Noise has been widely used to investigate the processing properties of various visual functions (e.g. detection, discrimination, attention, perceptual learning, averaging, crowding, face recognition), in various populations (e.g. older adults, amblyopes, migrainers, dyslexic children), using noise along various dimensions (e.g. pixel noise, orientation jitter, contrast jitter). The reason to use external noise is generally not to characterize visual processing in external noise per se, but rather to reveal how vision works in ordinary conditions, without externally added noise. For instance, reverse correlation aims at identifying the relevant information to perform a given task in noiseless conditions and measuring contrast thresholds in various noise levels can be used to measure factors limiting sensitivity in noiseless conditions (e.g. equivalent input noise and calculation efficiency).
Why use noise? Since Fechner named it, psychophysics has always emphasized the systematic investigation of conditions that break vision. External noise raises threshold hugely and selectively. In hearing, Fletcher used noise in his famous critical-band experiments to reveal frequency-selective channels in hearing. Critical bands have been found in vision too. More generally, the big reliable effects of noise give important clues to how the system works. And simple models have been proposed to account for the effects of visual noise.
As noise has been more widely used, questions have been raised about the simplifying assumptions that link the processing properties in noiseless conditions to measurements in external noise. For instance, it is usually assumed that the processing strategy (or mechanism) used to perform a task and its processing properties (e.g. filter tuning) are unaffected by the addition of external noise. Some have suggested that the processing properties could change with the addition of external noise (e.g. change in filter tuning or more lateral masking in noise), which would need to be considered before drawing conclusions about the processing properties in noiseless condition. Others have suggested that different processing properties (or mechanisms) could be solicited in low and high noise conditions, complicating the characterization of processing properties in noiseless condition based on processing properties identified in noise conditions. These recent findings welcome reinterpretation of previous findings made using visual noise.
The current Research Topic welcomes basic research that probes further into what the effects of visual noise tell us about vision in ordinary conditions. Do the processing strategies or processing properties change with noise level? Does it depend on the noise type? Which observer model should be used to fit and interpret data obtained in various noise levels? To address these issues, this Research Topic welcomes any articles addressing the use of noise to characterize ordinary vision.
Noise has been widely used to investigate the processing properties of various visual functions (e.g. detection, discrimination, attention, perceptual learning, averaging, crowding, face recognition), in various populations (e.g. older adults, amblyopes, migrainers, dyslexic children), using noise along various dimensions (e.g. pixel noise, orientation jitter, contrast jitter). The reason to use external noise is generally not to characterize visual processing in external noise per se, but rather to reveal how vision works in ordinary conditions, without externally added noise. For instance, reverse correlation aims at identifying the relevant information to perform a given task in noiseless conditions and measuring contrast thresholds in various noise levels can be used to measure factors limiting sensitivity in noiseless conditions (e.g. equivalent input noise and calculation efficiency).
Why use noise? Since Fechner named it, psychophysics has always emphasized the systematic investigation of conditions that break vision. External noise raises threshold hugely and selectively. In hearing, Fletcher used noise in his famous critical-band experiments to reveal frequency-selective channels in hearing. Critical bands have been found in vision too. More generally, the big reliable effects of noise give important clues to how the system works. And simple models have been proposed to account for the effects of visual noise.
As noise has been more widely used, questions have been raised about the simplifying assumptions that link the processing properties in noiseless conditions to measurements in external noise. For instance, it is usually assumed that the processing strategy (or mechanism) used to perform a task and its processing properties (e.g. filter tuning) are unaffected by the addition of external noise. Some have suggested that the processing properties could change with the addition of external noise (e.g. change in filter tuning or more lateral masking in noise), which would need to be considered before drawing conclusions about the processing properties in noiseless condition. Others have suggested that different processing properties (or mechanisms) could be solicited in low and high noise conditions, complicating the characterization of processing properties in noiseless condition based on processing properties identified in noise conditions. These recent findings welcome reinterpretation of previous findings made using visual noise.
The current Research Topic welcomes basic research that probes further into what the effects of visual noise tell us about vision in ordinary conditions. Do the processing strategies or processing properties change with noise level? Does it depend on the noise type? Which observer model should be used to fit and interpret data obtained in various noise levels? To address these issues, this Research Topic welcomes any articles addressing the use of noise to characterize ordinary vision.
