scholarly journals The effects of alcohol on the emotional stimuli processing through the investigation of neurophysiological signals

2012 ◽  
Author(s):  
Χρυσούλα Λιθαρή
Keyword(s):  
Human Brain ◽  
Functional Organization ◽  
Emotional States ◽  
Experimental Procedure ◽  
Additional Information ◽  
Work Related ◽  
Brain Responses ◽  
Social Drinking ◽  
Neural Underpinnings ◽  
The Brain

[…] Social drinking, for most people, is an inseparable part of every-day life. Alcohol is used and abused for its ability to modify emotional states, and more precisely, to reduce anxiety [1], [2]. It is therefore essential to study the effects of inebriation in healthy, non-dependent individuals, given the frequency of abuse and binge drinking. A better understanding of the neural underpinnings of alcohol consumption could have a number of social implications, including the origin of the inebriation-induced aggressiveness, the tendency to abuse and the driving or work-related hazards [3]. More precisely, this study aimed to answer to the following questions: - How acute alcohol intake affects the human brain responses to affective pictures? - Is the effect of alcohol emotion-specific or is it the same for all kinds of emotion-eliciting images? - Is the brain functional organization at rest modulated by inebriation? - What are the similarities and the differences between the EEG and MEG studies conducted? In a second level, there has been an effort to design the optimal experimental procedure to examine as accurately as possible the multi-factorial issue of inebriation effects on the human brain. Regarding the analysis of the recordings, the standard analysis techniques on sensor levels were first applied, and then, more advanced techniques, such as cortical source estimation and functional connectivity were used to examine whether any additional information is provided. […]

scholarly journals Speech perception at birth: The brain encodes fast and slow temporal information

2020 ◽  
Vol 6 (30) ◽  
pp. eaba7830
Author(s):  
Laurianne Cabrera ◽  
Judit Gervain
Keyword(s):  
Infrared Spectroscopy ◽  
Speech Perception ◽  
Human Brain ◽  
Language Learning ◽  
Auditory Processing ◽  
Near Infrared ◽  
Acoustic Cues ◽  
Language Experience ◽  
Brain Responses ◽  
The Brain

Speech perception is constrained by auditory processing. Although at birth infants have an immature auditory system and limited language experience, they show remarkable speech perception skills. To assess neonates’ ability to process the complex acoustic cues of speech, we combined near-infrared spectroscopy (NIRS) and electroencephalography (EEG) to measure brain responses to syllables differing in consonants. The syllables were presented in three conditions preserving (i) original temporal modulations of speech [both amplitude modulation (AM) and frequency modulation (FM)], (ii) both fast and slow AM, but not FM, or (iii) only the slowest AM (<8 Hz). EEG responses indicate that neonates can encode consonants in all conditions, even without the fast temporal modulations, similarly to adults. Yet, the fast and slow AM activate different neural areas, as shown by NIRS. Thus, the immature human brain is already able to decompose the acoustic components of speech, laying the foundations of language learning.

scholarly journals Consistency in macroscopic human brain responses to noisy time-varying visual inputs

2019 ◽  
Author(s):  
Keiichi Kitajo ◽  
Takumi Sase ◽  
Yoko Mizuno ◽  
Hiromichi Suetani
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Brain Dynamics ◽  
Time Varying ◽  
Ongoing Activity ◽  
Visual Inputs ◽  
Brain Responses ◽  
Individual Variations ◽  
Open Question ◽  
The Brain

AbstractIt is an open question as to whether macroscopic human brain responses to repeatedly presented external inputs show consistent patterns across trials. We here provide experimental evidence that human brain responses to noisy time-varying visual inputs, as measured by scalp electroencephalography (EEG), show a signature of consistency. The results indicate that the EEG-recorded responses are robust against fluctuating ongoing activity, and that they respond to visual stimuli in a repeatable manner. This consistency presumably mediates robust information processing in the brain. Moreover, the EEG response waveforms were discriminable between individuals, and were invariant over a number of days within individuals. We reveal that time-varying noisy visual inputs can harness macroscopic brain dynamics and can manifest hidden individual variations.

scholarly journals Functional parcellation of human brain using localized topo-connectivity mapping

2021 ◽  
Author(s):  
Yu Zhao ◽  
Yurui Gao ◽  
Muwei Li ◽  
Adam W. Anderson ◽  
Zhaohua Ding ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Organization ◽  
Statistical Tests ◽  
Simulated Data ◽  
Fmri Data ◽  
Anatomical Structures ◽  
Connectivity Mapping ◽  
Subcortical Region ◽  
Human Connectome Project ◽  
The Brain

<p>The analysis of connectivity between parcellated regions of cortex provides insights into the functional architecture of the brain at a systems level. However, there has been less progress in the derivation of functional structures from voxel-wise analyses at finer scales. We propose a novel method, called localized topo-connectivity mapping with singular-value-decomposition-informed filtering (or filtered LTM), to identify and characterize voxel-wise functional structures in the human brain using resting-state fMRI data. Here we describe its mathematical background and provide a proof-of-concept using simulated data that allow an intuitive interpretation of the results of filtered LTM. The algorithm has also been applied to 7T fMRI data as part of the Human Connectome Project to generate group-average LTM images. Functional structures revealed by this approach agree moderately well with anatomical structures identified by T<sub>1</sub>-weighted images and fractional anisotropy maps derived from diffusion MRI. Moreover, the LTM images also reveal subtle functional variations that are not apparent in the anatomical structures. To assess the performance of LTM images, the subcortical region and occipital white matter were separately parcellated. Statistical tests were performed to demonstrate that the synchronies of fMRI signals in LTM-informed parcellations are significantly larger than those of random parcellations. Overall, the filtered LTM approach can serve as a tool to investigate the functional organization of the brain at the scale of individual voxels as measured in fMRI.</p>

scholarly journals Functional reorganization of brain networks across the human menstrual cycle

2019 ◽  
Author(s):  
Laura Pritschet ◽  
Tyler Santander ◽  
Caitlin M. Taylor ◽  
Evan Layher ◽  
Shuying Yu ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Human Brain ◽  
Estrogen Receptors ◽  
Sex Hormones ◽  
Functional Organization ◽  
Brain Networks ◽  
List Type ◽  
Functional Architecture ◽  
Human Menstrual Cycle ◽  
The Brain

AbstractThe brain is an endocrine organ, sensitive to the rhythmic changes in sex hormone production that occurs in most mammalian species. In rodents and nonhuman primates, estrogen and progesterone’s impact on the brain is evident across a range of spatiotemporal scales. Yet, the influence of sex hormones on the functional architecture of the human brain is largely unknown. In this dense-sampling, deep phenotyping study, we examine the extent to which endogenous fluctuations in sex hormones alter intrinsic brain networks at rest in a woman who underwent brain imaging and venipuncture for 30 consecutive days. Standardized regression analyses illustrate estrogen and progesterone’s widespread associations with functional connectivity. Time-lagged analyses examined the temporal directionality of these relationships and suggest that cortical network dynamics (particularly in the Default Mode and Dorsal Attention Networks, whose hubs are densely populated with estrogen receptors) are preceded—and perhaps driven—by hormonal fluctuations. A similar pattern of associations was observed in a follow-up study one year later. Together, these results reveal the rhythmic nature in which brain networks reorganize across the human menstrual cycle. Neuroimaging studies that densely sample the individual connectome have begun to transform our understanding of the brain’s functional organization. As these results indicate, taking endocrine factors into account is critical for fully understanding the intrinsic dynamics of the human brain.HighlightsIntrinsic fluctuations in sex hormones shape the brain’s functional architecture.Estradiol facilitates tighter coherence within whole-brain functional networks.Progesterone has the opposite, reductive effect.Ovulation (via estradiol) modulates variation in topological network states.Effects are pronounced in network hubs densely populated with estrogen receptors.

scholarly journals Functional parcellation of human brain using localized topo-connectivity mapping

2021 ◽  
Author(s):  
Yu Zhao ◽  
Yurui Gao ◽  
Muwei Li ◽  
Adam W. Anderson ◽  
Zhaohua Ding ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Organization ◽  
Statistical Tests ◽  
Simulated Data ◽  
Fmri Data ◽  
Anatomical Structures ◽  
Connectivity Mapping ◽  
Subcortical Region ◽  
Human Connectome Project ◽  
The Brain

<p>The analysis of connectivity between parcellated regions of cortex provides insights into the functional architecture of the brain at a systems level. However, there has been less progress in the derivation of functional structures from voxel-wise analyses at finer scales. We propose a novel method, called localized topo-connectivity mapping with singular-value-decomposition-informed filtering (or filtered LTM), to identify and characterize voxel-wise functional structures in the human brain using resting-state fMRI data. Here we describe its mathematical background and provide a proof-of-concept using simulated data that allow an intuitive interpretation of the results of filtered LTM. The algorithm has also been applied to 7T fMRI data as part of the Human Connectome Project to generate group-average LTM images. Functional structures revealed by this approach agree moderately well with anatomical structures identified by T<sub>1</sub>-weighted images and fractional anisotropy maps derived from diffusion MRI. Moreover, the LTM images also reveal subtle functional variations that are not apparent in the anatomical structures. To assess the performance of LTM images, the subcortical region and occipital white matter were separately parcellated. Statistical tests were performed to demonstrate that the synchronies of fMRI signals in LTM-informed parcellations are significantly larger than those of random parcellations. Overall, the filtered LTM approach can serve as a tool to investigate the functional organization of the brain at the scale of individual voxels as measured in fMRI.</p>

scholarly journals Controlling Wheelchair Using Brain as Biosensor

2021 ◽  
Vol 9 (VIII) ◽  
pp. 471-479
Author(s):  
Chandana V
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Electrical Signal ◽  
Emotional States ◽  
Brain Wave ◽  
Computer Interfaces ◽  
The Disabled ◽  
Wheel Chair ◽  
And Control ◽  
The Brain

This project discusses about wheel chair controlled by brain based on Brain–computer interfaces (BCI). BCI’s are systems that can bypass conventional channels of communication (i.e., muscles and thoughts) to provide direct communication and control between the human brain and physical devices by translating different patterns of brain activity into commands in real time. The intention of the project is to develop a robot that can assist the disabled people in their daily life to do some work independent of others. Here, we analyse the brain wave signals. Human brain consists of millions of interconnected neurons, the pattern of interaction between these neurons are represented as thoughts and emotional states. According to the human thoughts, this pattern will be changing which in turn produce different electrical waves. A muscle contraction will also generate a unique electrical signal. All these electrical waves are sensed by the brain wave sensor and different patterns are used for controlling a wheel chair.

scholarly journals Limits to visual representational correspondence between convolutional neural networks and the human brain

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yaoda Xu ◽  
Maryam Vaziri-Pashkam
Keyword(s):  
Neural Networks ◽  
Human Brain ◽  
Convolutional Neural Networks ◽  
Real World ◽  
Visual Information ◽  
Visual Representations ◽  
Human Vision ◽  
Brain Responses ◽  
General Correspondence ◽  
The Brain

AbstractConvolutional neural networks (CNNs) are increasingly used to model human vision due to their high object categorization capabilities and general correspondence with human brain responses. Here we evaluate the performance of 14 different CNNs compared with human fMRI responses to natural and artificial images using representational similarity analysis. Despite the presence of some CNN-brain correspondence and CNNs’ impressive ability to fully capture lower level visual representation of real-world objects, we show that CNNs do not fully capture higher level visual representations of real-world objects, nor those of artificial objects, either at lower or higher levels of visual representations. The latter is particularly critical, as the processing of both real-world and artificial visual stimuli engages the same neural circuits. We report similar results regardless of differences in CNN architecture, training, or the presence of recurrent processing. This indicates some fundamental differences exist in how the brain and CNNs represent visual information.

scholarly journals Inductive biases, pretraining and fine-tuning jointly account for brain responses to speech

2021 ◽  
Author(s):  
Juliette MILLET ◽  
Jean-Remi KING
Keyword(s):  
Human Brain ◽  
Deep Neural Networks ◽  
Fine Tuning ◽  
Functional Magnetic Resonance ◽  
Scene Classification ◽  
Linear Projection ◽  
Brain Responses ◽  
Optimal Linear ◽  
The Brain ◽  
Fine Tune

Our ability to comprehend speech remains, to date, unrivaled by deep learning models. This feat could result from the brain’s ability to fine-tune generic sound representations for speech-specific processes. To test this hypothesis, we compare i) five types of deep neural networks to ii) human brain responses elicited by spoken sentences and recorded in 102 Dutch subjects using functional Magnetic Resonance Imaging (fMRI). Each network was either trained on an acoustics scene classification, a speech-to-text task (based on Bengali, English, or Dutch), or not trained. The similarity between each model and the brain is assessed by correlating their respective activations after an optimal linear projection. The differences in brain-similarity across networks revealed three main results. First, speech representations in the brain can be accounted for by random deep networks. Second, learning to classify acoustic scenes leads deep nets to increase their brain similarity. Third, learning to process phonetically-related speech inputs (i.e., Dutch vs English) leads deep nets to reach higher levels of brain-similarity than learning to process phonetically-distant speech inputs (i.e. Dutch vs Bengali). Together, these results suggest that the human brain fine-tunes its heavily-trained auditory hierarchy to learn to process speech.

Implications of the sociocultural brain

2017 ◽  
Author(s):  
Shihui Han
Keyword(s):  
Human Brain ◽  
Functional Organization ◽  
Human Cognition ◽  
Cultural Neuroscience ◽  
Cross Cultural Communication ◽  
Cognition And Emotion ◽  
Specific Effects ◽  
Neural Underpinnings ◽  
Adult Immigrants ◽  
Different Cultures

Chapter 9 discusses the implications of cultural-neuroscience findings for understanding of the biosocial nature of the human brain and the sociobiological nature of human culture. It examines how cultural-neuroscience findings help us to rethink educational approaches in terms of culturally specific effects on human brain development, as well as how changes of brain functional organization in adult immigrants can improve their adaption to new cultural environments. It also discusses how understanding cultural differences in the neural underpinnings of human cognition and emotion can improve cross-cultural communication. Finally, it discusses the implications of cultural-neuroscience findings for the clinical treatment of neuropsychological mental disorders in different cultures.

The human brain project: neuroscience perspectives and German contributions

e-Neuroforum ◽  
2014 ◽  
Vol 20 (2) ◽  
Author(s):  
K. Amunts
Keyword(s):  
Human Brain ◽  
High Performance ◽  
Functional Organization ◽  
Comprehensive Understanding ◽  
Human Brain Project ◽  
The Relationship ◽  
Organizational Principles ◽  
The Brain ◽  
Performance Computing ◽  
The Eu

AbstractStudying the human brain remains one of the greatest scientific challenges. A comprehensive understanding of the structural and functional organization of the brain is not only of great importance for basic science, but also for the development of new approaches that improve diagnosis and the treatment of neurological and psychiatric diseases. Thus, the Human Brain Project (HBP) was start­ed in October 2013. The immense complexity of the brain, with its approximately 86 bi­llion nerve cells, makes it essential to include modeling and simulation approaches, combined with methods of high performance computing (HPC), in order to analyze the organizational principles of the brain. Con­versely, the understanding of neural mecha­nisms might inspire new advancements for HPC. The project will be funded with approximately € 1.19 billion, with 75% of funding from the EU, and the rest provided by partner countries and their institutions. The HBP currently involves about 80 institutions from 22 countries and has a duration of 10 years, thus, making it one of the world’s largest re­search initiatives. This article is designed to give a brief overview of the HBP organization, and to illustrate the German neuroscientific contributions to the HBP and indicate the relationship to other projects within the HBP.

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