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Frontiers in Integrative Neuroscience 2024We investigated the factors underlying naturalistic action recognition and understanding, as well as the errors occurring during recognition failures.
INTRODUCTION
We investigated the factors underlying naturalistic action recognition and understanding, as well as the errors occurring during recognition failures.
METHODS
Participants saw full-light stimuli of ten different whole-body actions presented in three different conditions: as normal videos, as videos with the temporal order of the frames scrambled, and as single static representative frames. After each stimulus presentation participants completed one of two tasks-a forced choice task where they were given the ten potential action labels as options, or a free description task, where they could describe the action performed in each stimulus in their own words.
RESULTS
While generally, a combination of form, motion, and temporal information led to the highest action understanding, for some actions form information was sufficient and adding motion and temporal information did not increase recognition accuracy. We also analyzed errors in action recognition and found primarily two different types.
DISCUSSION
One type of error was on the semantic level, while the other consisted of reverting to the kinematic level of body part processing without any attribution of semantics. We elaborate on these results in the context of naturalistic action perception.
PubMed: 38533314
DOI: 10.3389/fnint.2024.1302960 -
PloS One 2024Animal-assisted interventions are being increasingly used in studies that support various health effects. This study compared the psychophysiological and emotional...
Animal-assisted interventions are being increasingly used in studies that support various health effects. This study compared the psychophysiological and emotional responses during diverse activities with a dog to understand the impact of activity type. This study included 30 healthy adults (average age: 27.9 ± 8.4 years). Participants performed eight different activities with a dog for 3 minutes each. These activities included meeting, playing, feeding, massaging, grooming, photographing, hugging, and walking. Brain waves in the prefrontal, frontal, parietal, and occipital lobes were measured during the activities. Subjective evaluation of their emotions was recorded after each activity via the Profile of Mood States, Semantic Differential Method, and Stress Numeric Rating Scale. The alpha (relative, relative slow, relative fast) power spectra indicated that the brain's relaxation and resting state significantly increased when playing with and walking a dog. The beta (relative, relative low, and relative mid) power spectra significantly increased during dog massage, grooming, and playing activities, indicating improved concentration without stress. Notably, playing with a dog positively affected both relaxation and concentration. The Profile of Mood States outcome showed that activities such as feeding, massaging, and hugging the dog decreased the total mood disorder score, which indicated a positive effect on participants' moods. The Semantic Differential Method revealed that participants felt comfortable and natural while walking with a dog and relaxed when massaging it. Participants showed significantly lower stress moods in all the activities. This study demonstrated that specific dog activities could activate stronger relaxation, emotional stability, attention, concentration, and creativity by facilitating increased brain activity. In addition, interactions with dogs could decrease stress and induce positive emotional responses. These results provide data that forms the basis for the composition of the AAI program and may be applicable as a reference to determine the most effective activities for specific applications.
Topics: Adult; Humans; Dogs; Animals; Young Adult; Emotions; Brain; Affect; Relaxation; Brain Waves
PubMed: 38478472
DOI: 10.1371/journal.pone.0298384 -
Scientific Reports Feb 2024Accurate labeling of lung nodules in computed tomography (CT) images is crucial in early lung cancer diagnosis and before nodule resection surgery. However, the...
Accurate labeling of lung nodules in computed tomography (CT) images is crucial in early lung cancer diagnosis and before nodule resection surgery. However, the irregular shape of lung nodules in CT images and the complex lung environment make it much more challenging to segment lung nodules accurately. On this basis, we propose an improved V-Net segmentation method based on pixel threshold separation and attention mechanism for lung nodules. This method first offers a data augment strategy to solve the problem of insufficient samples in 3D medical datasets. In addition, we integrate the feature extraction module based on pixel threshold separation into the model to enhance the feature extraction ability under different thresholds on the one hand. On the other hand, the model introduces channel and spatial attention modules to make the model pay more attention to important semantic information and improve its generalization ability and accuracy. Experiments show that the Dice similarity coefficients of the improved model on the public datasets LUNA16 and LNDb are 94.9% and 81.1% respectively, and the sensitivities reach 92.7% and 76.9% respectively. which is superior to most existing UNet architecture models and comparable to the manual level segmentation results by medical technologists.
Topics: Humans; Differential Threshold; Generalization, Psychological; Lung Neoplasms; Medical Laboratory Personnel; Product Labeling; Image Processing, Computer-Assisted
PubMed: 38413699
DOI: 10.1038/s41598-024-55178-3 -
Frontiers in Neuroscience 2024Frontotemporal dementia (FTD) represents a collection of neurobehavioral and neurocognitive syndromes that are associated with a significant degree of clinical,...
BACKGROUND
Frontotemporal dementia (FTD) represents a collection of neurobehavioral and neurocognitive syndromes that are associated with a significant degree of clinical, pathological, and genetic heterogeneity. Such heterogeneity hinders the identification of effective biomarkers, preventing effective targeted recruitment of participants in clinical trials for developing potential interventions and treatments. In the present study, we aim to automatically differentiate patients with three clinical phenotypes of FTD, behavioral-variant FTD (bvFTD), semantic variant PPA (svPPA), and nonfluent variant PPA (nfvPPA), based on their structural MRI by training a deep neural network (DNN).
METHODS
Data from 277 FTD patients (173 bvFTD, 63 nfvPPA, and 41 svPPA) recruited from two multi-site neuroimaging datasets: the Frontotemporal Lobar Degeneration Neuroimaging Initiative and the ARTFL-LEFFTDS Longitudinal Frontotemporal Lobar Degeneration databases. Raw T1-weighted MRI data were preprocessed and parcellated into patch-based ROIs, with cortical thickness and volume features extracted and harmonized to control the confounding effects of sex, age, total intracranial volume, cohort, and scanner difference. A multi-type parallel feature embedding framework was trained to classify three FTD subtypes with a weighted cross-entropy loss function used to account for unbalanced sample sizes. Feature visualization was achieved through post-hoc analysis using an integrated gradient approach.
RESULTS
The proposed differential diagnosis framework achieved a mean balanced accuracy of 0.80 for bvFTD, 0.82 for nfvPPA, 0.89 for svPPA, and an overall balanced accuracy of 0.84. Feature importance maps showed more localized differential patterns among different FTD subtypes compared to groupwise statistical mapping.
CONCLUSION
In this study, we demonstrated the efficiency and effectiveness of using explainable deep-learning-based parallel feature embedding and visualization framework on MRI-derived multi-type structural patterns to differentiate three clinically defined subphenotypes of FTD: bvFTD, nfvPPA, and svPPA, which could help with the identification of at-risk populations for early and precise diagnosis for intervention planning.
PubMed: 38384484
DOI: 10.3389/fnins.2024.1331677 -
Revista Da Escola de Enfermagem Da U S P 2024To characterize the perceptions and feelings of parents diagnosed with cancer in relation to communication with their children between 3 and 12 years old.
OBJECTIVE
To characterize the perceptions and feelings of parents diagnosed with cancer in relation to communication with their children between 3 and 12 years old.
METHOD
A cross-sectional, multicenter, with data triangulation, through structured and semi-structured interviews, with a question with a Semantic Differential Scale, carried out with the father or mother with cancer undergoing outpatient treatment in two hospital institutions in the city of São Paulo, São Paulo, Brazil. Data were analyzed using descriptive statistics, content analysis, using the ATLAS.ti 8.0R software and the Social Representation Theory.
RESULTS
Forty-three respondents participated, 37 (86.0%) were female, 23 (53.5%) aged between 31 and 50 years old, 29 (67.5%) with only children between 7 and 12 years old. The experience was considered painful (73.1%), stressful (53.6%), clear (53.7%) and safe (51.2%). The feelings experienced generated two categories: Trial by fire; and Grateful rewards. Children's reactions from parents' perspective generated the categories: Sadness and suffering; Trust and support; Change of behavior; and Denial or insensitivity.
CONCLUSION
Communication was assessed as negative and conflicting, positive and welcoming, and causing changes in children's behaviors.
Topics: Child; Humans; Female; Adult; Middle Aged; Child, Preschool; Male; Cross-Sectional Studies; Brazil; Parents; Neoplasms; Communication
PubMed: 38373186
DOI: 10.1590/1980-220X-REEUSP-2023-0079en -
Human Brain Mapping Feb 2024Wine tasting is a very complex process that integrates a combination of sensation, language, and memory. Taste and smell provide perceptual information that, together...
Wine tasting is a very complex process that integrates a combination of sensation, language, and memory. Taste and smell provide perceptual information that, together with the semantic narrative that converts flavor into words, seem to be processed differently between sommeliers and naïve wine consumers. We investigate whether sommeliers' wine experience shapes only chemosensory processing, as has been previously demonstrated, or if it also modulates the way in which the taste and olfactory circuits interact with the semantic network. Combining diffusion-weighted images and fMRI (activation and connectivity) we investigated whether brain response to tasting wine differs between sommeliers and nonexperts (1) in the sensory neural circuits representing flavor and/or (2) in the neural circuits for language and memory. We demonstrate that training in wine tasting shapes the microstructure of the left and right superior longitudinal fasciculus. Using mediation analysis, we showed that the experience modulates the relationship between fractional anisotropy and behavior: the higher the fractional anisotropy the higher the capacity to recognize wine complexity. In addition, we found functional differences between sommeliers and naïve consumers affecting the flavor sensory circuit, but also regions involved in semantic operations. The former reflects a capacity for differential sensory processing, while the latter reflects sommeliers' ability to attend to relevant sensory inputs and translate them into complex verbal descriptions. The enhanced synchronization between these apparently independent circuits suggests that sommeliers integrated these descriptions with previous semantic knowledge to optimize their capacity to distinguish between subtle differences in the qualitative character of the wine.
Topics: Humans; Semantics; Semantic Web; Smell; Taste Perception; Sensation; Taste
PubMed: 38339911
DOI: 10.1002/hbm.26564 -
Neuropsychologia Apr 2024Neural circuits related to language exhibit a remarkable ability to reorganize and adapt in response to visual deprivation. Particularly, early and late blindness induce...
Neural circuits related to language exhibit a remarkable ability to reorganize and adapt in response to visual deprivation. Particularly, early and late blindness induce distinct neuroplastic changes in the visual cortex, repurposing it for language and semantic processing. Interestingly, these functional changes provoke a unique cognitive advantage - enhanced verbal working memory, particularly in early blindness. Yet, the underlying neuromechanisms and the impact on language and memory-related circuits remain not fully understood. Here, we applied a brain-constrained neural network mimicking the structural and functional features of the frontotemporal-occipital cortices, to model conceptual acquisition in early and late blindness. The results revealed differential expansion of conceptual-related neural circuits into deprived visual areas depending on the timing of visual loss, which is most prominent in early blindness. This neural recruitment is fundamentally governed by the biological principles of neural circuit expansion and the absence of uncorrelated sensory input. Critically, the degree of these changes is constrained by the availability of neural matter previously allocated to visual experiences, as in the case of late blindness. Moreover, we shed light on the implication of visual deprivation on the neural underpinnings of verbal working memory, revealing longer reverberatory neural activity in 'blind models' as compared to the sighted ones. These findings provide a better understanding of the interplay between visual deprivations, neuroplasticity, language processing and verbal working memory.
Topics: Humans; Memory, Short-Term; Language; Blindness; Brain; Occipital Lobe
PubMed: 38331022
DOI: 10.1016/j.neuropsychologia.2024.108816 -
Journal of Health, Population, and... Feb 2024The health of city residents is at risk due to the high rate of urbanization and the extensive use of electronics. In the context of urbanization, individuals have...
The health of city residents is at risk due to the high rate of urbanization and the extensive use of electronics. In the context of urbanization, individuals have become increasingly disconnected from nature, resulting in elevated stress levels among adults. The goal of this study was to investigate the physical and psychological benefits of spending time in nature. The benefits of touching real grass and artificial turf (the control activity) outdoors with the palm of the hand for five minutes were measured. Blood pressure and electroencephalography (EEG) as well as State-trait Anxiety Inventory (STAI) scores, and the semantic differential scale (SDM) were used to investigate psychophysiological responses. Touching real grass was associated with significant changes in brainwave rhythms and a reduction in both systolic and diastolic blood pressure compared to touching artificial turf. In addition, SDM scores revealed that touching real grass increased relaxation, comfort, and a sense of naturalness while decreasing anxiety levels. Compared to the control group, the experimental group had higher mean scores in both meditation and attentiveness. Our findings indicate that contact with real grass may reduce physiological and psychological stress in adults.
Topics: Adult; Female; Humans; Blood Pressure; China; Poaceae; East Asian People; Touch; Stress, Psychological; Anxiety
PubMed: 38310320
DOI: 10.1186/s41043-024-00514-6 -
Journal of Neurology May 2024Amygdala atrophy has been found in frontotemporal dementia (FTD), yet the specific changes of its subregions across different FTD phenotypes remain unclear. The aim of...
Amygdala atrophy has been found in frontotemporal dementia (FTD), yet the specific changes of its subregions across different FTD phenotypes remain unclear. The aim of this study was to investigate the volumetric alterations of the amygdala subregions in FTD phenotypes and how they evolve with disease progression. Patients clinically diagnosed with behavioral variant FTD (bvFTD) (n = 20), semantic dementia (SD) (n = 20), primary nonfluent aphasia (PNFA) (n = 20), Alzheimer's disease (AD) (n = 20), and 20 matched healthy controls underwent whole brain structural MRI. The patient groups were followed up annually for up to 3.5 years. Amygdala nuclei were segmented using FreeSurfer, corrected by total intracranial volumes, and grouped into the basolateral, superficial, and centromedial subregions. Linear mixed effects models were applied to identify changes in amygdala subregional volumes over time. At baseline, bvFTD, SD, and AD displayed global amygdala volume reduction, whereas amygdala volume appeared to be preserved in PNFA. Asymmetrical amygdala atrophy (left > right) was most pronounced in SD. Longitudinally, SD and PNFA showed greater rates of annual decline in the right basolateral and superficial subregions compared to bvFTD and AD. The findings provide comprehensive insights into the differential impact of FTD pathology on amygdala subregions, revealing distinct atrophy patterns that evolve over disease progression. The characterization of amygdala subregional involvement in FTD and their potential role as biomarkers carry substantial clinical implications.
Topics: Amygdala; Frontotemporal Dementia; Female; Middle Aged; Aged; Organ Size; Time Factors; Longitudinal Studies; Cross-Sectional Studies; Magnetic Resonance Imaging; Disease Progression; Atrophy; Primary Progressive Nonfluent Aphasia; Alzheimer Disease
PubMed: 38265470
DOI: 10.1007/s00415-023-12172-5 -
Entropy (Basel, Switzerland) Jan 2024Image fusion is the generation of an informative image that contains complementary information from the original sensor images, such as texture details and attentional...
Image fusion is the generation of an informative image that contains complementary information from the original sensor images, such as texture details and attentional targets. Existing methods have designed a variety of feature extraction algorithms and fusion strategies to achieve image fusion. However, these methods ignore the extraction of common features in the original multi-source images. The point of view proposed in this paper is that image fusion is to retain, as much as possible, the useful shared features and complementary differential features of the original multi-source images. Shared and differential learning methods for infrared and visible light image fusion are proposed. An encoder with shared weights is used to extract shared common features contained in infrared and visible light images, and the other two encoder blocks are used to extract differential features of infrared images and visible light images, respectively. Effective learning of shared and differential features is achieved through weight sharing and loss functions. Then, the fusion of shared features and differential features is achieved via a weighted fusion strategy based on an entropy-weighted attention mechanism. The experimental results demonstrate the effectiveness of the proposed model with its algorithm. Compared with the-state-of-the-art methods, the significant advantage of the proposed method is that it retains the structural information of the original image and has better fusion accuracy and visual perception effect.
PubMed: 38248182
DOI: 10.3390/e26010057