A Comparison of Vestibular Spatiotemporal Tuning in Macaque Parietoinsular Vestibular Cortex, Ventral Intraparietal Area, and Medial Superior Temporal Area

Chen, Aihua; DeAngelis, Gregory C.; Angelaki, Dora E.

doi:10.1523/jneurosci.4476-10.2011

Cited by 103 publications

(107 citation statements)

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“…To evaluate whether the responses of populations of neurons in MT carry sufficient information about the bidirectional and unidirectional stimuli, we used a linear variant of the support vector machine (SVM) (Vapnik, 2000;Schölkopf et al, 2002;Graf et al, 2011;Chen et al, 2015) to discriminate the bidirectional stimuli from unidirectional stimuli and between bidirectional stimuli that had different angular separations. In our experiments, we did not record the responses from a population of neurons simultaneously.…”

Section: Methodsmentioning

confidence: 99%

“…The hit and false alarm rates were calculated over the classifications of 10 ϫ N pairs of single-trial population responses of the testing neurons. When the hit or false alarm rate occasionally reached 1, dЈ was calculated using a modified formula: dЈ ϭ norminv{[(100 ϫ hit rate) ϩ 1]/102} Ϫ norminv{[(100 ϫ false alarm rate) ϩ 1]/102} (Chen et al, 2015). We only needed to use the modified dЈ twice in all calculations and those occasions were for the neuronal population that showed two response peaks.…”

Section: Methodsmentioning

confidence: 99%

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Distributed and Dynamic Neural Encoding of Multiple Motion Directions of Transparently Moving Stimuli in Cortical Area MT

Xiao

Huang

2015

J. Neurosci.

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Segmenting visual scenes into distinct objects and surfaces is a fundamental visual function. To better understand the underlying neural mechanism, we investigated how neurons in the middle temporal cortex (MT) of macaque monkeys represent overlapping random-dot stimuli moving transparently in slightly different directions. It has been shown that the neuronal response elicited by two stimuli approximately follows the average of the responses elicited by the constituent stimulus components presented alone. In this scheme of response pooling, the ability to segment two simultaneously presented motion directions is limited by the width of the tuning curve to motion in a single direction. We found that, although the population-averaged neuronal tuning showed response averaging, subgroups of neurons showed distinct patterns of response tuning and were capable of representing component directions that were separated by a small angle-less than the tuning width to unidirectional stimuli. One group of neurons preferentially represented the component direction at a specific side of the bidirectional stimuli, weighting one stimulus component more strongly than the other. Another group of neurons pooled the component responses nonlinearly and showed two separate peaks in their tuning curves even when the average of the component responses was unimodal. We also show for the first time that the direction tuning of MT neurons evolved from initially representing the vector-averaged direction of slightly different stimuli to gradually representing the component directions. Our results reveal important neural processes underlying image segmentation and suggest that information about slightly different stimulus components is computed dynamically and distributed across neurons.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Distributed and Dynamic Neural Encoding of Multiple Motion Directions of Transparently Moving Stimuli in Cortical Area MT

Xiao

Huang

2015

J. Neurosci.

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“…In this regard, the vestibular system may provide an alternative model to probe the origin of CPs because similar basic forms of spatiotemporal directional selectivity are seen at many levels of processing, from afferents to cortex (12). Recently, we provided the first demonstration (13), to our knowledge, that subcortical neurons in the vestibular nuclei (VN) and cerebellar nuclei (CN) could exhibit robust CPs, and these effects were even larger than those effects measured in some cortical areas under identical stimulus conditions (e.g., ref.…”

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confidence: 99%

Neuronal thresholds and choice-related activity of otolith afferent fibers during heading perception

Dickman

DeAngelis

et al. 2015

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

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How activity of sensory neurons leads to perceptual decisions remains a challenge to understand. Correlations between choices and single neuron firing rates have been found early in vestibular processing, in the brainstem and cerebellum. To investigate the origins of choice-related activity, we have recorded from otolith afferent fibers while animals performed a fine heading discrimination task. We find that afferent fibers have similar discrimination thresholds as central cells, and the most sensitive fibers have thresholds that are only twofold or threefold greater than perceptual thresholds. Unlike brainstem and cerebellar nuclei neurons, spike counts from afferent fibers do not exhibit trial-by-trial correlations with perceptual decisions. This finding may reflect the fact that otolith afferent responses are poorly suited for driving heading perception because they fail to discriminate self-motion from changes in orientation relative to gravity. Alternatively, if choice probabilities reflect top-down inference signals, they are not relayed to the vestibular periphery.neuronal threshold | choice probability | psychophysical threshold | otolith afferent | heading discrimination T he neural basis of perception holds a long-standing fascination for neuroscientists. How do the properties of single neurons and populations of neurons relate to, and account for, sensory perception? In all sensory systems, information about the world is first translated into neural activity by peripheral receptor neurons, and then transformed by multiple stages of subcortical and cortical processing into a perceptual decision. How and where does perception emerge from multiple neural representations that appear to be at least partially redundant? These questions have been addressed often in sensory and multisensory cortex (e.g., in refs. 1-3 for vestibular perception), but much less is known about how the activity of sensory afferents relates to perceptual sensitivity and perceptual decisions.One way to assess a potential role of sensory neurons in a perceptual task is to compare neuronal and perceptual sensitivity, measured simultaneously in the same subject (4). Although this comparison has been done many times for cortical neurons (1, 5-7), little is known about how the sensitivity of peripheral afferents compares with behavior apart from microneurography studies of tactile afferents in humans (8, 9). To our knowledge, the present study provides the first direct comparison of afferent neuronal sensitivity and perceptual sensitivity, measured simultaneously in experimental animals. Results of such comparisons have important implications for understanding how population encoding and decoding may constrain and shape the information that guides behavior.Another way that neuroscientists have explored the functional links between sensory neurons and perception is by measuring the trial-by-trial correlations between neural activity and perceptual decisions, which are typically quantified as "choice probabilities" (CPs) (10). The "bottom-...

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“…Figure 4A summarizes a cortical circuit including areas with neurons tuned to both optic flow and inertial heading cues (varying shades of red and dark yellow, respectively). Based on these findings, heading perception likely involves several multisensory cortical regions, such as the dorsal medial superior temporal (MSTd) area (Bremmer et al 1997;Duffy 1998;Page and Duffy 2003;Gu et al 2006;Maciokas and Britten 2010), the ventral intraparietal (VIP) area (Bremmer et al 1999Schlack et al 2002;Zhang et al 2004;Maciokas and Britten 2010;Chen et al 2011aChen et al ,b, 2013a, the visual posterior sylvian (VPS) area (Chen et al 2011c), and the pursuit area of the frontal eye fields (FEF; Y Gu, GC DeAngelis, DE Angelaki, unpubl. ).…”

Section: Neural Correlates Of Multisensory Heading Perceptionmentioning

confidence: 99%

“…Although some differences in response properties between VIP and MSTd have been noted (e.g., Chen et al 2011a;Yang et al 2011), MSTd and VIP share many similarities in their tuning to visual and vestibular stimuli and also show strong correlations between neural activity and perceptual choice (Gu et al 2008;Maciokas and Britten 2010;Chen et al 2011aChen et al ,b, 2013a. As illustrated in Figure 5, where firing rate is plotted as a function of heading direction for the vestibular (dark yellow) and visual (red) conditions, multisensory MSTd/ VIP cells fall into one of two groups, which were identified by constructing spatial tuning curves as heading direction was varied: (1) "Congruent" neurons had similar visual/vestibular preferred stimuli and thus signaled the same heading direction under both single-cue stimulus conditions.…”

Section: Neural Correlates Of Multisensory Heading Perceptionmentioning

confidence: 99%

How Optic Flow and Inertial Cues Improve Motion Perception

Angelaki

2014

Cold Spring Harb Symp Quant Biol

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Estimating our egocentric heading direction is an important component of navigation. Recent studies have explored how inertial cues from the vestibular system and optic flow signals from the visual system interact to improve perceptual precision and accuracy. Heading precision is improved through multisensory integration, whereas heading accuracy is maintained through multisensory calibration mechanisms. Neural correlates of these behaviors are found in a large interconnected cortical network, although the specific contributions of each area remain to be explored. Whether and how this multisensory selfmotion cortical circuit contributes to navigation and how egocentric heading signals interact with the allocentric representations for foraging and exploration also remain challenges for the future.

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A Comparison of Vestibular Spatiotemporal Tuning in Macaque Parietoinsular Vestibular Cortex, Ventral Intraparietal Area, and Medial Superior Temporal Area

Cited by 103 publications

References 58 publications

Distributed and Dynamic Neural Encoding of Multiple Motion Directions of Transparently Moving Stimuli in Cortical Area MT

Distributed and Dynamic Neural Encoding of Multiple Motion Directions of Transparently Moving Stimuli in Cortical Area MT

Neuronal thresholds and choice-related activity of otolith afferent fibers during heading perception

How Optic Flow and Inertial Cues Improve Motion Perception

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