What drives the automatic retrieval of real-world object size knowledge?

Real-world object size is a behaviorally relevant object property that is automatically retrieved when viewing object images: participants are faster to indicate the bigger of two object images when this object is also bigger in the real world. What drives this size Stroop effect? One possibility is that it reflects the automatic retrieval of real-world size after objects are recognized at the basic level (e.g., recognizing an object as a plane activates large real-world size). An alternative possibility is that the size Stroop effect is driven by automatic associations between low-/mid-level visual features (e.g., rectilinearity) and real-world size, bypassing object recognition. Here, we tested both accounts. In Experiment 1, objects were displayed upright and inverted, slowing down recognition while equating visual features. Inversion strongly reduced the Stroop effect, indicating that object recognition contributed to the Stroop effect. Independently of inversion, however, trial-wise differences in rectilinearity also contributed to the Stroop effect. In Experiment 2, the Stroop effect was compared between manmade objects (for which rectilinearity was associated with size) and animals (no association between rectilinearity and size). The Stroop effect was larger for animals than for manmade objects, indicating that rectilinear feature differences were not necessary for the Stroop effect. Finally, in Experiment 3, unrecognizable "texform" objects that maintained size-related visual feature differences were displayed upright and inverted. Results revealed a small Stroop effect for both upright and inverted conditions. Altogether, these results indicate that the size Stroop effect partly follows object recognition with an additional contribution from visual feature associations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Category-based attention facilitates memory search.

We often need to decide whether the object we look at is also the object we look for. When we look for one specific object, this process can be facilitated by feature-based attention. However, when we look for many objects at the same time (e.g., the products on our shopping list) such a strategy may no longer be possible, as research has shown that we can actively prepare to detect only one or two objects at a time. Therefore, looking for multiple objects additionally requires long-term memory search, slowing down decision making. Interestingly, however, previous research has shown that distractor objects can be efficiently rejected during memory search when they are from a different category than the items in the memory set. Here, using EEG, we show that this efficiency is supported by top-down attention at the category level. In Experiment 1, human participants (both sexes) performed a memory search task on individually presented objects from different categories, most of which were distractors. We observed category-level attentional modulation of distractor processing from ∼150 ms after stimulus onset, expressed both as an evoked response modulation and as an increase in decoding accuracy of same-category distractors. In Experiment 2, memory search was performed on two concurrently presented objects. When both objects were distractors, spatial attention (indexed by the N2pc component) was directed to the object that was of the same category as the objects in the memory set. Together, these results demonstrate how top-down attention can facilitate memory search.Significance statement When we are in the supermarket, we repeatedly decide whether a product we look at (e.g., a banana) is on our memorized shopping list (e.g., apples, oranges, kiwis). This requires searching our memory, which takes time. However, when the product is of an entirely different category (e.g., dairy instead of fruit), the decision can be made quickly. Here, we used EEG to show that this between-category advantage in memory search tasks is supported by top-down attentional modulation of visual processing: The visual response evoked by distractor objects was modulated by category membership, and spatial attention was quickly directed to the location of within-category (vs. between-category) distractors. These results demonstrate a close link between attention and memory.

Dynamic changes in ambient PM2.5 and body mass index among old adults: a nationwide cohort study.

Outdoor air pollution has been considered as a severe environmental health issue that almost affecting everyone in the world, and intensive actions were launched. However, little is known about the association between dynamic changes in ambient fine particulate matter (PM2.5) exposure and body mass index (BMI) among old adults. To investigate the dynamic changes in ambient PM2.5 and body mass index among the elderly, we included a total of 7204 participants from 28 provinces of China during 2011-2015 in the China Health and Retirement Longitudinal Study (CHARLS). Ambient fine particle matter (PM2.5) was estimated using a well-validated space-time extremely randomized trees model. Change in PM2.5 and BMI (ΔPM2.5 and ΔBMI) were calculated as the value at a follow-up visit minus value at baseline. Linear mixed-effects models were applied to quantify the associations, controlling for sociodemographic factors. We found that per 1 µg/m3 increase in PM2.5 exposure was associated with a 0.031-0.044 kg/m2 increase in BMI among the elderly. We observed an approximate linear concentration-response relationship of PM2.5 and BMI in each visit. Each 1 µg/m3 increase in ΔPM2.5 exposure was associated with an increase in ΔBMI (ß = 0.040, 95% CI 0.030, 0.049), while per 1 µg/m3 decrease in the ΔPM2.5 exposure level was associated with a decrease in ΔBMI (ß = -0.016, 95% CI -0.027, -0.004). Our findings suggest that dynamic changes in ambient PM2.5 was positively associated with changes in BMI among old Chinese population.

A new fault feature extraction method of rolling bearings based on the improved self-selection ICEEMDAN-permutation entropy.

The vibration signals of rolling bearings are complex and changeable, and extracting meaningful features is difficult. Currently, the commonly used empirical mode decomposition (EMD) algorithms have the problem of mode aliasing. In this paper, a new feature extraction method based on the improved complete ensemble empirical mode decomposition with adapted noise (ICEEMDAN) and permutation entropy is proposed. In this method, the ICEEMDAN algorithm is first improved and optimized to enable a self-selection function The vibration signal is then decomposed into several intrinsic modal functions using this algorithm, and the permutation entropy is extracted as the fault feature of rolling bearings, which improves the accuracy of fault classification and realizes the intelligent feature extraction of different fault states. Then, the Case Western Reserve University dataset is used for verification, and the results show that this scheme can effectively separate the vibration signal characteristics of bearings in different states, and can be used to characterize the characteristics of different bearing signals. Finally, based on the mechanical transmission system bearing experimental platform independently developed by our school, the experimental results show that compared with the unimproved ICEEMDAN algorithm, the diagnostic accuracy rate of the proposed method is 99.5%, which is increased by 6.4%, and it can be effectively used for feature extraction of rolling bearings.

Multiple-stage impairments of unfamiliar face learning in developmental prosopagnosia: Evidence from fMRI repetition suppression and multi-voxel pattern stability.

Individuals with developmental prosopagnosia (DP) are characterized by severe face recognition deficits, yet it remains unknown how they are hindered in the process of unfamiliar face learning. Here we tracked the changes of neural activation during unfamiliar face repetition in DP with fMRI to reveal their neural deficits in learning unfamiliar faces. At the perceptual level, we found that the bilateral fusiform face area (FFA) in individuals with DP showed attenuated repetition suppression for faces, suggesting an inefficient perceptual analysis for learned faces. At the mnemonic level, individuals with DP showed decreased multi-voxel pattern stability for repeated faces in bilateral medial temporal lobe (MTL), suggesting an unstable mnemonic representation for learned faces. In addition, resting-state functional connectivity between the FFA and MTL was also disrupted in individuals with DP. Finally, the MTL's unstable mnemonic representation was associated with the impaired face recognition performance in DP. In sum, our study provides evidence that individuals with DP showed multi-stage neural deficits in unfamiliar face learning and sheds new light on how unfamiliar faces are learned in normal population.

A Highly Versatile Porous Core Photonic Quasicrystal Fiber Based Refractive Index Terahertz Sensor.

Miniaturized real-time fiber optic sensing systems with high sensing performance are in extreme demand. In this work, we propose a novel photonic quasicrystal fiber sensor in the terahertz region and test its sensing characteristics using the finite element method. The proposed simulated sensor numerically investigates the cancer-infected cells from the normal cells in the human cervix, blood, adrenal glands, and breast based on the difference in their refractive index changes. The effective refractive index of core-guided mode is due to the interaction of light between the refractive index of the fiber material and infiltrated normal and cancer cells, respectively. The proposed sensor exhibits a high birefringence of 0.03, a low dispersion of 0.35 ps/THz/cm, along with a high numerical aperture of 0.99. Besides, the sensor holds a less-effective material loss of 2.53 × 10-9 (dB/cm), a maximum power fraction of 88.10, a maximum relative sensitivity of 82.67%, and an effective mode area of 3.16 mm2. The results envisage that the proposed sensor displays high sensing performances with a rapid cancer detection mechanism.

Highly sensitive refractive index sensor based on plastic optical fiber balloon structure.

A novel, to the best of our knowledge, design of plastic optical fiber (POF) balloon-based refractive index sensor for the detection of different concentrations of sodium chloride is proposed and experimentally investigated. The experimental characterization supports the finding that the transmission loss is sensitive to the external environment's targeted refractive index changes of the analyte. The proposed sensor achieves a maximum intensity-based sensitivity of 3105 RIU-1, resolution of 3.22 ×10-7, and the figure of merit (FOM) is 326 RIU-1 from 2 to 2.5 Mol/L of the analyte with the chosen refractive index changes at 680 nm for a diameter D = 0.1 cm of the POF balloon structure. Furthermore, a high linear performance of 0.9896 is achieved with good robustness against the fabrication imperfection. The ultra-sensitiveness to the refractive index with a simple demonstration of the POF balloon-based structure has potential applications in the chemical, biological, and food safety sensing fields.

Sensitivity investigation of cascaded abruptly tapered fiber based on the Vernier effect.

In this paper, we propose and experimentally demonstrate a sensitivity-enhanced temperature sensor by cascading two non-adiabatic tapered fibers (NATFs) based on the Vernier effect. In addition, we investigate the influence of the presence of the reference arm on the cascaded NATFs and compare the temperature response. The experimental results show that a cascaded NATF configuration in which one NATF acts as a sensing arm and the other acts as a reference arm, achieves a temperature sensitivity of -917p m/∘ C, which is 13.28 times that of the single NATF (-69p m/∘ C), while a cascaded NATF configuration in which both NATFs act as a sensing arm attains a temperature sensitivity of 440 pm/°C, which is lower than the configuration with a reference arm. It is confirmed that the synchronous change of the two interferometers will reduce the sensing sensitivity of Vernier effect-based sensors by theory and experiments, and provides guidance for the design of Vernier effect-based sensors.

Ultrasensitive temperature sensor with Vernier-effect improved fiber Michelson interferometer.

A novel fiber Michelson interferometer (FMI) based on parallel dual polarization maintaining fiber Sagnac interferometers (PMF-SIs) is proposed and experimentally demonstrated for temperature sensing. The free spectral range (FSR) difference of dual PMF-SIs determines the FSR of envelope and sensitivity of the sensor. The temperature sensitivity of parallel dual PMF-SIs is greatly enhanced by the Vernier effect. Experimental results show that the temperature sensitivity of the proposed sensor is improved from -1.646 nm/°C (single PMF-SI) to 78.984 nm/°C (parallel dual PMF-SIs), with a magnification factor of 47.99, and the temperature resolution is improved from ±0.03037°C to ±0.00063°C by optimizing the FSR difference between the two PMF-SIs. Our proposed ultrasensitive temperature sensor is with easy fabrication, low cost and simple configuration which can be implemented for various real applications that need high precision temperature measurement.

Perirhinal Cortex is Involved in the Resolution of Learned Approach-Avoidance Conflict Associated with Discrete Objects.

The rodent ventral and primate anterior hippocampus have been implicated in approach-avoidance (AA) conflict processing. It is unclear, however, whether this structure contributes to AA conflict detection and/or resolution, and if its involvement extends to conditions of AA conflict devoid of spatial/contextual information. To investigate this, neurologically healthy human participants first learned to approach or avoid single novel visual objects with the goal of maximizing earned points. Approaching led to point gain and loss for positive and negative objects, respectively, whereas avoidance had no impact on score. Pairs of these objects, each possessing nonconflicting (positive-positive/negative-negative) or conflicting (positive-negative) valences, were then presented during functional magnetic resonance imaging. Participants either made an AA decision to score points (Decision task), indicated whether the objects had identical or differing valences (Memory task), or followed a visual instruction to approach or avoid (Action task). Converging multivariate and univariate results revealed that within the medial temporal lobe, perirhinal cortex, rather than the anterior hippocampus, was predominantly associated with object-based AA conflict resolution. We suggest the anterior hippocampus may not contribute equally to all learned AA conflict scenarios and that stimulus information type may be a critical and overlooked determinant of the neural mechanisms underlying AA conflict behavior.

Vernier effect assisted sucrose sensor based on a cascaded Sagnac interferometer with no-core fiber.

We propose a sucrose concentration sensor by utilizing a fiber Sagnac interferometer with no-core fiber (SI-NCF) based on the Vernier effect. The Vernier effect is realized by introducing a single Sagnac interferometer (SI) with a similar free spectral range of SI-NCF. When the NCF is exposed to the external sucrose solution, the cladding state of NCF is changed, which induces the wavelength shift of the SI-NCF. The measured sucrose concentration sensitivity of a single SI-NCF is 2.97 nm/M, and the sensitivity can be improved to -13.84 nm/M with the assistance of the Vernier effect, which is 4.66 times of the single SI-NCF. The sensor has the advantages of high sensitivity, easy-fabrication and cost-effectiveness which can be applied in the field of the food industry, chemistry and agriculture.

State-of-the-Art Optical Microfiber Coupler Sensors for Physical and Biochemical Sensing Applications.

An optical fiber coupler is a simple and fundamental component for fiber optic technologies that works by reducing the fiber diameter to hundred nanometers or several micrometers. The microfiber coupler (MFC) has regained interest in optical fiber sensing in recent years. The subwavelength diameter rationales vast refractive index (RI) contrast between microfiber "core" and surrounding "cladding", a large portion of energy transmits in the form of an evanescent wave over the fiber surface that determines the MFC ultrasensitive to local environmental changes. Consequently, MFC has the potential to develop as a sensor. With the merits of easy fabrication, low cost and compact size, numerous researches have been carried out on different microfiber coupler configurations for various sensing applications, such as refractive index (RI), temperature, humidity, magnetic field, gas, biomolecule, and so on. In this manuscript, the fabrication and operation principle of an MFC are elaborated and recent advances of MFC-based sensors for scientific and technological applications are comprehensively reviewed.

Multi-Item Discriminability Pattern to Faces in Developmental Prosopagnosia Reveals Distinct Mechanisms of Face Processing.

Previous studies have shown that individuals with developmental prosopagnosia (DP) show specific deficits in face processing. However, the mechanism underlying the deficits remains largely unknown. One hypothesis suggests that DP shares the same mechanism as normal population, though their faces processing is disproportionally impaired. An alternative hypothesis emphasizes a qualitatively different mechanism of DP processing faces. To test these hypotheses, we instructed DP and normal individuals to perceive faces and objects. Instead of calculating accuracy averaging across stimulus items, we used the discrimination accuracy for each item to construct a multi-item discriminability pattern. We found DP's discriminability pattern was less similar to that of normal individuals when perceiving faces than perceiving objects, suggesting that DP has qualitatively different mechanism in representing faces. A functional magnetic resonance imaging study was conducted to reveal the neural basis and found that multi-voxel activation patterns for faces in the right fusiform face area and occipital face area of DP were deviated away from the mean activation pattern of normal individuals. Further, the face representation was more heterogeneous in DP, suggesting that deficits of DP may come from multiple sources. In short, our study provides the first direct evidence that DP processes faces qualitatively different from normal population.

Magnetic bead-gold nanoparticle hybrids probe based on optically countable gold nanoparticles with dark-field microscope for T4 polynucleotide kinase activity assay.

T4 polynucleotide kinase (T4 PNK) plays an essential role in DNA phosphorylation during the DNA repair process. Therefore, the sensitive, selective and convenient detection of T4 PNK activity is of great significance. In this work, we proposed a sensitive non-amplification strategy for the sensing of T4 PNK activity via dark field microscope (DFM) based on magnetic bead (MB)-gold nanoparticle (AuNP) hybrids probe, MB-dsDNA-AuNP (MDA). In the presence of T4 PNK, the 5'-OH termini of DNA are phosphorylated and cleaved into oligonucleotides by lambda exonuclease (λexo), resulting in the destruction of the MDA probe and the separation of AuNP from the MB. Through automatic counting of AuNPs from DFM images, T4 PNK activity can be quantitatively measured. This strategy revealed a limit of detection (LOD) as low as 0.0058 U/mL and exhibited a dynamic range from 0.01 to 1 U/mL. The strategy presents an excellent ability to discriminate T4 PNK from the other proteins and enzymes. Notably, this strategy was applied to screen the T4 PNK inhibitors and test the activity in cell lysates, showing great potential for the discovery of new anticancer drugs and other related research field.

An aptasensor based on the microscopic enumeration of encoding gold nanoparticles for the detection of C-reactive protein.

C-reactive protein (CRP) is a crucial clinical biomarker for inflammatory and cardiovascular diseases. Therefore, the sensitive, selective and convenient detection of CRP is of great significance. Using gold nanoparticles (AuNPs) and combining the specific interaction between an aptamer and CRP, we developed a simple and convenient assay for CRP detection. The aptamer-based probe was fabricated through the hybridization of CRP-aptamer immobilized on magnetic beads (MBs) to a short complementary DNA (cDNA) chain attached to AuNPs to form a MB-Aptamer-AuNP sandwich structure. Upon the addition of CRP, aptamer-cDNA dehybridization occurred due to the strong interaction between CRP and the aptamer, resulting in the release of AuNPs, which were subjected to DFM imaging and subsequently counted using the MATLAB program. The number of AuNPs was therefore positively correlated to the concentration of CRP and a detection limit as low as 2.71 nM was achieved. The current approach could also exclude the disturbance of other proteins, including thrombin, IgG, Lys and BSA. In addition, the concentration of CRP detected was in good agreement with the amount cast in bovine and mouse serum, indicating that the proposed probe is robust and accurate, and it is very promising for practical applications where CRP detection is necessary. The current strategy is also promising for the detection of other proteins where a suitable aptamer is selected.

The neural network for face recognition: Insights from an fMRI study on developmental prosopagnosia.

Face recognition is supported by collaborative work of multiple face-responsive regions in the brain. Based on findings from individuals with normal face recognition ability, a neural model has been proposed with the occipital face area (OFA), fusiform face area (FFA), and face-selective posterior superior temporal sulcus (pSTS) as the core face network (CFN) and the rest of the face-responsive regions as the extended face network (EFN). However, little is known about how these regions work collaboratively for face recognition in our daily life. Here we focused on individuals suffering developmental prosopagnosia (DP), a neurodevelopmental disorder specifically impairing face recognition, to shed light on the infrastructure of the neural model of face recognition. Specifically, we used a variant of global brain connectivity method to comprehensively explore resting-state functional connectivity (FC) among face-responsive regions in a large sample of DPs (N = 64). We found that both the FCs within the CFN and those between the CFN and EFN were largely reduced in DP. Importantly, the right OFA and FFA served as the dysconnectivity hubs within the CFN, i.e., FCs concerning these two regions within the CFN were largely disrupted. In addition, DPs' right FFA also showed reduced FCs with the EFN. Moreover, these disrupted FCs were related to DP's behavioral deficit in face recognition, with the FCs from the FFA to the anterior temporal lobe (ATL) and pSTS the most predictive. Based on these findings, we proposed a revised neural model of face recognition demonstrating the relatedness of interactions among face-responsive regions to face recognition.

Unsatisfied relatedness, not competence or autonomy, increases trait anger through the right amygdala.

Anger is a common negative emotion in social life. Behavioral research suggests that unsatisfied relatedness, autonomy, and competence are related to anger. However, it remains unclear whether these unsatisfied needs all contribute to anger or just a particular unsatisfied need is the main source of anger. In addition, little is known about the neural substrate between unsatisfied needs and anger. To address these two questions, we used voxel-based morphometry (VBM) to explore the neural substrate underlying the relation between unsatisfied needs and trait anger. Behaviorally, we found that although all three unsatisfied needs were correlated with trait anger, unsatisfied relatedness was the only factor that was uniquely related to trait anger. Neurally, the gray matter volume of the right amygdala was correlated with trait anger, which fits nicely with the role of the amygdala as a core region for processing anger. Importantly, the right amygdala mediated the total effect of unsatisfied relatedness on trait anger, even after controlling for general personality dispositions. Our results contribute to the theoretical conceptualization of anger by elucidating the unique role of unsatisfied relatedness in anger and the neural substrate underlying such relation.

Altered spontaneous neural activity in the occipital face area reflects behavioral deficits in developmental prosopagnosia.

Individuals with developmental prosopagnosia (DP) exhibit severe difficulties in recognizing faces and to a lesser extent, also exhibit difficulties in recognizing non-face objects. We used fMRI to investigate whether these behavioral deficits could be accounted for by altered spontaneous neural activity. Two aspects of spontaneous neural activity were measured: the intensity of neural activity in a voxel indexed by the fractional amplitude of spontaneous low-frequency fluctuations (fALFF), and the connectivity of a voxel to neighboring voxels indexed by regional homogeneity (ReHo). Compared with normal adults, both the fALFF and ReHo values within the right occipital face area (rOFA) were significantly reduced in DP subjects. Follow-up studies on the normal adults revealed that these two measures indicated further functional division of labor within the rOFA. The fALFF in the rOFA was positively correlated with behavioral performance in recognition of non-face objects, whereas ReHo in the rOFA was positively correlated with processing of faces. When considered together, the altered fALFF and ReHo within the same region (rOFA) may account for the comorbid deficits in both face and object recognition in DPs, whereas the functional division of labor in these two measures helps to explain the relative independency of deficits in face recognition and object recognition in DP.

The Competitive Influences of Perceptual Load and Working Memory Guidance on Selective Attention.

The perceptual load theory in selective attention literature proposes that the interference from task-irrelevant distractor is eliminated when perceptual capacity is fully consumed by task-relevant information. However, the biased competition model suggests that the contents of working memory (WM) can guide attentional selection automatically, even when this guidance is detrimental to visual search. An intriguing but unsolved question is what will happen when selective attention is influenced by both perceptual load and WM guidance. To study this issue, behavioral performances and event-related potentials (ERPs) were recorded when participants were presented with a cue to either identify or hold in memory and had to perform a visual search task subsequently, under conditions of low or high perceptual load. Behavioural data showed that high perceptual load eliminated the attentional capture by WM. The ERP results revealed an obvious WM guidance effect in P1 component with invalid trials eliciting larger P1 than neutral trials, regardless of the level of perceptual load. The interaction between perceptual load and WM guidance was significant for the posterior N1 component. The memory guidance effect on N1 was eliminated by high perceptual load. Standardized Low Resolution Electrical Tomography Analysis (sLORETA) showed that the WM guidance effect and the perceptual load effect on attention can be localized into the occipital area and parietal lobe, respectively. Merely identifying the cue produced no effect on the P1 or N1 component. These results suggest that in selective attention, the information held in WM could capture attention at the early stage of visual processing in the occipital cortex. Interestingly, this initial capture of attention by WM could be modulated by the level of perceptual load and the parietal lobe mediates target selection at the discrimination stage.