Visual-auditory interactions in sensorimotor processing: Saccades versus manual responses.

Hughes, Heather; Reuter‐Lorenz, Patricia A.; Nozawa, George; Fendrich, Robert

doi:10.1037/0096-1523.20.1.131

Cited by 202 publications

(213 citation statements)

References 35 publications

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“…Note that to clearly illustrate this relationship, only 1 significant interaction per neuron is contained within this plot because spontaneous activity was invariant across conditions. Again, the relationship was most apparent in the log-log transformed plot and points were best fit to the power function y ϭ 38.152 x Ϫ0.3615 with an r 2 ϭ 0.3401. multisensory responses may speed the time to the initiation of premotor activity in the SC (Bell et al 2001), a result that fits nicely with observations of multisensory-mediated speeding of eye movements (Corneil and Munoz 1996;Frens and Van Opstal 1998;Frens et al 1995;Harrington and Peck 1998;Hughes et al 1994), the role of the different subpopulations of SC multisensory neurons to this effect remain to be determined. From a mechanistic perspective, the current study illustrates that fundamental features of a given neuron's response characteristics are strong determinants of multisensory integration.…”

Section: Introductionsupporting

confidence: 52%

Neuron-Specific Response Characteristics Predict the Magnitude of Multisensory Integration

Perrault

Vaughan

Stein

et al. 2003

Journal of Neurophysiology

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. Neuron-specific response characteristics predict the magnitude of multisensory integration. J Neurophysiol 90: 4022-4026, 2003. First published August 20, 2003 10.1152/jn.00494.2003. Multisensory neurons in the superior colliculus (SC) typically respond to combinations of stimuli from multiple modalities with enhancements and/or depressions in their activity. Although such changes in response have been shown to follow a predictive set of integrative principles, these principles fail to completely account for the full range of interactions seen throughout the SC population. In an effort to better define this variability, we sought to determine if there were additional features of the neuronal response profile that were predictive of the magnitude of the multisensory interaction. To do this, we recorded from 109 visualauditory SC neurons while systematically manipulating stimulus intensity. Along with the previously described roles of space, time, and stimulus effectiveness, two features of a neuron's response profile were found to offer predictive value as to the magnitude of the multisensory interaction: spontaneous activity and the level of sensory responsiveness. Multisensory neurons with little or no spontaneous activity and weak sensory responses had the capacity to exhibit large response enhancements. Conversely, neurons with modest spontaneous activity and robust sensory responses exhibited relatively small response enhancements. Together, these results provide a better view into multisensory integration, and suggest substantial heterogeneity in the integrative characteristics of the multisensory SC population.

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Section: Introductionsupporting

confidence: 52%

Neuron-Specific Response Characteristics Predict the Magnitude of Multisensory Integration

Perrault

Vaughan

Stein

et al. 2003

Journal of Neurophysiology

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“…It may, therefore, be concluded that the stage of processing at which the integration of the spatially congruent information occurs is not influenced by the response relevance of the stimulus components. A spatial congruency effect for bimodal stimuli has also been observed by Hughes et al (1994) when participants had to selectively elicit a saccade to a visual stimulus that was accompanied by an auditory distractor. By contrast, for manual responses, Hughes et al did not find a spatial congruency effect (however, only 3 Note-ANOVA results for the analysis outlined in Table 3A.…”

Section: Discussionmentioning

confidence: 94%

“…For bimodal divided attention tasks, the RT gain observed with bimodal stimuli is usually larger than that predicted by separate activation models, so that coactivation models have been adopted (Giray & Ulrich, 1993;Gondan, Lange, Rösler, & Röder, 2004;Hughes, ReuterLorenz, Nozawa, & Fendrich, 1994;Miller, 1982Miller, , 1986Miller, , 1991Molholm et al, 2002;Plat, Praamstra, & Horstink, 2000;Schröger & Widmann, 1998). Different loci at which the coactivation may take place have been suggested: Multisensory interactions may take place (1) at perceptual stages (Hershenson, 1962;Hughes et al, 1994;Molholm et al, 2002), (2) at higher cognitive stages (e.g., decision or memory; Miller, 1982;Mordkoff & Yantis, 1991;Schröger & Widmann, 1998), and/or (3) during motor preparation and execution (Diederich & Colonius, 1987;Giray & Ulrich, 1993; but see Miller, Ulrich, & Lamarre, 2001;Mordkoff, Miller, & Roch, 1996).…”

mentioning

confidence: 99%

Multisensory processing in the redundant-target effect: A behavioral and event-related potential study

Gondan

Niederhaus

Rösler

et al. 2005

Perception & Psychophysics

135

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In a typical redundant-target experiment, participants are asked to respond to events of two modalities, which are presented either alone or simultaneously (Miller, 1982). Combined (bimodal) stimuli are called redundant because the same reaction is required for both targets, irrespective of their modality. Reaction times (RTs) to redundant targets are commonly found to be shorter than RTs to simple (unimodal) targets. Two alternative models have been suggested to explain this redundant-target effect (RTE). Separate activation models, or race models, hold that the two components of a bimodal event are processed in separate channels and that the channel that has first finished processing first triggers the response. By analogy, the probability of obtaining a six is higher when two dice are tossed instead of one. Similarly, the probability of getting an RT, t, lower than a given t 0 is higher for bimodal (e.g., auditory-visual, AV) than for unimodal (A or V) stimuli, resulting in a lower mean RT. This effect has been called statistical facilitation (Raab, 1962; see Figure 1). Given the RT distributions to simple stimuli, the redundancy gain that can be explained by statistical facilitation has a clearly defined upper limit, which is described by the race model inequality (Miller, 1982):A race model requires that this inequality should hold for the cumulative RT distributions for both unimodal and bimodal stimuli. If the redundancy gain surpasses that predicted by the race model, rejecting the race model in favor of a coactivation model is justified. Proponents of the latter model disagree with the separate processing view and suggest that information from the two modality channels is integrated at a particular processing level and subsequently processed as a combined entity. This processing stage gains from redundant information, resulting in faster responses to redundant stimuli.The race model is typically sufficient to explain the redundancy gain of healthy participants in simple unimodal detection tasks with two classes of visual stimuli (see, e.g., Corballis, 1998Corballis, , 2002; a weak violation was found by Miniussi, Girelli, & Marzi, 1998, which was, however, not statistically tested). Surprisingly, split-brain patients have displayed redundancy gains larger than those predicted by the race model when bilateral stimuli have been used (Corballis, 1998(Corballis, , 2002Reuter-Lorenz, Nozawa, Gazzaniga, & Hughes, 1995;Roser & Corballis, 2002 Participants respond more quickly to two simultaneously presented target stimuli of two different modalities (redundant targets) than would be predicted from their reaction times to the unimodal targets. To examine the neural correlates of this redundant-target effect, event-related potentials (ERPs) were recorded to auditory, visual, and bimodal standard and target stimuli presented at two locations (left and right of central fixation). Bimodal stimuli were combinations of two standards, two targets, or a standard and a target, presented either from the same or from diff...

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“…In this case, their synergistic effects would enhance the likelihood of orienting to the initiating event, and this has been shown to be the case in behaving animals (Stein et al, 1988(Stein et al, , 1989Wilkinson et al, 1996;Stein, 1998;Jiang et al, 2002Jiang et al, , 2007Van Opstal and Munoz, 2004). Analogous multisensory benefits have also been repeatedly demonstrated in human subjects (Engelken and Stevens, 1989;Perrott et al, 1990;Hughes et al, 1994;Frens et al, 1995;Corneil and Munoz, 1996 The individual modalityspecific responses during the cortical deactivation and in the control condition were plotted together across all levels of stimulus effectiveness. A, During the cross-modal tests, the majority of the modality-specific responses in visual 1, visual 2, and auditory fell below the line of unity during the cortical deactivation.…”

Section: Cortico-sc Influence On Integration Is Multisensory-specificmentioning

confidence: 99%

Cortex Mediates Multisensory But Not Unisensory Integration in Superior Colliculus

Alvarado¹,

Stanford²,

Vaughan³

et al. 2007

J. Neurosci.

105

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Converging cortical influences from the anterior ectosylvian sulcus and the rostral lateral suprasylvian sulcus were shown to have a multisensory-specific role in the integration of sensory information in superior colliculus (SC) neurons. These observations were based on changes induced by cryogenic deactivation of these cortico-SC projections. Thus, although the results indicated that they played a critical role in integrating SC responses to stimuli derived from different senses (i.e., visual-auditory), they played no role in synthesizing its responses to stimuli derived from within the same sense (visual-visual). This was evident even in the same multisensory neurons. The results suggest that very different neural circuits have evolved to code combinations of cross-modal and within-modal stimuli in the SC, and that the differences in multisensory and unisensory integration are likely caused by differences in the configuration of each neuron's functional inputs rather than to any inherent differences among the neurons themselves. The specificity of these descending influences was also apparent in the very different ways in which they affected responses to the component cross-modal stimuli and their actual integration. Furthermore, they appeared to target only multisensory neurons and not their unisensory neighbors.

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Visual-auditory interactions in sensorimotor processing: Saccades versus manual responses.

Cited by 202 publications

References 35 publications

Neuron-Specific Response Characteristics Predict the Magnitude of Multisensory Integration

Neuron-Specific Response Characteristics Predict the Magnitude of Multisensory Integration

Multisensory processing in the redundant-target effect: A behavioral and event-related potential study

Cortex Mediates Multisensory But Not Unisensory Integration in Superior Colliculus

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