The visual encoding of graspable unfamiliar objects

Abstract

We explored by eye-tracking the visual encoding modalities of participants (N = 20) involved in a freeobservation task in which three repetitions of ten unfamiliar graspable objects were administered. Then, we analysed the temporal allocation (t = 1500ms) of visual-spatial attention to objects' manipulation (i.e., the part aimed at grasping the object) and functional (i.e., the part aimed at recognizing the function and identity of the object) areas. We found a reversed quadratic trend in the way participants visually explored the objects. Within the rst 750ms, participants tended to shift their gaze on the functional areas while decreasing their attention on the manipulation areas. Then, participants reversed this trend, decreasing their visual-spatial attention to the functional areas while relatively increasing xations to the manipulation areas. Crucially, the global amount of visual-spatial attention for objects' functional areas signi cantly decreased as an effect of stimuli repetition while remaining stable for the manipulation areas, thus indicating stimulus familiarity effects. These ndings support the action reappraisal theoretical approach, which considers object processing and tool use as abilities emerging from the integration among semantic, technical/mechanical, and sensorimotor knowledge.

The cortical thickness of the area PF of the left inferior parietal cortex mediates technical-reasoning skills

“…Transversally, in line with the above-discussed evolutionary perspective, neuro-archaeological research emphasized how the acquisition of tool-making abilities is correlated with the structural remodelling of the parietal regions 50 . Also, alongside middle-temporal and frontal areas, IPC is critically involved in integrating multiple information modalities (e.g., somatosensory, visual, auditory, and semantic) to generate representations usable in everyday-life technical problem-solving activities 51 – 56 .…”

Functional Characteristics and Coping Strategies among Rugby Athletes: A Cluster Analysis Approach

“…This indicates the positive impact of physical activity on cognitive flexibility throughout one’s entire lifespan [ 95 , 96 , 97 ]. Such a strong association between physical activity and cognitive flexibility highlights the need to view exercise not only as a means of preserving physical fitness but also as a valuable means of enhancing mental health and well-being [ 98 , 99 , 100 , 101 , 102 , 103 , 104 ].…”

DPVis: Automatic Visual Encoding Based on Deep Learning

“…The Softmax function must process the output layer results before the final model results can be achieved, as illustrated in (2). The multiclassification output sequences may be converted into relative probabilities using the Softmax function, which maps the output neurons to real values between 0-1 and guarantees that the normalized guaranteed sum is 1.…”

“…The efficiency of data visualization critically depends on the accuracy of visual encoding, which is the fundamental theory and core component of data visualization. Visual encoding refers to encoding the semantics and properties of data while following to certain principles and making full use of prior knowledge to reduce the time consumption of graphic perception and cognition [2]. Automatic visual encoding is performed utilizing defined visual encoding rules by conventional automatic visualization techniques.…”