Memory Scanning Research Articles

The Generality of Dynamic Adjustments in Decision Processes across Trials and Tasks.

There is a growing interest in understanding how aspects of binary decision-making change dynamically at the trial level. For example, in lexical decision, there is a well-established interaction between current and previous trial characteristics (e.g., lexicality and stimulus degradation) that suggests that participants adjust their decision processes based on the relative match in signal strength between the current and previous trial. The present study assessed the generality of this finding by examining the presence of such cross-trial adjustments in two new tasks, syntactic classification, and memory scanning. Stimulus degradation is manipulated in both tasks. Results indicate that response latencies are facilitated when salient aspects of the stimulus repeat across trials. These findings are interpreted within the context of a flexible processor that utilizes information from the prior target to prime the relevant processing pathway on the current trial. Candidate models that potentially can accommodate the pattern are briefly discussed.

High-Throughput Non-Binary LDPC Decoder Based on Aggressive Overlap Scheduling

Non-binary LDPC (NB-LDPC) codes offer better error correcting performance than their binary counterparts. However, to achieve excellent performance, decoding complexity and large memory are required, which makes it difficult to implement the high-throughput decoder. This paper presents a fully overlapped NB-LDPC decoder using three proposed techniques to improve throughput performance. First, an early bubble check is presented to reduce the initialization latency of the check node processing (CNP). Second, the CNP and variable node processing (VNP) are overlapped with the proposed backward memory scan method to hide the CNP latency within the VNP. Finally, we propose a redundant memory reuse technique to further decrease the latency of a single decoding iteration. We implemented the high-throughput decoder for (160, 80) regular (2, 4) NB-LDPC code over GF (64). The iteration latency was decreased by up to 57.5% with our three proposed methods. The proposed decoder achieved a throughput of 2.22 Gb/s at a 625-MHz frequency with 2.96-M gates in a 65-nm CMOS process. The proposed decoder showed outstanding area efficiency compared with the state-of-the-art decoders.

Spatio-temporal dynamics of working memory maintenance and scanning of verbal information.

During verbal communication, humans briefly maintain mental representations of speech sounds conveying verbal information, and constantly scan these representations for comparison to incoming information. We determined the spatio-temporal dynamics of such short-term maintenance and subsequent scanning of verbal information, by intracranially measuring high-gamma activity at 70-110Hz during a working memory task. Patients listened to a stimulus set of two or four spoken letters and were instructed to remember those letters over a two-second interval, following which they were asked to determine if a subsequent target letter had been presented earlier in that trial's stimulus set. Auditory presentation of letter stimuli sequentially elicited high-gamma augmentation bilaterally in the superior-temporal and pre-central gyri. During the two-second maintenance period, high-gamma activity was augmented in the left pre-central gyrus, and this effect was larger during the maintenance of stimulus sets consisting of four compared to two letters. During the scanning period following target presentation, high-gamma augmentation involved the left inferior-frontal and supra-marginal gyri. Short-term maintenance of verbal information is, at least in part, supported by the left pre-central gyrus, whereas scanning by the left inferior-frontal and supra-marginal gyri. The cortical structures involved in short-term maintenance and scanning of speech stimuli were segregated with an excellent temporal resolution.

A randomised-controlled trial of the effects of very low-carbohydrate and high-carbohydrate diets on cognitive performance in patients with type 2 diabetes.

This study compared the longer-term effects of a very low-carbohydrate, high-fat diet with a high-carbohydrate, low-fat diet on cognitive performance in individuals with type 2 diabetes (T2D). In total, 115 obese adults with T2D (sixty-six males, BMI: 34·6 (sd 4·3) kg/m2, age: 58 (sd 7) years, HbA1c: 7·3 (sd 1·1) %, diabetes duration: 8 (sd 6) years) were randomised to consume either an energy-restricted, very low-carbohydrate, low-saturated-fat (LC) diet or an energy-matched high unrefined carbohydrate, low-fat (HC) diet with supervised aerobic/resistance exercise (60 min, 3 d/week) for 52 weeks. Body weight, HbA1c and cognitive performance assessing perceptual speed, reasoning speed, reasoning ability, working memory, verbal fluency, processing speed, short-term memory, inhibition and memory scanning speed were assessed before and after intervention. No differences in the changes in cognitive test performance scores between the diet groups were observed for any of the cognitive function outcomes assessed (P≥0·24 time×diet). Percentage reduction in body weight correlated with improvements with perceptual speed performance. In obese adults with T2D, both LC and HC weight-loss diets combined with exercise training had similar effects on cognitive performance. This suggests that an LC diet integrated within a lifestyle modification programme can be used as a strategy for weight and diabetes management without the concern of negatively affecting cognitive function.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

In defence of high-speed memory scanning.

This paper reviews some of the evidence that bears on the existence of a mental high-speed serial exhaustive scanning process (SES) used by humans to interrogate the active memory of a set of items to determine whether it contains a test item. First proposed in the 1960s, based on patterns of reaction times (RTs), numerous later studies supported, elaborated, extended, and limited the generality of SES, while critics claimed that SES never occurred, that predictions from SES were violated, and that other mechanisms produced the RT patterns that led to the idea. I show that some of these claims result from ignoring variations in experimental procedure that produce superficially similar but quantitatively different RT patterns and that, for the original procedures, the most frequently repeated claims that predictions are violated are false. I also discuss evidence against the generality of competing theories of active-memory interrogation, especially those that depend on discrimination of directly accessible "memory-strength". Some of this evidence has been available since the 1960s but has been ignored by some proponents of alternative theories. Other evidence presented herein is derived from results of one relevant experiment described for the first time, results of another described in more detail than heretofore, and new analyses of old data. Knowledge of brain function acquired during the past half century has increased the plausibility of SES. SES is alive and well, but many associated puzzles merit further investigation, suggestions for which are offered.

Brain network changes and memory decline in aging.

One theory of age-related cognitive decline proposes that changes within the default mode network (DMN) of the brain impact the ability to successfully perform cognitive operations. To investigate this theory, we examined functional covariance within brain networks using regional cerebral blood flow data, measured by 15O-water PET, from 99 participants (mean baseline age 68.6±7.5) in the Baltimore Longitudinal Study of Aging collected over a 7.4year period. The sample was divided in tertiles based on longitudinal performance on a verbal recognition memory task administered during scanning, and functional covariance was compared between the upper (improvers) and lower (decliners) tertile groups. The DMN and verbal memory networks (VMN) were then examined during the verbal memory scan condition. For each network, group differences in node-to-network coherence and individual node-to-node covariance relationships were assessed at baseline and in change over time. Compared with improvers, decliners showed differences in node-to-network coherence and in node-to-node relationships in the DMN but not the VMN during verbal memory. These DMN differences reflected greater covariance with better task performance at baseline and both increasing and declining covariance with declining task performance over time for decliners. When examined during the resting state alone, the direction of change in DMN covariance was similar to that seen during task performance, but node-to-node relationships differed from those observed during the task condition. These results suggest that disengagement of DMN components during task performance is not essential for successful cognitive performance as previously proposed. Instead, a proper balance in network processes may be needed to support optimal task performance.

Design and implementation of an efficient hardware integer motion estimator for an HEVC video encoder

High-Efficiency Video Coding (HEVC) was developed to improve its predecessor standard, H264/AVC, by doubling its compression efficiency. As in previous standards, Motion Estimation (ME) is one of the encoder critical blocks to achieve significant compression gains. However, it demands an overwhelming complexity cost to accurately remove video temporal redundancy, especially when encoding very high-resolution video sequences. To reduce the overall video encoding time, we propose the implementation of the HEVC ME block in hardware. The proposed architecture is based on (a) a new memory scan order, and (b) a new adder tree structure, which supports asymmetric partitioning modes in a fast and efficient way. The proposed system has been designed in VHDL (VHSIC Hardware Description Language), synthesized and implemented by means of the Xilinx FPGA, Virtex-7 XC7VX550T-3FFG1158. Our design achieves encoding frame rates up to 116 and 30 fps at 2 and 4K video formats, respectively.

Evaluation of magnetic flux leakage signals on fatigue crack growth of mild steel

In engineering applications, analysis of crack growth life is useful in situations where an unexpected crack has been found in a component of a machine, vehicle, or structure. The objective of this research is to investigate the correlation curve of magnetic flux leakage, Hp(y) signals by evaluating their critical value point with respect to step size. Moreover, the relation of fatigue crack growth rate, da/dN toward the stress intensity range, ΔK and Hp(y) in metal components is also discussed in this paper. The tension-tension fatigue test was conducted with the metal magnetic memory scanning device and crack opening displacement (COD) gauges in 10 Hz (testing frequency) by applying a load for 3.0-5.0 kN respectively. As a result, the correlation curve of Hp(y) was built with the R-Squared values in the range of 0.99 and one mathematical model has been developed for estimation analysis. The sigmoidal shape curve was plotted on the graph of da/dN versus ΔK and also with Hp(y). Thus, for validation, the linear relation is represented between ΔK and Hp(y) that present a good approach for magnetic parameter to be developed in the fatigue crack growth analysis. Therefore, the magnetic method has greater capability to analyze the fatigue crack propagation life in a real application.

Low intensity magnetic field influences short-term memory: A study in a group of healthy students.

This study analyzes if an external magnetic stimulus (2 kHz and approximately 0.1 μT applied near frontal cortex) influences working memory, perception, binary decision, motor execution, and sustained attention in humans. A magnetic stimulus and a sham stimulus were applied to both sides of the head (frontal cortex close to temporal-parietal area) in young and healthy male test subjects (n = 65) while performing Sternberg's memory scanning task. There was a significant change in reaction time. Times recorded for perception, sustained attention, and motor execution were lower in exposed subjects (P < 0.01). However, time employed in binary decision increased for subjects exposed to magnetic fields. From results, it seems that a low intensity 2 kHz exposure modifies short-term working memory, as well as perception, binary decision, motor execution, and sustained attention.

FFT transformed quantitative EEG analysis of short term memory load.

The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.

Decomposing the relationship between mental speed and mental abilities

It is unclear whether different elementary cognitive tasks (ECTs) are associated with intelligence because these tasks tap the same basic cognitive process (suggesting a single mental speed factor) or different ones (suggesting several mental speed factors), as it is not known which specific cognitive processes are measured in ECTs and because the factor structure of these processes is unknown. To address these questions, 40 participants (50% males) between 18 and 75years drawn from a community sample completed the Hick paradigm, the Sternberg memory scanning paradigm, and the Posner letter matching paradigm while an EEG was recorded. We applied a diffusion model approach to the response-time data, which allows the mathematical decomposition of different cognitive parameters involved in speeded binary decisions. Behavioral and electrophysiological results indicated that ECT conditions varied in different neuro-cognitive components of information processing. Further analyses revealed that all speed and latency variables had substantial loadings on a second-order general factor marked by general intelligence, and that the association between ERP latencies and general intelligence was mediated by reaction times. These results suggest that there is a general neuro-cognitive speed factor across different tasks and different levels of measurement that is associated with general intelligence.

Optimization of rs-fMRI Pre-processing for Enhanced Signal-Noise Separation, Test-Retest Reliability, and Group Discrimination

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly important tool in mapping the functional networks of the brain. This tool has been used to examine network changes induced by cognitive and emotional states, neurological traits, and neuropsychiatric disorders. However, noise that remains in the rs-fMRI data after preprocessing has limited the reliability of individual-subject results, wherein scanner artifacts, subject movements, and other noise sources induce non-neural temporal correlations in the blood oxygen level-dependent (BOLD) timeseries. Numerous preprocessing methods have been proposed to isolate and remove these confounds; however, the field has not coalesced around a standard preprocessing pipeline. In comparisons, these preprocessing methods are often assessed with only a single metric of rs-fMRI data quality, such as reliability, without considering other aspects in tandem, such as signal-to-noise ratio and group discriminability. The present study seeks to identify the data preprocessing pipeline that optimizes rs-fMRI data across multiple outcome measures. Specifically, we aim to minimize the noise in the data and maximize result reliability, while retaining the unique features that characterize distinct groups. We examine how these metrics are influenced by bandpass filter selection and noise regression in four datasets, totaling 181 rs-fMRI scans and 38 subject-driven memory scans. Additionally, we perform two different rs-fMRI analysis methods – dual regression and region-of-interest based functional connectivity – and highlight the preprocessing parameters that optimize both approaches. Our results expand upon previous reports of individual-scan reliability, and demonstrate that preprocessing parameter selection can significantly change the noisiness, reliability, and heterogeneity of rs-fMRI data. The application of our findings to rs-fMRI data analysis should improve the validity and reliability of rs-fMRI results, both at the individual-subject level and the group level.

Forward scanning in verbal working memory updating.

Effective use of working memory (WM) for high-level cognitive tasks requires coordinating two conflicting requirements: robust maintenance and rapid updating. Models of WM suggest that these demands are coordinated by a gate between perceptual input and WM. Previous work with a letter-updating paradigm (Kessler & Oberauer, Journal of Experimental Psychology: Learning, Memory, and Cognition, 40, 738-754, 2014) supported a scanning and gate-switching (SGS) model of WM updating. The present work provides further evidence for the SGS model. Participants were required to keep track of the last letter that appeared in each of a row of frames on the screen. On each updating step, a variable subset of letters in varying positions in the row had to be updated. The SGS model assumes that on each updating step, participants scan through the memory set sequentially, opening the gate when a letter requires updating, and closing the gate when the next letter needs to be maintained. As is predicted by the SGS model, the reaction times for each updating step increased with the number of updated items and with the number of gate switches. In addition, the present experiment provides direct evidence supporting the scanning assumption of the model. Hebrew-speaking participants performed the task with either Hebrew or English letter stimuli, in different blocks. As was predicted, the scanning direction of the stimulus set was from left to right in English and from right to left in Hebrew. The SGS model fit the data only when the scanning direction was taken into account, establishing the role of item-based forward scanning during WM updating.

Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback.

To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Twenty-six subjects (22-40 y of age; 10 women). Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information.

Event-related desynchronization in EEG alpha band during graphical and phonemic memory scan for visually presented kana-characters based on Sernberg memory task

Event-related desynchronization in EEG alpha band during graphical and phonemic memory scan for visually presented kana-characters based on Sernberg memory task

Testosterone and male cognitive performance in Tsimane forager-horticulturalists.

Testosterone plays a vital role in brain function and behavior. Among humans, age-related decline in testosterone is associated with declining cognitive functioning, and aging men with higher testosterone maintain better cognitive performance. However, most research focuses on industrialized populations with widespread access to formal schooling, high testosterone, and low parasite and pathogen load. We examine whether men's testosterone is associated with cognitive performance among Tsimane forager-horticulturalists of Bolivia despite relatively lower levels of testosterone and higher immune burden. Ninety-four Tsimane men aged 36-86 (median = 49) participated in a cognitive battery (assessing short- and long-term recall, digit span, semantic memory, and visual scan) and provided urine and blood samples to measure testosterone and markers of immune activation. Linear mixed effects regressions were used to model associations between cognitive performance and testosterone, controlling for age, years of schooling, Spanish fluency, and village residence. For a subset (n = 66) we included immune activation markers to examine mediator effects. Testosterone is positively associated with short- and long-term verbal memory (β = 0.267, P = 0.018; β = 0.326, P = 0.005 respectively) and visual scanning (β = 0.306, P = 0.008) after controlling for potential confounders. Markers of immune activation were negatively associated with cognitive function, but did not change the associations between testosterone and cognitive performance. Tsimane men show positive associations between testosterone and cognitive performance, particularly for recall and visual scanning, despite higher immune burden. Testosterone may help motivate both physical and cognitive capacities that were essential for extracting the difficult-to-acquire, high-quality resources upon which humans relied over evolutionary history.

一款用于多媒体处理的异构多核系统芯片的可测试性设计

With the development of integrated circuit technology, system-on-chip (SoC)integration has become the mainstream method of VLSI design. SoC design usually has three features: emphasis on top-down design, outstanding design reusability, and need of low-power facilities, which brings great challenges to design for testability (DFT). This paper proposes a complete DFT scheme for a heterogeneous multi-core system-on-chip on multimedia processing, DPU-m. The proposed DFT scheme supports three operation modes: function mode, memory built-in self-test mode (BIST)and scan test mode. This thesis uses a top-down and modular design method for the DFT of DPU-m logic circuit. It proposes and implements a distributed and multiplexed test access mechanism; Experimental results show that test coverage of the single stuck-at fault for DPU-m logic circuit is 98.58%, which meets the requirements of the designer. In order to meet the need of at-speed testing, this thesis designs and implements an on-chip clock controller based on an on-chip clock generator, which supports at-speed testing of different clock domains. This thesis designs and implements a serial and parallel combined BIST structure for the on-chip memory, which meets the constraints of test power and reduces test time. Then, this thesis designs and implements the test results output circuit, with a memory diagnostic resolution meeting the requirements of the designer; the results show that the test time for memories is 14 ms at the test frequency of 100 MHz.

Out of Sight but Not Out of Mind: Memory Scanning is Attuned to Threatening Faces

Working memory (WM) theoretically affords the ability to privilege social threats and opportunities over other more mundane information, but few experiments have sought support for this contention. Using a functional logic, we predicted that threatening faces are likely to elicit encoding benefits in WM. Critically, however, threat depends on both the capacities and inclinations of the potential aggressor and the possible responses available to the perceiver. Two experiments demonstrate that participants more efficiently scan memory for angry facial expressions, but only when the faces also bear other cues that are heuristically associated with threat: masculinity in Study 1 and outgroup status in Study 2. Moreover, male participants showed robust speed and accuracy benefits, whereas female participants showed somewhat weaker effects, and only when threat was clearly expressed. Overall results indicate that working memory for faces depends on the accessibility of self-protective goals and on the functional relevance of other social attributes of the face.

A Demonstration of Malicious Insider Attacks inside Cloud IaaS Vendor

 Abstract—Until now, many researches have carried out analyzing the vulnerabilities as well as finding the defense strategies for malicious insider (MI) at cloud environment. However, all these previous works only considered the perspective of MI attacks that are originated from tenant side in a public cloud. Furthermore, in these existing works, the MI attack techniques are only basically and abstractly described. Without the proof of concept, MI attacks are just theoretical threats. In this paper, we consider the scenario that MI executes the attack inside the Cloud IaaS vendor. Moreover, in order to show the realistic of MI attacks in the scenario, this paper introduces three concrete MI attacks with a proof of concept implementation based on existing tools. Three introduced MI attacks in this paper are: memory scanning, template poisoning, and snapshot cracking. The demonstration result shows that MI attacks inside cloud IaaS vendor are no longer potential threats but realistic issues that we need to consider.