Abstract
Whether subsecond timing relies on a centralized clock, or on distributed temporal mechanisms, has been a central theme in time research. Current views favor distributed mechanisms because of the interval specificity in temporal interval discrimination (TID) learning, which contradicts a dedicated centralized clock account.
We first ran a double training procedure to eliminate interval specificity in learning of TID with intervals marked by pairs of auditory beeps. TID learning was initially interval specific: TID learning with a 100-interval after 5 sessions of practice reduced TID thresholds by 42.8±10.0% at a 100-ms interval (p<0.001), but it had no significant impact on TID thresholds at 200-ms (15.9±6.7%, p=0.15). However, when TID training at 100-ms was paired with auditory frequency discrimination (FD) learning at 200-ms in alternating blocks of trials, TID thresholds at 100-ms and 200-ms were both improved (41.8±8.9% & 32.7±1.6%, p<0.001). A control experiment excluded the possibility that TID improvement at 200-ms was caused by FD learning. Similar double training procedures also enabled complete TID learning transfer between visual and auditory modalities. These results suggest an interval-unspecific supramodal representation of subsecond time. Training may refine this centralized clock-like representation, so that learning can transfer across intervals and modalities.
Next we tested whether supramodal TID training could improve unimodal TID performance. Participants practiced supramodal TID of a 200-ms interval defined by an auditory and a visual signal (AV), which not only reduced AV TID thresholds by 36.7±5.4% (p<0.001), but also reduced auditory-auditory (AA) TID at 200-ms by 27.8±4.1% (p<0.001). Continued training of AA TID failed to further improve AA TID thresholds (0.5±9.2%, p=0.96). This finding indicates that precise subsecond timing can be achieved through training of more centralized supramodal timing mechanisms, with no necessity of engaging more peripheral unimodal timing mechanisms.