Acoustic Patterns of Infant Vocalizations Expressing Emotions and Communicative Functions

2002 ◽  
Vol 45 (2) ◽  
pp. 311-317 ◽  
Author(s):  
C. Papaeliou ◽  
G. Minadakis ◽  
D. Cavouras
Keyword(s):  
Classification Accuracy ◽  
Acoustic Analysis ◽  
Cooperative Interaction ◽  
First Year ◽  
Vocal Repertoire ◽  
System A ◽  
Communicative Functions ◽  
Infant Vocalizations ◽  
Signal Features ◽  
Acoustic Pattern

The present study aimed at identifying the acoustic pattern of vocalizations, produced by 7- to 11-month-old infants, that were interpreted by their mothers as expressing emotions or communicative functions. Participants were 6 healthy, first-born English infants, 3 boys and 3 girls, and their mothers. The acoustic analysis of the vocalizations was performed using a pattern recognition (PR) software system. A PR system not only calculates signal features, it also automatically detects patterns in the arrangement of such features. The following results were obtained: (a) the PR system distinguished vocalizations interpreted as emotions from vocalizations interpreted as communicative functions with an overall accuracy of 87.34%; (b) the classification accuracy of the PR system for vocalizations that convey emotions was 85.4% and for vocalizations that convey communicative functions was 89.5%; and (c) compared to vocalizations that express emotions, vocalizations that express communicative functions were shorter, displayed lower fundamental frequency values, and had greater overall intensity. These findings suggest that in the second half of the first year, infants possess a vocal repertoire that contributes to regulating cooperative interaction with their mothers, which is considered one of the major prerequisites for language acquisition.

scholarly journals Biomimetic Sonar for Electrical Activation of the Auditory Pathway

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
D. Menniti ◽  
S. A. Pullano ◽  
M. G. Bianco ◽  
R. Citraro ◽  
E. Russo ◽  
...  
Keyword(s):  
Spatial Information ◽  
Electronic Device ◽  
Principal Component ◽  
Auditory Pathway ◽  
Brain Response ◽  
Implanted Electrodes ◽  
System A ◽  
Signal Features ◽  
New Perspective ◽  
Rate Frequency

Relying on the mechanism of bat’s echolocation system, a bioinspired electronic device has been developed to investigate the cortical activity of mammals in response to auditory sensorial stimuli. By means of implanted electrodes, acoustical information about the external environment generated by a biomimetic system and converted in electrical signals was delivered to anatomically selected structures of the auditory pathway. Electrocorticographic recordings showed that cerebral activity response is highly dependent on the information carried out by ultrasounds and is frequency-locked with the signal repetition rate. Frequency analysis reveals that delta and beta rhythm content increases, suggesting that sensorial information is successfully transferred and integrated. In addition, principal component analysis highlights how all the stimuli generate patterns of neural activity which can be clearly classified. The results show that brain response is modulated by echo signal features suggesting that spatial information sent by biomimetic sonar is efficiently interpreted and encoded by the auditory system. Consequently, these results give new perspective in artificial environmental perception, which could be used for developing new techniques useful in treating pathological conditions or influencing our perception of the surroundings.

Development of V-Shaped Hybrid Mass Damper and its Application to High-Rise Buildings

1995 ◽  
Author(s):  
Masanori Imazeki ◽  
Koji Tanida ◽  
Masao Mutaguchi ◽  
Yuji Koike ◽  
Tamotsu Murata ◽  
...  
Keyword(s):  
First Year ◽  
Building Structures ◽  
Large Space ◽  
Natural Period ◽  
High Rise ◽  
High Rise Building ◽  
System A ◽  
Mass Damper ◽  
Story Building ◽  
Auxiliary Mass

Abstract A hybrid mass damper system has been developed with a view to counteracting wind- and earthquake-excited vibrations of large high-rise building structures. In order to eliminate the large space needed to accommodate a pendulum-type mass damper adapted to the long period of high-rise building, mechanism has been devised for suspending the auxiliary mass on a V-shaped rail sliding on rollers. The base angle of the V-shaped rail is varied for adjusting the natural period of the mass damper system. A suboptimal algorithm based on the minimum norm method has been adopted for designing the auxiliary mass driving system. Three units of this damper system, each equipped with auxiliary mass weighing 110 tons, have been installed on a 52-story building. Satisfactory performance conforming in all practical aspects with design has been verified from vibration test on actual building after installation. As sequel, the functioning of the system during the first year of service is also reported.

scholarly journals EEG and Deep Learning Based Brain Cognitive Function Classification

Computers ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 104
Author(s):  
Saraswati Sridhar ◽  
Vidya Manian
Keyword(s):  
Deep Learning ◽  
Motor Imagery ◽  
Cognitive Aging ◽  
Classification Accuracy ◽  
Short Term Memory ◽  
Principal Component ◽  
Learning System ◽  
Detection Accuracy ◽  
Band Power ◽  
Signal Features

Electroencephalogram signals are used to assess neurodegenerative diseases and develop sophisticated brain machine interfaces for rehabilitation and gaming. Most of the applications use only motor imagery or evoked potentials. Here, a deep learning network based on a sensory motor paradigm (auditory, olfactory, movement, and motor-imagery) that employs a subject-agnostic Bidirectional Long Short-Term Memory (BLSTM) Network is developed to assess cognitive functions and identify its relationship with brain signal features, which is hypothesized to consistently indicate cognitive decline. Testing occurred with healthy subjects of age 20–40, 40–60, and >60, and mildly cognitive impaired subjects. Auditory and olfactory stimuli were presented to the subjects and the subjects imagined and conducted movement of each arm during which Electroencephalogram (EEG)/Electromyogram (EMG) signals were recorded. A deep BLSTM Neural Network is trained with Principal Component features from evoked signals and assesses their corresponding pathways. Wavelet analysis is used to decompose evoked signals and calculate the band power of component frequency bands. This deep learning system performs better than conventional deep neural networks in detecting MCI. Most features studied peaked at the age range 40–60 and were lower for the MCI group than for any other group tested. Detection accuracy of left-hand motor imagery signals best indicated cognitive aging (p = 0.0012); here, the mean classification accuracy per age group declined from 91.93% to 81.64%, and is 69.53% for MCI subjects. Motor-imagery-evoked band power, particularly in gamma bands, best indicated (p = 0.007) cognitive aging. Although the classification accuracy of the potentials effectively distinguished cognitive aging from MCI (p < 0.05), followed by gamma-band power.

Cooperation between the Hippocampus and the Striatum during Episodic Encoding

2011 ◽  
Vol 23 (7) ◽  
pp. 1597-1608 ◽  
Author(s):  
Talya Sadeh ◽  
Daphna Shohamy ◽  
Dana Rubi Levy ◽  
Niv Reggev ◽  
Anat Maril
Keyword(s):  
Episodic Memory ◽  
Learning And Memory ◽  
Cooperative Interaction ◽  
Memory Encoding ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
System A ◽  
Episodic Encoding ◽  
Within Subjects

The hippocampus and the striatum are thought to play distinct roles in learning and memory, each supporting an independent memory system. A fundamental question is whether, and how, these systems interact to jointly contribute to learning and memory. In particular, it remains unknown whether the striatum contributes selectively to implicit, habitual learning, or whether the striatum may also contribute to long-term episodic memory. Here, we show with functional magnetic resonance imaging (fMRI) that the hippocampus and the striatum interact cooperatively to support episodic memory formation. Participants were scanned during a memory encoding paradigm and, subsequently, were tested for memory of encoded items. fMRI data revealed that successful memory was associated with greater activity in both the hippocampus and the striatum (putamen) during encoding. Furthermore, activity in the hippocampus and the striatum was correlated within subjects for items that were later remembered, but not for items that were forgotten. Finally, across subjects, the strength of the correlation between the hippocampus and the striatum predicted memory success. These findings provide novel evidence for contributions of both the striatum and the hippocampus to successful episodic encoding and for a cooperative interaction between them.

RO-ILS: Radiation Oncology Incident Learning System: A report from the first year of experience

2015 ◽  
Vol 5 (5) ◽  
pp. 312-318 ◽  
Author(s):  
David J. Hoopes ◽  
Adam P. Dicker ◽  
Nadine L. Eads ◽  
Gary A. Ezzell ◽  
Benedick A. Fraass ◽  
...  
Keyword(s):  
Radiation Oncology ◽  
Learning System ◽  
First Year ◽  
System A ◽  
Incident Learning

Sex differences in the vocal repertoire of adult red-capped mangabeys (Cercocebus torquatus): a multi-level acoustic analysis

2010 ◽  
Vol 72 (4) ◽  
pp. 360-375 ◽  
Author(s):  
Hélène Bouchet ◽  
Anne-Sophie Pellier ◽  
Catherine Blois-Heulin ◽  
Alban Lemasson
Keyword(s):  
Sex Differences ◽  
Acoustic Analysis ◽  
Vocal Repertoire ◽  
Cercocebus Torquatus ◽  
Multi Level

scholarly journals Content and Language Integrated Learning Methodology in Optional Humanities Courses for First-Year University Students: A Case Study

2020 ◽  
Vol 89 ◽  
pp. 51-62
Author(s):  
Oleg Tarnopolsky ◽  
Marina Kabanova
Keyword(s):  
University Students ◽  
Information Search ◽  
Learning Activities ◽  
Target Language ◽  
Cooperative Interaction ◽  
First Year ◽  
Online Information ◽  
Integrated Learning ◽  
First Year Students ◽  
Clear Cut

The article analyzes using Content and Language Integrated Learning (CLIL) for teaching one of the optional humanities disciplines to Ukrainian university students of different majors. The discipline discussed in the article as an example of using CLIL methodology is “The Fundamentals of Psychology and Pedagogy” and it is in the list of optional humanities subjects for the first-year students of Alfred Nobel University in Dnipro, Ukraine. However, unlike the other optional humanities disciplines, the methodology underlying this course is based on teaching the subject in English, instead of Ukrainian, following the CLIL approach widely used in the European education but still little known in Ukraine. The purpose of the paper is to expose and analyze the original methodology developed that conditioned the specific structure of the relevant course, and the specific learning activities used in it. The essence of the developed CLIL theory-based methodology and its practical application are manifested through learning activities that include students’ mini-lectures/workshop-type presentations, brainstorming, case-studies, discussions, and a learning project with its results summarized in students’ essays, abstracts, and summaries written in English. The students collect the information required for completing their tasks not only from the teacher’s lectures and the recommended literature but also (and mostly) by way of doing extensive Internet-search on psychological and pedagogical sites in English. All this makes CLIL in the case under discussion experiential-interactive (through personal experience in extra-linguistic subject-related activities gained in interaction with other students), blended (with the organic combination of traditional in-class learning and out-of-class online information search), autonomous (students’ autonomous learning activities-centered), and cooperative (with those activities being done in students’ cooperative interaction). As the result, students mostly self-construct their knowledge of the discipline by way of using the target language as the tool for such self-construction. This makes the elaborated course a clear-cut case of constructivism in CLIL pedagogy. Subject Classification Numbers: PACS 01.40.-d (Education)

scholarly journals Adenohypophyseal function in children aged under 1 born to mothers in whom pregnancy was induced

1996 ◽  
Vol 42 (1) ◽  
pp. 9-11
Author(s):  
A. A. Afonin ◽  
V. I. Orlov ◽  
Yu. A. Knyazev ◽  
E. P. Rymanhevskaya ◽  
L. A. Polschikova ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Follicle Stimulating Hormone ◽  
First Year ◽  
Polycystic Ovaries ◽  
Somatotropic Hormone ◽  
Hormonal Function ◽  
System A ◽  
The Central Nervous System ◽  
First Year Of Life

A total of 143 children born to mothers who suffered from various forms of endocrine sterility and in whom pregnancy was induced were examined. The levels of somatotropic hormone, prolactin, luteotropic hormone, and follicle-stimulating hormone were measured in the blood on days 1, 3, 6 of life and at the age of 3, 6, and 12 months. The hormones were radioimmunoassayed and measured by imnmnofluorescent methods. The results indicate marked disorders of the adenohypophyseal function in these children, these disorders persisting through the first year of life. The most evident shifts of hormonal parameters are observed in children born to mothers with primary disorders of ovarian hormonal function, particularly so in cases with the polycystic ovaries syndrome, and in children with perinatal involvement of the central nervous system. A high correlation between adenohypophyseal and peripheral gland hormone levels and the concentration of somatotropic hormone was detected.

scholarly journals Classification of Targets and Distractors Present in Visual Hemifields Using Time-Frequency Domain EEG Features

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Sweeti ◽  
Deepak Joshi ◽  
B. K. Panigrahi ◽  
Sneh Anand ◽  
Jayasree Santhosh
Keyword(s):  
Classification Accuracy ◽  
Statistical Significance ◽  
Repeated Measure ◽  
Stepwise Discriminant Analysis ◽  
Attention Task ◽  
Time Frequency ◽  
Signal Features ◽  
Measure Analysis ◽  
Task Conditions ◽  
Visual Hemifields

This paper presents a classification system to classify the cognitive load corresponding to targets and distractors present in opposite visual hemifields. The approach includes the study of EEG (electroencephalogram) signal features acquired in a spatial attention task. The process comprises of EEG feature selection based on the feature distribution, followed by the stepwise discriminant analysis- (SDA-) based channel selection. Repeated measure analysis of variance (rANOVA) is applied to test the statistical significance of the selected features. Classifiers are developed and compared using the selected features to classify the target and distractor present in visual hemifields. The results provide a maximum classification accuracy of 87.2% and 86.1% and an average classification accuracy of 76.5 ± 4% and 76.2 ± 5.3% over the thirteen subjects corresponding to the two task conditions. These correlates present a step towards building a feature-based neurofeedback system for visual attention.

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