Processing of Complex Sounds in the Auditory Cortex of Cat, Monkey, and Man

Rauschecker, Josef P.

doi:10.3109/00016489709126142

Cited by 142 publications

(112 citation statements)

References 13 publications

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“…The anatomy and physiology of the auditory cortex has w x been studied extensively in both humans 4,18,22,49,53,54 w x and primates 19,21,28,44 . Language-related functions of the brain have been studied extensively since the advent of w x functional neuroimaging 2-6,38,39 .…”

Section: Introductionmentioning

confidence: 99%

Recognition of emotional prosody and verbal components of spoken language: an fMRI study

Buchanan

Lutz

Mirzazade

et al. 2000

Cognitive Brain Research

387

231

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This study examined the neural areas involved in the recognition of both emotional prosody and phonemic components of words Ž . expressed in spoken language using echo-planar, functional magnetic resonance imaging fMRI . Ten right-handed males were asked to Ž . discriminate words based on either expressed emotional tone angry, happy, sad, or neutral or phonemic characteristics, specifically, Ž . initial consonant sound bower, dower, power, or tower . Significant bilateral activity was observed in the detection of both emotional and verbal aspects of language when compared to baseline activity. We found that the detection of emotion compared with verbal detection resulted in significant activity in the right inferior frontal lobe. Conversely, the detection of verbal stimuli compared with the detection of emotion activated left inferior frontal lobe regions most significantly. Specific analysis of the anterior auditory cortex revealed increased right hemisphere activity during the detection of emotion compared to activity during verbal detection. These findings illustrate bilateral involvement in the detection of emotion in language while concomitantly showing significantly lateralized activity in both emotional and verbal detection, in both the temporal and frontal lobes. q

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Section: Introductionmentioning

confidence: 99%

Recognition of emotional prosody and verbal components of spoken language: an fMRI study

Buchanan

Lutz

Mirzazade

et al. 2000

Cognitive Brain Research

387

231

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“…Primate electrophysiology identifies CS as occurring as early as core's supragranular layers and in lateral belt (16,17,19,37). In the macaque, selectivity for communication calls-similar in spectrotemporal structure to phonemes or consonant-vowel (CV) syllables-is observed in belt area AL (54) and, to an even greater degree, in a more anterior field, RTp (55).…”

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confidence: 99%

“…However, a formal equivalence is yet to be demonstrated (37,38). Auditory cortex's predominant processing pathways, ventral and dorsal (39,40), appear to be optimized for pattern recognition and action planning, respectively (17,18,(40)(41)(42)(43)(44). Speechspecific models generally concur (45)(46)(47)(48), creating a wide consensus that word recognition is performed in the auditory ventral stream (refs.…”

mentioning

confidence: 99%

Phoneme and word recognition in the auditory ventral stream

DeWitt

Rauschecker²

2012

Proc. Natl. Acad. Sci. U.S.A.

401

328

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Spoken word recognition requires complex, invariant representations. Using a meta-analytic approach incorporating more than 100 functional imaging experiments, we show that preference for complex sounds emerges in the human auditory ventral stream in a hierarchical fashion, consistent with nonhuman primate electrophysiology. Examining speech sounds, we show that activation associated with the processing of short-timescale patterns (i.e., phonemes) is consistently localized to left mid-superior temporal gyrus (STG), whereas activation associated with the integration of phonemes into temporally complex patterns (i.e., words) is consistently localized to left anterior STG. Further, we show left midto anterior STG is reliably implicated in the invariant representation of phonetic forms and that this area also responds preferentially to phonetic sounds, above artificial control sounds or environmental sounds. Together, this shows increasing encoding specificity and invariance along the auditory ventral stream for temporally complex speech sounds.functional MRI | meta-analysis | auditory cortex | object recognition | language S poken word recognition presents several challenges to the brain. Two key challenges are the assembly of complex auditory representations and the variability of natural speech (SI Appendix, Fig. S1) (1). Representation at the level of primary auditory cortex is precise: fine-grained in scale and local in spectrotemporal space (2, 3). The recognition of complex spectrotemporal forms, like words, in higher areas of auditory cortex requires the transformation of this granular representation into Gestalt-like, object-centered representations. In brief, local features must be bound together to form representations of complex spectrotemporal contours, which are themselves the constituents of auditory "objects" or complex sound patterns (4, 5). Next, representations must be generalized and abstracted. Coding in primary auditory cortex is sensitive even to minor physical transformations. Object-centered coding in higher areas, however, must be invariant (i.e., tolerant of natural stimulus variation) (6). For example, whereas the phonemic structure of a word is fixed, there is considerable variation in physical, spectrotemporal form-attributable to accent, pronunciation, body size, and the like-among utterances of a given word. It has been proposed for visual cortical processing that a feed-forward, hierarchical architecture (7) may be capable of simultaneously solving the problems of complexity and variability (8-12). Here, we examine these ideas in the context of auditory cortex.In a hierarchical pattern-recognition scheme (8), coding in the earliest cortical field would reflect the tuning and organization of primary auditory cortex (or core) (2, 3, 13). That is, single-neuron receptive fields (more precisely, frequency-response areas) would be tuned to particular center frequencies and would have minimal spectrotemporal complexity (i.e., a single excitatory zone and one-to-two inhibitory side bands). ...

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“…Neurons in these areas seem to be engaged in processing the location of objects in space. Recent investigations in primates, including humans, have given rise to the hypothesis, proposed by Kaas [111], Rauschecker [112] and others [6], that like the visual system, auditory areas in the cerebral cortex contain at least two primary processing pathways -a ventral stream running from primary auditory cortex anteriorly along the superior temporal gyrus that is associated with processing the features of auditory objects, and a dorsal stream that goes into the parietal lobe that is concerned with the spatial location of the auditory input. This notion, however, is more controversial (especially the part concerning the dorsal pathway being associated with spatial processing), and lacks strong experimental support.…”

Section: Short-term Memory For Objectsmentioning

confidence: 99%

A link between neuroscience and informatics: Large-scale modeling of memory processes

Horwitz¹,

Smith²

2008

Methods

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Utilizing advances in functional neuroimaging and computational neural modeling, neuroscientists have increasingly sought to investigate how distributed networks, composed of functionally defined subregions, combine to produce cognition. Large-scale, biologically realistic neural models, which integrate data from cellular, regional, whole brain, and behavioral sources, delineate specific hypotheses about how these interacting neural populations might carry out high-level cognitive tasks. In this review, we discuss neuroimaging, neural modeling, and the utility of large-scale biologically realistic models using modeling of short-term memory as an example. We present a sketch of the data regarding the neural basis of short-term memory from non-human electrophysiological, computational and neuroimaging perspectives, highlighting the multiple interacting brain regions believed to be involved. Through a review of several efforts, including our own, to combine neural modeling and neuroimaging data, we argue that large scale neural models provide specific advantages in understanding the distributed networks underlying cognition and behavior.

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Processing of Complex Sounds in the Auditory Cortex of Cat, Monkey, and Man

Cited by 142 publications

References 13 publications

Recognition of emotional prosody and verbal components of spoken language: an fMRI study

Recognition of emotional prosody and verbal components of spoken language: an fMRI study

Phoneme and word recognition in the auditory ventral stream

A link between neuroscience and informatics: Large-scale modeling of memory processes

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