Rémy Allard

Crowding in a detection task: External noise triggers change in processing strategy

External noise paradigms have been widely used to probe different levels of visual processing (Pelli & Farell, 1999). A basic assumption of this paradigm is that the processing strategy is noise-invariant, remaining the same in low and high external noise. We tested this assumption by examining crowding in a detection task where traditionally crowding has no effect. In the first experiment, we measured detection thresholds for a vertically oriented sine wave grating (target) surrounded by four sine wave gratings (flankers) that were either vertically or horizontally oriented. At low noise levels, the detection threshold for the target was unaffected by the orientation of the flankers--there was no crowding. Surprisingly, however, there was crowding for detection at high noise levels: the threshold increased for the similarly-oriented flankers. This suggests that high noise triggered a change in processing strategy, increasing the range of space or features over which the visual signal was sampled. In a second experiment, we evaluated the impact of the spatial and temporal window of the noise on this crowding effect. Although crowding was observed for detection when the spatial and/or temporal window of the noise was localized (i.e. identical to the signal window), no crowding was observed when the noise was spatially and temporally extended (i.e. continuously displayed, full screen dynamic noise). Our results show that certain spatiotemporal distributions of external noise can elicit a change in processing strategy, invalidating the noise-invariant assumption that underlies external noise paradigms. In contrast, spatiotemporally extended noise maintains the required noise-indifference, perhaps because it matches the characteristics of the internal noise that determines the contrast threshold in low noise.

To characterize contrast detection, noise should be extended, not localized

Adding noise to a stimulus is useful to characterize visual processing. To avoid triggering a processing strategy shift between the processing in low and high noise, Allard and Cavanagh (2011) recommended using noise that is extended as a function of all dimensions such as space, time, frequency and orientation. Contrariwise, to avoid cross-channel suppression affecting contrast detection, Baker and Meese (2012) suggested using noise that is localized as a function of all dimensions, namely “0D noise,” which basically consists in randomly jittering the target contrast (and, for blank intervals or catch trials, jittering the contrast of an identical zero-contrast signal). Here we argue that contrast thresholds in extended noise are not contaminated by noise-induced cross-channel suppression because contrast gains affect signal and noise by the same proportion leaving the signal-to-noise ratio intact. We also review empirical findings showing that detecting a target in 0D noise involves a different processing strategy than detecting in absence of noise or in extended noise. Given that internal noise is extended as a function of all dimensions, we therefore recommend using external noise that is also extended as a function of all dimensions when assuming that the same processing strategy operates in low and high noise.

Maximizing noise energy for noise-masking studies

Noise-masking experiments are widely used to investigate visual functions. To be useful, noise generally needs to be strong enough to noticeably impair performance, but under some conditions, noise does not impair performance even when its contrast approaches the maximal displayable limit of 100xa0%. To extend the usefulness of noise-masking paradigms over a wider range of conditions, the present study developed a noise with great masking strength. There are two typical ways of increasing masking strength without exceeding the limited contrast range: use binary noise instead of Gaussian noise or filter out frequencies that are not relevant to the task (i.e., which can be removed without affecting performance). The present study combined these two approaches to further increase masking strength. We show that binarizing the noise after the filtering process substantially increases the energy at frequencies within the pass-band of the filter given equated total contrast ranges. A validation experiment showed that similar performances were obtained using binarized-filtered noise and filtered noise (given equated noise energy at the frequencies within the pass-band) suggesting that the binarization operation, which substantially reduced the contrast range, had no significant impact on performance. We conclude that binarized-filtered noise (and more generally, truncated-filtered noise) can substantially increase the energy of the noise at frequencies within the pass-band. Thus, given a limited contrast range, binarized-filtered noise can display higher energy levels than Gaussian noise and thereby widen the range of conditions over which noise-masking paradigms can be useful.

Internal noise sources limiting contrast sensitivity

Contrast sensitivity varies substantially as a function of spatial frequency and luminance intensity. The variation as a function of luminance intensity is well known and characterized by three laws that can be attributed to the impact of three internal noise sources: early spontaneous neural activity limiting contrast sensitivity at low luminance intensities (i.e. early noise responsible for the linear law), probabilistic photon absorption at intermediate luminance intensities (i.e. photon noise responsible for de Vries-Rose law) and late spontaneous neural activity at high luminance intensities (i.e. late noise responsible for Weber’s law). The aim of this study was to characterize how the impact of these three internal noise sources vary with spatial frequency and determine which one is limiting contrast sensitivity as a function of luminance intensity and spatial frequency. To estimate the impact of the different internal noise sources, the current study used an external noise paradigm to factorize contrast sensitivity into equivalent input noise and calculation efficiency over a wide range of luminance intensities and spatial frequencies. The impact of early and late noise was found to drop linearly with spatial frequency, whereas the impact of photon noise rose with spatial frequency due to ocular factors.

Adding temporally localized noise can enhance the contribution of target knowledge on contrast detection

External noise paradigms are widely used to characterize sensitivity by comparing the effect of a variable on contrast threshold when it is limited by internal versus external noise. A basic assumption of external noise paradigms is that the processing properties are the same in low and high noise. However, recent studies (e.g., Allard & Cavanagh, 2011; Allard & Faubert, 2014b) suggest that this assumption could be violated when using spatiotemporally localized noise (i.e., appearing simultaneously and at the same location as the target) but not when using spatiotemporally extended noise (i.e., continuously displayed, full-screen, dynamic noise). These previous findings may have been specific to the crowding and 0D noise paradigms that were used, so the purpose of the current study is to test if this violation of noise-invariant processing also occurs in a standard contrast detection task in white noise. The rationale of the current study is that local external noise triggers the use of recognition rather than detection and that a recognition process should be more affected by uncertainty about the shape of the target than one involving detection. To investigate the contribution of target knowledge on contrast detection, the effect of orientation uncertainty was evaluated for a contrast detection task in the absence of noise and in the presence of spatiotemporally localized or extended noise. A larger orientation uncertainty effect was observed with temporally localized noise than with temporally extended noise or with no external noise, indicating a change in the nature of the processing for temporally localized noise. We conclude that the use of temporally localized noise in external noise paradigms risks triggering a shift in process, invalidating the noise-invariant processing required for the paradigm. If, instead, temporally extended external noise is used to match the properties of internal noise, no such processing change occurs.

Reducing luminance intensity can improve motion perception in noise

Visual perception generally improves under brighter environments. For instance, motion sensitivity is known to improve with luminance intensity especially at high temporal frequencies. However, the current study counter-intuitively shows that increasing luminance intensity can impair motion sensitivity in noise. Motion sensitivity was measured with and without noise added to a drifting Gabor patch as a function of the temporal frequency and luminance intensity. As expected, motion sensitivity in absence of noise reached a ceiling performance at a relatively low luminance intensity (about 35 td) for low temporal frequencies and improved with luminance intensity up to the highest luminance intensity tested (353 td) for high temporal frequencies. In noise, reducing mean luminance intensity facilitated motion sensitivity (up to a factor of about 1.7) for temporal frequencies up to 7.5u2009Hz and impaired sensitivity at higher temporal frequencies (15 and 30u2009Hz). We conclude that reducing luminance intensity is effectively equivalent to applying a low-pass filter, which can improve motion sensitivity in noise to low and middle temporal frequencies. This counterintuitive facilitation effect can be explained by two known properties of the visual system: decreasing luminance intensity impairs the visibility of high temporal frequencies (equivalent to a low-pass filter) and motion detectors are broadly tuned.

Factorizing the motion sensitivity function into equivalent input noise and calculation efficiency

The photopic motion sensitivity function of the energy-based motion system is band-pass peaking around 8 Hz. Using an external noise paradigm to factorize the sensitivity into equivalent input noise and calculation efficiency, the present study investigated if the variation in photopic motion sensitivity as a function of the temporal frequency is due to a variation of equivalent input noise (e.g., early temporal filtering) or calculation efficiency (ability to select and integrate motion). For various temporal frequencies, contrast thresholds for a direction discrimination task were measured in presence and absence of noise. Up to 15 Hz, the sensitivity variation was mainly due to a variation of equivalent input noise and little variation in calculation efficiency was observed. The sensitivity fall-off at very high temporal frequencies (from 15 to 30 Hz) was due to a combination of a drop of calculation efficiency and a rise of equivalent input noise. A control experiment in which an artificial temporal integration was applied to the stimulus showed that an early temporal filter (generally assumed to affect equivalent input noise, not calculation efficiency) could impair both the calculation efficiency and equivalent input noise at very high temporal frequencies. We conclude that at the photopic luminance intensity tested, the variation of motion sensitivity as a function of the temporal frequency was mainly due to early temporal filtering, not to the ability to select and integrate motion. More specifically, we conclude that photopic motion sensitivity at high temporal frequencies is limited by internal noise occurring after the transduction process (i.e., neural noise), not by quantal noise resulting from the probabilistic absorption of photons by the photoreceptors as previously suggested.

Detection mechanisms selective to combinations of luminance- and contrast-modulations

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