Cognitive State
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2021 ◽  
Vol 17 (9) ◽  
pp. e1009358
Nathaniel J. Zuk ◽  
Jeremy W. Murphy ◽  
Richard B. Reilly ◽  
Edmund C. Lalor

The human brain tracks amplitude fluctuations of both speech and music, which reflects acoustic processing in addition to the encoding of higher-order features and one’s cognitive state. Comparing neural tracking of speech and music envelopes can elucidate stimulus-general mechanisms, but direct comparisons are confounded by differences in their envelope spectra. Here, we use a novel method of frequency-constrained reconstruction of stimulus envelopes using EEG recorded during passive listening. We expected to see music reconstruction match speech in a narrow range of frequencies, but instead we found that speech was reconstructed better than music for all frequencies we examined. Additionally, models trained on all stimulus types performed as well or better than the stimulus-specific models at higher modulation frequencies, suggesting a common neural mechanism for tracking speech and music. However, speech envelope tracking at low frequencies, below 1 Hz, was associated with increased weighting over parietal channels, which was not present for the other stimuli. Our results highlight the importance of low-frequency speech tracking and suggest an origin from speech-specific processing in the brain.

2021 ◽  
Hongmi Lee ◽  
Janice Chen

AbstractCurrent theory and empirical studies suggest that humans segment continuous experiences into events based on the mismatch between predicted and actual sensory inputs; detection of these “event boundaries” evokes transient neural responses. However, boundaries can also occur at transitions between internal mental states, without relevant external input changes. To what extent do such “internal boundaries” share neural response properties with externally-driven boundaries? We conducted an fMRI experiment where subjects watched a series of short movies and then verbally recalled the movies, unprompted, in the order of their choosing. During recall, transitions between movies thus constituted major boundaries between internal mental contexts, generated purely by subjects’ unguided thoughts. Following the offset of each recalled movie, we observed stereotyped spatial activation patterns in the default mode network, especially the posterior medial cortex, consistent across different movie contents and even across the different tasks of movie watching and recall. Surprisingly, the between-movie boundary patterns were negatively correlated with patterns at boundaries between events within a movie. Thus, major transitions between mental contexts elicit neural phenomena shared across internal and external modes and distinct from within-context event boundary detection, potentially reflecting a cognitive state related to the flushing and reconfiguration of situation models.

Jorge Serrano-Malebrán ◽  
Jorge Arenas-Gaitán

AbstractThe aim of this research is to find a segment of consumers of fashion products based on their personal visions of personalization of shoppable ads on mobile social media. To meet this objective, three operational objectives are defined. First, a theoretical model is evaluated based on the stimulus-organism-response framework (S–O–R). This examines, with a PLS-SEM approach, how the stimulation of personalization will affect consumers' internal cognitive state (perceived usefulness) and consequently generates a behavioral response (intention to buy). Second, we look for fashion consumer segments based on their perception of personalization through prediction-oriented segmentation (PLS-POS). Third, the segments are explained based on three constructs that were considered important in fashion consumption through mobile social networks: purchase intention, concern for privacy, and perception of trend. The inclusion of personalization and the perception of usefulness of advertisements can greatly help the intention to purchase clothing to be understood. The application of a posterior segmentation helps to better understand the different types of users exposed to shoppable ads on mobile social networks and their relationship with the purchase intention, concern for privacy and trend. While the measures and scales were tested in a context of mobile clothing trade, the methodology can be applied to other types of products or services.

2021 ◽  
Wendy Ross

Traditionally insight occurs after an impasse, that is when a problem solver is aware that she does not have the right answer but a new one does not come to mind. This impasse is relieved by a sudden restructuring of the problem to a more helpful one which then leads to a feeling of insight. More recently the role of impasse has been downplayed because qualitative empirical data suggest that it is not an essential part of experiencing insight however this fails to explain what a cognitive state of repeated failure looks like. The current research aimed to disentangle the different dimensions of impasse along motivation lines and shows across two studies that while the feeling of being stuck is a negative predictor of levels of insight, the feeling of being challenged significantly positively predicts insight. These results form the preliminary basis of understanding the phenomenology of impasse and how it interacts with motivational states.

2021 ◽  
Vol 11 (9) ◽  
pp. 1166
Magdalena Bury-Kamińska ◽  
Aneta Szudy-Szczyrek ◽  
Aleksandra Nowaczyńska ◽  
Olga Jankowska-Łęcka ◽  
Marek Hus ◽  

The paper presents a study on the changes in cognitive functioning in patients undergoing chemotherapy with diagnosed multiple myeloma (MM). The aim of the study was to answer the following two main research questions: Does the treatment stage differentiate the functioning of cognitive processes in patients with diagnosed MM and to what extent? Is it possible to treat biological factors (TNF-α, IL-6, IL-10, and BDNF) as predictors of patients’ cognitive functioning? The patients were examined twice, before the treatment and after 4–6 cycles of chemotherapy. Selected neuropsychological research methods as well as experimental and clinical trials were employed to diagnose the patients’ general cognitive state, attention, memory, and executive functions. The level of biological factors was assessed with the ELISA test. The results show that the patients’ cognitive functioning was worse before the treatment than during the cytostatic therapy. It was also possible to predict the cognitive state of patients suffering from multiple myeloma based on a selected biological parameter (neurotrophin BDNF).

Amy S. McDonnell ◽  
Trent G. Simmons ◽  
Gus G. Erickson ◽  
Monika Lohani ◽  
Joel M. Cooper ◽  

Objective This research explores the effect of partial vehicle automation on neural indices of mental workload and visual engagement during on-road driving. Background There is concern that the introduction of automated technology in vehicles may lead to low driver stimulation and subsequent disengagement from the driving environment. Simulator-based studies have examined the effect of automation on a driver’s cognitive state, but it is unknown how the conclusions translate to on-road driving. Electroencephalographic (EEG) measures of frontal theta and parietal alpha can provide insight into a driver’s mental workload and visual engagement while driving under various conditions. Method EEG was recorded from 71 participants while driving on the roadway. We examined two age cohorts, on two different highway configurations, in four different vehicles, with partial vehicle automation both engaged and disengaged. Results Analysis of frontal theta and parietal alpha power revealed that there was no change in mental workload or visual engagement when driving manually compared with driving under partial vehicle automation. Conclusion Drivers new to the technology remained engaged with the driving environment when operating under partial vehicle automation. These findings suggest that the concern surrounding driver disengagement under vehicle automation may need to be tempered, at least for drivers new to the experience. Application These findings expand our understanding of the effects of partial vehicle automation on drivers’ cognitive states.

2021 ◽  
Vol 22 (1) ◽  
Dalia Farouk Hussen ◽  
Ayat Allah Farouk Hussein ◽  
Mahmoud Abdel Moety Monzer ◽  
Saida Ali Hammad

Abstract Background Alzheimer’s disease (AD) is the most widely recognized type of dementia. It is associated with cell cycle abnormalities including genomic instability and increased micronuclei (MNi) which usually evolve many years before the appearance of the clinical manifestations. Digital electroencephalogram (EEG) has a role in perceiving brain changes in dementia and in early detection of cognitive decline. This study aimed to assess the competency of using neurophysiological markers including absolute power of alpha waves and a cytogenetic marker which comprises scoring of MNi as a step toward early and preclinical diagnosis of AD. The study was conducted on 27 subjects; they were 15 patients diagnosed as sporadic AD and a group of 12 age and sex-matched controls. All subjects were subjected to Mini-Mental State Examination (MMSE), conventional EEG, digital EEG, and cytokinesis-block micronucleus assay (CBMN) in peripheral blood lymphocytes. Results Conventional EEG showed a normal background activity with no abnormal epileptogenic discharges in both groups. Digital EEG showed significant reduction of the absolute power of alpha waves for AD patients as compared to the control group (P < 0.0001). Score of MNi showed statistical significant difference between the two groups (P < 0.0001). By linking scores of both cognitive state using MMSE and MNi among the group of patients, a significant negative correlation was detected (r = −0.6066). The correlations between cognitive state and the absolute power of alpha wave among the patients revealed a positive correlation (r = 0.2235). Conclusions The combination of both cytogenetic and neurophysiological markers can be beneficial for early detection of cognitive decline and may lead to preclinical identification of individuals at increased risk for AD, where at this stage treatment is constructive. The negative correlation between the scores of MNi and MMSE is suggestive for the impact of genomic instability on the cognitive state.

2021 ◽  
Vol 25 (2) ◽  
pp. 157-178
Theparambil Asharaf Suhail ◽  
Kottanayil Pally Indiradevi ◽  
Ekkarakkudy Makkar Suhara ◽  
Poovathinal Azhakan Suresh ◽  

Detecting cognitive states during learning tasks is an essential component in neurocognitive experiments for assessing and enhancing the cognitive performance of individuals. Studies have demonstrated that mental state recognition systems utilizing brain signals are proficient in the automated monitoring of learners’ cognitive states. The current study focuses on developing an efficient individualized and cross-subject cognitive state assessment model based on Electroencephalography (EEG) patterns during learning tasks. For this study, EEGs of 20 healthy subjects were recorded during a resting state followed by a learning task and examined EEG activations patterns in a wide perspective of feature types and rhythms. The extracted features included time-domain features such as Hjorth parameters, Wavelet-based features, and Spectral entropy. Three classifiers, Support Vector Machine, k-Nearest Neighbor, and Linear Discriminant Analysis were employed to recognize the mental state. A new EEG-based attention index using band ratios is proposed and is demonstrated as an effective predictor for recognizing attentive reading. The proposed model can yield recognition performance with an accuracy of 92.9% in the subject-dependent approach and 77.2% in the subject-independent approach with the Support Vector Machine Classifier. The findings are useful for the design and development of neurofeedback systems that monitor and enhance the cognitive performance in healthy individuals, as well as in individuals with cognitive deficits.

Sumit Hazra ◽  
Acharya Aditya Pratap ◽  
Oshin Agrawal ◽  
Anup Nandy

2021 ◽  
pp. 002216782110180
Michaela Guthridge ◽  
Melita J. Giummarra

The conceptual diversity in the definition of empathy has resulted in descriptions of a highly heterogeneous collection of related phenomena, causing confusion as to what empathy actually is. Some of this heterogeneity arises due to disparate viewpoints across different disciplines. Capturing this transdisciplinary construct and arriving at a clear and unambiguous overarching definition of empathy will help provide a clearer outline of the fundamental dimensions of empathy, and will facilitate greater consistency in research and discussion of empathy across and between a range of disciplines. An inductive conceptual content analysis of the existing definitions of empathy was undertaken to distil the common higher order and lower order components of empathy definitions that have been used in the literature since 1980. A total of 146 definitions of empathy were sourced from a sample of 506 publications. Nine overarching dimensions were identified within the 146 definitions, including empathy as a catalyst, function, process, outcome, affective state, cognitive state, involving self and other, leading to a behaviour, and occurring in a specific context. The resultant meta-definition of empathy is “the ability to experience affective and cognitive states of another person, while maintaining a distinct self, in order to understand the other.” The results reveal empathy as a complex series of processes that we argue should be considered an “empathic system” given its multidimensional nature.

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