Memory Errors Research Articles

Wavelet estimation for the nonparametric additive model in random design and long-memory dependent errors

We investigate the nonparametric additive regression estimation in random design and long-memory errors and construct adaptive thresholding estimators based on wavelet series. The proposed approach achieves asymptotically near-optimal convergence rates when the unknown function and its univariate additive components belong to Besov space. We consider the problem under two noise structures; (1) homoskedastic Gaussian long memory errors and (2) heteroskedastic Gaussian long memory errors. In the homoskedastic long-memory error case, the estimator is completely adaptive with respect to the long-memory parameter. In the heteroskedastic long-memory case, the estimator may not be adaptive with respect to the long-memory parameter unless the heteroskedasticity is of polynomial form. In either case, the convergence rates depend on the long-memory parameter only when long-memory is strong enough, otherwise, the rates are identical to those under i.i.d. errors. In addition, convergence rates are free from the curse of dimensionality.

FormatFuzzer : Effective Fuzzing of Binary File Formats

Effective fuzzing of programs that process structured binary inputs, such as multimedia files, is a challenging task, since those programs expect a very specific input format. Existing fuzzers, however, are mostly format-agnostic, which makes them versatile, but also ineffective when a specific format is required. We present FormatFuzzer , a generator for format-specific fuzzers . FormatFuzzer takes as input a binary template (a format specification used by the 010 Editor) and compiles it into C++ code that acts as parser, mutator, and highly efficient generator of inputs conforming to the rules of the language. The resulting format-specific fuzzer can be used as a standalone producer or mutator in black-box settings, where no guidance from the program is available. In addition, by providing mutable decision seeds, it can be easily integrated with arbitrary format-agnostic fuzzers such as AFL to make them format-aware. In our evaluation on complex formats such as MP4 or ZIP, FormatFuzzer showed to be a highly effective producer of valid inputs that also detected previously unknown memory errors in ffmpeg and timidity .

A RANDOMIZED CONTROLLED TRIAL OF THE EVERYDAY MEMORY AND METACOGNITIVE INTERVENTION IN OLDER ADULTS

Abstract This study evaluated an intervention to improve remembering in everyday life, the Everyday Memory and Metacognitive Intervention (EMMI). EMMI uses strategies designed to enhance everyday remembering and self-regulatory approaches to monitor goal pursuit, anticipate, and address memory demands. A randomized controlled trial compared a group assigned to EMMI with a traditional memory strategy training control (MSC) group. Expanding on earlier work (Pearman et al., 2020) we created a new event-based ecological momentary assessment (EB-EMA) smartphone application for reporting everyday memory errors when they occurred, synched to a nightly diary for collecting additional information about each event. The pretest-posttest design assessed changes in subjective memory beliefs and episodic memory performance and also measured posttest-only performance measures, including EB-EMA frequency of memory errors and a laboratory contact task assessing everyday prospective memory. The protocol was reduced in scope to accommodate fully remote participation due to the pandemic. The final sample included 30 EMMI and 32 MSC participants. Memory strategy training differentially improved MSC associative memory test performance. There were no group differences in EB-EMA reported memory errors or successful prospective memory contacts. The EMMI group showed more improvement in memory self-efficacy than the MSC group; both groups showed increases in perceived control over everyday memory. Individual differences in EMMI intervention benefits suggest that the program worked well in reducing memory errors for some but not all older adults. The EMMI shows promise but may require more extensive in-person training and behavioral shaping than this study provided to improve everyday memory.

A Smart Status Based Monitoring Algorithm for the Dynamic Analysis of Memory Safety

C is a dominant programming language for implementing system and low-level embedded software. Unfortunately, the unsafe nature of its low-level control of memory often leads to memory errors. Dynamic analysis has been widely used to detect memory errors at runtime. However, existing monitoring algorithms for dynamic analysis are not yet satisfactory as they cannot deterministically and completely detect some types of errors, e.g., segment confusion errors, sub-object overflows, use-after-frees and memory leaks. We propose a new monitoring algorithm, namely Smatus , short for smart status , that improves memory safety by performing comprehensive dynamic analysis. The key innovation is to maintain at runtime a small status node for each memory object. A status node records the status value and reference count of an object, where the status value denotes the liveness and segment type of this object, and the reference count tracks the number of pointer variables pointing to this object. Smatus maintains at runtime a pointer metadata for each pointer variable, to record not only the base and bound of a pointer’s referent but also the address of the referent’s status node. All the pointers pointing to the same referent share the same status node in their pointer metadata. A status node is smart in the sense that it is automatically deleted when it becomes useless (indicated by its reference count reaching zero). To the best of our knowledge, Smatus represents the most comprehensive approach of its kind. We have evaluated Smatus by using a large set of programs including the NIST Software Assurance Reference Dataset, MSBench, MiBench, SPEC and stress testing benchmarks. In terms of effectiveness (detecting different types of memory errors), Smatus outperforms state-of-the-art tools, Google’s AddressSanitizer, SoftBoundCETS and Valgrind, as it is capable of detecting more errors. In terms of performance (the time and memory overheads), Smatus outperforms SoftBoundCETS and Valgrind in terms of both lower time and memory overheads incurred, and is on par with AddressSanitizer in terms of the time and memory overhead tradeoff made (with much lower memory overheads incurred).

Robust testing for explosive behavior with strongly dependent errors

A heteroskedasticity-autocorrelation robust (HAR) test statistic is proposed to test for the presence of explosive roots in financial or real asset prices when the equation errors are strongly dependent. Limit theory for the test statistic is developed and extended to heteroskedastic models. The new test has stable size properties unlike conventional test statistics that typically lead to size distortion and inconsistency in the presence of strongly dependent equation errors. The new procedure can be used to consistently time-stamp the origination and termination of an explosive episode under similar conditions of long memory errors. Simulations are conducted to assess the finite sample performance of the proposed test and estimators. An empirical application to the S&P 500 index highlights the usefulness of the proposed procedures in practical work.

The dynamics of auditory working memory impairment in logopenic aphasia and Alzheimer’s disease

AbstractBackgroundImpaired auditory verbal working memory is a diagnostic hallmark and integral driver of the clinical phenotype in logopenic aphasia. However, the physiology of the working memory buffer in this syndrome is poorly characterised. Here we addressed the temporal dynamics of auditory verbal working memory in patients with logopenic aphasia and typical Alzheimer’s disease.MethodIn a cohort of patients with logopenic aphasia and typical Alzheimer’s disease and in healthy age‐matched controls, we assessed how temporal manipulations of standard auditory verbal working memory tasks (forward and reverse digit span and phrasal repetition) affected performance. We varied tempo of delivery and inter‐trial gap and performed a detailed analysis of error types. Participants also had pure tone audiometry to assess peripheral hearing function and a comprehensive general neuropsychological assessment.ResultCompared with healthy controls, patients with logopenic aphasia and Alzheimer’s disease showed increased sensitivity to temporal manipulation of auditory verbal working memory tasks and error profiles suggesting a dynamic physiological lesion of the working memory buffer. These effects were particularly marked in the logopenic group.ConclusionOur findings open a novel physiological window on working memory dynamics in Alzheimer’s disease syndromes. Further work is warranted to assess how this dynamic deficit impacts communication in patients’ daily lives, how it can best inform management interventions and its potential as a novel, rapid read‐out of neural function in the era of disease‐modifying therapies.

POORANA CHANDROTHAYA CHENTHURAM (PCC), A SIDDHA SYSTEM OF MEDICINE PROTECTS AGAINST SCOPOLAMINE‐INDUCED COGNITIVE IMPAIRMENTS IN EXPERIMENTAL RATS

AbstractBackgroundIndian Systems of Medicine (ISM) are considered to be of native medical systems which were assimilated into Indian culture. ISM comprising of Ayurveda, Yoga, and Naturopathy, Unani and Siddha which are in practice since time immemorial much before the recognized health system came into existence. In Siddha system, higher order pharmaceutical forms of medicine called PCC are predominantly prepared with metals and minerals through well‐coined pharmaceutical procedures and techniques that have been inscribed in the Siddha literature. The methods which convert the toxic metals/ minerals into compatible form that fits for human consumption. It has the privilege that these drug forms can cure many chronic diseases, in precise dosage. PCC is an imperative medicine which contains gold, mercury and sulphur in defined quantity. As given in Siddha vaithiyathirattu PCC is prepared from Gold, Mercury, and Sulphur in a ratio of 1:8:16 and processed with the required amount of red cotton flower juice and plantain stem pith juice. It is well known for its effectiveness in respiratory disorders especially bronchitis, hepatic disorders, renal diseases, neurological disorders, and skin diseases. However, there are no reports on whether PCC may improve cognitive dysfunction.MethodsWe used RAM and NORT models to evaluate cognitive improvement. In addition, the acetylcholinesterase enzyme was assessed in the brain tissues. Further, protein expression of BDNF was also assessed in hippocampus tissues after the behavioral tasks.ResultRepeated administration of PCC (2.5, 5 and 10 mg/kg., p.o) before the acquisition trial (T1) explored the object significantly more than the familiar one during the discrimination trial (T2) respectively, showing an increase in memory retention. In the radial arm‐maze task, scopolamine‐treated rats with PCC showed decreased working memory errors as compared to scopolamine‐alone treated rats. Treatment with different doses of PCC showed up‐regulation of BDNF with a significant effect by inhibiting the elevation of acetylcholinesterase activity when compared to the vehicle‐treated group.ConclusionsThese results suggest that the PCC ameliorates scopolamine‐induced impairment of cognitive functions in rats. These data further support that the anti‐amnestic effect of PCC recommends it as a promising candidate for clinical trials in patients with cognitive impairment.

Speech and Language characteristics of Kannada and Hindi speaking individuals with Primary Progressive Aphasia

AbstractBackgroundLinguistic typology plays an important role in identifying clinical markers of language deficits that characterise Primary Progressive Aphasia (PPA). The current International criteria to diagnose PPA were primarily developed for English. Typological characteristics of Indian languages however differ from English in their morpho‐syntactic complexity, a flexible‐word order, richer morphology, ‘pro‐drop’ languages with absence of prepositions and transparent orthography. We aimed to develop a novel test in Kannada (Dravidian) and Hindi (Indo‐Aryan) to identify language deficits in Indian language speakers with PPA.MethodThe speech‐language test systematically developed for Kannada and Hindi consisted of unique tasks for syntax, semantics, phonology, motor speech and working memory. Participants underwent assessment of cognition and language with Addenbrooke’s Cognitive Examination‐III, Western Aphasia Battery‐Revised and Indian Semantic Memory Battery (ISMB) in addition to the novel test.ResultsOf 26 patients with PPA (Kannada 13, Hindi 13), 15 had non‐fluent variant (nfvPPA), 8 semantic variant (svPPA) and 3 logopenic variant (lvPPA). On the novel test, PPA had higher phonological, motor speech, syntactic and semantic errors compared to 60 controls. nfvPPA had higher phonological, motor speech and syntactic errors and lesser semantic errors compared to svPPA. Semantic and working memory errors discriminated between nfvPPA and svPPA. On qualitative analysis, 5 patients of nfvPPA had significant apraxia of speech. The other 10 had a unique syntactic profile: agrammatism was not prominent in their spontaneous speech and picture description. Sentences were relatively fluent, complete and sufficient for functional communication. The consistent abnormality observed was a reduction in overall length of utterance. Agrammatisms such as inappropriate use of case markers were restricted to specific tests of syntax. svPPA patients had increased verbal output and prominent paragrammatisms. Testing for surface dyslexia was not relevant due to the orthographic transparency of Indian languages.ConclusionThe novel language test for evaluation of Indian speakers of PPA revealed unique findings for diagnosis of nfvPPA. Reduction in length of utterances and lack of prominent agrammatism was a consistent clinical marker and owes itself to morpho‐syntactic complexity of Indian languages. Our study emphasises the need to account for linguistic typology in diagnosis of PPA.

Memory error speed predicts subsequent accuracy for recognition misses but not false alarms

ABSTRACT The current study aims to test whether faster recognition memory errors tend to result from stronger misleading retrieval, making them harder to correct in subsequent decisions than slower errors, and whether this pattern holds for both miss and false-alarm errors. We used a paradigm in which each single-item Old/New recognition decision was followed by a two-alternative forced-choice (2AFC) test between a target and a lure. Each 2AFC trial had one item that had just been tested for an Old/New judgment and one item that had not been previously tested. Across 183 participants, the RTs for single-item recognition errors were used to predict accuracy in the 2AFC test using a hierarchical logistic regression model. The results showed a relationship between error RT and subsequent 2AFC accuracy that was qualified by an interaction with error type. Slower miss responses were more likely to be corrected than faster misses, but no accuracy differences were observed between slower and faster false alarms. The implications of these findings are discussed as they relate to assumptions about memory processes underlying inaccurate retrieval, using the diffusion model and the two-high-threshold model as examples of accounts that explain errors in terms of misleading retrieval and failed retrieval, respectively.

Separating climate change and human activities' effects on flow regime with hydrological model error correction

Climate change and human activities have markedly altered flow regimes, leading to deleterious consequences for riverine ecosystems. The widely employed hydrological modeling restoration method for conducting flow regime attribution often tends to underemphasize the impact of simulation errors on attribution outcomes. Moreover, the issue of ambiguous attribution targets in flow regime attribution remains a critical concern. This study presented a flow regime attribution framework integrated the hydrological model error correction. Indicators of hydrologic alteration (IHA) simulated by the XAJ and GR4J hydrological models and corrected using the quantile-mapping (QM) and convolutional neural network-long short term memory (CNN-LSTM) error correction methods, were employed to create 6 scenarios for assessing the impacts of climate change and human activities on flow regime changes. A case study was conducted in the Xitiaoxi basin, located in the upper reaches of Lake Tai in China. The results demonstrated that CNN-LSTM's superior performance over QM in correcting IHA metrics simulated by both XAJ and GR4J. The mean flow regime attribution results obtained from XAJ and GR4J simulations following the application of CNN-LSTM correction, mitigated the underestimation of contributions from the primary driving factors, in contrast to uncorrected or QM-corrected IHA metrics attribution results. Additionally, the regime attribution findings revealed all 33 IHA metrics experienced changes, with 73 % of them attributing human activities as the predominant driving forces. Substantial variations in IHA metrics exerted a certain degree of pressure on riverine habitats, particularly impacting the spawning and reproductive activities of piscine species.

Valkyrie: Improving fuzzing performance through deterministic techniques

Greybox fuzzing has received much attention from developers and researchers due to its success in discovering bugs within many programs. However, randomized algorithms have limited fuzzers’ effectiveness. First, branch coverage feedback that is based on random edge ID can lead to branch collision. Besides, state-of-the-art fuzzers heavily rely on randomized methods to reach new coverage. Finally, some state-of-the-art fuzzers only employ heuristics-based bug exploitation methods, which are not effective in triggering those that require non-trivial triggering conditions.We believe deterministic techniques deliver consistent and reproducible results. We propose Valkyrie, a greybox fuzzer whose performance is boosted primarily by deterministic techniques. Valkyrie combines collision-free branch coverage with context sensitivity to maintain accuracy while introducing an instrumentation removal algorithm to reduce overhead. It also pioneers a new mutation method, compensated step, allowing fuzzers that use solvers to adapt to real-world fuzzing scenarios without randomness. Additionally, Valkyrie proactively identifies possible exploit points in target programs and utilizes solvers to trigger actual bugs. We implement and evaluate Valkyrie’s effectiveness on the standard benchmark Magma, and a wide variety of real-world programs. Valkyrie triggered 21 unique integer and memory errors, 10.5% and 50% more than AFL++ and Angora, respectively. Valkyrie reached 8.2% and 12.4% more branches in real-world programs, compared with AFL++ and Angora, respectively. We also verify that our branch counting and mutation method is better than the state-of-the-art, which shows that deterministic techniques trump random techniques in consistency, reproducibility, and performance.

Younger and older adults’ memory of past feelings surrounding an election

ABSTRACT People often misremember their past feelings, especially when recalling their prior mood as opposed to their specific emotions in response to events. A previous study also found that the direction of memory errors varies based on feeling type; younger adults overestimated the intensity of prior moods but underestimated the intensity of prior event-specific emotions. This study aimed to replicate these patterns and test whether they vary with age. In doing so, we also tested whether an age-related positivity effect would emerge, such that older adults would be relatively more likely to overestimate past positive feelings and underestimate past negative feelings. Using a sample of American voters, who reported their feelings following the 2020 United States presidential election, we found that both younger and older adults subsequently overestimated the intensity of their past mood in the week following the election but were relatively accurate in recalling the intensity of their prior emotions about the election result. Unexpectedly, among election losers, we also observed an age-related negativity effect in recall for prior mood. When faced with negative real-world events, older adults may not show the same positivity biases that are observed in lab studies.

14 A Potential Behavioral Sign for Detection of Mild HIV-Related Neuropsychological Impairment

Objective:Even though the severity of HIV-associated neurocognitive disorders (HAND) has decreased with the introduction of combination antiretroviral therapy, mild forms of HAND remain prevalent. Many HIV-infected individuals live alone, so mild cognitive impairments are easily missed. It is important to check their neurocognitive and everyday functions during hospital visits; however, it is challenging for Japanese clinicians because many hospitals do not have enough clinical psychologists or neuropsychologists. Additionally, neuropsychological (NP) test results may not detect those mild cognitive impairments. A micro error has been given more attention as a new behavioral sign of the early stages of cognitive decline, especially among people with Mild Cognitive Impairment (MCI). The current study aimed to 1) develop a touch-panel HAND screening battery and 2) evaluate if the micro errors could differentiate individuals with HAND from their counterpart healthy individuals.Participants and Methods:Forty HIV-infected men (age: 49.0±8.51 years old, education: 18.5±2.17 years) and 44 healthy men (age: 45.4±8.49 years old, education: 14.4±2.27 years) completed the touch-panel HAND screening battery which assessed six NP domains by seven subtests, everyday functions, and depression. A micro error is defined as a subtle action disruption or hesitation occurring immediately before making final actions. We evaluated the micro errors in short-term memory (STM) and long-term memory (LTM) of verbal learning tests (VLT).Results:Mann Whitney U tests revealed that the HIV+ group made significantly more micro errors on both STM (HIV+: 1.45±0.90 times, Healthy: 0.52±0.84 times) and LTM (HIV+: 1.85±0.73 times, Healthy: 1.29±0.71 times) than the healthy group (STM: W=1362, p< .001, Effect Size (EF)= .548; LTM: W=1199.5, p= .002, EF= .363). An independent samples T-test showed that the HAND group made significantly more micro errors than the non-HAND group (t=1.822, p= .038, ES= .595) on STM; moreover, the Asymptomatic Neurocognitive Impairment (ANI) group made significantly more micro errors than the healthy group (W=446, p< .001, ES= .689). On LTM, no significant micro error differences between HAND and non-HAND (W=184.5, p= .539, ES= -.189) nor between ANI and healthy group (W=327.5, p= .103, ES= .241) were found.Conclusions:The present study suggests that a novel behavioral measure, micro errors, may be able to help detect even the mildest form of HAND, ANI. Given that the touch-panel HAND screening battery consists of NP and IADL tests, it is important to evaluate micro errors on these various measures. Additionally, the touch-panel screening battery requires minimal administrative staff involvement, which could be beneficial for busy HIV clinicians.

The Edible Seaweed Gelidium amansii Promotes Structural Plasticity of Hippocampal Neurons and Improves Scopolamine-Induced Learning and Memory Impairment in Mice.

Gelidium amansii has been gaining profound interest in East Asian countries due to its enormous commercial value for agar production and its extensive pharmacological properties. Previous studies have shown that the ethanol extract of Gelidium amansii (GAE) has promising neurotrophic effects in in vitro conditions. The present study aimed at investigating the protective effects of GAE against scopolamine-induced cognitive deficits and its modulatory effects on hippocampal plasticity in mice. For memory-related behavioral studies, the passive avoidance test and radial arm maze paradigm were conducted. The brain slices of the hippocampus CA1 neurons of experimental mice were then prepared to perform Golgi staining for analyzing spine density and its characteristic shape, and immunohistochemistry for assessing the expression of different pre- and postsynaptic proteins. Following oral administration of GAE (0.5 mg/g body weight), mice with memory deficits exhibited a significant increase in the latency time on the passive avoidance test and a decrease in the number of working and reference memory errors and latency time on the radial arm maze test. Microscopic observations of Golgi-impregnated tissue sections and immunohistochemistry of hippocampal slices showed that neurons from GAE-treated mice displayed higher spine density and spine dynamics, increased synaptic contact, and the recruitment of memory-associated proteins such as N-methyl-D-aspartate receptors (NR2A and NR2B) and postsynaptic density-95 (PSD-95) when compared with the control group. With these memory-protective functions and a modulatory role in underlying memory-related events, GAE could be a potential functional food and a promising source of pharmacological agents for the prevention and treatment of memory-related brain disorders.

Anterior Hippocampal Engagement during Memory Formation Predicts Subsequent False Recognition of Similar Experiences.

People better remember experiences when they orient to meaning over surface-level perceptual features. Such an orientation-related memory boost has been associated with engagement of both hippocampus (HPC) and neocortex during encoding. However, less is known about the neural mechanisms by which a cognitive orientation toward meaning might also promote memory errors, with one open question being whether the HPC-a region traditionally implicated in precise memory formation-also contributes to behavioral imprecision. We used fMRI to characterize encoding-phase signatures as people oriented toward the meaning (story) versus perceptual style (artist) of storybook-style illustrations and then linked them to subsequent true and false memories. We found that story and artist orientation tasks were each associated with both unique univariate profiles and consistent neural states defined using multivoxel patterns. Linking these neural signatures to behavior, we found that greater medial pFC activation and alignment of neural patterns to the story (but not artist) state was related to subsequent memory success on a trial-by-trial basis. Moreover, among successfully remembered experiences, greater anterior HPC engagement at encoding was associated with a higher likelihood of related false recognitions, consistent with the encoding of broad traces in this region. Interestingly, these effects did not reliably vary by cued orientation. These results suggest that, irrespective of the cued encoding orientation, neocortical and hippocampal mechanisms associated with orienting to meaning (story) over perceptual (artist) features may support memory, with the formation of generalizable memories being a specialty of anterior HPC.

Andrew Mayes’ expert analysis of a case of memory distortion

In this single-case study of memory distortion where Andrew Mayes was involved as an expert witness, a surgeon falsely recalled aspects of a patient safety adverse event in which he was involved, and where he was put through an investigatory process by a regulatory body. Andrew Mayes’ expert analysis of the role of memory distortion in this case resulted in the surgeon being exonerated.

Fecal microbiota transplantation and short-chain fatty acids improve learning and memory in fluorosis mice by BDNF-PI3K/AKT pathway

Fluoride, an environmental toxicant, not only arouses intestinal microbiota dysbiosis, but also causes neuronal apoptosis and a decline in learning and memory ability. The purpose of this study was to explore whether fecal microbiota transplantation (FMT) from healthy mice and bacteria-derived metabolites short-chain fatty acids (SCFAs) supplement protect against fluoride-induced learning and memory impairment. Results showed that FMT reversed the elevated percentage of working memory errors (WME) and reference memory errors (RME) in fluorosis mice during the eight-arm maze test. Nissl and TUNEL staining presented that fluoride led to a decreased proportion of Nissl bodies area in the hippocampal CA3 region and an increased apoptotic ratio of nerve cells in CA1, CA3 and DG areas, whereas FMT alleviated those pathological damages. Moreover, the expressions of mRNA in hippocampal BDNF, PDK1, AKT, Bcl-2, and Bcl-xL were downregulated in mice exposed to fluoride, but the levels of PI3K, Bax, Bak, and Caspase-7 mRNA were upregulated. NaF treatment had an increase in PI3K and Caspase-3 protein levels and reduced the expressions of these four proteins, including BDNF, p-PI3K, AKT and p-AKT. By contrast, FMT enhanced the expression of BDNF and thus activated the PI3K/AKT pathway. Besides, the 16S rRNA sequencing revealed that fluoride caused a reduction in certain SCFA producers in the colon as evidenced by a decline in Erysipelatoclostridiaceae, and a downward trend in Akkermansia, Blautia and Alistipes. However, the disordered gut microbiome was restored via frequent FMT. Of note, SCFAs administration also increased BDNF levels and regulated its downstream pathways, which contributed to cell survival and learning and memory function recovery. In conclusion, FMT and SCFAs may activate the BDNF-PI3K/AKT pathway to play an anti-apoptotic role and ultimately improve learning and memory deficits in fluorosis mice.

Can compression take place in working memory without a central contribution of long-term memory?

Information is easier to remember when it is recognized as structured. One explanation for this benefit is that people represent structured information in a compressed form, thus reducing memory load. However, the contribution of long-term memory and working memory to compression are not yet disentangled. Previous work has mostly produced evidence that long-term memory is the main source of compression. In the present work, we reveal two signatures of compression in working memory using a large-scale naturalistic data set from a science museum. Analyzing data from more than 32,000 memory trials, in which people attempted to recall briefly displayed sequences of colors, we examined how the estimated compressibility of each sequence predicted memory performance. Besides finding that compressibility predicted memory performance, we found that greater compressibility of early subsections of sequences predicted better memory for later subsections, and that mis-recalled sequences were simpler than the originals. These findings suggest that (1) more compressibility reduces memory load, leaving space for additional information; (2) memory errors are not random and instead reflect compression gone awry. Together, these findings suggest that compression can take place in working memory. This may enable efficient storage on the spot without direct contributions from long-term memory. However, we also discuss ways long-term memory could explain our findings.

A Lévy Walk Model not Affected by the Memory Error

In this paper, we investigate the influence of memory errors on a random walk model (the direction-comparison (DC) model), which was developed by the authors. In the DC model, a walker sometimes alters its directional rule, which is dependent on the directional inconsistency between the current direction and the past movement direction. Here, we introduced two different types of memory errors into the DC model: the recall error and the direction error. We found that the DC model was not influenced by a former type of error, suggesting that our model could be robust against some kinds of errors.

Performance analysis of several common error correction codes

With the rapid development of information technology and advances in science and technology, people are constantly interacting with data and coding. Error correction codes are integral to ensuring the security, robustness, and accuracy of information and systems, used not only in various engineering fields but in our daily lives as well. Systems that incorporate error correction codes have been proven to perform significantly better than those that do not, which makes it essential to understand the principles behind coding, encoding techniques, and their performance in specific domains.This paper focuses on three widely used error correction codes: Hamming code, RS code, and convolutional code. By introducing each code separately and evaluating their performance in different practical areas using proper simulations and relevant research results, this paper provides a comprehensive understanding of the vital role of error correction codes in channel encoding. Each code has its strengths, weaknesses, and specific applications. Hamming code, for example, is suitable for correcting bit errors in computer memories and communication systems. RS code is widely used in digital storage and broadcast systems due to its high level of error correction capability. Convolutional code is ideal for correcting bit-errors in continuous channels, making it an excellent choice for wireless communication systems. Overall, the results demonstrate that these error correction codes are crucial to guaranteeing data transmission integrity and system robustness. Understanding their principles and performance can guide future research and development of coding techniques in advancing technological progress and improving our daily lives.