False Recognition Rate Research Articles

Increased phantom recollection after sleep.

Sleep is known to benefit memory consolidation, but its effect on false memory is less clear. We applied the simplified conjoint recognition paradigm to investigate how sleep affects the cognitive processes behind correct or false recognition, according to fuzzy-trace theory, and measured the retrieval of verbatim traces, retrieval of gist traces, and phantom recollection. Participants studied 24 lists of semantically related words lacking the strongest common associate or theme word. Recognition was tested 12 h later, following either a night's sleep or daytime wakefulness. The recognition test featured studied words, nonstudied theme words (false recognition), and unrelated words. False recognition rate was higher after sleep than after daytime wakefulness. True recognition rate was the same. Analysis of the cognitive processes underlying recognition showed that phantom recollection was higher after sleep. Assuming that phantom recollection reflects the retrieval of strong gist traces, sleep may strengthen gist traces and promote gist extraction.

Electrophysiological evidence for the effects of emotional content on false recognition memory

Two competing hypotheses attempt to explain the effects of emotional content on the production of false memory. The conceptual relatedness account posits that negative emotion increases false memory by strengthening familiarity process, whereas the distinctiveness heuristic account postulates that negative emotion reduces false memory by influencing recollection process. Here, using the categorized pictures paradigm, we examined these hypotheses by investigating emotional influences on false recognition memory performance and the event-related potential (ERP) correlates of familiarity and recollection. Participants were presented with positive, neutral, or negative pictures from various categories during encoding and later completed a recognition test while electroencephalogram data were recorded. Behavioral results revealed lower corrected false recognition rates for negative and neutral pictures than for positive ones, with no significant difference between negative and neutral pictures. In addition, negative pictures were associated with a more conservative response bias in comparison with neutral and positive pictures. Importantly, ERP results revealed enhanced recollection-related parietal old/new effects for negative pictures relative to positive and neutral pictures, but comparable familiarity-related early frontal old/new effects across each type of emotional valence category during both true and false recognition. Our results suggest that emotionally negative content may affect production of false memory mainly by engaging a distinctiveness heuristic. Methodological implications of these findings are discussed.

Item-specific processing reduces false recognition in older and younger adults: Separating encoding and retrieval using signal detection and the diffusion model.

Our study examined processing effects in improving memory accuracy in older and younger adults. Specifically, we evaluated the effectiveness of item-specific and relational processing instructions relative to a read-only control task on correct and false recognition in younger and older adults using a categorized-list paradigm. In both age groups, item-specific and relational processing improved correct recognition versus a read-only control task, and item-specific encoding decreased false recognition relative to both the relational and read-only groups. This pattern was found in older adults despite overall elevated rates of false recognition. We then applied signal-detection and diffusion-modeling analyses, which separately utilized recognition responses and the latencies to those responses to estimate contributions of encoding and monitoring processes on recognition decisions. Converging evidence from both analyses demonstrated that item-specific processing benefits to memory accuracy were due to improvements of both encoding (estimates of d' and drift rate) and monitoring (estimates of lambda and boundary separation) processes, and, importantly, occurred similarly in both younger and older adults. Thus, older and younger adults showed similar encoding-based and test-based benefits of item-specific processing to enhance memory accuracy.

Experimental Effects of Acute Exercise on Prospective Memory and False Memory.

Research demonstrates that acute exercise can enhance retrospective episodic memory performance. However, limited research has examined the effects of acute exercise on prospective memory, and no studies have examined the effects of exercise on false memory performance. This study examined the potential effects of acute exercise on prospective memory and false memory performance. A between-group randomized controlled trial was employed, with participants (college students; Mage = 20 years) randomized into an exercise group (15-minute acute bout of treadmill walking; N = 25) or a control group (15 minutes of sitting; N = 26). Prospective memory was assessed from two laboratory and two naturalistic assessments outside the lab. False memory was assessed using a word-list trial. There were no statistically significant differences in prospective memory based on group allocation (FGroup×Time = 1.17; P = 0.32; η2 = 0.06). However, the control group recalled more false words and had a higher rate of false memory recognition (FGroup×Time = 3.15; P = 0.01; η2 = 0.26). These findings indicate that acute moderate-intensity aerobic exercise is not associated with prospective memory performance but provides some suggestive evidence that acute exercise may reduce the rate of false memories.

Research on Signature Verification Method Based on Discrete Fréchet Distance

This paper proposes a multi-feature signature template based on discrete Fréchet distance, which breaks through the limitation of traditional signature authentication using a single signature feature. It solves the online handwritten signature authentication signature global feature template extraction calculation workload, signature feature selection unreasonable problem. In this experiment, the false recognition rate (FAR) and false rejection rate (FRR) of the statistical signature are calculated and the average equal error rate (AEER) is calculated. The feasibility of the combined template scheme is verified by comparing the average equal error rate of the combination template and the original template.

A closer look at children’s metacognitive skills: The case of the distinctiveness heuristic

The primary aim of this study was to document the developmental course of distinctiveness effects throughout childhood. Specifically, we examined whether the reduction in false recognition rates that is traditionally observed in children after distinctive encoding could be explained not only by enhanced discrimination between studied and new items but also by the implementation of a conservative response criterion resulting from the use of metacognitive expectations about the quality of memories (i.e., distinctiveness heuristic). Two experiments were conducted in which children in three age groups—4–5, 6–7, and 8–9 years—were asked to study a set of items presented in either pictorial (distinctive) or word (less distinctive) form. In Experiment 1, pictures and words were displayed in two separate lists, a design that is supposed to favor reliance on the distinctiveness heuristic. In Experiment 2, the two types of stimuli were presented within the same list, a design that is supposed to make using the metacognitive heuristic ineffective. Overall, Experiments 1 and 2 provide evidence that children as young as 4 years rely on the distinctiveness heuristic to guide their memory decisions, resulting in a reduction in the false recognition rate when items are presented using a pure-list design (Experiment 1) but not when they are presented using a mixed-list design (Experiment 2). The implications of these findings for our understanding of the development of metacognition and the involvement of metacognitive skills in children’s memory performance are discussed.

The role of KIBRA in reconstructive episodic memory

BackgroundIn order to retrieve episodic past events, the missing information needs to be reconstructed using information stored in semantic memory. Failures in these reconstructive processes are expressed as false memories. KIBRA single nucleotide polymorphism (rs17070145) has been linked to episodic memory performance as well as an increased risk of Alzheimer’s disease and post-traumatic stress disorder (PTSD).MethodsHere, the role of KIBRA rs17070145 polymorphism (male and female CC vs. CT/TT carriers) in reconstructive episodic memory in the Deese-Roediger-McDermott (DRM) paradigm was investigated in N = 219 healthy individuals.ResultsFemale participants outperformed males in the free recall condition. Furthermore, a trend towards a gender x genotype interaction was found for false recognition rates. Female CT/TT carriers exhibited a lower proportion of false recognition rates for associated critical lures as compared to male CT/TT. Additionally, an association between KIBRA rs17070145 genotype, familiarity and recollection based recognition performance was found. In trials with correct recognition of listed items CT/TT carriers showed more “remember”, but fewer “know” responses as compared to CC carriers.Discussion and conclusionOur findings suggest that the T-allele of KIBRA rs17070145 supports recollection based episodic memory retrieval and contributes to memory accuracy in a gender dependent manner. Findings are discussed in the context of the specific contribution of KIBRA related SNPs to reconstructive episodic memory and its implications for cognitive and emotional symptoms in dementia and PTSD.

The role of decision criterion in the Deese-Roediger-McDermott (DRM) false recognition memory: False memory falls and rises as a function of restriction on criterion setting.

How much of the Deese-Roediger-McDermott (DRM) false memory is attributable to decision criterion is so far a controversial issue. Previous studies typically used explicit warnings against accepting the critical lure to investigate this issue. The assumption is that if the false memory results from using a liberally biased criterion, it should be greatly reduced or eliminated by an explicit warning against accepting the critical lure. Results showed that warning was generally ineffective. We asked the question of whether subjects can substantially reduce false recognition without being warned when the test forces them to make a distinction between true and false memories. Using a two-alternative forced choice in which criterion plays a relatively smaller role, we showed that subjects could indeed greatly reduce the rate of false recognition. However, when the forced-choice restriction was removed from the two-item choice test, the rate of false recognition rebounded to that of the hit for studied list words, indicating the role of criterion in false recognition.

Declines in representational quality and strategic retrieval processes contribute to age-related increases in false recognition.

In a Yes/No object recognition memory test with similar lures, older adults typically exhibit elevated rates of false recognition. However, the contributions of impaired retrieval, relative to reduced availability of target details, are difficult to disentangle using such a test. The present investigation sought to decouple these factors by comparing performance on a Yes/No (YN) test to that on a Forced Choice (FC) test, which minimizes demands on strategic retrieval processes, enabling a more direct measure of the availability of object details. Older adults exhibited increased lure false recognition across test formats (Experiment 1), suggesting a decline in the availability of object details contributes to deficits in performance. Manipulating interference by varying the number of objects studied selectively enhanced performance in the FC test, resulting in matched performance across groups, whereas age differences in YN performance persisted (Experiment 2), indicating an additional contribution of impaired strategic retrieval. Consistent with differential sensitivity of test format to strategic retrieval and the quality of stimulus representations among older adults, variability in the quality of object representations, measured using a perceptual discrimination task, was selectively related to FC performance. In contrast, variability in memory control processes, as measured with tests of recall and executive function, was related to performance across test formats. These results suggest that both declines in the availability of object details and impaired retrieval of object details contribute to elevated rates of lure false recognition with age, and highlight the utility of test format for dissociating these factors in memory-impaired populations.

Train bogie part recognition with multi-object multi-template matching adaptive algorithm

Automation of train rolling stock monitoring system by recognizing the bogie parts is a process of identifying defects in the train undercarriage moving at >30 Kmph. Recognizing the parts of a moving train using computer vision models based on color and texture with deformable curve segmentation models is a challenging and computationally intensive. A multi object multi-template model is proposed to solve this problem in a computationally less intensive process. A multi object multi template library with 26 objects in 40 bogie frames was created based on statistical parameters of the bogie part in the center of the frame through template extraction model. Fifty templates were designed from 250 frames of the first bogie movement through the camera plane. Maximum normalized cross correlation coefficient calculated on each frame with a 26 – by – 40 template matrices identifies the bogie parts in the frame in a single computation. High speed recording of the train bogies at 240 fps establishes the datasets for experimentation having 2 trains with 20 coaches each capturing 15,000 frames per train. The correct recognition accuracy is 91% with a false recognition rate of 15%.

A new test for exemplar theory: Varying versus non-varying words in Spanish

We used a Deese-Roediger-McDermott false memory paradigm to compare Spanish words in which the phonetic realization of /s/ can vary (word-medial positions: bu[s]to ~ bu[h]to ‘chest’, word-final positions: remo[s] ~ remo[h] ‘oars’) to words in which it cannot (word-initial positions: [s]opa ~ *[h]opa ‘soup’). At study, participants listened to lists of nine words that were phonological neighbors of an unheard critical item (e.g., popa, sepa, soja, etc. for the critical item sopa). At test, participants performed free recall and yes/no recognition tasks. Replicating previous work in this paradigm, results showed robust false memory effects: that is, participants were more likely to (falsely) remember a critical item than a random intrusion. When the realization of /s/ was consistent across conditions (Experiment 1), false memory rates for varying versus non-varying words did not significantly differ. However, when the realization of /s/ varied between [s] and [h] in those positions which allow it (Experiment 2), false recognition rates for varying words like busto were significantly higher than those for non-varying words like sopa. Assuming that higher false memory rates are indicative of greater lexical activation, we interpret these results to support the predictions of exemplar theory, which claims that words with heterogeneous versus homogeneous acoustic realizations should exhibit distinct patterns of activation.

Relation between backward associative strength and false recognition rates for picture lists

Relation between backward associative strength and false recognition rates for picture lists

A 3D Laser Profiling System for Rail Surface Defect Detection.

Rail surface defects such as the abrasion, scratch and peeling often cause damages to the train wheels and rail bearings. An efficient and accurate detection of rail defects is of vital importance for the safety of railway transportation. In the past few decades, automatic rail defect detection has been studied; however, most developed methods use optic-imaging techniques to collect the rail surface data and are still suffering from a high false recognition rate. In this paper, a novel 3D laser profiling system (3D-LPS) is proposed, which integrates a laser scanner, odometer, inertial measurement unit (IMU) and global position system (GPS) to capture the rail surface profile data. For automatic defect detection, first, the deviation between the measured profile and a standard rail model profile is computed for each laser-imaging profile, and the points with large deviations are marked as candidate defect points. Specifically, an adaptive iterative closest point (AICP) algorithm is proposed to register the point sets of the measured profile with the standard rail model profile, and the registration precision is improved to the sub-millimeter level. Second, all of the measured profiles are combined together to form the rail surface through a high-precision positioning process with the IMU, odometer and GPS data. Third, the candidate defect points are merged into candidate defect regions using the K-means clustering. At last, the candidate defect regions are classified by a decision tree classifier. Experimental results demonstrate the effectiveness of the proposed laser-profiling system in rail surface defect detection and classification.

How important is the name in predicting false recognition for lookalike brands?

An underexploited role for psychology in trademark law is the testing of explicit or implicit judicial assumptions about consumer behavior. In this article we examine an assumption that is common across Commonwealth countries, namely, that similar packaging is unlikely to cause consumer confusion provided the brand names are dissimilar. We began by selecting branded products commonly found in supermarkets. For each existing brand we created 2 novel (fictitious) brands with highly similar packaging to the existing brand. One of these lookalike products had a similar name, the other a dissimilar name. Across 2 yes/no and 1 forced-choice experiments using photographs of the real and fictitious products we looked at false recognition rates. Contrary to the judicial assumption participants largely ignored the brand names when making their decisions based on memory. It was only when the pictures of the products were placed side-by-side (in the forced-choice task) that they paid the brand name any significant attention.

Automatic recognition of epileptic discharges based on shape similarity in time-domain

Abstract Background Epilepsy is a common neurological disease, and electroencephalogram (EEG) contains massive epilepsy information. Automatic recognition of epileptic discharges has great significance in diagnosis of epilepsy. New method This paper proposes a novel automatic recognition of epileptic waves method in EEG signals based on shape similarity in time-series sequence directly. Merger of the increasing and decreasing sequences (MIDS) was used to improve the recognition accuracy and reduce the computation cost. Then shape templates were designed, and the modified Hausdorff distance was employed to measure the shape similarity of waveforms in template matching part. This approach imitates human visual cognitive process to analyze EEG and employs image recognition method into one-dimensional signals, which is a direct, original and effective method. Results 373 epileptic discharge fragments marked by clinicians from 20 patients’ EEG recordings were selected. By fusing significance rules, 98.39% of them were recognized, with the false recognition rate 1.1%. Comparison with existing methods Experimental results indicate that the proposed approach yielded better performance for interictal epileptiform discharges (IEDS) recognition compared with the previous methods. Conclusions The proposed approach has good performance and high stability in automatic recognition of epileptic discharges both in ictal and interictal period, which could support the diagnosis of epilepsy greatly.

The impact of aging on associative memory for preexisting unitized associations

ABSTRACTAging is accompanied by a decline in associative memory that can, however, be attenuated when associations are unitized at encoding, that is, when they form an integrated entity. Unitization is thought to promote familiarity-based recognition memory, which is preserved in aging. We examined whether preexperimentally unitized associations (compound words (CWs)) do indeed reduce age differences in memory, and whether preexperimental unitization promotes familiarity. In Experiment 1, we assessed the memory of 20 young and 20 older participants for compound versus unrelated word pairs using a yes/no recognition test with Remember/Know/Guess judgments. In Experiment 2, we tested 20 young and 20 older participants using the same procedure, except for the use of a two-alternative forced-choice recognition paradigm, which is thought to enhance the contribution of familiarity. The results of both experiments corroborated the greater contribution of familiarity to recognition of unitized associations. In Experiment 1, however, the use of CWs did not attenuate the age-related associative decline. We suggest that preexisting knowledge associated with recombined compounds induced high absolute familiarity and illusory recollection, leading to high false-recognition rates for the older adults. By contrast, the two groups performed similarly across both conditions in Experiment 2. Thus, the forced-choice procedure facilitates the use of familiarity in such a way that it improves older adults’ associative memory to the level of young participants. These results suggest that the modulation of associative memory in aging by preexisting unitization varies according to methodological parameters, such as the nature of the lures and the test format.

Numeric Digit Classification Using HOG Feature Space and Multiclass Support Vector Machine Classifier

Pattern recognition is one of the major challenges in statistics framework. Its primary goal is to extract efficient feature and accurately classify the patterns into categories. A well-known and vital application in this field is the handwritten digit classification and recognition where digits have to be assigned into one of the 10 classes using some classification method. There are several approaches for handwritten digits classification and recognition. This paper proposed an efficient image appearance feature based approach which process the acquired digit image using Histogram of Oriented Gradients (HOG). HOG is a very efficient feature descriptor for data discrimination and very stable on illumination variation because it is a gradient based descriptor. For the efficient classification of the HOG features of numeric digits, a linear multiclass Support Vector Machine (SVM) classifier has been proposed, because it has better responses for nonlinear classification cases also. Mixed National Institute of Standards and Technology (MNIST) hand written numeric digit dataset has been used to test the classification accuracy of the proposed numeric digit classification system. For the implementation and testing of proposed system MATLAB 2015 (a) software platform has been used. The proposed system has been evaluated against the Neural Network based classification system. The classification and recognition efficiency of the proposed system and NN classifier based system has been evaluated using True Recognition Efficiency (FRE) and False Recognition Rate (FRR) parameters.

The effects of acute alcohol intoxication on the cognitive mechanisms underlying false facial recognition.

RationaleFalse face recognition rates are sometimes higher when faces are learned while under the influence of alcohol. Alcohol myopia theory (AMT) proposes that acute alcohol intoxication during face learning causes people to attend to only the most salient features of a face, impairing the encoding of less salient facial features. Yet, there is currently no direct evidence to support this claim.ObjectivesOur objective was to test whether acute alcohol intoxication impairs face learning by causing subjects to attend to a salient (i.e., distinctive) facial feature over other facial features, as per AMT.MethodsWe employed a balanced placebo design (N = 100). Subjects in the alcohol group were dosed to achieve a blood alcohol concentration (BAC) of 0.06 %, whereas the no alcohol group consumed tonic water. Alcohol expectancy was controlled. Subjects studied faces with or without a distinctive feature (e.g., scar, piercing). An old-new recognition test followed. Some of the test faces were “old” (i.e., previously studied), and some were “new” (i.e., not previously studied). We varied whether the new test faces had a previously studied distinctive feature versus other familiar characteristics.ResultsIntoxicated and sober recognition accuracy was comparable, but subjects in the alcohol group made more positive identifications overall compared to the no alcohol group.ConclusionsThe results are not in keeping with AMT. Rather, a more general cognitive mechanism appears to underlie false face recognition in intoxicated subjects. Specifically, acute alcohol intoxication during face learning results in more liberal choosing, perhaps because of an increased reliance on familiarity.

Faces with Light Makeup Are Better Recognized than Faces with Heavy Makeup.

Many women wear facial makeup to accentuate their appeal and attractiveness. Makeup may vary from natural (light) to glamorous (heavy), depending of the context of interpersonal situations, an emphasis on femininity, and current societal makeup trends. This study examined how light makeup and heavy makeup influenced attractiveness ratings and facial recognition. In a rating task, 38 Japanese women assigned attractiveness ratings to 36 Japanese female faces with no makeup, light makeup, and heavy makeup (12 each). In a subsequent recognition task, the participants were presented with 36 old and 36 new faces. Results indicated that attractiveness was rated highest for the light makeup faces and lowest for the no makeup faces. In contrast, recognition performance was higher for the no makeup and light make up faces than for the heavy makeup faces. Faces with heavy makeup produced a higher rate of false recognition than did other faces, possibly because heavy makeup creates an impression of the style of makeup itself, rather than the individual wearing the makeup. The present study suggests that light makeup is preferable to heavy makeup in that light makeup does not interfere with individual recognition and gives beholders positive impressions.

Automatic recognition of chewing noises in epileptic EEG based on period segmentation

Automatic detection of Interictal Epileptiform Discharges (IED) has the great significance in diagnosis of epilepsy and relieves the heavy workload of inspecting electroencephalogram (EEG). The artifacts in epileptic EEG strongly affect the detection results, especially in the form of chewing noises. This paper proposes a novel time-domain approach to process chewing noises in epileptic EEG signals based on period segmentation. Firstly, merger of increasing and decreasing sequences (MIDS) is employed to segment EEG periods. This period segmentation approach considers information of waveform rather than a single sample point and applies human vision principle. Experimental results show that the performance of merger and period segmentation is close to clinical visual detection. Secondly, chewing noises are recognized in epilepsy patients׳ EEG following period segmentation. To reduce the false recognition rate, classification results of four channels F3, F4, F7 and F8, which acquire high sensitivity and low false recognition rate, are fused to determine fragments׳ classification by weighting. With this method, EEG recordings of 20 epilepsy patients were analyzed. The results showed that a sensitivity of 98.10% and a false recognition rate of 0.01375/s were achieved. It demonstrates that the proposed approach performs well in automatic recognition of chewing noises in epileptic EEG, which is of crucial importance to automatic detection of IED.