AIMC Topic: Photic Stimulation

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Maintaining visual stability in naturalistic scenes: The roles of trans-saccadic memory and default assumptions.

Cognition
How is visual stability maintained across saccades? One theory poses the visual system has an underlying assumption that the visual world has not changed during the saccade, and scrutinization of trans-saccadic memory occurs only when there is strong...

Concurrent emergence of view invariance, sensitivity to critical features, and identity face classification through visual experience: Insights from deep learning algorithms.

Journal of vision
Visual experience is known to play a critical role in face recognition. This experience is thought to enable the formation of a view-invariant representation by learning which features are critical to identify faces across views. Discovering these cr...

Data augmentation using masked principal component representation for deep learning-based SSVEP-BCIs.

Journal of neural engineering
Data augmentation has been demonstrated to improve the classification accuracy of deep learning models in steady-state visual evoked potential-based brain-computer interfaces (BCIs), particularly when dealing with limited electroencephalography (EEG)...

Does surface completion fail to support uncrowding?

Journal of vision
In crowding, perception of a target deteriorates in the presence of nearby elements. As the entire stimulus configuration across large parts of the visual field influences crowding and not just nearby elements, low-level explanations, such as local p...

Stimulus Selection Influences Prediction of Individual Phenotypes in Naturalistic Conditions.

Human brain mapping
While the use of naturalistic stimuli such as movie clips for understanding individual differences and brain-behaviour relationships attracts increasing interest, the influence of stimulus selection remains largely unclear. By using machine learning ...

A robotics-inspired scanpath model reveals the importance of uncertainty and semantic object cues for gaze guidance in dynamic scenes.

Journal of vision
The objects we perceive guide our eye movements when observing real-world dynamic scenes. Yet, gaze shifts and selective attention are critical for perceiving details and refining object boundaries. Object segmentation and gaze behavior are, however,...

Convolutional neural networks uncover the dynamics of human visual memory representations over time.

Cerebral cortex (New York, N.Y. : 1991)
The ability to accurately retrieve visual details of past events is a fundamental cognitive function relevant for daily life. While a visual stimulus contains an abundance of information, only some of it is later encoded into long-term memory represe...

Human Visual Pathways for Action Recognition versus Deep Convolutional Neural Networks: Representation Correspondence in Late but Not Early Layers.

Journal of cognitive neuroscience
Deep convolutional neural networks (DCNNs) have attained human-level performance for object categorization and exhibited representation alignment between network layers and brain regions. Does such representation alignment naturally extend to other v...

Convolutional neural network models applied to neuronal responses in macaque V1 reveal limited nonlinear processing.

Journal of vision
Computational models of the primary visual cortex (V1) have suggested that V1 neurons behave like Gabor filters followed by simple nonlinearities. However, recent work employing convolutional neural network (CNN) models has suggested that V1 relies o...