to a large degree by internal cognitive states, but it is unknown whether these states are similar across species. To address this question, here we develop a virtual reality setup in which male mice and macaques engage in the same naturalistic visual foraging task. We exploit the richness of a wide range of facial features extracted from video recordings during the task, to train a Markov-Switching Linear Regression (MSLR). By doing so, we identify, on a singletrial basis, a set of internal states that reliably predicts when the animals are going to react to the presented stimuli. Even though the model is trained purely on reaction times, it can also predict task outcome, supporting the behavioural relevance of the inferred states. The relationship of the identified states to task performance is comparable between mice and monkeys. Furthermore, each state corresponds to a characteristic pattern of facial features that partially overlaps between species, highlighting the importance of facial expressions as manifestations of internal cognitive states across species.

animal behavior and cognition↗