Object representation: Dissociating contributions of outline and nonoutline contour information to the priming and online recognition of animals

AbstractWe applied high-density EEG to examine steady-state visual evoked potentials (SSVEPs) during a perceptual/semantic stimulus repetition design. SSVEPs are evoked oscillatory cortical responses at the same frequency as visual stimuli flickered at this frequency. In repetition designs, stimuli are presented twice with the repetition being task irrelevant. The cortical processing of the second stimulus is commonly characterized by decreased neuronal activity (repetition suppression). The behavioral consequences of stimulus repetition were examined in a companion reaction time pre-study using the same experimental design as the EEG study. During the first presentation of a stimulus, we confronted participants with drawings of familiar object images or object words, respectively. The second stimulus was either a repetition of the same object image (perceptual repetition; PR) or an image depicting the word presented during the first presentation (semantic repetition; SR)—all flickered at 15 Hz to elicit SSVEPs. The behavioral study revealed priming effects in both experimental conditions (PR and SR). In the EEG, PR was associated with repetition suppression of SSVEP amplitudes at left occipital and repetition enhancement at left temporal electrodes. In contrast, SR was associated with SSVEP suppression at left occipital and central electrodes originating in bilateral postcentral and occipital gyri, right middle frontal and right temporal gyrus. The conclusion of the presented study is twofold. First, SSVEP amplitudes do not only index perceptual aspects of incoming sensory information but also semantic aspects of cortical object representation. Second, our electrophysiological findings can be interpreted as neuronal underpinnings of perceptual and semantic priming.

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Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Frontiers of Environmental Science & Engineering ◽

10.1007/s11783-021-1430-6 ◽

2021 ◽

Vol 15 (6) ◽

Author(s):

Qiyun Zhu ◽

April Gu ◽

Dan Li ◽

Tianmu Zhang ◽

Lunhong Xiang ◽

...

Keyword(s):

Neural Network ◽

Online Recognition ◽

Network Algorithm ◽

Neural Network Algorithm

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Spanning the Face Space

Journal of Biological System ◽

10.1142/s0218339098000182 ◽

1998 ◽

Vol 06 (03) ◽

pp. 265-279 ◽

Cited By ~ 1

Author(s):

Shimon Edelman

Keyword(s):

Computational Modeling ◽

Object Representation ◽

Receptive Fields ◽

Computational Approach ◽

Face Representation ◽

Comprehensive Theory ◽

Visual Areas ◽

The Face ◽

Higher Visual Areas ◽

Perceptual Systems

The paper outlines a computational approach to face representation and recognition, inspired by two major features of biological perceptual systems: graded-profile overlapping receptive fields, and object-specific responses in the higher visual areas. This approach, according to which a face is ultimately represented by its similarities to a number of reference faces, led to the development of a comprehensive theory of object representation in biological vision, and to its subsequent psychophysical exploration and computational modeling.

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