Parallel processing of multiple sensory stimuli is critical for efficient, successful interaction with the environment. It allows for the simultaneous identification of multiple stimuli and thus swift action. An experimental approach to studying parallel processing in sensorimotor integration is to examine responses to multiple copies of the same stimulus. Reaction time tends to be faster to bilateral, redundant copies than to a single copy of a stimulus. Responding faster to redundant stimuli is known as the ‘redundant targets effect’ 
. The redundant target effect has been obtained with unimodal redundant visual 
and auditory 
stimuli as well as with bimodal audio-visual stimuli 
, and it has been observed in both choice 
, and simple detection tasks 
Two alternative mechanisms have been proposed to account for the redundant target effect. “Statistical facilitation” posits that the observed facilitation in reaction time to redundant targets occurs because redundant targets activate multiple, independent, parallel processing channels. Each channel processes one of the redundant targets, and its speed varies from trial to trial as a stochastic process. Consequently, reaction time in a given trial reflects the processing time of whichever channel happened to be faster on that trial, causing the average reaction time to multiple redundant targets to be shorter than the average reaction time for any of the two channels alone. By analogy, statistical facilitation is sometimes described as a ‘horse race’, where the winner initiates the response 
. This mechanism assumes that there is no interaction among the channels. “Coactivation models”, on the other hand, posit that engaging parallel channels results in a multiplicative activation, or interaction of channels, prior to response initiation 
. This pooled activation, thus, yields a faster initiation of the motor response. The original coactivation model was abstract and did not take into consideration the underlying neural architecture. Recently, however, coactivation has been typically interpreted as indicating neural summation 
proposed a mathematical test (see Methods
) to differentiate between statistical facilitation and coactivation accounts of the redundant target effect. His equation establishes the maximum difference between reaction times to single versus redundant presentations for which statistical facilitation can adequately explain the redundant target effect. In practice, this limit is exceeded on some trials, evidence that some other mechanism must be responsible for response facilitation, at least in those trials. [See, for example, 2,3,15,16]. It is important to note that when this limit is exceeded, statistical facilitation is ruled out as an explanation of the redundant target effect. However, when the limit is not exceeded, coactivation cannot be ruled out.
Theoretically, the functional locus of the redundant target effect may occur at a sensory, central (cognitive), or motor stage of processing. The empirical data are mixed. Many studies have ruled out that it occurs at either very early perceptual or late motor stages of processing. The redundant target effect is typically greater with bimodal stimuli (for example, visual-tactile) than with unimodal stimuli (for example, visual-visual) 
. These instances provide evidence that the effect occurs after early sensory processing, when information from different modalities is integrated (Miller, 1982). On the other hand, two event-related potential studies reported an early locus of the redundant target effect 
. In both studies, earlier peak P1 latencies were observed for redundant visual stimuli compared to single visual stimulus trials. Another event-related potential study used redundant audio-visual stimuli and reported early audio-visual interactions consistent with sensory processing 
. Likewise, Cavina-Pratesi et al. 
addressed whether the redundant target effect occurs as late as a motor stage of processing, using a task where subjects had to withhold responses on trials with stop-signals. Redundant stop-signals were more effective than single stop-signals in inhibiting motor responses. Similarly, responses to redundant stimuli were more difficult to inhibit compared to single stimuli. The effects of redundant signals on motor responses in these two stop-signal experiments suggest that the redundant target effect occurs at a late, pre-motor, stage, prior to late ballistic motor output 
As for the anatomical locus of the effect, reports have suggested that it occurs in either extrastriate or premotor regions, in line with information processing accounts of the effect. The event-related potential data suggest that the redundant target effect is detectable in the extrastriate cortex, but the poor spatial resolution of the event-related potential technique makes it difficult to precisely identify sources of influence 
. A single-trial fMRI study, on the other hand, found increased blood oxygen-level dependent (BOLD) signal in the left and right dorsal premotor cortex and right intraparietal sulcus for redundant compared to single stimulus targets 
. The premotor activations reported in that study support a later, motor, stage of processing.
Given the conflicting reports in the literature, the critical brain regions associated with parallel processing of stimuli remain a matter of investigation. Importantly, previous studies have only considered redundant versus single target conditions without distinguishing between performance explained by statistical facilitation and coactivation. Therefore an investigation of the neural locus of coactivation must look at these special trials separately.
The bilateral display used in this paradigm introduces an interhemispheric component to the task. Somewhat paradoxically, split brain and acallosal subjects often exhibit redundant target effects much larger than those in normal subjects which often exceed the boundary predicted by statistical facilitation 
. These results suggest, counterintuitively, a greater degree of interhemispheric interaction in the absence of the corpus callosum and that, in the normal brain, the corpus callosum may serve to inhibit interhemispheric interaction 
. Analysis of the functional connectivity of brain regions associated with the redundant target effect could prove useful in determining the role of interhemispheric connections in mediating it. Functional connectivity analyses allow us to examine the temporal cross-correlation of brain regions associated with activity in a seed region and are presumed to reflect structural connectivity between functionally related regions 
. This analysis is complementary to task activation maps because it describes regions that follow the temporal sequence of information processing rather than the regions that engage simultaneously.
In the present study, we used event-related fMRI to investigate the BOLD signal associated specifically with those trials that exceed the limit for the statistical facilitation account of the redundant target effect. Thus, rather than considering the anatomical localization of fast responses to redundant targets in general, we examined the anatomical localization of the neural coactivation. We also used functional connectivity analyses to investigate interaction within and between the hemispheres during instances of coactivation.