scholarly journals Hyperactive sensorimotor cortex during voice perception in spasmodic dysphonia

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yuji Kanazawa ◽  
Yo Kishimoto ◽  
Ichiro Tateya ◽  
Toru Ishii ◽  
Tetsuji Sanuki ◽  
...  
Keyword(s):  
Sensorimotor Cortex ◽  
Judgment Task ◽  
Neural Systems ◽  
Spasmodic Dysphonia ◽  
Neural Activation ◽  
Voice Perception ◽  
Linear Discriminant ◽  
Voice Production ◽  
Sound Discrimination ◽  
Healthy Participants

Abstract Spasmodic dysphonia (SD) is characterized by an involuntary laryngeal muscle spasm during vocalization. Previous studies measured brain activation during voice production and suggested that SD arises from abnormal sensorimotor integration involving the sensorimotor cortex. However, it remains unclear whether this abnormal sensorimotor activation merely reflects neural activation produced by abnormal vocalization. To identify the specific neural correlates of SD, we used a sound discrimination task without overt vocalization to compare neural activation between 11 patients with SD and healthy participants. Participants underwent functional MRI during a two-alternative judgment task for auditory stimuli, which could be modal or falsetto voice. Since vocalization in falsetto is intact in SD, we predicted that neural activation during speech perception would differ between the two groups only for modal voice and not for falsetto voice. Group-by-stimulus interaction was observed in the left sensorimotor cortex and thalamus, suggesting that voice perception activates different neural systems between the two groups. Moreover, the sensorimotor signals positively correlated with disease severity of SD, and classified the two groups with 73% accuracy in linear discriminant analysis. Thus, the sensorimotor cortex and thalamus play a central role in SD pathophysiology and sensorimotor signals can be a new biomarker for SD diagnosis.

Sensorimotor Cortex Activation during Voice Perception in Spasmodic Dysphonia

2021 ◽  
Vol 62 (4) ◽  
pp. 287-293
Author(s):  
Yuji Kanazawa ◽  
Yo Kishimoto ◽  
Tetsuji Sanuki ◽  
Shinya Hiroshiba ◽  
Koichi Omori ◽  
...  
Keyword(s):  
Sensorimotor Cortex ◽  
Spasmodic Dysphonia ◽  
Voice Perception

scholarly journals Apparent physical brightness of graphemes is altered by their synaesthetic colour in grapheme-colour synaesthetes

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Kyuto Uno ◽  
Kazuhiko Yokosawa
Keyword(s):  
Visual Processing ◽  
Standard Stimulus ◽  
Judgment Task ◽  
Neural Activation ◽  
Brightness Perception ◽  
Early Visual Processing ◽  
Colour Sensation ◽  
Colour Experience ◽  
Dark Colour ◽  
Mind's Eye

AbstractGrapheme-colour synaesthesia is a condition in which the visual perception of letters or numbers induces a specific colour sensation. In this study, we demonstrated that the apparent physical brightness of graphemes is modulated by the synaesthetic colours elicited by them. Synaesthetes first selected a synaesthetic colour corresponding to each capital letter and digit. Then, we selected a grapheme stimulus with a bright synaesthetic colour and one with a dark colour for each synaesthete. Finally, synaesthetes and non-synaesthete controls participated in a brightness judgment task, in which each participant judged the real brightness of each of the two stimuli compared to a standard stimulus. Compared to non-synaesthetes, synaesthetes judged a grapheme with a bright synaesthetic colour to be brighter than one with a dark synaesthetic colour, suggesting that the synaesthetic colour experience of synaesthetes alters their brightness perception. Such alteration in real brightness perception was observed both in those who experienced synaesthetic colours in external space (projector-type synaesthetes) and in those who experienced such colours ‘in the mind’s eye’ (associator-type synaesthetes). These results support the view that early visual processing is modulated by feedback transmitted from the V4 colour area, the neural activation of which accompanies synaesthetic colour experience.

Voice Perception Across Species

2018 ◽  
pp. 362-392 ◽  
Author(s):  
Attila Andics ◽  
Tamás Faragó
Keyword(s):  
Vocal Communication ◽  
Neural Substrates ◽  
Auditory Cues ◽  
Voice Perception ◽  
Voice Production ◽  
Good Basis ◽  
General Ability ◽  
Wide Range ◽  
Species Specific ◽  
Voice Processing

This chapter provides a wide comparative perspective on the behavioural and neural capacities for vocalization processing in general, and for cross-species voice processing in particular. Vocal communication usually takes place among conspecifics, but in certain cases heterospecific vocalizations can also help optimize behaviour. Vocal anatomy and the neurophysiological processes of voice production are highly conserved across vertebrates, and the perception of basic biological meanings from vocalizations is thus based on auditory cues that are not species-specific. This chapter suggests that these similarities, and also the general ability to learn about vocal sounds, provide a good basis to assume that specific cues in heterospecific vocalizations may be efficiently processed. The chapter reviews the anatomical, behavioural, and neuroscientific evidence suggesting that heterospecific vocalization processing may work efficiently across a wide range of taxa, and shares the neural substrates involved in the processing of conspecific communication sounds.

scholarly journals Mental Mechanisms for Topics Identification

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Louis Massey
Keyword(s):  
Baseline Level ◽  
Short Term Memory ◽  
Decay Rates ◽  
Neural Systems ◽  
Long Term Memory ◽  
Neural Activation ◽  
Main Hypothesis ◽  
Term Memory

Topics identification (TI) is the process that consists in determining the main themes present in natural language documents. The current TI modeling paradigm aims at acquiring semantic information from statistic properties of large text datasets. We investigate the mental mechanisms responsible for the identification of topics in a single document given existing knowledge. Our main hypothesis is that topics are the result of accumulated neural activation of loosely organized information stored in long-term memory (LTM). We experimentally tested our hypothesis with a computational model that simulates LTM activation. The model assumes activation decay as an unavoidable phenomenon originating from the bioelectric nature of neural systems. Since decay should negatively affect the quality of topics, the model predicts the presence of short-term memory (STM) to keep the focus of attention on a few words, with the expected outcome of restoring quality to a baseline level. Our experiments measured topics quality of over 300 documents with various decay rates and STM capacity. Our results showed that accumulated activation of loosely organized information was an effective mental computational commodity to identify topics. It was furthermore confirmed that rapid decay is detrimental to topics quality but that limited capacity STM restores quality to a baseline level, even exceeding it slightly.

scholarly journals Biometric application and classification of individuals using postural parameters

2013 ◽  
Vol 7 (2) ◽  
pp. 580-593 ◽  
Author(s):  
Dhouha Maatar ◽  
Régis Fournier ◽  
Zied Lachiri ◽  
Amine Naitali
Keyword(s):  
Postural Control ◽  
Behavioral Characteristics ◽  
K Nearest Neighbors ◽  
Linear Discriminant ◽  
Wavelet Features ◽  
Level 3 ◽  
Orthostatic Position ◽  
Level 2 ◽  
Healthy Participants

This Biometrics refers to automatic recognition of individuals based on their physiological and/or behavioral characteristics. The displacement of the centre of pressure (COP) is a measure that has been successfully employed in studies regarding the postural control. So why not using the postural control as a behavioral characteristic to recognize individuals? The purpose of this study is to recognize individuals and to classify them by their age, gender, height and weight using postural features. The recognition approaches: Linear Discriminant Analysis (LDA), Support Vectors Machine (SVM) and K Nearest Neighbors (KNN) are applied to these biometric application. The postural features using in this application are extracted from data from twenty five healthy participants (average age 31 ± 11 years) standing in orthostatic position on an electromagnetic platform. The features are divided into three categories: classical features (extracted directly from the signals), mPCA features (extracted from the components trembling and rambling issued from the mPCA decomposition) and wavelet features (extracted from the components detail signal level 3 and detail signal level 2 issued from the wavelet decomposition. The results show that the ten subjects chosen for the recognition application are identified by the LDA with the rate of 80.43%. The classification applications (according to age, gender, height and weight) are performed for the all participants and the best resulted classification rates ranged from 82.61% to 93.48%. Most of these best rates are performed by the SVM classifiers using the totality of the features.

The effects of sleep deprivation on vigilance and neural activation during the Sustained Attention to Response Task

2019 ◽  
Author(s):  
Johnny Soares
Keyword(s):  
Sleep Deprivation ◽  
Sustained Attention ◽  
Response Times ◽  
Neural Activation ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Normal Sleep ◽  
Response Task ◽  
Error Percentage ◽  
Healthy Participants

The effects of sleep deprivation on vigilance and neural activation during the Sustained Attention to Response TaskIntroduction: Sleep deprivation is common and can result in impaired vigilance with fatal consequences, but little is known about effects of sleep deprivation on neural activation. With functional magnetic resonance imaging (fMRI), neural activation associated with an attention-demanding task such as the Sustained Attention to Response Task (SART) can be visualized and analyzed. This is one of the first studies combining SART with fMRI to study total sleep deprivation. Aims: This study aimed to determine how sleep deprivation affects vigilance and neural activation during the SART. Primary outcomes are the number of errors committed during the SART and fMRI activity associated to the SART task. Material and Methods: This cross-over study compares sleep deprivation and full sleep. 9 healthy participants (6 males and 3 females) with normal sleep patterns were included. Participants were randomized to undergo both conditions in counterbalanced order and were planned for a total of three different MRI sessions and two SART evaluations. Results: No SART results were statistically significant, however there was a tendency of increased error percentage in the sleep deprived condition. There was no strong tendency of longer response times in sleep deprived condition. Clusters of neural activation were observed in areas associated with the executive network. However, none were statistically significant. Conclusions: This study suggests that SART performance regarding accuracy may be affected by sleep deprivation; however response times are not. No significant effect of sleep deprivation on neural activation was found, however indications of areas related to vigilance were located in expected areas.

scholarly journals Central voice production and pathophysiology of spasmodic dysphonia

2017 ◽  
Vol 128 (1) ◽  
pp. 177-183 ◽  
Author(s):  
Niv Mor ◽  
Kristina Simonyan ◽  
Andrew Blitzer
Keyword(s):  
Spasmodic Dysphonia ◽  
Voice Production

Parameter Extraction from Population Codes: A Critical Assessment

1996 ◽  
Vol 8 (3) ◽  
pp. 511-529 ◽  
Author(s):  
Herman P. Snippe
Keyword(s):  
Parameter Extraction ◽  
Minimum Variance ◽  
Neural System ◽  
Center Of Gravity ◽  
Movement Direction ◽  
Neural Systems ◽  
Neural Activation ◽  
Neuronal Ensemble ◽  
Activation Profile ◽  
Perceptual Systems

In perceptual systems, a stimulus parameter can be extracted by determining the center-of-gravity of the response profile of a population of neural sensors. Likewise at the motor end of a neural system, center-of-gravity decoding, also known as vector decoding, generates a movement direction from the neural activation profile. We evaluate these schemes from a statistical perspective, by comparing their statistical variance with the minimum variance possible for an unbiased parameter extraction from the noisy neuronal ensemble activation profile. Center-of-gravity decoding can be statistically optimal. This is the case for regular arrays of sensors with gaussian tuning profiles that have an output described by Poisson statistics, and for arrays of sensors with a sinusoidal tuning profile for the (angular) parameter estimated. However, there are also many cases in which center-of-gravity decoding is highly inefficient. This includes the important case where sensor positions are very irregular. Finally, we study the robustness of center-of-gravity decoding against response nonlinearities at different stages of an information processing hierarchy. We conclude that, in neural systems, instead of representing a parameter explicitly, it is safer to leave the parameter coded implicitly in a neuronal ensemble activation profile.

scholarly journals Repeated binge access to a palatable food alters feeding behavior, hormone profile, and hindbrain c-Fos responses to a test meal in adult male rats

2009 ◽  
Vol 297 (3) ◽  
pp. R622-R631 ◽  
Author(s):  
Nicholas T. Bello ◽  
Angela S. Guarda ◽  
Chantelle E. Terrillion ◽  
Graham W. Redgrave ◽  
Janelle W. Coughlin ◽  
...  
Keyword(s):  
Calorie Restriction ◽  
Adult Male ◽  
Male Rats ◽  
Neural Systems ◽  
Neural Activation ◽  
Palatable Food ◽  
Sprague Dawley ◽  
Continuous Access ◽  
Physiological Alterations ◽  
Sprague Dawley Rats

Repetitive cycles of palatable food access and chronic calorie restriction alter feeding behaviors and forebrain neural systems. The purpose of this study was to determine the behavioral, endocrine, and meal-related hindbrain neural activation in adult male Sprague-Dawley rats exposed to a binge-access feeding schedule. The binge-access schedule consisted of repeated twice-per-week episodes of acute calorie restriction (to one-third of the previous day's intake) followed by 2 h of concurrent access to high-calorie palatable food (sweetened fat: 90% vegetable shortening-10% sucrose) and chow. The binge-access rats consumed more calories during the “binge” period than rats with continuous access to sweetened fat (continuous-access group) or subjected to repeated acute calorie restriction only (chow-restricted group). The binge-access group also exhibited a ∼25% increase in sweetened fat intake from week 1 to week 6. Persistence of the binge phenotype in the binge-access animals was demonstrated 2 wk, but not 4 wk, after ad libitum chow. The binge-access and chow-restricted groups maintained a similar normal body composition and hormonal profiles, whereas the continuous-access animals developed an obese phenotype. Terminal ghrelin levels were significantly higher in the binge-access group than in the continuous-access group. Consumption of a standardized meal resulted in more c-Fos-positive cells along the anterior-posterior nucleus of the solitary tract regions in the binge-access group than in naive controls. These results suggest that repeated cycles of acute calorie restriction followed by palatable food produce physiological alterations that may facilitate overconsumption of a highly palatable food during limited-access periods.

scholarly journals Cross-participant prediction of vigilance stages through the combined use of wPLI and wSMI EEG functional connectivity metrics

SLEEP ◽  
2020 ◽  
Author(s):  
Laura Sophie Imperatori ◽  
Jacinthe Cataldi ◽  
Monica Betta ◽  
Emiliano Ricciardi ◽  
Robin A A Ince ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Rem Sleep ◽  
Phase Lag ◽  
Linear Discriminant ◽  
Functional Differences ◽  
Combined Use ◽  
Discriminant Analyses ◽  
Eeg Functional Connectivity ◽  
Weighted Phase Lag Index ◽  
Healthy Participants

Abstract Functional connectivity (FC) metrics describe brain inter-regional interactions and may complement information provided by common power-based analyses. Here, we investigated whether the FC-metrics weighted Phase Lag Index (wPLI) and weighted Symbolic Mutual Information (wSMI) may unveil functional differences across four stages of vigilance—wakefulness (W), NREM-N2, NREM-N3, and REM sleep—with respect to each other and to power-based features. Moreover, we explored their possible contribution in identifying differences between stages characterized by distinct levels of consciousness (REM+W vs. N2+N3) or sensory disconnection (REM vs. W). Overnight sleep and resting-state wakefulness recordings from 24 healthy participants (27 ± 6 years, 13F) were analyzed to extract power and FC-based features in six classical frequency bands. Cross-validated linear discriminant analyses (LDA) were applied to investigate the ability of extracted features to discriminate (1) the four vigilance stages, (2) W+REM vs. N2+N3, and (3) W vs. REM. For the four-way vigilance stages classification, combining features based on power and both connectivity metrics significantly increased accuracy relative to considering only power, wPLI, or wSMI features. Delta-power and connectivity (0.5–4 Hz) represented the most relevant features for all the tested classifications, in line with a possible involvement of slow waves in consciousness and sensory disconnection. Sigma-FC, but not sigma-power (12–16 Hz), was found to strongly contribute to the differentiation between states characterized by higher (W+REM) and lower (N2+N3) probabilities of conscious experiences. Finally, alpha-FC resulted as the most relevant FC-feature for distinguishing among wakefulness and REM sleep and may thus reflect the level of disconnection from the external environment.

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