scholarly journals Semantic scene-object consistency modulates N300/400 EEG components, but does not automatically facilitate object representations

2021 ◽  
Author(s):  
Lixiang Chen ◽  
Radoslaw Martin Cichy ◽  
Daniel Kaiser
Keyword(s):  
Object Perception ◽  
Object Representations ◽  
Natural Vision ◽  
Index Changes ◽  
Eeg Recordings ◽  
Semantic Scene ◽  
Task Irrelevant ◽  
Inconsistent Objects ◽  
Scene Object

AbstractDuring natural vision, objects rarely appear in isolation, but often within a semantically related scene context. Previous studies reported that semantic consistency between objects and scenes facilitates object perception, and that scene-object consistency is reflected in changes in the N300 and N400 components in EEG recordings. Here, we investigate whether these N300/N400 differences are indicative of changes in the cortical representation of objects. In two experiments, we recorded EEG signals while participants viewed semantically consistent or inconsistent objects within a scene; in Experiment 1, these objects were task-irrelevant, while in Experiment 2, they were directly relevant for behavior. In both experiments, we found reliable and comparable N300/400 differences between consistent and inconsistent scene-object combinations. To probe the quality of object representations, we performed multivariate classification analyses, in which we decoded the category of the objects contained in the scene. In Experiment 1, in which the objects were not task-relevant, object category could be decoded from around 100 ms after the object presentation, but no difference in decoding performance was found between consistent and inconsistent objects. By contrast, when the objects were task-relevant in Experiment 2, we found enhanced decoding of semantically consistent, compared to semantically inconsistent, objects. These results show that differences in N300/N400 components related to scene-object consistency do not index changes in cortical object representations, but rather reflect a generic marker of semantic violations. Further, our findings suggest that facilitatory effects between objects and scenes are task-dependent rather than automatic.

scholarly journals The steady-state visual evoked potential (SSVEP) reflects the activation of cortical object representations: evidence from semantic stimulus repetition

2020 ◽  
Author(s):  
Elise L. Radtke ◽  
Ulla Martens ◽  
Thomas Gruber
Keyword(s):  
Steady State ◽  
Object Representation ◽  
Sensory Information ◽  
Familiar Object ◽  
Object Representations ◽  
Stimulus Repetition ◽  
Experimental Conditions ◽  
Repetition Suppression ◽  
Task Irrelevant ◽  
Visual Evoked

AbstractWe applied high-density EEG to examine steady-state visual evoked potentials (SSVEPs) during a perceptual/semantic stimulus repetition design. SSVEPs are evoked oscillatory cortical responses at the same frequency as visual stimuli flickered at this frequency. In repetition designs, stimuli are presented twice with the repetition being task irrelevant. The cortical processing of the second stimulus is commonly characterized by decreased neuronal activity (repetition suppression). The behavioral consequences of stimulus repetition were examined in a companion reaction time pre-study using the same experimental design as the EEG study. During the first presentation of a stimulus, we confronted participants with drawings of familiar object images or object words, respectively. The second stimulus was either a repetition of the same object image (perceptual repetition; PR) or an image depicting the word presented during the first presentation (semantic repetition; SR)—all flickered at 15 Hz to elicit SSVEPs. The behavioral study revealed priming effects in both experimental conditions (PR and SR). In the EEG, PR was associated with repetition suppression of SSVEP amplitudes at left occipital and repetition enhancement at left temporal electrodes. In contrast, SR was associated with SSVEP suppression at left occipital and central electrodes originating in bilateral postcentral and occipital gyri, right middle frontal and right temporal gyrus. The conclusion of the presented study is twofold. First, SSVEP amplitudes do not only index perceptual aspects of incoming sensory information but also semantic aspects of cortical object representation. Second, our electrophysiological findings can be interpreted as neuronal underpinnings of perceptual and semantic priming.

An Ego-Psychological Approach to the Rorschach

1995 ◽  
Vol 77 (3) ◽  
pp. 911-930
Author(s):  
George Frank
Keyword(s):  
Object Relations ◽  
Psychological Assessment ◽  
Comprehensive Assessment ◽  
Point Of View ◽  
Object Representations ◽  
Psychological Approach ◽  
Contemporary View ◽  
Present Purpose ◽  
Ego Psychology

This presentation is an extension and amplification of the ego-psychological assessment of Rorschach data initiated in 1946 by Rapaport, Gill, and Schafer whose focus was on the quality of the perception of reality and the assessment of defence. A more contemporary view of ego psychology not only includes an expanded view of defence but also of the nature of self- and object representations and the nature of object relations. An assessment of the synthesizing function of the ego was also discussed. The present purpose was to present a comprehensive assessment of Rorschach data from the point of view of contemporary ego psychology.

EARLY PREDICTION OF MEDICATION REFRACTORINESS IN CHILDREN WITH IDIOPATHIC EPILEPSY BASED ON SCALP EEG ANALYSIS

2014 ◽  
Vol 24 (07) ◽  
pp. 1450023 ◽  
Author(s):  
LUNG-CHANG LIN ◽  
CHEN-SEN OUYANG ◽  
CHING-TAI CHIANG ◽  
REI-CHENG YANG ◽  
RONG-CHING WU ◽  
...  
Keyword(s):  
Refractory Epilepsy ◽  
Recall Rate ◽  
Idiopathic Epilepsy ◽  
Spectral Edge Frequency ◽  
Scalp Eeg ◽  
Feature Descriptors ◽  
Antiepileptic Drug Treatment ◽  
Eeg Recordings ◽  
Precision Rate

Refractory epilepsy often has deleterious effects on an individual's health and quality of life. Early identification of patients whose seizures are refractory to antiepileptic drugs is important in considering the use of alternative treatments. Although idiopathic epilepsy is regarded as having a significantly lower risk factor of developing refractory epilepsy, still a subset of patients with idiopathic epilepsy might be refractory to medical treatment. In this study, we developed an effective method to predict the refractoriness of idiopathic epilepsy. Sixteen EEG segments from 12 well-controlled patients and 14 EEG segments from 11 refractory patients were analyzed at the time of first EEG recordings before antiepileptic drug treatment. Ten crucial EEG feature descriptors were selected for classification. Three of 10 were related to decorrelation time, and four of 10 were related to relative power of delta/gamma. There were significantly higher values in these seven feature descriptors in the well-controlled group as compared to the refractory group. On the contrary, the remaining three feature descriptors related to spectral edge frequency, kurtosis, and energy of wavelet coefficients demonstrated significantly lower values in the well-controlled group as compared to the refractory group. The analyses yielded a weighted precision rate of 94.2%, and a 93.3% recall rate. Therefore, the developed method is a useful tool in identifying the possibility of developing refractory epilepsy in patients with idiopathic epilepsy.

Parametric Description of EEG Profiles for Assessment of Sleep Architecture in Disorders of Consciousness

2019 ◽  
Vol 29 (03) ◽  
pp. 1850049 ◽  
Author(s):  
Magdalena Zieleniewska ◽  
Anna Duszyk ◽  
Piotr Różański ◽  
Marcin Pietrzak ◽  
Marta Bogotko ◽  
...  
Keyword(s):  
Matching Pursuit ◽  
Disorders Of Consciousness ◽  
Sleep Architecture ◽  
Quality Of Sleep ◽  
Software Environment ◽  
Continuous Description ◽  
Matching Pursuit Decomposition ◽  
Parametric Description ◽  
Eeg Recordings

We propose a fully parametric approach to the assessment of sleep architecture, based upon the classical electroencephalographic criteria, applicable also to the recordings of patients with disorders of consciousness (DOC). Sleep spindles and slow waves are automatically detected from the matching pursuit decomposition of overnight EEG recordings. Their evolution can be presented in the form of EEG profiles, yielding a continuous description of sleep architecture, compatible with the classical criteria used in sleep staging. We propose assessment of these EEG profiles by five parameters, which can be combined by a linear classifier, assessing the quality of sleep architecture. Proposed methodology is evaluated on 59 overnight EEG recordings from 19 patients from a hospital for children with severe brain damage, in relation to their behavioral diagnosis according to the Coma Recovery Scale-Revised. Presented results indicate robustness of the proposed approach, which may serve as a valuable aid in diagnosis of DOC patients. Complete software environment for computing and presentation of EEG profiles is freely available from http://svarog.pl .

scholarly journals Knowledge-driven perceptual organization reshapes information sampling via eye movements

2021 ◽  
Author(s):  
Marek A. Pedziwiatr ◽  
Elisabeth von dem Hagen ◽  
Christoph Teufel
Keyword(s):  
Eye Movements ◽  
Feature Space ◽  
Object Perception ◽  
Visual Features ◽  
Object Representations ◽  
Object Knowledge ◽  
Recent Developments ◽  
Gaze Behaviour ◽  
Information Sampling ◽  
High Level

Humans constantly move their eyes to explore the environment and obtain information. Competing theories of gaze guidance consider the factors driving eye movements within a dichotomy between low-level visual features and high-level object representations. However, recent developments in object perception indicate a complex and intricate relationship between features and objects. Specifically, image-independent object-knowledge can generate objecthood by dynamically reconfiguring how feature space is carved up by the visual system. Here, we adopt this emerging perspective of object perception, moving away from the simplifying dichotomy between features and objects in explanations of gaze guidance. We recorded eye movements in response to stimuli that appear as meaningless patches on initial viewing but are experienced as coherent objects once relevant object-knowledge has been acquired. We demonstrate that gaze guidance differs substantially depending on whether observers experienced the same stimuli as meaningless patches or organised them into object representations. In particular, fixations on identical images became object-centred, less dispersed, and more consistent across observers once exposed to relevant prior object-knowledge. Observers' gaze behaviour also indicated a shift from exploratory information-sampling to a strategy of extracting information mainly from selected, object-related image areas. These effects were evident from the first fixations on the image. Importantly, however, eye-movements were not fully determined by object representations but were best explained by a simple model that integrates image-computable features and high-level, knowledge-dependent object representations. Overall, the results show how information sampling via eye-movements in humans is guided by a dynamic interaction between image-computable features and knowledge-driven perceptual organisation.

The Effect of Memory Schemas on Object Recognition in Virtual Environments

2005 ◽  
Vol 14 (5) ◽  
pp. 606-615 ◽  
Author(s):  
Katerina Mania ◽  
Andrew Robinson ◽  
Karen R. Brandt
Keyword(s):  
Object Recognition ◽  
Computer Graphics ◽  
Scene Perception ◽  
Recognition Task ◽  
Theoretical Work ◽  
Head Tracking ◽  
Head Mounted Display ◽  
Inconsistent Objects ◽  
Memory Recognition

Prior theoretical work on memory schemas, an influential concept of memory from the field of cognitive psychology, is presented for application to fidelity of computer graphics simulations. The basic assumption is that an individual's prior experience will influence how he or she perceives, comprehends, and remembers new information in a scene. Schemas are knowledge structures; a scene could incorporate objects that fit into a specific context or schema (e.g., an academic's office) referred to as consistent objects. A scene could also include objects that are not related to the schema in place referred to as inconsistent objects. In this paper, we describe ongoing development of a rendering framework related to scene perception based on schemas. An experiment was carried out to explore the effect of object type and rendering quality on object memory recognition in a room. The computer graphics simulation was displayed on a Head Mounted Display (HMD) utilizing stereo imagery and head tracking. Thirty-six participants across three conditions of varied rendering quality of the same space were exposed to the computer graphics environment and completed a memory recognition task. Results revealed that schema consistent elements of the scene were more likely to be recognized than inconsistent information. Overall higher confidence ratings were assigned for consistent objects compared to inconsistent ones. Total object recognition was better for the mid-quality condition compared to the low-quality one. The presence of shadow information, though, did not affect recognition of either consistent or inconsistent objects. Further explorations of the effect of schemas on spatial awareness in synthetic worlds could lead to identifying areas of a computer graphics scene that require better quality of rendering as well as areas for which lower fidelity could be sufficient. The ultimate goal of this work is to simulate a perceptual process rather than to simulate physics.

scholarly journals The Efficacy of Single-Trial Multisensory Memories

2013 ◽  
Vol 26 (5) ◽  
pp. 483-502 ◽  
Author(s):  
Antonia Thelen ◽  
Micah M. Murray
Keyword(s):  
Object Recognition ◽  
Brain Activity ◽  
Memory Performance ◽  
Stimulus Onset ◽  
Object Representations ◽  
Single Trial ◽  
Multisensory Interactions ◽  
Early Processing ◽  
Opposing Effects ◽  
Task Irrelevant

This review article summarizes evidence that multisensory experiences at one point in time have long-lasting effects on subsequent unisensory visual and auditory object recognition. The efficacy of single-trial exposure to task-irrelevant multisensory events is its ability to modulate memory performance and brain activity to unisensory components of these events presented later in time. Object recognition (either visual or auditory) is enhanced if the initial multisensory experience had been semantically congruent and can be impaired if this multisensory pairing was either semantically incongruent or entailed meaningless information in the task-irrelevant modality, when compared to objects encountered exclusively in a unisensory context. Processes active during encoding cannot straightforwardly explain these effects; performance on all initial presentations was indistinguishable despite leading to opposing effects with stimulus repetitions. Brain responses to unisensory stimulus repetitions differ during early processing stages (∼100 ms post-stimulus onset) according to whether or not they had been initially paired in a multisensory context. Plus, the network exhibiting differential responses varies according to whether or not memory performance is enhanced or impaired. The collective findings we review indicate that multisensory associations formedviasingle-trial learning exert influences on later unisensory processing to promote distinct object representations that manifest as differentiable brain networks whose activity is correlated with memory performance. These influences occur incidentally, despite many intervening stimuli, and are distinguishable from the encoding/learning processes during the formation of the multisensory associations. The consequences of multisensory interactions thus persist over time to impact memory retrieval and object discrimination.

From Geons to Structure. A Note on Object Representation

Perception ◽  
1994 ◽  
Vol 23 (5) ◽  
pp. 505-515 ◽  
Author(s):  
Emanuel Leeuwenberg ◽  
Peter Van der Helm ◽  
Rob Van Lier
Keyword(s):  
Information Theory ◽  
Object Representation ◽  
Structural Information ◽  
Object Classification ◽  
Object Perception ◽  
Complex Object ◽  
Object Representations ◽  
Perceptual Process

Two models of object perception are compared: recognition by components (RBC), proposed by Biederman, and structural information theory (SIT), initially proposed by Leeuwenberg. According to RBC a complex object is decomposed into predefined elementary objects, called geons. According to SIT, the decomposition is guided by regularities in the object. It is assumed that the simplest of all possible interpretations of any object is perceptually preferred. The comparison deals with two aspects of the models. One is the representation of simple objects—various definitions of object axes are considered. It is shown that the more these definitions account for object regularity and thus the more they agree with SIT, the better the object representations predict object classification. Another topic concerns assumptions underlying the models: the identification of geons is mediated by cues which are supposed to be invariant under varying viewpoints of objects. It is argued that such cues are not based on this invariance but on the regularity of actual objects. The latter conclusion is in line with SIT. An advantage of RBC, however, is that it deals with the perceptual process from stimulus to interpretation, whereas SIT merely concerns the outcome of the process, not the process itself.

scholarly journals Automated Inter-Ictal Epileptiform Discharge Detection from Routine EEG

2021 ◽  
Author(s):  
Duong Nhu ◽  
Mubeen Janmohamed ◽  
Lubna Shakhatreh ◽  
Ofer Gonen ◽  
Patrick Kwan ◽  
...  
Keyword(s):  
Royal Melbourne Hospital ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Model Variant ◽  
Eeg Recordings ◽  
Generalized Epilepsy ◽  
Electroencephalogram Eeg ◽  
Health Hospital ◽  
Epilepsy Monitoring

Epilepsy is the most common neurological disorder. The diagnosis commonly requires manual visual electroencephalogram (EEG) analysis which is time-consuming. Deep learning has shown promising performance in detecting interictal epileptiform discharges (IED) and may improve the quality of epilepsy monitoring. However, most of the datasets in the literature are small (n≤100) and collected from single clinical centre, limiting the generalization across different devices and settings. To better automate IED detection, we cross-evaluated a Resnet architecture on 2 sets of routine EEG recordings from patients with idiopathic generalized epilepsy collected at the Alfred Health Hospital and Royal Melbourne Hospital (RMH). We split these EEG recordings into 2s windows with or without IED and evaluated different model variants in terms of how well they classified these windows. The results from our experiment showed that the architecture generalized well across different datasets with an AUC score of 0.894 (95% CI, 0.881–0.907) when trained on Alfred’s dataset and tested on RMH’s dataset, and 0.857 (95% CI, 0.847–0.867) vice versa. In addition, we compared our best model variant with Persyst and observed that the model was comparable.

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