Two previous fMRI studies have investigated the effect of temporal frequency for achromatic stimuli and these have produced differing results. Singh et al. (
2000) used spatiotemporally sinusoidally modulated stimuli, as we used here. Like ours, their results show a loss of response between 9 and 18 Hz, although overall they had a more band-pass effect with a peak in response at 9 Hz compared to 2 Hz, which may be a result of the higher spatial frequency used (2 cycles/degree). Curiously, they also report a clear loss of response at higher temporal frequencies for area MT, showing similar band-pass results as were found for the other cortical areas. It is not clear why their MT results differ from ours. Kastner et al. (
2004), on the other hand, report a high-pass dependence for temporal frequency for all cortical areas, including MT, a pattern that clearly differs from our own results. Two factors may account for this difference. First, Kastner et al. (
2004) defined temporal frequency as half a cycle (stimulus on or stimulus off) so effectively doubling the reported temporal frequency value compared to the full cycle frequency, and taking this into account, the three temporal frequencies actually measured were 0.25, 3.75, and 10 Hz. Hence, any loss of response at high temporal frequencies (above 10 Hz) may have been missed, although we still find clear low-pass effects even within the range used by Kastner et al. (
2004). Second, Kastner et al. (
2004) use spatiotemporally square-wave stimuli (checkerboard with abrupt onset and offset). The use of square waveforms spreads the spatiotemporal representation across frequency by introducing spatial and temporal higher harmonics, producing a broadband temporal frequency stimulus, so confounding any interpretation of the shape of the temporal frequency dependence. An effective investigation of the effect of temporal frequency requires stimuli to be sinusoidally represented and so confined to a narrow band of spatiotemporal frequencies, as was used in our study and that of Singh et al. (
2000). Additionally, it is known that the use of square-wave stimuli reveals dynamic non-linearities of temporal summation in the response of cortical neurons in cat area 17 (Dean, Tolhurst, & Walker,
1982; Tolhurst, Walker, Thompson, & Dean,
1980) and primate area V1 (Reid, Victor, & Shapley,
1992; Williams & Shapley,
2007), which boost the response to higher temporal frequencies (e.g. for transient onsets), although this explanation remains to be tested for BOLD responses. One other fMRI study (Mirzajani, Riyahi-Alam, Oghabian, Saberi, & Firouznia,
2007) that used square-wave checkerboards also reported a high-pass dependence on temporal frequency for large-sized checks (similar to Kastner et al.,
2004) supporting the idea that the spatiotemporal spectrum of the stimulus is influential.