AIMC Topic: Photic Stimulation

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Attentional responses in toddlers: A protocol for assessing the impact of a robotic animated animal and a real dog.

PloS one
BACKGROUND: Attentional processes in toddlers are characterized by a state of alertness in which they focus their waking state for short periods. It is essential to develop assessment and attention stimulation protocols from an early age to improve t...

A simplified minimodel of visual cortical neurons.

Nature communications
Artificial neural networks (ANNs) have been shown to predict neural responses in primary visual cortex (V1) better than classical models. However, this performance often comes at the expense of simplicity and interpretability. Here we introduce a new...

Spatial reasoning via recurrent neural dynamics in mouse retrosplenial cortex.

Nature neuroscience
From visual perception to language, sensory stimuli change their meaning depending on previous experience. Recurrent neural dynamics can interpret stimuli based on externally cued context, but it is unknown whether they can compute and employ interna...

Evaluating the capacity of large language models to interpret emotions in images.

PloS one
The integration of artificial intelligence, specifically large language models (LLMs), in emotional stimulus selection and validation offers a promising avenue for enhancing emotion comprehension frameworks. Traditional methods in this domain are oft...

Brain-guided convolutional neural networks reveal task-specific representations in scene processing.

Scientific reports
Scene categorization is the dominant proxy for visual understanding, yet humans can perform a large number of visual tasks within any scene. Consequently, we know little about how different tasks change how a scene is processed, represented, and its ...

Neural correlates of the uncanny valley effect for robots and hyper-realistic masks.

PloS one
Viewing artificial objects and images that are designed to appear human can elicit a sense of unease, referred to as the 'uncanny valley' effect. Here we investigate neural correlates of the uncanny valley, using still images of androids (robots desi...

Pre-training artificial neural networks with spontaneous retinal activity improves motion prediction in natural scenes.

PLoS computational biology
The ability to process visual stimuli rich with motion represents an essential skill for animal survival and is largely already present at the onset of vision. Although the exact mechanisms underlying its maturation remain elusive, spontaneous activi...

Configural processing as an optimized strategy for robust object recognition in neural networks.

Communications biology
Configural processing, the perception of spatial relationships among an object's components, is crucial for object recognition, yet its teleology and underlying mechanisms remain unclear. We hypothesize that configural processing drives robust recogn...

Machine learning analysis of cortical activity in visual associative learning tasks with differing stimulus complexity.

Physiology international
Associative learning tests are cognitive assessments that evaluate the ability of individuals to learn and remember relationships between pairs of stimuli. The Rutgers Acquired Equivalence Test (RAET) is an associative learning test that utilizes ima...

Enhancing detection of SSVEPs using discriminant compacted network.

Journal of neural engineering
. Steady-state visual evoked potential-based brain-computer interfaces (SSVEP-BCIs) have gained significant attention due to their simplicity, high signal to noise ratio and high information transfer rates (ITRs). Currently, accurate detection is a c...