scholarly journals Infants differentially extract rules from language

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Iris Berent ◽  
Irene de la Cruz-Pavía ◽  
Diane Brentari ◽  
Judit Gervain
Keyword(s):  
Sign Language ◽  
Sensory Modality ◽  
Rule Learning ◽  
Neural Response ◽  
Previous Experience ◽  
Brain Response ◽  
Speech Stimuli ◽  
Linguistic Rules ◽  
Rule System ◽  
The Brain

AbstractInfants readily extract linguistic rules from speech. Here, we ask whether this advantage extends to linguistic stimuli that do not rely on the spoken modality. To address this question, we first examine whether infants can differentially learn rules from linguistic signs. We show that, despite having no previous experience with a sign language, six-month-old infants can extract the reduplicative rule (AA) from dynamic linguistic signs, and the neural response to reduplicative linguistic signs differs from reduplicative visual controls, matched for the dynamic spatiotemporal properties of signs. We next demonstrate that the brain response for reduplicative signs is similar to the response to reduplicative speech stimuli. Rule learning, then, apparently depends on the linguistic status of the stimulus, not its sensory modality. These results suggest that infants are language-ready. They possess a powerful rule system that is differentially engaged by all linguistic stimuli, speech or sign.

scholarly journals Neural Underpinnings of Phonotactic Rule Learning

2019 ◽  
Vol 7 ◽  
Author(s):  
Enes Avcu ◽  
Ryan Rhodes ◽  
Arild Hestvik
Keyword(s):  
Rule Learning ◽  
Simple Rule ◽  
Brain Response ◽  
Behavioral Measures ◽  
Sensitivity Measure ◽  
Behavioral Level ◽  
Neural Underpinnings ◽  
The Brain ◽  
Exact Point

This study used behavioral measures and ERP difference waves to measure the underlying brain processes during the categorization of grammatical vs ungrammatical stimuli according to a lab learned phonotactic rule. The results show that participants learned the simple rule at the behavioral level (as measured with d-prime, a sensitivity measure to rule violations). This rule learning is also reflected in the brain response to violations of the rule, which is indexed by the P3 rare-minus-frequent difference waveform. The neural results indicate that this learning took the form of a neural commitment. Participants learned the rule and used it to make active predictions, categorizing words as ungrammatical at the exact point of violation. This ability must be instantiated at the neural level, meaning rapid neural tuning has occurred in this lab setting.

scholarly journals Conditional Entropy: A Potential Digital Marker for Stress

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 286
Author(s):  
Soheil Keshmiri
Keyword(s):  
Resting State ◽  
Nearest Neighbor ◽  
Brain Activity ◽  
Solution Concept ◽  
Conditional Entropy ◽  
K Nearest Neighbor ◽  
Brain Response ◽  
Substantial Progress ◽  
Eeg Recordings ◽  
The Brain

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.

A discussion of apraxia, aphasia, and gestural language

1984 ◽  
Vol 246 (6) ◽  
pp. R884-R887
Author(s):  
N. Helm-Estabrooks
Keyword(s):  
Sign Language ◽  
Cerebral Hemisphere ◽  
Communication Disorder ◽  
Left Cerebral Hemisphere ◽  
Language Behavior ◽  
Normal Language ◽  
Symbolic Gestures ◽  
The Many ◽  
The Relationship ◽  
The Brain

It is understood that damage to the left cerebral hemisphere in adulthood may result in syndromes of language disturbances called the aphasias. The study of these syndromes sheds light on normal language processes, the relationship between language behavior and the brain, and how best to treat aphasic individuals. Aphasia, for some, is a central communication disorder affecting all symbolic behavior in all modalities (i.e., speech, writing, and gesture). Difficulty producing symbolic gestures on command is called apraxia. Others view aphasia as a manifestation of a motor-sequencing disorder affecting all gestural systems including those required for speech movements. These divergent theories of the underlying nature of aphasia can be tested through examination of deaf individuals who use sign language before onset of aphasia. Poizner et al. [Am. J. Physiol. 246 (Regulatory Integrative Comp. Physiol. 15): R868-R883, 1984] studied three such patients with different aphasia syndromes: one patient had a nonsymbolic, motor-sequencing disorder; one had a gestural apraxia; and one had neither. These findings force the conclusion that neither the symbolic nor motor-sequencing theory of aphasia can account for the many varieties of that disorder.

Effects of CSF Properties on Brain Response Under Impact Loading

2009 ◽  
Author(s):  
M. S. Chafi ◽  
V. Dirisala ◽  
G. Karami ◽  
M. Ziejewski
Keyword(s):  
Human Head ◽  
Brain Response ◽  
Pia Mater ◽  
Mechanical Shocks ◽  
The Central Nervous System ◽  
Simultaneous Loading ◽  
The Impact ◽  
Impact Experiments ◽  
The Brain

In the central nervous system, the subarachnoid space is the interval between the arachnoid membrane and the pia mater. It is filled with a clear, watery liquid called cerebrospinal fluid (CSF). The CSF buffers the brain against mechanical shocks and creates buoyancy to protect it from the forces of gravity. The relative motion of the brain due to a simultaneous loading is caused because the skull and brain have different densities and the CSF surrounds the brain. The impact experiments are usually carried out on cadavers with no CSF included because of the autolysis. Even in the cadaveric head impact experiments by Hardy et al. [1], where the specimens are repressurized using artificial CSF, this is not known how far this can replicate the real functionality of CSF. With such motivation, a special interest lies on how to model this feature in a finite element (FE) modeling of the human head because it is questionable if one uses in vivo CSF properties (i.e. bulk modulus of 2.19 GPa) to validate a FE human head against cadaveric experimental data.

scholarly journals Brain signatures of surprise in EEG and MEG data

2020 ◽  
Author(s):  
Zahra Mousavi ◽  
Mohammad Mahdi Kiani ◽  
Hamid Aghajan
Keyword(s):  
Sensory Modality ◽  
Ideal Observer ◽  
Neural Signals ◽  
Sensory Data ◽  
Temporal Features ◽  
Recorded Data ◽  
Recent Trends ◽  
Temporal Sample ◽  
Past Experiences ◽  
The Brain

AbstractThe brain is constantly anticipating the future of sensory inputs based on past experiences. When new sensory data is different from predictions shaped by recent trends, neural signals are generated to report this surprise. Existing models for quantifying surprise are based on an ideal observer assumption operating under one of the three definitions of surprise set forth as the Shannon, Bayesian, and Confidence-corrected surprise. In this paper, we analyze both visual and auditory EEG and auditory MEG signals recorded during oddball tasks to examine which temporal components in these signals are sufficient to decode the brain’s surprise based on each of these three definitions. We found that for both recording systems the Shannon surprise is always significantly better decoded than the Bayesian surprise regardless of the sensory modality and the selected temporal features used for decoding.Author summaryA regression model is proposed for decoding the level of the brain’s surprise in response to sensory sequences using selected temporal components of recorded EEG and MEG data. Three surprise quantification definitions (Shannon, Bayesian, and Confidence-corrected surprise) are compared in offering decoding power. Four different regimes for selecting temporal samples of EEG and MEG data are used to evaluate which part of the recorded data may contain signatures that represent the brain’s surprise in terms of offering a high decoding power. We found that both the middle and late components of the EEG response offer strong decoding power for surprise while the early components are significantly weaker in decoding surprise. In the MEG response, we found that the middle components have the highest decoding power while the late components offer moderate decoding powers. When using a single temporal sample for decoding surprise, samples of the middle segment possess the highest decoding power. Shannon surprise is always better decoded than the other definitions of surprise for all the four temporal feature selection regimes. Similar superiority for Shannon surprise is observed for the EEG and MEG data across the entire range of temporal sample regimes used in our analysis.

scholarly journals Gaming enhances learning-induced plastic changes in the brain

2020 ◽  
Author(s):  
Katja Junttila ◽  
Anna-Riikka Smolander ◽  
Reima Karhila ◽  
Anastasia Giannakopoulou ◽  
Maria Uther ◽  
...  
Keyword(s):  
Language Learning ◽  
Event Related Potentials ◽  
Speech Sounds ◽  
Digital Game ◽  
Game Based Learning ◽  
Brain Response ◽  
Related Potentials ◽  
Plastic Changes ◽  
Game Condition ◽  
The Brain

Learning is increasingly assisted by technology. Digital games may be useful for learning, especially in children. However, more research is needed to understand the factors that induce gaming benefits to cognition. In this study, we investigated the effectiveness of digital game-based learning approach in children by comparing the learning of foreign speech sounds and words in a digital game or a non-game digital application with equal amount of exposure and practice. To evaluate gaming-induced plastic changes in the brain function, we used the mismatch negativity (MMN) brain response that reflects the activation of long-term memory representations for speech sounds and words. We recorded auditory event-related potentials (ERPs) from 37 school-aged Finnish-speaking children before and after playing the “Say it again, kid!” (SIAK) language-learning game where they explored game boards, produced English words aloud, and got stars as feedback from an automatic speech recognizer to proceed in the game. The learning of foreign speech sounds and words was compared in two conditions embedded in the game: a game condition and a non-game condition with the same speech production task but lacking visual game elements and feedback. The MMN amplitude increased between the pre-measurement and the post-measurement for the word trained with the game but not for the word trained with the non-game condition, suggesting that the gaming intervention enhanced learning more than the non-game intervention. The results indicate that digital game-based learning can be beneficial for children’s language learning and that gaming elements per se, not just practise time, support learning.

scholarly journals The Tell-Tale Hand: Gothic Narratives and the Brain

Text Matters ◽  
2016 ◽  
pp. 96-113
Author(s):  
Neil Forsyth
Keyword(s):  
Sign Language ◽  
Medical Literature ◽  
Sherwood Anderson ◽  
Emery Paper ◽  
Hands On ◽  
Montessori Method ◽  
The Brain

The opening story in Winesburg, Ohio (1919) by Sherwood Anderson is called simply “Hands.” It is about a teacher’s remarkable hands that sometimes seem to move independently of his will. This essay explores some of the relevant contexts and potential links, beginning with other representations of teachers’ hands, such as Caravaggio’s St. Matthew and the Angel, early efforts to establish a sign-language for the deaf, and including the Montessori method of teaching children to read and write by tracing the shape of letters with their hands on rough emery paper. The essay then explores filmic hands that betray or work independently of conscious intentions, from Dr Strangelove, Mad Love, to The Beast With Five Fingers. Discussion of the medical literature about the “double” of our hands in the brain, including “phantom hands,” leads on to a series of images that register Rodin’s lifelong fascination with sculpting separate hands.

scholarly journals Brain Responses to Acupuncture Are Probably Dependent on the Brain Functional Status

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Chuanfu Li ◽  
Jun Yang ◽  
Jinbo Sun ◽  
Chunsheng Xu ◽  
Yuanqiang Zhu ◽  
...  
Keyword(s):  
Functional Status ◽  
Bell’S Palsy ◽  
Healthy Adults ◽  
Bell's Palsy ◽  
Brain Response ◽  
Brain Responses ◽  
Underlying Mechanisms ◽  
Pathological Stages ◽  
The Brain ◽  
Normal Controls

In recent years, neuroimaging studies of acupuncture have explored extensive aspects of brain responses to acupuncture in finding its underlying mechanisms. Most of these studies have been performed on healthy adults. Only a few studies have been performed on patients with diseases. Brain responses to acupuncture in patients with the same disease at different pathological stages have not been explored, although it may be more important and helpful in uncovering its underlying mechanisms. In the present study, we used fMRI to compare brain responses to acupuncture in patients with Bell’s palsy at different pathological stages with normal controls and found that the brain response to acupuncture varied at different pathological stages of Bell’s palsy. The brain response to acupuncture decreased in the early stages, increased in the later stages, and nearly returned to normal in the recovered group. All of the changes in the brain response to acupuncture could be explained as resulting from the changes in the brain functional status. Therefore, we proposed that the brain response to acupuncture is dependent on the brain functional status, while further investigation is needed to provide more evidence in support of this proposition.

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