Orientation Code Research Articles

Identification of cultural conversations in therapy using natural language processing models.

Researchers have historically focused on understanding therapist multicultural competency and orientation through client self-report measures and behavioral coding. While client perceptions of therapist cultural competency and multicultural orientation and behavioral coding are important, reliance on these methods limits therapists receiving systematic, scalable feedback on cultural opportunities within sessions. Prior research demonstrating the feasibility of automatically identifying topics of conversation in psychotherapy suggests that natural language processing (NLP) models could be trained to automatically identify when clients and therapists are talking about cultural concerns and could inform training and provision of rapid feedback to therapists. Utilizing 103,170 labeled talk turns from 188 psychotherapy sessions, we developed NLP models that recognized the discussion of cultural topics in psychotherapy (F-1 = 70.0; Spearman's ρ = 0.78, p < .001). We discuss implications for research and practice and applications for future NLP-based feedback tools. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Possible Optimal Strategies for Orientation Coding in Macaque V1 Revealed with a Self-Attention Deep Neural Network (SA-DNN) Model

Possible Optimal Strategies for Orientation Coding in Macaque V1 Revealed with a Self-Attention Deep Neural Network (SA-DNN) Model

Toward Large-Scale Palmprint Image Analysis by a Rich Orientation Code

Toward Large-Scale Palmprint Image Analysis by a Rich Orientation Code

COVID-19 related messaging, beliefs, information sources, and mitigation behaviors in Virginia: a cross-sectional survey in the summer of 2020.

Conflicting messages and misleading information related to the coronavirus (COVID-19) pandemic (SARS-CoV-2) have hindered mitigation efforts. It is important that trust in evidence-based public health information be maintained to effectively continue pandemic mitigation strategies. Officials, researchers, and the public can benefit from exploring how people receive information they believe and trust, and how their beliefs influence their behaviors. To gain insight and inform effective evidence-based public health messaging, we distributed an anonymous online cross-sectional survey from May to July, 2020 to Virginia residents, 18 years of age or older. Participants were surveyed about their perceptions of COVID-19, risk mitigation behaviors, messages and events they felt influenced their beliefs and behaviors, and where they obtained information that they trust. The survey also collected socio-demographic information, including gender, age, race, ethnicity, level of education, income, employment status, occupation, changes in employment due to the pandemic, political affiliation, sexual orientation, and zip code. Analyses included specific focus on the most effective behavioral measures: wearing a face mask and distancing in public. Among 3,488 respondents, systematic differences were observed in information sources that people trust, events that impacted beliefs and behaviors, and how behaviors changed by socio-demographics, political identity, and geography within Virginia. Characteristics significantly associated (p<0.025) with not wearing a mask in public included identifying as non-Hispanic white, male, Republican political identity, younger age, lower income, not trusting national science and health organizations, believing one or more non-evidence-based messages, and residing in Southwest Virginia in logistic regression. Similar, lesser in magnitude correlations, were observed for distancing in public. This study describes how information sources considered trustworthy vary across different populations and identities, and how these differentially correspond to beliefs and behaviors. This study can assist decision makers and the public to improve and effectively target public health messaging related to the ongoing COVID-19 pandemic and future public health challenges in Virginia and similar jurisdictions.

Diversity in Gender Identity and Sexual Orientation and Professional Ethics Codes in Psychiatry

Diversity in Gender Identity and Sexual Orientation and Professional Ethics Codes in Psychiatry

Biased population coding of visual orientation in the human brain

Biased population coding of visual orientation in the human brain

Psychotherapy training via a task‐based assessment of the multicultural orientation framework: A pilot study

AbstractThis pilot study involved the development and initial testing of an applied Multicultural Orientation Performance Task (MCO‐PT) and coding system. The MCO‐PT was comprised of seven brief video simulations of cultural exchanges. Seventy‐four graduate students recorded responses and then completed measures of desirable responding and multicultural competence. Research assistants coded the videos on three dimensions: cultural humility, cultural opportunities and cultural comfort (ICCs 0.61–0.97). Exploratory factor analysis yielded three factors that corresponded with the MCO constructs (alphas 0.77–0.97). Cultural opportunities were positively correlated with multicultural competence, and none of the subscales were associated with social desirability.

The Relation between Ensemble Coding of Length and Orientation Does Not Depend on Spatial Attention

Most people are good at estimating summary statistics for different features of groups of objects. For instance, people can selectively attend to different features of a group of lines and report ensemble properties such as the mean length or mean orientation and there are reliable individual differences in such ensemble judgment abilities. Our recent study found decisive evidence in support of a correlation between the errors on mean length and mean orientation judgments (r = 0.62). The present study investigates one possible mechanism for this correlation. The ability to allocate spatial attention to single items varies across individuals, and in the recent study, this variability could have contributed to both judgments because the location of lines was unpredictable. Here, we replicate this prior work with arrays of lines with fully predictable spatial locations, to lower the contribution of the ability to distribute attention effectively over all items in a display. We observed a strong positive correlation between errors on the length and orientation averaging tasks (r = 0.65). This provides evidence against individual differences in spatial attention as a common mechanism supporting mean length and orientation judgments. The present result aligns with the growing evidence for at least one ensemble-specific ability that applies across different kinds of features and stimuli.

Using an entorhinal cortex‐based virtual reality navigation task to differentiate between individuals with and without subjective cognitive decline

AbstractBackgroundEntorhinal cortex is vulnerable to neurodegenerative changes in the earliest stages of AD. However, this early AD stage cannot be detected by currently available neuropsychological tests. The entorhinal cortex contains spatial modulated cells, known as grid cells, that play a key role in supporting path integration (PI), a crucial component of spatial navigation that supports continuous integration of self‐motion information and in combination with environmental cues provides accurate internal representation of space. Previously, PI deficits were associaed with impaired grid cell function in healthy older adults and in young APOE‐E4 carriers. Importantly, PI performance has successfully discriminated between biomarker positive and negative mild cognitive impairment patients and between healthy older adults at higher and lower risk of AD. In this study, we tested whether performance on an immersive virtual reality PI task can differentiate between patients with and without subjective cognitive decline (SCD).MethodA group of healthy older adults and SCD patients will perform an immersive virtual reality PI task. In this task, participants are immersed in an open‐field virtual environment and are guided along short, curved paths. At certain points they are asked to stop and indicate their initial heading orientation and the location of an object, providing information about distance and orientation coding. During the task participants have access to multisensory self‐motion cues (visual, vestibular and proprioceptive), all of which are pivotal for supporting grid cell function. Additionally, participants will be screened for presence of objective cognitive impairments and will undergo an assessment of their visuospatial working memory and balance.ResultWe will compare if SCD patients perform worse than healthy older controls in the general PI performance measures (e.g., PI error, response time). Furthermore, we will apply a recently developed computational model to identify multiple sources of PI error. This approach allows for a very nuanced characterization of PI deficits, and, as a result, provides additional, potentially even more sensitive markers of very early AD compared to typical PI performance measures.ConclusionThe results will be discussed with reference to the utility of immersive virtual PI as a sensitive biomarker for early, preclinical, AD manifestation.

Neural coding of 3D spatial location, orientation, and action selection in echolocating bats

Echolocating bats are among the only mammals capable of powered flight, and they rely on active sensing to find food and steer around obstacles in 3D environments. These natural behaviors depend on neural circuits that support 3D auditory localization, audio-motor integration, navigation, and flight control, which are modulated by spatial attention and action selection.

A Distributed Model of Face and Body Integration.

Separated face- and body-responsive brain networks have been identified that show strong responses when observers view faces and bodies. It has been proposed that face and body processing may be initially separated in the lateral occipitotemporal cortex and then combined into a whole person representation in the anterior temporal cortex, or elsewhere in the brain. However, in contrast to this proposal, our recent study identified a common coding of face and body orientation (ie, facing direction) in the lateral occipitotemporal cortex, demonstrating an integration of face and body information at an early stage of face and body processing. These results, in combination with findings that show integration of face and body identity in the lateral occipitotemporal, parahippocampal and superior parietal cortex, and face and body emotional expression in the posterior superior temporal sulcus and medial prefrontal cortex, suggest that face and body integration may be more distributed than previously considered. I propose a new model of face and body integration, where areas at the intersection of face- and body-responsive regions play a role in integrating specific properties of faces and bodies, and distributed regions across the brain contribute to high-level, abstract integration of shared face and body properties.

The neural coding of face and body orientation in occipitotemporal cortex

Face and body orientation convey important information for us to understand other people's actions, intentions and social interactions. It has been shown that several occipitotemporal areas respond differently to faces or bodies of different orientations. However, whether face and body orientation are processed by partially overlapping or completely separate brain networks remains unclear, as the neural coding of face and body orientation is often investigated separately. Here, we recorded participants’ brain activity using fMRI while they viewed faces and bodies shown from three different orientations, while attending to either orientation or identity information. Using multivoxel pattern analysis we investigated which brain regions process face and body orientation respectively, and which regions encode both face and body orientation in a stimulus-independent manner. We found that patterns of neural responses evoked by different stimulus orientations in the occipital face area, extrastriate body area, lateral occipital complex and right early visual cortex could generalise across faces and bodies, suggesting a stimulus-independent encoding of person orientation in occipitotemporal cortex. This finding was consistent across functionally defined regions of interest and a whole-brain searchlight approach. The fusiform face area responded to face but not body orientation, suggesting that orientation responses in this area are face-specific. Moreover, neural responses to orientation were remarkably consistent regardless of whether participants attended to the orientation of faces and bodies or not. Together, these results demonstrate that face and body orientation are processed in a partially overlapping brain network, with a stimulus-independent neural code for face and body orientation in occipitotemporal cortex.

Ensemble coding of average length and average orientation are correlated

Viewers can summarize redundant features in groups of objects into an ensemble percept. There appears to be separate mechanisms underlying ensemble perception of low- and high-level visual features, but it is unclear whether ensemble perception of different low-level features is supported by common mechanisms. Yörük and Boduroglu, in Attention, Perception, & Psychophysics 82 (2020) 852–864, investigated whether length and orientation summarization tap common mechanisms by examining the correlation between errors on length- and orientation-averaging tasks and concluded that because they did not find any correlations, the two features are summarized by different, feature-specific mechanisms. However, their study was conducted with a small sample size and included sources of individual performance variance that may have diminished correlations. We report two studies that tested the correlation between performance in the length- and orientation-averaging tasks, with larger samples and modifications that sought to reduce the sources of variance. Study 1 used ensembles that varied in both feature dimensions and Study 2 used ensembles that only varied in the task-relevant dimension. Both studies showed that errors in length- and orientation-averaging are correlated, suggesting that ensemble perception of these low-level features is supported, at least to some extent, by a common ability.

Micro Displacement and Strain Detection for Crack Prediction on Concrete Surface Using Optical Nondestructive Evaluation Methods

Continuous inspection of the concrete structures is important for extending the operating life span of nuclear power plants. Restricted physical accessibility to the nuclear plant structures, due to concerns of radiation, presents a unique challenge to the conventional visual inspection and contact-type nondestructive evaluation (NDE) technologies. Digital image correlation (DIC) is an optical NDE method that can measure the structural parameters such as displacement and strain. However, it is highly challenging to accurately detect micro displacement on the concrete surface because of weathering and change in illumination conditions. Usually, an artificial speckle pattern with good contrast to the object surface is needed for calibration and tracking, but it is difficult to apply in the field. In order to be able to detect micro surface strain for crack prediction in outdoor environment, a DIC-based NDE technology is developed to significantly improve the measurement accuracy by incorporating the orientation code matching (OCM) technique, a robust and accurate template matching algorithm. Concrete specimens were built and tested under four-point bending. Using the remotely measured images, the OCM incorporated DIC method successfully predicted concrete cracks before they emerged on the surface. The experiments also demonstrated the robustness of the method against the optical noise including weathering and change in illumination conditions.

Robust defect detection in 2D images printed on 3D micro‐textured surfaces by multiple paired pixel consistency in orientation codes

Defect detection is now an active research area for production quality assurance. Traditional visual inspection systems are developed by human beings, which is a time-consuming, labour-intensive, and highly error-prone process, and are therefore unreliable. To overcome these problems, the authors proposed a new method for detecting defects when printing on a 3D micro-textured surface. They utilise an orientation code as the basis to resist the fluctuations in illumination. Based on the consistency of the pixel pairs, they developed a model called multiple paired pixel consistency to represent the statistical relationship between each pixel pair in defect-free images. Finally, based on this model, they designed a defect detection method. Even with different defect sizes, illumination conditions, noise intensities, and other characteristics, the performance of the proposed algorithm is extremely stable and highly accurate, and the recall, precision, and F-measure in most of the results can reach 0.85,0.93, and 0.9, respectively. In addition, the defect detection rate can reach almost 100%. This demonstrates that the authors' approach can achieve state-of-the-art accuracy in real industrial applications.

Orientation Field Code Hashing: A Novel Method for Fast Palmprint Identification

For a large-scale palmprint identification system, it is necessary to speed up the identification process to reduce the response time and also to have a high rate of identification accuracy. In this paper, we propose a novel hashing-based technique called orientation field code hashing for fast palmprint identification. By investigating hashing-based algorithms, we first propose a double-orientation encoding method to eliminate the instability of orientation codes and make the orientation codes more reasonable. Secondly, we propose a window-based feature measurement for rapid searching of the target. We explore the influence of parameters related to hashing-based palmprint identification. We have carried out a number of experiments on the Hong Kong PolyU large-scale database and the CASIA palmprint database plus a synthetic database. The results show that on the Hong Kong PolyU large-scale database, the proposed method is about 1.5 times faster than the state-of-the-art ones, while achieves the comparable identification accuracy. On the CASIA database plus the synthetic database, the proposed method also achieves a better performance on identification speed.

Deformation measurement of high-speed rotating drone blades based on digital image correlation combined with ring projection transform and orientation codes

Digital image correlation (DIC) is a versatile non-contact optical measurement method, but it still has many shortcomings in theory and application. For example, the traditional DIC method has difficulty obtaining the desired result when the surface of the test object is rotated substantially or the deformation involves large rotation. Some scholars argue that a rotation angle greater than 7° will not work with the DIC algorithm, and this phenomenon is called decorrelation. To solve this problem, this study proposes the rotation-invariant DIC (RI-DIC) method that combines rotation-invariant template matching with traditional DIC. A pre-matching method based on ring projection transform (RPT) and orientation codes (OC) is proposed to provide the initial values for the DIC iteration process. The algorithm consists of three stages. In the first stage, the RPT process is used to convert the 2D template in a circular region into a 1D grey-level signal as a function of radius, and the template matching based on RPT is used to obtain a series of candidate points. The advantages of RPT process are the characterisation of its rotation invariance and the reduction of computational complexity. In the second stage, a fine matching process based on OC is performed on a limited number of candidate points to obtain the integer pixel matching position and the initial value. Finally, the inverse compositional Gauss–Newton (IC-GN) iteration method is used to further calculate the displacement and strain information accurately on the basis of the initial values. The novelty of this paper is to fuse the ring projection transform and orientation codes in machine vision into the traditional DIC algorithm, finally propose the RI-DIC algorithm. By the proposed method, we can measure the strain generated by the centrifugal force of a drone blade rotating at a high speed. Experimental results indicate that the method can accurately measure the surface deformation of a test object at any rotation angle.

Laminar segregation of sensory coding and behavioral readout in macaque V4

Neurons in sensory areas of the neocortex are known to represent information both about sensory stimuli and behavioral state, but how these 2 disparate signals are integrated across cortical layers is poorly understood. To study this issue, we measured the coding of visual stimulus orientation and of behavioral state by neurons within superficial and deep layers of area V4 in monkeys while they covertly attended or prepared eye movements to visual stimuli. We show that whereas single neurons and neuronal populations in the superficial layers conveyed more information about the orientation of visual stimuli than neurons in deep layers, the opposite was true of information about the behavioral relevance of those stimuli. In particular, deep layer neurons encoded greater information about the direction of planned eye movements than superficial neurons. These results suggest a division of labor between cortical layers in the coding of visual input and visually guided behavior.

Unsupervised Temporal Contiguity Experience Does Not Break the Invariance of Orientation Selectivity Across Spatial Frequency.

The images projected onto the retina can vary widely for a single object. Despite these transformations primates can quickly and reliably recognize objects. At the neural level, transformation tolerance in monkey inferotemporal cortex is affected by the temporal contiguity statistics of the visual input. Here we investigated whether temporal contiguity learning also influences the basic feature detectors in lower levels of the visual hierarchy, in particular the independent coding of orientation and spatial frequency (SF) in primary visual cortex. Eight male Long Evans rats were repeatedly exposed to a temporal transition between two gratings that changed in SF and had either the same (control SF) or a different (swap SF) orientation. Electrophysiological evidence showed that the responses of single neurons during this exposure were sensitive to the change in orientation. Nevertheless, the tolerance of orientation selectivity for changes in SF was unaffected by the temporal contiguity manipulation, as observed in 239 single neurons isolated pre-exposure and 234 post-exposure. Temporal contiguity learning did not affect orientation selectivity in V1. The basic filter mechanisms that characterize V1 processing seem unaffected by temporal contiguity manipulations.

A robust 2D-Cochlear transform-based palmprint recognition

In this paper, a noise-robust palmprint recognition system is discussed with a novel feature extraction technique: two-dimensional Cochlear transform (2D-CT) based on the textural analysis of image sample. Orthogonality of 2D-CT is proved which shows the high robustness of the proposed 2D-CT to noise. To validate the proposed feature extraction technique, palmprint recognition has been tested on both left and right palm of IITD database of 230 persons, CASIA palmprint database of 312 persons, polyU palmprint database of 386 persons and achieved high accuracy. The proposed 2D-CT method is compared with discriminative and robust competitive code, double orientation code, competitive coding, ordinal coding, Gabor transform, Gaussian membership-based features, absolute average deviation and mean features. Further, K-nearest neighbor is used to validate the matching stage. The results show superiority of the proposed method over other feature extraction methods.