coding of sound location in auditory cortex (AC) is only partially understood. Recent electrophysiological research suggests that neurons in mammalian auditory cortex are characterized by broad spatial tuning and a pr...
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coding of sound location in auditory cortex (AC) is only partially understood. Recent electrophysiological research suggests that neurons in mammalian auditory cortex are characterized by broad spatial tuning and a preference for the contralateral hemifield, that is, a nonuniform sampling of sound azimuth. Additionally, spatial selectivity decreases with increasing sound intensity. To accommodate these findings, it has been proposed that sound location is encoded by the integrated activity of neuronal populations with opposite hemifield tuning ("opponent channel model"). In this study, we investigated the validity of such a model in human AC with functional magnetic resonance imaging (fMRI) and a phase-encoding paradigm employing binaural stimuli recorded individually for each participant. In all subjects, we observed preferential fMRI responses to contralateral azimuth positions. Additionally, in most AC locations, spatial tuning was broad and not level invariant. We derived an opponent channel model of the fMRI responses by subtracting the activity of contralaterally tuned regions in bilateral planum temporale. This resulted in accurate decoding of sound azimuth location, which was unaffected by changes in sound level. Our data thus support opponent channel coding as a neural mechanism for representing acoustic azimuth in human AC.
Previous studies reported that auditory cortices (AC) were mostly activated by sounds coming from the contralateral hemifield. As a result, sound locations could be encoded by integrating opposite activations from bot...
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Previous studies reported that auditory cortices (AC) were mostly activated by sounds coming from the contralateral hemifield. As a result, sound locations could be encoded by integrating opposite activations from both sides of AC ("opponent hemifield coding"). However, human auditory "where" pathway also includes a series of parietal and prefrontal regions. It was unknown how sound locations were represented in those high-level regions during passive listening. Here, we investigated the neural representation of sound locations in high-level regions by voxel-level tuning analysis, regions-of-interest-level (ROI-level) laterality analysis, and ROI-level multivariate pattern analysis. Functional magnetic resonance imaging data were collected while participants listened passively to sounds from various horizontal locations. We found that opponent hemifield coding of sound locations not only existed in AC, but also spanned over intraparietal sulcus, superior parietal lobule, and frontal eye field (FEF). Furthermore, multivariate pattern representation of sound locations in both hemifields could be observed in left AC, right AC, and left FEF. Overall, our results demonstrate that left FEF, a high-level region along the auditory "where" pathway, encodes sound locations during passive listening in two ways: a univariate opponent hemifield activation representation and a multivariate full-field activation pattern representation.
Perception of a facial expression can be altered or biased by a prolonged viewing of other facial expressions, known as the facial expression adaptation aftereffect (FEAA). Recent studies using antiexpressions have de...
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Perception of a facial expression can be altered or biased by a prolonged viewing of other facial expressions, known as the facial expression adaptation aftereffect (FEAA). Recent studies using antiexpressions have demonstrated a monotonic relation between the magnitude of the FEAA and adaptor extremity, suggesting that facial expressions are opponent coded and represented continuously from one expression to its antiexpression. However, it is unclear whether the opponent-coding scheme can account for the FEAA between two facial expressions. In the current study, we demonstrated that the magnitude of the FEAA between two facial expressions increased monotonically as a function of the intensity of adapting facial expressions, consistent with the predictions based on the opponent-coding model. Further, the monotonic increase in the FEAA occurred even when the intensity of an adapting face was too weak for its expression to be recognized. These results together suggest that multiple facial expressions are encoded and represented by balanced activity of neural populations tuned to different facial expressions.
Face adaptation generates striking face aftereffects, but is this adaptation useful? The answer appears to be yes, with several lines of evidence suggesting that it contributes to our face-recognition ability. Adaptat...
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Face adaptation generates striking face aftereffects, but is this adaptation useful? The answer appears to be yes, with several lines of evidence suggesting that it contributes to our face-recognition ability. Adaptation to face identity is reduced in a variety of clinical populations with impaired face recognition. In addition, individual differences in face adaptation are linked to face-recognition ability in typical adults. People who adapt more readily to new faces are better at recognizing faces. This link between adaptation and recognition holds for both identity and expression recognition. Adaptation updates face norms, which represent the typical or average properties of the faces we experience. By using these norms to code how faces differ from average, the visual system can make explicit the distinctive information that we need to recognize faces. Thus, adaptive norm-based coding may help us to discriminate and recognize faces despite their similarity as visual patterns.
face perception system flexibly adjusts its neural responses to current face exposure, inducing aftereffects in the perception of subsequent faces. For instance, adaptation to expanded faces makes undistorted faces ap...
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face perception system flexibly adjusts its neural responses to current face exposure, inducing aftereffects in the perception of subsequent faces. For instance, adaptation to expanded faces makes undistorted faces appear compressed, and adaptation to compressed faces makes undistorted faces appear expanded. Such distortion aftereffects have been proposed to result from renormalization, in which the visual system constantly updates a prototype according to the adaptors' characteristics and evaluates subsequent faces relative to that. However, although consequences of adaptation are easily observed in behavioral aftereffects, it has proven difficult to observe renormalization during adaptation itself. Here we directly measured brain responses during adaptation to establish a neural correlate of renormalization. Given that the face-evoked occipito-temporal P2 event-related brain potential has been found to increase with face prototypicality, we reasoned that the adaptor-elicited P2 could serve as an electrophysiological indicator for renormalization. Participants adapted to sequences of four distorted (compressed or expanded) or undistorted faces, followed by a slightly distorted test face, which they had to classify as undistorted or distorted. We analysed ERPs evoked by each of the adaptors and found that P2 (but not N170) amplitudes evoked by consecutive adaptor faces exhibited an electrophysiological pattern of renormalization during adaptation to distorted faces: P2 amplitudes evoked by both compressed and expanded adaptors significantly increased towards asymptotic levels as adaptation proceeded. P2 amplitudes were smallest for the first adaptor, significantly larger for the second, and yet larger for the third adaptor. We conclude that the sensitivity of the occipito-temporal P2 to the perceived deviation of a face from the norm makes this component an excellent tool to study adaptation-induced renormalization.
Face aftereffects can help adjudicate between theories of how facial attributes are encoded. O'Neil and colleagues (2014) compared age estimates for faces before and after adapting to young, middle-aged or old fac...
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Face aftereffects can help adjudicate between theories of how facial attributes are encoded. O'Neil and colleagues (2014) compared age estimates for faces before and after adapting to young, middle-aged or old faces. They concluded that age aftereffects are best described as a simple renormalisation-e.g. after adapting to old faces, all faces look younger than they did initially. Here I argue that this conclusion is not substantiated by the reported data. The authors fit only a linear regression model, which captures the predictions of re-normalisation, but not alternative hypotheses such as local repulsion away from the adapted age. A second concern is that the authors analysed absolute age estimates after adaptation, as a function of baseline estimates, so goodness-of-fit measures primarily reflect the physical ages of test faces, rather than the impact of adaptation. When data are re-expressed as aftereffects and fit with a nonlinear "locally repulsive" model, this model performs equal to or better than a linear model in all adaptation conditions. Data in O'Neil et al. do not provide strong evidence for either re-normalisation or local repulsion in facial age aftereffects, but are more consistent with local repulsion (and exemplar-based encoding of facial age), contrary to the original report.
After prolonged exposure to a female face, faces that had previously seemed androgynous are more likely to be judged as male. Similarly, after prolonged exposure to a face with expanded features, faces that had previo...
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After prolonged exposure to a female face, faces that had previously seemed androgynous are more likely to be judged as male. Similarly, after prolonged exposure to a face with expanded features, faces that had previously seemed normal are more likely to be judged as having contracted features. These facial aftereffects have both been attributed to the impact of adaptation upon a norm-based opponent code, akin to low-level analyses of colour. While a good deal of evidence is consistent with this, some recent data is contradictory, motivating a more rigorous test. In behaviourally matched tasks we compared the characteristics of aftereffects generated by adapting to colour, to expanded or contracted faces, and to male or female faces. In our experiments opponent coding predicted that the appearance of the adapting image should change and that adaptation should induce symmetrical shifts of two category boundaries. This combination of predictions was firmly supported for colour adaptation, somewhat supported for facial distortion aftereffects, but not supported for facial gender aftereffects. Interestingly, the two face aftereffects we tested generated discrepant patterns of response shifts. Our data suggest that superficially similar aftereffects can ensue from mechanisms that differ qualitatively, and therefore that not all high-level categorical face aftereffects can be attributed to a common coding strategy. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.
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