Interactions Among Converging Sensory Inputs in the Superior Colliculus

Meredith, M. Alex; Stein, Barry E.

doi:10.1126/science.6867718

Cited by 754 publications

(578 citation statements)

References 21 publications

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“…Interestingly, most of the significant effects of the clarity of visual articulation occurred during this period, even though no cortical visual areas were significantly affected. In the absence of significant effects of stimulus and response conditions on visual cortical areas at this time, integration and the effects of visual articulation may involve subcortical audio‐visual inputs to these areas, possibly from the superior colliculus (Meredith and Stein 1983; Calvert et al. 2001; Fairhall and Macaluso 2009).…”

Section: Discussionmentioning

confidence: 99%

Spatio‐temporal distribution of brain activity associated with audio‐visually congruent and incongruent speech and the McGurk Effect

2015

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IntroductionSpatio‐temporal distributions of cortical activity to audio‐visual presentations of meaningless vowel‐consonant‐vowels and the effects of audio‐visual congruence/incongruence, with emphasis on the McGurk effect, were studied. The McGurk effect occurs when a clearly audible syllable with one consonant, is presented simultaneously with a visual presentation of a face articulating a syllable with a different consonant and the resulting percept is a syllable with a consonant other than the auditorily presented one.MethodsTwenty subjects listened to pairs of audio‐visually congruent or incongruent utterances and indicated whether pair members were the same or not. Source current densities of event‐related potentials to the first utterance in the pair were estimated and effects of stimulus–response combinations, brain area, hemisphere, and clarity of visual articulation were assessed.ResultsAuditory cortex, superior parietal cortex, and middle temporal cortex were the most consistently involved areas across experimental conditions. Early (<200 msec) processing of the consonant was overall prominent in the left hemisphere, except right hemisphere prominence in superior parietal cortex and secondary visual cortex. Clarity of visual articulation impacted activity in secondary visual cortex and Wernicke's area. McGurk perception was associated with decreased activity in primary and secondary auditory cortices and Wernicke's area before 100 msec, increased activity around 100 msec which decreased again around 180 msec. Activity in Broca's area was unaffected by McGurk perception and was only increased to congruent audio‐visual stimuli 30–70 msec following consonant onset.ConclusionsThe results suggest left hemisphere prominence in the effects of stimulus and response conditions on eight brain areas involved in dynamically distributed parallel processing of audio‐visual integration. Initially (30–70 msec) subcortical contributions to auditory cortex, superior parietal cortex, and middle temporal cortex occur. During 100–140 msec, peristriate visual influences and Wernicke's area join in the processing. Resolution of incongruent audio‐visual inputs is then attempted, and if successful, McGurk perception occurs and cortical activity in left hemisphere further increases between 170 and 260 msec.

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Section: Discussionmentioning

confidence: 99%

Spatio‐temporal distribution of brain activity associated with audio‐visually congruent and incongruent speech and the McGurk Effect

2015

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“…In other words, the numerical intersensory redundancy could have selectively recruited infants' attention to the amodal, redundant property of number and caused more effective encoding of this property. A possible underlying mechanism for this selective attentional recruitment is an increase in neural responsiveness to redundant stimulation (e.g., Meredith and Stein, 1983;Stein, Huneycutt, and Meredith, 1988). Previous work on the effects of intersensory redundancy in infancy in non-numerical domains suggests that this selective attentional recruitment may even occur at the expense of accurate encoding of other nonredundantly specified and modality-specific properties, such as color and pitch.…”

Section: Discussionmentioning

confidence: 99%

“…When given information that is redundant across multiple senses, nonhuman animals and humans tested on a wide variety of non-numerical dimensions have been shown to improve in accuracy and/or reaction time, relative to performance with unisensory stimuli (e.g., Bahrick and Lickliter, 2000;Gogate and Bahrick, 1998;Lewkowicz and Kraebel, 2004;Lickliter et al, 2002;Lovelace et al, 2003;Mellon et al, 1991;Meredith and Stein, 1983). For example, multimodal cues occurring together in time and space enhance responses of multisensory neurons in the superior colliculus of cats to a level above the responses evoked by unisensory cues; multisensory cues also produce behaviorally evident increases in cats' effectiveness at detecting, orienting towards, and approaching the cue as compared with responses to unimodal sensory cues (e.g., Meredith and Stein, 1983;Stein, Huneycutt, and Meredith, 1988). Intersensory redundancy also facilitates prenatal perceptual learning in bobwhite quail .…”

Section: Introductionmentioning

confidence: 99%

Intersensory redundancy accelerates preverbal numerical competence

2008

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Intersensory redundancy can facilitate animal and human behavior in areas as diverse as rhythm discrimination, signal detection, orienting responses, maternal call learning, and associative learning. In the realm of numerical development, infants show similar sensitivity to numerical differences in both the visual and auditory modalities. Using a habituation-dishabituation paradigm, we ask here whether providing redundant, multisensory numerical information allows six-month-old infants to make more precise numerical discriminations. Results indicate that perceptually redundant information improved preverbal numerical precision to a level of discrimination previously thought attainable only after additional months of development. Multimodal stimuli may thus boost abstract cognitive abilities such as numerical competence.

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“…Enhancement index-This index quantifies the degree to which the response to a combined visual-visual stimulus exceeds the most effective modality-specific component stimulus according to the formula (Meredith and Stein 1983): Where CR is the response (mean number of impulses/trial) evoked by the combined visualvisual stimuli and MSR max is the response (mean number of impulses/trial) evoked by the most effective of the two modality-specific (visual) stimuli.…”

Section: Data Analysis and Models For Unisensory Integrationmentioning

confidence: 99%

“…visual, auditory, and somatosensory), and the ability of its neurons to integrate the information derived from cross-modal events. Consequently, concordant cross-modal stimuli evoke SC responses that can be well above those elicited by their individual component stimuli (e.g., Meredith and Stein 1983;Wallace et al, 1998;Jiang et al, 2001;Calvert et al, 2004;Perrault et al, 2005;Stanford et al, 2005). Multisensory response enhancement in single neurons in the cat SC depends mostly on the synergistic interaction of unisensory descending influences from the anterior ectosylvian cortex (AES) (Wallace and Stein 1994;Wilkinson et al, 1996;Jiang, et al, 2001Jiang, et al, , 2002Stein 2005;Stein and Stanford 2008).…”

Section: Introductionmentioning

confidence: 99%

A neural network model of multisensory integration also accounts for unisensory integration in superior colliculus

et al. 2008

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Sensory integration is a characteristic feature of superior colliculus (SC) neurons. A recent neural network model of single-neuron integration derived a set of basic biological constraints sufficient to replicate a number of physiological findings pertaining to multisensory responses. The present study examined the accuracy of this model in predicting the responses of SC neurons to pairs of visual stimuli placed within their receptive fields. The accuracy of this model was compared to that of three other computational models (additive, averaging and maximum operator) previously used to fit these data. Each neuron's behavior was assessed by examining its mean responses to the component stimuli individually and together, and each model's performance was assessed to determine how close its prediction came to the actual mean response of each neuron and the magnitude of its predicted residual error. Predictions from the additive model significantly overshot the actual responses of SC neurons and predictions from the averaging model significantly undershot them. Only the predictions of the maximum operator and neural network model were not significantly different from the actual responses. However, the neural network model outperformed even the maximum operator model in predicting the responses of these neurons. The neural network model is derived from a larger model that also has substantial predictive power in multisensory integration, and provides a single computational vehicle for assessing the responses of SC neurons to different combinations of crossmodal and within-modal stimuli of different efficacies.

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Interactions Among Converging Sensory Inputs in the Superior Colliculus

Cited by 754 publications

References 21 publications

Spatio‐temporal distribution of brain activity associated with audio‐visually congruent and incongruent speech and the McGurk Effect

Spatio‐temporal distribution of brain activity associated with audio‐visually congruent and incongruent speech and the McGurk Effect

Intersensory redundancy accelerates preverbal numerical competence

A neural network model of multisensory integration also accounts for unisensory integration in superior colliculus

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