Object Recognition Ability Research Articles

Aerobic exercise prevents and improves cognitive dysfunction caused by morphine withdrawal via regulating endogenous opioid peptides in the brain.

Morphine withdrawal leads to serious cognitive deficits in which dynorphins are directly involved. Recently, exercise has been shown to prevent and improve cognition dysfunction in a variety of ways. Meanwhile, exercise can regulate the endogenous opioid peptides including dynorphins. However, it remains unclear whether exercise influences cognitive dysfunction caused by morphine withdrawal via dynorphins. In the current study, we investigate the physiological mechanism of exercise prevention and improvement aganist cognition dysfunction caused by morphine withdrawal. Male, adult C57BL/6 mice were randomly divided into 5 groups : Saline control (WT), exercise (EXE), morphine withdrawl (MW), exercise + morphine withdrawl (EMW), morphine withdrawl + exercise (MWE). We established aerobic exercise prevention/improvement models, and conducted behavioral tests including Open field test (OFT), Temporal order memory test (TOM) and Y-maze. Through Western Blotting and immunofluorescence staining, we detected endogenous opioid peptides in hippocampus and mPFC. Compared with MW group, EMW group and MWE group showed the same performance as WT group in TOM and Y-maze, with correct object recognition and memory ability. In Western Blotting and immunofluorescence staining experiments, it indicated that EMW group reduced the expression of PDYN and its fluorescence intensity in hippocampus; MWE group reduced the expression of OPRK1 and its fluorescence intensity in mPFC. Our data suggest that aerobic exercise can both prevent and improve cognitive dysfunction caused by acute morphine withdrawal via respectively down-regulating PDYN in the hippocampus and down-regulating OPRK1 in the mPFC. They may become new targets for drugs development in the future.

Skills and cautiousness predict performance in difficult search.

People differ in how well they search. What are the factors that might contribute to this variability? We tested the contribution of two cognitive abilities: visual working memory (VWM) capacity and object recognition ability. Participants completed three tasks: a difficult inefficient visual search task, where they searched for a target letter T among skewed L distractors; a VWM task, where they memorized a color array and then identified whether a probed color belonged to the previous array; and the Novel Object Memory Test (NOMT), where they learnt complex novel objects and then identified them amongst objects that closely resembled them. Exploratory and confirmatory factor analyses revealed that there are two latent factors that explain the shared variance among these three tasks: a factor indicative of the level of caution participants exercised during the challenging visual search task, and a factor representing their visual cognitive abilities. People who score high on the search cautiousness tend to perform a more accurate but slower search. People who score high on the visual cognitive ability factor tend to have a higher VWM capacity, a better object recognition ability, and a faster search speed. The results reflect two points: (1) Visual search tasks share components with visual working memory and object recognition tasks. (2) Search performance is influenced not only by the search display's properties but also by individual predispositions such as caution and general visual abilities. This study introduces new factors for consideration when interpreting variations in visual search behaviors.

Heat-Killed Lactococcus Lactis KC24 Ameliorates Scopolamine-Induced Memory Impairment in ICR Mice.

Heat-killed Lactococcus lactis KC24 (H-KC24) has been examined for its neuroprotective effects in SH-SY5Y cells. We hypothesized that H-KC24 could alleviate memory impairment through the gut-brain axis. Scopolamine (1mg/kg/day) was administered to ICR mice to induce memory impairment. Low- and high-dose H-KC24 cells (1 × 109 and 2 × 109 CFU/day, respectively) or donepezil (DO, 2mg/kg) were administered for 14 days. H-KC24 treatment alleviated the deleterious scopolamine-induced memory effects on the recognition index and object recognition ability in the novel object recognition test and the Y-maze test. Changes in neurotransmitters and synaptic plasticity were confirmed by measuring acetylcholine, acetylcholinesterase, choline acetyltransferase, brain-derived neurotrophic factor, cyclic AMP response element-binding protein, and phosphorylated cyclic AMP response element-binding protein expression in brain tissues. In the H-KC24 and DO groups, β-secretase levels increased, whereas amyloid β levels decreased, demonstrating that H-KC24 can improve memory impairment caused by oxidative stress. This study demonstrated the positive effects of H-KC24 in a scopolamine-induced memory impairment mouse model.

Measuring object recognition ability: Reliability, validity, and the aggregate z-score approach.

Measurement of domain-general object recognition ability (o) requires minimization of domain-specific variance. One approach is to model o as a latent variable explaining performance on a battery of tests which differ in task demands and stimuli; however, time and sample requirements may be prohibitive. Alternatively, an aggregate measure of o can be obtained by averaging z-scores across tests. Using data from Sunday et al., Journal of Experimental Psychology: General, 151, 676-694, (2022), we demonstrated that aggregate scores from just two such object recognition tests provide a good approximation (r = .79) of factor scores calculated from a model using a much larger set of tests. Some test combinations produced correlations of up to r = .87 with factor scores. We then revised these tests to reduce testing time, and developed an oddoneout task, using a unique object category on nearly every trial, to increase task and stimuli diversity. To validate our measures, 163 participants completed the object recognition tests on two occasions, one month apart. Providing the first evidence that o is stable over time, our short aggregate o measure demonstrated good test-retest reliability (r = .77). The stability of o could not be completely accounted for by intelligence, perceptual speed, and early visual ability. Structural equation modeling suggestedthat our tests load significantly onto the same latent variable, and revealed that as a latent variable, o is highly stable (r = .93). Aggregation is an efficient method for estimating o, allowing investigation of individual differences in object recognition ability to be more accessible in future studies.

Synergistic effects of tilapia head protein hydrolysate and walnut protein hydrolysate on the amelioration of cognitive impairment in mice.

Cognitive impairment (CI) is a significant public health concern, and bioactive peptides have shown potential as therapeutic agents. However, information about their synergistic effects on cognitive function is still limited. Here, we investigated the synergistic effects of tilapia head protein hydrolysate (THPH) and walnut protein hydrolysate (WPH) in mitigating CI induced by scopolamine in mice. The results showed that the combined supplementation of THPH and WPH (mass ratio, 1:1) was superior to either individual supplement in enhancing spatial memory and object recognition abilities in CI mice, and significantly lessened brain injury in CI mice by alleviating neuronal damage, reducing oxidative stress and stabilizing the cholinergic system. In addition, the combined supplementation was found to be more conducive to remodeling the gut microbiota structure in CI mice by not only remarkably reducing the ratio of Firmicutes to Bacteroidota, but also specifically enriching the genus Roseburia. On the other hand, the combined supplementation regulated the disorders of sphingolipid and amino acid metabolism in CI mice, particularly upregulating glutathione and histidine metabolism, and displayed a stronger ability to increase the expression of genes and proteins related to the brain-derived neurotrophic factor (BDNF)/TrkB/CrEB signaling pathway in the brain. These findings demonstrate that tilapia head and walnut-derived protein hydrolysates exerted synergistic effects in ameliorating CI, which was achieved through modulation of gut microbiota, serum metabolic pathways and BDNF signaling pathways. © 2024 Society of Chemical Industry.

Distinct but related abilities for visual and haptic object recognition.

People vary in their ability to recognize objects visually. Individual differences for matching and recognizing objects visually is supported by a domain-general ability capturing common variance across different tasks (e.g., Richler et al., Psychological Review, 126, 226-251, 2019). Behavioral (e.g., Cooke et al., Neuropsychologia, 45, 484-495, 2007) and neural evidence (e.g., Amedi, Cerebral Cortex, 12, 1202-1212, 2002) suggest overlapping mechanisms in the processing of visual and haptic information in the service of object recognition, but it is unclear whether such group-average results generalize to individual differences. Psychometrically validated measures are required, which have been lacking in the haptic modality. We investigate whether object recognition ability is specific to vision or extends to haptics using psychometric measures we have developed. We use multiple visual and haptic tests with different objects and different formats to measure domain-general visual and haptic abilities and to test for relations across them. We measured object recognition abilities using two visual tests and four haptic tests (two each for two kinds of haptic exploration) in 97 participants. Partial correlation and confirmatory factor analyses converge to support the existence of a domain-general haptic object recognition ability that is moderately correlated with domain-general visual object recognition ability. Visual and haptic abilities share about 25% of their variance, supporting the existence of a multisensory domain-general ability while leaving a substantial amount of residual variance for modality-specific abilities. These results extend our understanding of the structure of object recognition abilities; while there are mechanisms that may generalize across categories, tasks, and modalities, there are still other mechanisms that are distinct between modalities.

Abstract TMP118: Aged Maternal Gut Microbiome Impairs Offspring Behavior and Exacerbates Stroke Outcome

The microbiome plays a significant role in influencing general health. A disruption of the gut biome homeostasis, dysbiosis, can be both the effect of disease or a precondition. The maternal biome has been shown to play a vital role in offspring brain and immune development by shaping the metabolic environment for the embryo. Therefore, an aged dysbiotic maternal biome may increase stroke risk factors among offspring and additionally, worsen stroke outcome. Young female C57B6 mice 3-month (M) of age had their host gut bacteria cleared via antibiotic treatment prior to recolonization via fecal microbiome transplants from 3M control, and 14M middle aged female mice. After breeding, the subsequent offspring was aged to 14 months, followed by behavioral tests, glucose tolerance, prior to a transient 60-minute middle cerebral artery occlusion (MCAO or sham surgery). The maternal biome had a significant effect on offspring biome at 2M, 6M and 9M of age, shifting the beta-diversity of females significantly (p=<0.01), and males to a lesser extent (p=0.241), extending into adulthood. Additional sex specific changes were observed in adult mouse behavior with decreased motor function and increased anxiety being prevalent in male offspring at 2 months of age (p=0.0338 and 0.0261 respectively) but not in females. At 6 months of age female offspring from dysbiotic mothers exhibited significantly impaired object recognition abilities compared to control (p=>0.01). Once the offspring had been subjected to a 60 min MCAO, a spontaneous recovery was observed in NDS scores in all females and in the control males, but not in males from dysbiotic mothers, suggesting that male stroke outcome is negatively affected by dysbiotic mothers. The maternal microbiome has a significant impact on offspring biome composition and health. Mice from mothers with aged microbiome exhibited sex specific early life motor function and cognitive impairment. Additionally, male offspring from dysbiotic mothers have a worsened stroke outcome.

Simulation of neuroplasticity in a CNN-based in-silico model of neurodegeneration of the visual system.

The aim of this work was to enhance the biological feasibility of a deep convolutional neural network-based in-silico model of neurodegeneration of the visual system by equipping it with a mechanism to simulate neuroplasticity. Therefore, deep convolutional networks of multiple sizes were trained for object recognition tasks and progressively lesioned to simulate neurodegeneration of the visual cortex. More specifically, the injured parts of the network remained injured while we investigated how the added retraining steps were able to recover some of the model's object recognition baseline performance. The results showed with retraining, model object recognition abilities are subject to a smoother and more gradual decline with increasing injury levels than without retraining and, therefore, more similar to the longitudinal cognition impairments of patients diagnosed with Alzheimer's disease (AD). Moreover, with retraining, the injured model exhibits internal activation patterns similar to those of the healthy baseline model when compared to the injured model without retraining. Furthermore, we conducted this analysis on a network that had been extensively pruned, resulting in an optimized number of parameters or synapses. Our findings show that this network exhibited remarkably similar capability to recover task performance with decreasingly viable pathways through the network. In conclusion, adding a retraining step to the in-silico setup that simulates neuroplasticity improves the model's biological feasibility considerably and could prove valuable to test different rehabilitation approaches in-silico.

Deactivation of dorsal CA1 pyramidal neurons projecting to medial prefrontal cortex contributes to neuropathic pain and short-term memory impairment.

Neuropathic pain after peripheral nerve injury is a multidimensional experience that includes sensory, affective, and cognitive components that interact with one another. Hypoexcitation of the medial prefrontal cortex (mPFC) was observed in mice with peripheral nerve injury, but the changes in neural inputs onto the mPFC have not been completely explored. Here, we report that the neural terminals from the dorsal hippocampus CA1 (dCA1) form excitatory connection with layer 5 pyramidal neurons in the prelimbic area (PrL) of the mPFC. Spared nerve injury (SNI) induced a reduction in the intrinsic excitability of dCA1 pyramidal neurons innervating the PrL and impairment in excitatory synaptic transmission onto dCA1 pyramidal cells. Specifically, activating the neural circuit from dCA1 to mPFC alleviated neuropathic pain behaviors and improved novel object recognition ability in SNI mice, whereas deactivating this pathway in naïve animals recapitulated tactile allodynia and memory deficits. These results indicated that hypoactivity in dCA1 pyramidal cells after SNI in turn deactivated layer 5 pyramidal neurons in PrL and ultimately caused pain hypersensitivity and memory deficits.

High-dimensional topographic organization of visual features in the primate temporal lobe

The inferotemporal cortex supports our supreme object recognition ability. Numerous studies have been conducted to elucidate the functional organization of this brain area, but there are still important questions that remain unanswered, including how this organization differs between humans and non-human primates. Here, we use deep neural networks trained on object categorization to construct a 25-dimensional space of visual features, and systematically measure the spatial organization of feature preference in both male monkey brains and human brains using fMRI. These feature maps allow us to predict the selectivity of a previously unknown region in monkey brains, which is corroborated by additional fMRI and electrophysiology experiments. These maps also enable quantitative analyses of the topographic organization of the temporal lobe, demonstrating the existence of a pair of orthogonal gradients that differ in spatial scale and revealing significant differences in the functional organization of high-level visual areas between monkey and human brains.

An improved YOLOv5 model: Application to leaky eggs detection

In order to quickly and correctly detect the leaky eggs on the egg processing line, this article proposed a leaky eggs detection model based on an improved YOLOv5 network. Firstly, we replaced the feature pyramid network and path aggregation network (FPN + PANet) with bidirectional feature pyramid network (BiFPN) to improve the multi-scale object recognition ability without increasing computational costs and improve the detection accuracy of small objects in egg images. Secondly, we added the Convolutional Attention Mechanism Module (CBAM) to enhance the ability for perceiving target information to improve the model's detection performance. This result shows that the improved model for detecting leaky eggs has an average precision (AP) of 92.4%, which is 3.9% higher than the original network and also outperforms other target detection models. Moreover, in three group of comparison experiments completed on a laboratory platform with different conveying speeds, the detection accuracy of leaky eggs was 97.1%, 91.4% and 87.1%, respectively, indicating that the improved YOLOv5 model has good performance but the missed rate will increase with the increase of conveying speed. Finally, the test results on the factory egg processing line (Kyowa/FP-600) show that the improved model can detect the leaky eggs appearing in the visual window in real time, meeting the detection requirements of the egg processing line.

Measuring Object Recognition Ability: Reliability, Validity, and the Aggregate z-score Approach.

Measuring Object Recognition Ability: Reliability, Validity, and the Aggregate z-score Approach.

TCNet: A Novel Triple-Cooperative Network for Video Object Detection

Video object detection aims at accurately localizing the objects in videos and correctly recognizing their categories. Off-the-shelf video object detection methods have made some progress in recent years but they still suffer from the problems of inaccurate object localization, incorrect object recognition or insufficient relation learning, resulting in limited detection performance. In this paper, we propose a novel triple-cooperative network (TCNet) for high-performance video object detection, with three substantial improvements to ameliorate the problems of existing methods. First, we develop a context-aware proposal refinement module to generate high-quality proposals, enabling our TCNet to achieve more accurate object localization. Second, we present a similarity-aware semantic distillation module that innovatively leverages the semantic knowledge of class labels as additional supervisory signals to enhance the object recognition ability of our TCNet. Third, we design a structure-aware relation learning module to effectively model the structural relations between features with an adaptive-pruning residual graph convolutional network, making our TCNet perform more effective feature aggregation. We conduct extensive experiments on the challenging ImageNet VID dataset and the experimental results demonstrate that our TCNet outperforms current state-of-the-art methods. More remarkably, our TCNet achieves 85.2% mAP and 86.3% mAP with ResNet-101 and ResNeXt-101, respectively.

Evidence for an amodal domain-general object recognition ability

A general object recognition ability predicts performance across a variety of high-level visual tests, categories, and performance in haptic recognition. Does this ability extend to auditory recognition? Vision and haptics tap into similar representations of shape and texture. In contrast, features of auditory perception like pitch, timbre, or loudness do not readily translate into shape percepts related to edges, surfaces, or spatial arrangement of parts. We find that an auditory object recognition ability correlates highly with a visual object recognition ability after controlling for general intelligence, perceptual speed, low-level visual ability, and memory ability. Auditory object recognition was a stronger predictor of visual object recognition than all control measures across two experiments, even though those control variables were also tested visually. These results point towards a single high-level ability used in both vision and audition. Much work highlights how the integration of visual and auditory information is important in specific domains (e.g., speech, music), with evidence for some overlap of visual and auditory neural representations. Our results are the first to reveal a domain-general ability, o, that predicts object recognition performance in both visual and auditory tests. Because o is domain-general, it reveals mechanisms that apply across a wide range of situations, independent of experience and knowledge. As o is distinct from general intelligence, it is well positioned to potentially add predictive validity when explaining individual differences in a variety of tasks, above and beyond measures of common cognitive abilities like general intelligence and working memory.

Physically informed machine-learning algorithms for the identification of two-dimensional atomic crystals

After graphene was first exfoliated in 2004, research worldwide has focused on discovering and exploiting its distinctive electronic, mechanical, and structural properties. Application of the efficacious methodology used to fabricate graphene, mechanical exfoliation followed by optical microscopy inspection, to other analogous bulk materials has resulted in many more two-dimensional (2D) atomic crystals. Despite their fascinating physical properties, manual identification of 2D atomic crystals has the clear drawback of low-throughput and hence is impractical for any scale-up applications of 2D samples. To combat this, recent integration of high-performance machine-learning techniques, usually deep learning algorithms because of their impressive object recognition abilities, with optical microscopy have been used to accelerate and automate this traditional flake identification process. However, deep learning methods require immense datasets and rely on uninterpretable and complicated algorithms for predictions. Conversely, tree-based machine-learning algorithms represent highly transparent and accessible models. We investigate these tree-based algorithms, with features that mimic color contrast, for automating the manual inspection process of exfoliated 2D materials (e.g., MoSe2). We examine their performance in comparison to ResNet, a famous Convolutional Neural Network (CNN), in terms of accuracy and the physical nature of their decision-making process. We find that the decision trees, gradient boosted decision trees, and random forests utilize physical aspects of the images to successfully identify 2D atomic crystals without suffering from extreme overfitting and high training dataset demands. We also employ a post-hoc study that identifies the sub-regions CNNs rely on for classification and find that they regularly utilize physically insignificant image attributes when correctly identifying thin materials.

Effects of subchronic exposure of perfluorooctane sulfonate on cognitive function of mice and its mechanism

Perfluorooctane sulfonate (PFOS) is an emerging persistent organic pollutant, and its potential impact on cognitive function remains unclear. We adopted the C57BL/6J mouse model to investigate the effect of PFOS on cognitive function, as well as the underlying mechanisms. Subchronic exposure was performed by administering PFOS via drinking water for 6 months (at doses of 0, 0.2, and 2.0 mg/kg/day), starting from 10.5 months old. The object recognition ability was tested at 2, 4, and 6 months of exposure, and spatial learning and memory were assessed at endpoint. The apoptosis of neurons and astrocytes in the cortex and hippocampus was analyzed, as well as the potential apoptotic signaling pathways. Our results showed that exposure to PFOS for 6 months caused a decrease in object recognition ability and a decline in learning and spatial memory. PFOS selectively increased apoptosis in neurons of the cerebral cortex and specifically activated the endoplasmic reticulum stress PERK/CHOP signaling pathway. In conclusion, our results confirmed that subchronic exposure to PFOS can lead to cognitive impairment in mice, which might be closely associated with the specific activation of an endoplasmic reticulum stress-induced pro-apoptosis pathway in the cerebral cortex neurons.

Object recognition ability predicts category learning with medical images

We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category learning. This lack of correlation occurred despite high reliability in all measurements. However, participants only received feedback on the first 10 of 60 trials. In study 2, we assigned participants to one of two conditions: feedback on only the first 10 trials, or on all 60 trials of the category learning test. We found strong Bayesian evidence for a correlation between o and categorisation accuracy in the full-feedback condition, but not when feedback was limited to early trials. Moderate Bayesian evidence supported a difference between these correlations. Without feedback, participants may stick to simple rules they formulate at the start of category learning, when trials are easier. Feedback may encourage participants to abandon less effective rules and switch to exemplar learning. This work provides the first evidence relating o to a specific learning mechanism, suggesting this ability is more dependent upon exemplar learning mechanisms than rule abstraction. Object-recognition ability could complement other sources of individual differences when predicting accuracy of medical image interpretation.

Mormyrid fish as models for investigating sensory-motor integration: A behavioural perspective.

Animals possess senses which gather information from their environment. They can tune into important aspects of this information and decide on the most appropriate response, requiring coordination of their sensory and motor systems. This interaction is bidirectional. Animals can actively shape their perception with self-driven motion, altering sensory flow to maximise the environmental information they are able to extract. Mormyrid fish are excellent candidates for studying sensory-motor interactions, because they possess a unique sensory system (the active electric sense) and exhibit notable behaviours that seem to be associated with electrosensing. This review will take a behavioural approach to unpicking this relationship, using active electrolocation as an example where body movements and sensing capabilities are highly related and can be assessed in tandem. Active electrolocation is the process where individuals will generate and detect low-voltage electric fields to locate and recognise nearby objects. We will focus on research in the mormyrid Gnathonemus petersii (G.petersii), given the extensive study of this species, particularly its object recognition abilities. By studying object detection and recognition, we can assess the potential benefits of self-driven movements to enhance selection of biologically relevant information. Finally, these findings are highly relevant to understanding the involvement of movement in shaping the sensory experience of animals that use other sensory modalities. Understanding the overlap between sensory and motor systems will give insight into how different species have become adapted to their environments.

Adolescence Predatory Risk Alters Social Behaviors and Cognitive Ability and Central Oxytocin and Vasopressin Expression in Adult Brandt’s Voles

Introduction: Stress during adolescence causes long-term behavioral changes in adulthood. We previously found that adolescent exposure to predatory risk augments adolescent social contact and adult parental behavior in Brandt’s voles (Lasiopodomys brandtii). Methods: Here, we determined whether this experience alters sexual behavior, pair-bond formation, and recognition ability as well as basal HPA axis activity, central oxytocin (OT), and arginine-vasopressin (AVP) expression in adulthood. Results: In the social interaction test, repeated cat odor (CO) exposure enhanced the frequency of lordosis by female voles toward an unfamiliar opposite-sex conspecific. CO voles preferred to engage with their partners after 48-h cohabitation whereas the control groups did not, which may reflect stable pair bonds in the CO treatment group. Furthermore, adolescent exposure to CO inhibited novel object recognition and place recognition ability, while it influenced social recognition only among adult males. No effect of adolescent CO exposure was observed for basal HPA axis activity, showing a habituation effect. Finally, we found that CO exposure increased OT and decreased AVP expression in the hypothalamus, including the paraventricular nucleus and anterior hypothalamus. The levels of OT in the medial amygdala were lower, and AVP in the lateral septum was higher in CO voles compared with the control. Conclusion: These findings demonstrate that adolescent exposure to predator risk promotes adult reproductive behavior of Brandt’s voles. Deficits in recognition ability may necessitate alterations in reproductive strategies to enhance inclusive fitness. OT and AVP systems may play a modulatory role in the alteration of social behaviors elicited by adolescent predatory risk.

Haptic object recognition abilities correlate across feature types and with visual object recognition ability

Haptic object recognition abilities correlate across feature types and with visual object recognition ability