Subsequent Recognition Performance Research Articles

Непроизвольное запоминание и контекстно- зависимое узнавание лексической информации

Introduction. Two lines of research stand out in the field of context-dependent memory research: context-dependent reproduction and context-dependent recognition. Different environmental contexts influence the productivity of involuntary memory using free playback and recognition techniques. Our study aims to establish the influence of external contexts of involuntary memorization of lexical items on their subsequent recognition performance. Methods. The procedure varied the states of two variables: global context (room view) and local context (background color and localization of the word on the screen). In the first phase, 107 subjects performed a sensorimotor task that involved the identification of a target stimulus with a recognizable characteristic (the letter ‘a’ as part of a word). In the second stage, where contextual conditions varied, subjects were required to recognize previously presented words in a series of new distractor words. The recognition accuracy, the reaction time, and the response confidence were evaluated. Results. It was found that the empirical markers "recognition accuracy" and "reaction time" are uninformative in assessing mnemic productivity. The analysis of the indicator "degree of confidence" showed that regardless of the retention / change of contexts, correct answers are given with greater confidence. Repetition of the local context in the situation of verbal stimuli recognition leads to a decrease in response time and an increase in confidence for words with the recognition feature that was relevant to the goal of the activity during memorization. Changing the global context does not induce a similar effect. Discussion. The main factors on which the recognition of lexical units during their unintentional memorization depends are the local context and the "key feature" (E. Tulving) with which the response was associated during encoding. The study of the role of motor context in mnemic activity may become a perspective in the study of the phenomenology of context-dependent memory.

Children’s affective involvement in early word learning

The current study set out to examine the underlying physiological mechanisms of and the emotional response associated with word learning success in young 3-year-old predominantly white children. In particular, we examined whether children’s physiological arousal following a word learning task predicts their word learning success and whether successful learning in turn predicts children’s subsequent positive emotions. We presented children (n = 50) with a cross-situational word learning task and measured their pupillary arousal following completion of the task, as well as changes to their upper body posture following completion of the task, as indices of children’s emotions following task completion. Children who showed greater physiological arousal following the novel word recognition task (n = 40) showed improved subsequent word recognition performance. We found that children showed more elevated posture after completing a familiar word learning task compared to completing a novel word learning task (n = 33) but results on children’s individual learning success and postural elevation were mixed. We discuss the findings with regards to children’s affective involvement in word learning.

2022 Practice Census Shows Impact of COVID-19 Pandemic on Hair Restoration

Our ability to focus attention on task-relevant information and ignore distractions is reflected by differential enhancement and suppression of neural activity in sensory cortex (i.e., top-down modulation). Such selective, goal-directed modulation of activity may be intimately related to memory, such that the focus of attention biases the likelihood of successfully maintaining relevant information by limiting interference from irrelevant stimuli. Despite recent studies elucidating the mechanistic overlap between attention and memory, the relationship between top-down modulation of visual processing during working memory (WM) encoding, and subsequent recognition performance has not yet been established. Here, we provide neurophysiological evidence in healthy, young adults that top-down modulation of early visual processing (< 200 ms from stimulus onset) is intimately related to subsequent WM performance, such that the likelihood of successfully remembering relevant information is associated with limiting interference from irrelevant stimuli. The consequences of a failure to ignore distractors on recognition performance was replicated for two types of feature-based memory, motion direction and color. Moreover, attention to irrelevant stimuli was reflected neurally during the WM maintenance period as an increased memory load. These results suggest that neural enhancement of relevant information is not the primary determinant of high-level performance, but rather optimal WM performance is dependent on effectively filtering irrelevant information through neural suppression to prevent overloading a limited memory capacity.

The graded novelty encoding task: Novelty gradually improves recognition of visual stimuli under incidental learning conditions

It has been argued that novel compared to familiar stimuli are preferentially encoded into memory. Nevertheless, treating novelty as a categorical variable in experimental research is considered simplistic. We highlight the dimensional aspect of novelty and propose an experimental design that manipulates novelty continuously. We created the Graded Novelty Encoding Task (GNET), in which the difference between stimuli (i.e. novelty) is parametrically manipulated, paving the way for quantitative models of novelty processing. We designed an algorithm which generates visual stimuli by placing colored shapes in a grid. During the familiarization phase of the task, we repeatedly presented five pictures to the participants. In a subsequent incidental learning phase, participants were asked to differentiate between the “familiars” and novel images that varied in the degree of difference to the familiarized pictures (i.e. novelty). Finally, participants completed a surprise recognition memory test, where the novel stimuli from the previous phase were interspersed with distractors with similar difference characteristics. We numerically expressed the differences between the stimuli to compute a dimensional indicator of novelty and assessed whether it predicted recognition memory performance. Based on previous studies showing the beneficial effect of novelty on memory formation, we hypothesized that the more novel a given picture was, the better subsequent recognition performance participants would demonstrate. Our hypothesis was confirmed: recognition performance was higher for more novel stimuli. The GNET captures the continuous nature of novelty, and it may be useful in future studies that examine the behavioral and neurocognitive aspects of novelty processing.

An ROI Extraction Method of Finger Vein Images Based on Large Receptive Field Gradient Operator for Accurate Localization of Joint Cavity.

Region of interest (ROI) extraction is a key step in finger vein recognition preprocessing. The current method takes the finger region in the vein image as the ROI, but this method cannot obtain better recognition accuracy because it only removes the background noise of the image and ignores factors such as the position and shape of the finger. To solve this problem, we limited the ROI to a fixed region between two finger joint cavities, proposed a new large receptive field gradient operator, and designed and implemented a new method for ROI extraction. It uses a large receptive field to search the target, which is similar to human vision, thus solving the problem of difficult ROI localization for images with large gradient areas. Moreover, for external factors such as noise and uneven illumination in the vein image, the interference factors can be eliminated by averaging them to a larger range with a larger size operator to improve the accuracy of the subsequent matching recognition. To verify the effectiveness of the proposed method, we conducted sufficient matching experiments on three public finger vein datasets. On various datasets, our method significantly reduced the identified EER value, with the lowest EER value reaching 0.96%. The experimental results show that the proposed ROI extraction method can effectively eliminate the influence of finger position, finger shape, and other factors on the subsequent recognition performance, accurately locate the finger joint cavity, and effectively improve the recognition performance.

CNN‐based off‐angle iris segmentation and recognition

Accurate segmentation and parameterisation of the iris in eye images still remain a significant challenge for achieving robust iris recognition, especially in off-angle images captured in less constrained environments. While deep learning techniques (i.e. segmentation-based convolutional neural networks (CNNs)) are increasingly being used to address this problem, there is a significant lack of information about the mechanism of the related distortions affecting the performance of these networks and no comprehensive recognition framework is dedicated, in particular, to off-angle iris recognition using such modules. In this work, the general effect of different gaze angles on ocular biometrics is discussed, and the findings are then related to the CNN-based off-angle iris segmentation results and the subsequent recognition performance. An improvement scheme is also introduced to compensate for some segmentation degradations caused by the off-angle distortions, and a new gaze-angle estimation and parameterisation module is further proposed to estimate and re-project (correct) the off-angle iris images back to frontal view. Taking benefit of these, several approaches (pipelines) are formulated to configure an end-to-end framework for the CNN-based off-angle iris segmentation and recognition. Within the framework of these approaches, a series of experiments is carried out to determine whether (i) improving the segmentation outputs and/or correcting the output iris images before or after the segmentation can compensate for some off-angle distortions, (ii) a CNN trained on frontal eye images is capable of detecting and extracting the learnt features on the corrected images, or (iii) the generalisation capability of the network can be improved by training it on iris images of different gaze angles. Finally, the recognition performance of the selected approach is compared against some state-of-the-art off-angle iris recognition algorithms.

Long term fMRI adaptation depends on adapter response in face-selective cortex

Repetition suppression (RS) reflects a neural attenuation during repeated stimulation. We used fMRI and the subsequent memory paradigm to test the predictive coding hypothesis for RS during visual memory processing by investigating the interaction between RS and differences due to memory in category-selective cortex (FFA, pSTS, PPA, and RSC). Fifty-six participants encoded face and house stimuli twice, followed by an immediate and delayed (48 h) recognition memory assessment. Linear Mixed Model analyses with repetition, subsequent recognition performance, and their interaction as fixed effects revealed that absolute RS during encoding interacts with probability of future remembrance in face-selective cortex. This effect was not observed for relative RS, i.e. when controlled for adapter-response. The findings also reveal an association between adapter response and RS, both for short and long term (48h) intervals, after controlling for the mathematical dependence between both measures. These combined findings are challenging for predictive coding models of visual memory and are more compatible with adapter-related and familiarity accounts.

Improving SAR Target Recognition Performance Using Multiple Preprocessing Techniques.

The synthetic aperture radar (SAR) image preprocessing techniques and their impact on target recognition performance are researched. The performance of SAR target recognition is improved by composing a variety of preprocessing techniques. The preprocessing techniques achieve the effects of suppressing background redundancy and enhancing target characteristics by processing the size and gray distribution of the original SAR image, thereby improving the subsequent target recognition performance. In this study, image cropping, target segmentation, and image enhancement algorithms are used to preprocess the original SAR image, and the target recognition performance is effectively improved by combining the above three preprocessing techniques. On the basis of image enhancement, the monogenic signal is used for feature extraction and then the sparse representation-based classification (SRC) is used to complete the decision. The experiments are conveyed on the moving and stationary target acquisition and recognition (MSTAR) dataset, and the results prove that the combination of multiple preprocessing techniques can effectively improve the SAR target recognition performance.

Research on a software architecture of speech recognition and detection based on interactive reconstruction model

The natural, fast, stable and reliable interaction between human and machine is the ideal interaction mode pursued by human beings. Speech recognition is a process of pattern matching recognition. Effective speech detection technology can not only reduce the processing time of the system, improve the real-time and accuracy of the system processing, but also eliminate the noise interference of the silent segment, so as to improve the subsequent recognition performance. Through speech recognition, the machine can understand human language, complete the corresponding calculation tasks according to these instructions, and meet the needs of people. The traditional speech recognition method uses acoustic features to describe the model. No matter using model compensation method or normalization method, it can not solve the influence of speaker difference on the performance of recognition system. In this paper, we study a speech recognition detection system based on almost interactive reconstruction model, and analyze the continuous speech signal. The experimental results show that the proposed method has a high recognition rate and a shorter time. Compared with the state-of-the-art methodologies, the proposed model can achieve the better performance.

Altered modulation of beta band oscillations during memory encoding is predictive of lower subsequent recognition performance in post-traumatic stress disorder.

We studied the relationship between electrophysiological markers of memory encoding, subsequent recognition performance, and severity of PTSD symptoms in service members with combat exposure (n=40, age: 41.2±7.2 years) and various levels of PTSD symptom severity assessed using the PTSD Check List for DSM V version (PCL-5). Brain activity was recorded using magnetoencephalography during a serial presentation of 86 images of outdoor scenes that were studied by participants for an upcoming recognition test. In a second session, the original images were shown intermixed with an equal number of novel images while participants performed the recognition task. Participants recognized 76.0%±12.1% of the original images and correctly categorized as novel 89.9%±7.0% of the novel images. A negative correlation was present between PCL-5 scores and discrimination performance (Spearman rs=-0.38, p=0.016). PCL-5 scores were also negatively correlated with the recognition accuracy for original images (rs=-0.37, p=0.02). Increases in theta and gamma power and decreases in alpha and beta power were observed over distributed brain networks during memory encoding. Higher PCL-5 scores were associated with less suppression of beta band power in bilateral ventral and medial temporal regions and in the left orbitofrontal cortex. These regions also showed positive correlations between the magnitude of suppression of beta power during encoding and subsequent recognition accuracy. These findings indicate that the lower recognition performance in participants with greater PTSD symptom severity may be due in part to ineffective encoding reflected in altered modulation of beta band oscillatory activity.

Mechanisms underlying the production effect for singing.

The production effect is defined as better memory for items that were read aloud compared with items that were read silently. Quinlan and Taylor (2013) expanded the findings of the production effect by demonstrating that singing items produces even better recognition performance than reading aloud, and argued that this was due to enhanced relative distinctiveness. The current study tested three alternative accounts. In Experiment 1, we explored whether singing results in a larger production effect because it is deemed more bizarre than reading aloud. To address this, we tested a sample for whom singing does not seem bizarre: experienced singers. They also showed better recognition of items that were sung compared with those that were read aloud. In Experiment 2, we determined that singing appears to take longer than either reading aloud or reading silently; however, the possible effect of production time was further explored in Experiment 3. We did this by instructing participants to sing quickly, read aloud slowly, or read silently. Altering relative production times resulted in no discernible changes in subsequent recognition performance. Finally, in Experiment 4, we explored whether singing might strengthen the memory trace relative to reading aloud. We tested this by manipulating the production instruction between subjects. This eliminated the recognition advantage for both reading items aloud as well as for singing them aloud. Having ruled out these alternatives, we argue that singing improves subsequent recognition because it offers more distinctive elements than either reading aloud or reading silently. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Voices to remember: Comparing neural signatures of intentional and non-intentional voice learning and recognition

Recent electrophysiological evidence suggests a rapid acquisition of novel speaker representations during intentional voice learning. We investigated effects of learning intention on voice recognition, using a variant of the directed forgetting paradigm. In an old/new recognition task following voice learning, we compared performance and event-related brain potentials (ERPs) for studied voices, half of which had been prompted to be remembered (TBR) or forgotten (TBF). Furthermore, to assess incidental encoding of episodic information, participants indicated for each recognized test voice the ear of presentation during study. During study, TBR voices elicited more positive ERPs than TBF voices (from ∼250 ms), possibly reflecting deeper voice encoding. In parallel, subsequent recognition performance was higher for TBR than for TBF voices. Importantly, above-chance recognition for both learning conditions nevertheless suggested a degree of non-intentional voice learning. In a surprise episodic memory test for voice location, above-chance performance was observed for TBR voices only, suggesting that episodic memory for ear of presentation depended on intentional voice encoding. At test, a left posterior ERP OLD/NEW effect for both TBR and TBF voices (from ∼500 ms) reflected recognition of studied voices under both encoding conditions. By contrast, a right frontal ERP OLD/NEW effect for TBF voices only (from ∼800 ms) possibly reflected additional elaborative retrieval processes. Overall, we show that ERPs are sensitive 1) to strategic voice encoding during study (from ∼250 ms), and 2) to voice recognition at test (from ∼500 ms), with the specific pattern of ERP OLD/NEW effects partly depending on previous encoding intention.

It doesn't matter what you say: FMRI correlates of voice learning and recognition independent of speech content

Listeners can recognize newly learned voices from previously unheard utterances, suggesting the acquisition of high-level speech-invariant voice representations during learning. Using functional magnetic resonance imaging (fMRI) we investigated the anatomical basis underlying the acquisition of voice representations for unfamiliar speakers independent of speech, and their subsequent recognition among novel voices. Specifically, listeners studied voices of unfamiliar speakers uttering short sentences and subsequently classified studied and novel voices as “old” or “new” in a recognition test. To investigate “pure” voice learning, i.e., independent of sentence meaning, we presented German sentence stimuli to non-German speaking listeners. To disentangle stimulus-invariant and stimulus-dependent learning, during the test phase we contrasted a “same sentence” condition in which listeners heard speakers repeating the sentences from the preceding study phase, with a “different sentence” condition. Voice recognition performance was above chance in both conditions although, as expected, performance was higher for same than for different sentences. During study phases activity in the left inferior frontal gyrus (IFG) was related to subsequent voice recognition performance and same versus different sentence condition, suggesting an involvement of the left IFG in the interactive processing of speaker and speech information during learning. Importantly, at test reduced activation for voices correctly classified as “old” compared to “new” emerged in a network of brain areas including temporal voice areas (TVAs) of the right posterior superior temporal gyrus (pSTG), as well as the right inferior/middle frontal gyrus (IFG/MFG), the right medial frontal gyrus, and the left caudate. This effect of voice novelty did not interact with sentence condition, suggesting a role of temporal voice-selective areas and extra-temporal areas in the explicit recognition of learned voice identity, independent of speech content.

Hippocampal structure predicts cortical indices of reactivation of related items

One of the key components of relational memory is the ability to bind together the constituent elements of a memory experience, and this ability is thought to be supported by the hippocampus. Previously we had shown that these relational bindings can be used to reactivate the cortical processors of an absent item in the presence of a relationally bound associate (Walker et al., 2014). Specifically, we recorded the event-related optical signal (EROS) when presenting the scene of a face-scene pair during a preview period immediately preceding a test display, and demonstrated reactivation of a face-processing cortical area (the superior temporal sulcus, STS) for scenes that had been previously paired with faces, relative to scenes that had not. Here we combined the EROS measures during the same preview paradigm with anatomical estimates of hippocampal integrity (structural MRI measures of hippocampal volume and diffusion tensor imaging measures of mean fractional anisotropy and diffusivity) to provide evidence that the hippocampus is mediating this reactivation phenomenon. The study was run in a sample of older adults aged 55–87, taking advantage of the high amount of hippocampal variability present in aging. We replicated the functional reactivation of STS during the preview period, specific to scenes previously paired with faces. Crucially, we also found that this phenomenon is correlated with structural hippocampus integrity. Both STS reactivation and hippocampal structure predicted subsequent recognition performance. These data support the theory that relational memory is sustained by an interaction between hippocampal and cortical sensory processing regions, and that these functions may be at the basis of episodic memory changes in normal aging.

Prestimulus default mode activity influences depth of processing and recognition in an emotional memory task.

Low self-referential thoughts are associated with better concentration, which leads to deeper encoding and increases learning and subsequent retrieval. There is evidence that being engaged in externally rather than internally focused tasks is related to low neural activity in the default mode network (DMN) promoting open mind and the deep elaboration of new information. Thus, reduced DMN activity should lead to enhanced concentration, comprehensive stimulus evaluation including emotional categorization, deeper stimulus processing, and better long-term retention over one whole week. In this fMRI study, we investigated brain activation preceding and during incidental encoding of emotional pictures and on subsequent recognition performance. During fMRI, 24 subjects were exposed to 80 pictures of different emotional valence and subsequently asked to complete an online recognition task one week later. Results indicate that neural activity within the medial temporal lobes during encoding predicts subsequent memory performance. Moreover, a low activity of the default mode network preceding incidental encoding leads to slightly better recognition performance independent of the emotional perception of a picture. The findings indicate that the suppression of internally-oriented thoughts leads to a more comprehensive and thorough evaluation of a stimulus and its emotional valence. Reduced activation of the DMN prior to stimulus onset is associated with deeper encoding and enhanced consolidation and retrieval performance even one week later. Even small prestimulus lapses of attention influence consolidation and subsequent recognition performance.

Disentangling Spatial Perception and Spatial Memory in the Hippocampus: A Univariate and Multivariate Pattern Analysis fMRI Study

Although the role of the hippocampus in spatial cognition is well accepted, it is unclear whether its involvement is restricted to the mnemonic domain or also extends to perception. We used fMRI to scan neurologically healthy participants during a scene oddity judgment task that placed no explicit demand on long-term memory. Crucially, a surprise recognition test was administered after scanning so that each trial could be categorized not only according to oddity accuracy but also according to subsequent memory. Univariate analyses showed significant hippocampal activity in association with correct oddity judgment, whereas greater parahippocampal place area (PPA) activity was observed during incorrect oddity trials, both irrespective of subsequent recognition performance. Consistent with this, multivariate pattern analyses revealed that a linear support vector machine was able to distinguish correct from incorrect oddity trials on the basis of activity in voxels within the hippocampus or PPA. Although no significant regions of activity were identified by univariate analyses in association with memory performance, a classifier was able to predict subsequent memory using voxels in either the hippocampus or PPA. Our findings are consistent with the idea that the hippocampus is important for processes beyond long-term declarative memory and that this structure may also play a role in complex spatial perception.

Neural correlates of relational and item-specific encoding during working and long-term memory in schizophrenia

Successful long-term memory (LTM) depends upon effective control of information in working memory (WM), and there is evidence that both WM and LTM are impaired by schizophrenia. This study tests the hypothesis that LTM deficits in schizophrenia may result from impaired control of relational processing in WM due to dorsolateral prefrontal cortex (DLPFC) dysfunction. fMRI was performed on 19 healthy controls and 20 patients with schizophrenia during WM tasks emphasizing relational (reorder trials) versus item-specific (rehearse trials) processing. WM activity was also examined with respect to LTM recognition on a task administered outside the scanner. Receiver operator characteristic analysis assessed familiarity and recollection components of LTM. Patients showed a disproportionate familiarity deficit for reorder versus rehearse trials against a background of generalized LTM impairments. Relational processing during WM led to DLPFC activation in both groups. However, this activation was less focal in patients than in controls, and patients with more severe negative symptoms showed less of a DLPFC increase. fMRI analysis of subsequent recognition performance revealed a group by condition interaction. High LTM for reorder versus rehearse trials was associated with bilateral DLPFC activation in controls, but not in patients who activated the left middle temporal and inferior occipital gyrus. Results indicate that although patients can activate the DLPFC on a structured relational WM task, this activation is less focal and does not translate to high retrieval success, suggesting a disruption in the interaction between WM and LTM processes in schizophrenia.

Prediction of subsequent recognition performance using brain activity in the medial temporal lobe

Application of multivoxel pattern analysis (MVPA) to functional magnetic resonance imaging (fMRI) data enables reconstruction and classification of cognitive status from brain activity. However, previous studies using MVPA have extracted information about cognitive status that is experienced simultaneously with fMRI scanning, but not one that will be observed after the scanning. In this study, by focusing on activity in the medial temporal lobe (MTL), we demonstrate that MVPA on fMRI data is capable of predicting subsequent recognition performance. In this experiment, six runs of fMRI signals were acquired during encoding of phonogram stimuli. In the analysis, using data acquired in runs 1–3, we first conducted MVPA-based voxel-wise search for the clusters in the MTL whose signals contained the most information about subsequent recognition performance. Next, using the fMRI signals acquired in runs 1–3 from the selected clusters, we trained a classifier function in MVPA. Finally, the trained classifier function was applied to fMRI signals acquired in runs 4–6. Consequently, we succeeded in predicting the subsequent recognition performance for stimuli studied in runs 4–6 with significant accuracy. This accurate prediction suggests that MVPA can extract information that is associated not only with concurrent cognitive status, but also with behavior in the near future.

Learning about objects in motion: Better generalization and sensitivity through temporal association

When learning to recognize a new object, the visual system must learn to bind together disparate images of that object. Temporal association is a candidate mechanism for achieving this binding. By linking images that are close in time, invariance to observed appearance transformations can be achieved. This hypothesis has derived psychophysical support from studies showing that frames in a motion sequence can be perceptually bound in such a way as to lead to predictable errors in subsequent recognition performance; temporal neighbors are found to be harder to discriminate, even if they come from two different objects. Here, we demonstrate two distinct effects of temporal association using non-rigid objects. First, in contrast to predictions from previous work, we demonstrate that shape discrimination between images actually improves following temporal association. Second, we measure the extent of image binding over time. Our experimental procedure dispenses with explicit recognition judgments (since these are susceptible to cognitive interference) and instead uses a priming task as an implicit measure of generalization. We find that frames within short temporal windows eventually serve as equally effective priming cues, indicating a linkage of their representations. Taken together, these results suggest that temporal association can simultaneously yield improved discriminability between, as well as an implicit linkage across, frames of a sequence. We demonstrate that this pattern of results can arise from a model of object representation in which temporal association leads to coarse coding across a population of object units.

Delays in neural processing during working memory encoding in normal aging

Declines in neural processing speed have been proposed to underlie a broad range of cognitive deficits in older adults. However, the impact of delays in neural processing during stimulus encoding on working memory (WM) performance is not well understood. In the current study, we assessed the influence of aging on the relationship between neural measures of processing speed and WM performance during a selective delayed-recognition task for color and motion stimuli, while electroencephalography (EEG) was recorded in young and older adults. A latency delay was observed for the selection negativity (SN) and alpha band activity (measures of attentional allocation) in older adults during WM encoding of both motion and color stimuli, with the latency and magnitude of the SN predicting subsequent recognition performance. Furthermore, an age-related delay in the N1 latency occurred specifically during the encoding of color stimuli. These results suggest that the presence of both generalized feature-based and feature-specific deficits in the speed of selective encoding of information contributes to WM performance deficits in older adults.