It is well established that mammalian visual cortex possesses a large proportion of orientation-selective neurons. Attempts to measure the bandwidth of these mechanisms psychophysically have yielded highly variable results (∼6°–180°). Two stimulus factors have been proposed to account for this variability: spatial and temporal frequency; with several studies indicating broader bandwidths at low spatial and high temporal frequencies. We estimated orientation bandwidths using a classic overlay masking paradigm across a range of spatiotemporal frequencies (0.5, 2, and 8 c.p.d.; 1.6 and 12.5 Hz) with target and mask presented either monoptically or dichoptically. A standard three-parameter Gaussian model (amplitude and width, mean fixed at 0°) confirms that bandwidths generally increase at low spatial and high temporal frequencies. When incorporating an additional orientation-untuned (isotropic) amplitude component, however, we find that not only are the amplitudes of isotropic and orientation-tuned components highly dependent upon stimulus spatiotemporal frequency, but orientation bandwidths are highly invariant (∼30° half width half amplitude). These results suggest that previously reported spatiotemporally contingent bandwidth effects may have confounded bandwidth with isotropic (so-called cross-orientation) masking. Interestingly, the magnitudes of all monoptically derived parameter estimates were found to transfer dichoptically suggesting a cortical locus for both isotropic and orientation-tuned masking.

^{2}) with a linearized gamma. The 10.8-bit luminance resolution was achieved using bit-stealing. Stimuli were viewed through a bench-mounted mirror stereoscope to bring the eyes into alignment. Total viewing distance (including reflective path) was 57 cm.

*SD*= 20 pixels) against a gray background held at mean luminance. Target and masking stimuli were each created from independent noise sources on each trial. Noise was generated by assigning each pixel within a 128 × 128 × 64 matrix, a luminance value derived from a uniformly random distribution of values between −1 and 1. The dc component of this distribution was set to zero and later rescaled to mean luminance (52 cd/m

^{2}) to ensure that the mean luminance of each image sequence was identical. The fast Fourier transform (FFT) was calculated for each image within each movie sequence image (i.e., spatially) and between images within each sequence (i.e., temporally). The spatiotemporal amplitude spectrum of each image was band-pass (

*SD*= 0.1 octaves) centered at one of three spatial frequencies (0.5, 2 and 8 c.p.d.) and one of two temporal frequencies (1.6 and 12.5 Hz). For any given block of trials, the spatial and temporal frequency of target and masking stimuli were identical. The spatial and temporal phases of target and masking stimuli varied randomly both with respect to each other and across trials. Root mean squared (RMS) calculation of spatiotemporal image contrast was to constrain the luminance distribution of target and masking stimuli.

*SD*= 1°). Target orientation was centered at 135° and masking orientations varied between 135° and 225°, producing a range of orientation difference between target and masking stimuli between 0° and 90° (orientation differences used: 0°, 2.5°, 5°, 6.125°, 10°, 12.5°, 20°, 30°, 45°, 67.5°, and 90°). The total duration of each stimulus pattern was 640 ms and was ramped on and off using a raised cosine (

*SD*of ramp = 20 ms).

*σ*)

*σ*)) and a peak target-mask orientation difference parameter fixed at 0° (see dashed red and blue curves in Figure 3). The bandwidth estimates derived from this standard Gaussian fit are shown for each spatiotemporal frequency in Figure 5a. A three-way within-subjects ANOVA provides no evidence for any interaction between the effects of stimulus temporal frequency, spatial frequency, and ocularity (monoptic vs. dichoptic) on orientation bandwidths (

*p*> .05). No significant two-way interactions were observed between ocular presentation mode and spatial frequency or temporal frequency (both

*p*-values > .05). Significant two-way interactions were observed, however, between spatial and temporal frequency when collapsing across monoptic and dichoptic conditions (

*F*(2, 2) = 3.276,

*p*< .05). As can be seen in Figure 5, this interaction is due to broader bandwidths in response to 12.5 Hz compared with 1.6 Hz modulation at the lower spatial frequencies tested (117.4° vs. 58.3° (0.5 c.p.d.); 96.4° vs. 36.7° (2 c.p.d.)). Bandwidths did not vary as a function of temporal frequency at the highest spatial frequency tested. In the case of 12.5 Hz modulation, 8 c.p.d. stimuli generated significantly narrower bandwidths than lower spatial frequencies. For 1.6 Hz stimuli, both higher spatial frequencies (2 and 8 c.p.d.) elicited narrower bandwidths than the lowest spatial frequency tested (0.5 c.p.d.).

*α*) as a free parameter (see Equation 2, Figure 4b). Unsurprisingly, the addition of this isotropic free parameter improved the fits (average chi-square = 33.34 vs. 17.38). It is worth noting, however, that a within-subjects

*t*-test comparing these chi-squared estimates indicates that the benefit imparted by this isotropic component is highly significant (

*t*(22) = 3.56;

*p*< .01). As can be clearly observed in Figure 5b, incorporating this isotropic component has a striking effect on bandwidth estimates (compare dashed and solid curves). Not only are average bandwidth estimates far narrower on average (range = 22.6°–30.9°) than those derived using the standard Gaussian fit, but a three-way within-subjects ANOVA finds no significant interactions or main effects in bandwidth estimates as they occur across different spatial frequencies, temporal frequencies, or ocular modes of presentation (all

*p*-values > .05).

*A*) and isotropic amplitude (

*α*)) expressed as a function of the spatial and temporal frequency of target and masking stimuli. The left-hand column in Figure 6 represents parameter estimates as they occur monoptically (red) and dichoptically (blue), grouped by stimulus spatial and temporal frequency. The parameter estimates in the right column in Figure 6 show the same data collapsed across monoptic and dichoptic conditions, grouped by temporal frequency (

*x*-axis) with gray levels representing different spatial frequency conditions.

*α*)

*α*) (all

*p*-values > .05). Significant differences in the amplitudes of isotropic masking components were observed for different spatial frequencies (

*F*(2, 2) = 25.848,

*p*< .05). Figure 6 reveals that this main effect is driven by higher isotropic masking amplitudes at the lowest spatial frequency tested, which is evident in both 1.6 and 12.5 Hz conditions. No significant differences in isotropic amplitude were observed as a function temporal frequency or ocular mode of presentation (both

*p-values*> .05).

*A*)

*p*-values < .05).

*α*) and orientation-tuned (A) components, each of which exhibit distinctive systematic contingencies across different regions of spatiotemporal frequency space. Each of these components (

*α*and

*A*) may be independently integrated as a function of target-mask orientation difference (

*α*and

*A*) to reveal its relative contribution the total masking effect (

*α*+

*A*) as function of spatiotemporal frequency (collapsing across monoptic and dichoptic viewing conditions). As can be seen in Figure 7, the combined integral (

*α*+

*A*]) is maximal at 0.5 c.p.d. and decreases (approximately log-linearly) with spatial frequency. No significant differences in the combined integral are evident across temporal frequencies.

*p*> .05). However, significant interactions are observed (for each temporal frequency) between combined and orientation-tuned integrals as a function of spatial frequency. These results imply that the spatial frequency dependencies of isotropic masking resemble more closely the combined isotropic and orientation-tuned masking effects than do the orientation-tuned masking effects. Figure 7 shows that this difference in the spatial frequency dependencies of isotropic and orientation-tuned integrals are due to significantly higher isotropic masking integrals at 0.5 c.p.d., with no differences observed at either 2 or 8 c.p.d..

*increased*low-frequency response bias (albeit noisy), effectively increasing redundancies evident in the spatial correlational structure of natural scenes. Indeed, an analogous counter-interpretation could be applied to the oblique masking effects reported by Essock et al. (2009).