Inefficient Information Processing Research Articles

Flashlight model: Integrating attention distribution and attention resources for pilots’ visual behaviour analysis and performance prediction

Pilot performance is almost the last line of defense in aircraft safety. Recent years have seen a surge in research aimed at utilizing eye-tracking technology to predict pilot performance, enhancing aviation safety margins. A decline in pilot performance is often attributed to either misdirected attention towards irrelevant tasks or inefficient information processing owing to limited attention resources. Previous research has shown that eye-tracking data can effectively capture these issues and provide accurate performance predictions. Nevertheless, the existing studies either focus on attention distribution or attention resources separately, neglecting the complex interactions between them. To address this gap, our study proposes a synthesized Flashlight model-based eye-tracking analysis for pilot performance prediction, integrating the two perspectives. Accordingly, the combined AOI-gaze metrics are proposed to offer a more nuanced analysis of information processing across specific Areas of Interest (AOIs), thereby enhancing the analysis of gaze metrics. We examined the efficacy of the combined AOI-gaze metrics in the Gradient-boosted decision trees(GBDT) model for pilot performance prediction and compared them with other widely used eye-tracking metrics in a simulated flight experiment case study. Moreover, we employed the SHapley Additive exPlanations (SHAP) method to identify the most influential eye-tracking measurements for pilots’ performance prediction. The result demonstrated that the selected eye-tracking measurements obtained the highest accuracy in performance prediction.

Top-down Inhibitory Motor Control Is Preserved in Adults with Developmental Coordination Disorder

ABSTRACT Two paradigms were employed to disentangle information processing from executive motor inhibition in adults with Developmental Coordination Disorder (DCD). Choice Reaction and Stop Signal Tasks were compared between 13 adults fulfilling DSM-5 DCD criteria and 42 typically developing adults. Additional analyses included 16 probable DCD (pDCD) participants, who had motor difficulties but did not fulfil DSM-5 criteria. Analyses employed frequentist and Bayesian modeling. While DCD+pDCD showed slower reaction times and difficulty initiating Go responses, no impairments in Stop actions were found. These findings indicated no executive deficit in DCD, suggesting that previous results may be explained by inefficient information processing.

Behavioral and cognitive correlates of the aperiodic (1/f-like) exponent of the EEG power spectrum in adolescents with and without ADHD

Efficient information processing facilitates cognition and may be disrupted in a number of neurodevelopmental conditions. And yet, the role of inefficient information processing and its neural underpinnings remains poorly understood. In the current study, we examined the cognitive and behavioral correlates of the aperiodic exponent of the electroencephalogram (EEG) power spectrum, a putative marker of disrupted, inefficient neural communication, in a sample of adolescents with and without ADHD (n = 184 nADHD = 87; Mage = 13.95 years, SD = 1.36). Exponents were calculated via FOOOF (Donoghue et al., 2020a) from EEG data recorded during an 8-minute baseline episode. Reaction time speed and variability, as well as drift diffusion parameters (including the drift rate parameter, a cognitive parameter directly related to inefficient information processing) were calculated. Adolescents with ADHD had smaller aperiodic exponents (a “flattened” EEG power spectrum) relative to their typically-developing peers. After controlling for ADHD, aperiodic exponents were related to reaction time variability and the drift rate parameter, but not in the expected direction. Our findings lend support for the aperiodic exponent as a neural correlate of disrupted information processing, and provide insight into the role of cortical excitation/inhibition imbalance in the pathophysiology of ADHD.

Neurophysiological, Oculomotor, and Computational Modeling of Impaired Reading Ability in Schizophrenia.

Schizophrenia (Sz) is associated with deficits in fluent reading ability that compromise functional outcomes. Here, we utilize a combined eye-tracking, neurophysiological, and computational modeling approach to analyze underlying visual and oculomotor processes. Subjects included 26 Sz patients (SzP) and 26 healthy controls. Eye-tracking and electroencephalography data were acquired continuously during the reading of passages from the Gray Oral Reading Tests reading battery, permitting between-group evaluation of both oculomotor activity and fixation-related potentials (FRP). Schizophrenia patients showed a marked increase in time required per word (d = 1.3, P < .0001), reflecting both a moderate increase in fixation duration (d = .7, P = .026) and a large increase in the total saccade number (d = 1.6, P < .0001). Simulation models that incorporated alterations in both lower-level visual and oculomotor function as well as higher-level lexical processing performed better than models that assumed either deficit-type alone. In neurophysiological analyses, amplitude of the fixation-related P1 potential (P1f) was significantly reduced in SzP (d = .66, P = .013), reflecting reduced phase reset of ongoing theta-alpha band activity (d = .74, P = .019). In turn, P1f deficits significantly predicted increased saccade number both across groups (P = .017) and within SzP alone (P = .042). Computational and neurophysiological methods provide increasingly important approaches for investigating sensory contributions to impaired cognition during naturalistic processing in Sz. Here, we demonstrate deficits in reading rate that reflect both sensory/oculomotor- and semantic-level impairments and that manifest, respectively, as alterations in saccade number and fixation duration. Impaired P1f generation reflects impaired fixation-related reset of ongoing brain rhythms and suggests inefficient information processing within the early visual system as a basis for oculomotor dyscontrol during fluent reading in Sz.

The role of reinvestment in conservative gait in older adults.

Previous research suggests that reinvestment (i.e. conscious control of movements) is associated with inefficient information processing and compromised movement strategies in older adults during walking. We examined whether reinvestment propensity is associated with conservative gait behaviour in older adults. Trait Reinvestment propensity was measured using the Movement Specific Reinvestment Scale (Chinese version) (MSRS-C). Thirty-eight older adults were categorized into 'Low Reinvestor Group' (LRG) (MSRS-C<27) and another 38 were categorized into 'High Reinvestor Group' (HRG) (MSRS-C>38). There were no significant differences in physical and cognitive abilities between groups. Participants were asked to walk along a 6-m straight level-ground walkway at a self-selected pace under conditions of no instruction (Baseline), instruction related to self-focus on body movements (BI), and instruction related to the external environment (EI). No significant difference was found in gait behaviour between LRG and HRG at Baseline. However, significant changes, indicative of conservative gait patterns, were found in LRG when given instructions that prompted them to consciously control their body movements. No changes were observed in HRG under external-related instructions that are assumed to reduce conscious motor processing and improve motor performance. Our findings contradict previous views on the association between trait reinvestment propensity and compromised motor performance in older adults, which potentially reduces justification for reducing trait reinvestment propensity in older adults. We also suggest that MSRS is insensitive to reflect the degree of conscious control during gait tasks. Our findings also implicate the potential detrimental effect of applying inward-focus-related instructions in healthcare rehabilitation settings.

Identifying Brain Abnormalities with Schizophrenia Based on a Hybrid Feature Selection Technology

Many medical imaging data, especially the magnetic resonance imaging (MRI) data, usually have a small sample size, but a large number of features. How to reduce effectively the data dimension and locate accurately the biomarkers from such kinds of data are quite crucial for diagnosis and further precision medicine. In this paper, we propose a hybrid feature selection method based on machine learning and traditional statistical approaches and explore the brain abnormalities of schizophrenia by using the functional and structural MRI data. The results show that the abnormal brain regions are mainly distributed in the supramarginal gyrus, cingulate gyrus, frontal gyrus, precuneus and caudate, and the abnormal functional connections are related to the caudate nucleus, insula and rolandic operculum. In addition, some complex network analyses based on graph theory are utilized on the functional connection data, and the results demonstrate that the located abnormal functional connections in brain can distinguish schizophrenia patients from healthy controls. The identified abnormalities in brain with schizophrenia by the proposed hybrid feature selection method show that there do exist some abnormal brain regions and abnormal disruption of the network segregation and network integration for schizophrenia, and these changes may lead to inaccurate and inefficient information processing and synthesis in the brain, which provide further evidence for the cognitive dysmetria of schizophrenia.

Age-Sensitive Effects of Enduring Work with Alternating Cognitive and Physical Load. A Study Applying Mobile EEG in a Real Life Working Scenario.

Ergonomic assessment of a workplace requires the evaluation of physical as well as cognitive aspects of a particular working situation. In particular the latter is hardly possible without interfering in the natural setting. Mobile acquisition of neurophysiological measures (such as parameters of the EEG) may close this gap. At a simulated workplace we tracked older and younger participants with mobile EEG during a 4–5 h work shift. They had to perform either a monotonous cognitive task, a self-paced cognitive task or a self-paced physical task in a predefined order. Self assessment, behavioral performance and spectral measures of the EEG (before most alpha power) indicated that younger participants suffered from monotony. Older adults, on the other hand, were overall impaired by inefficient information processing. This was visible in EEG variations time-locked to eye blinks (blink-related synchronizations), a new measure to investigate cognitive processing in real life environments. Thus, we were able to distinguish between active and passive task-related aspects of mental fatigue without impinging on the natural working situation.

Is impulsive violence an addiction? The Habit Hypothesis.

Impulsive violence may be the behavioral consequence of inefficient information processing within specific neuronal networks. Analogous to the hypothetical pathophysiology of addiction, maladaptations within reward pathways may shift goal-directed behaviors to impulsive reactions and then to compulsive habits, in order to create impulsive violence.

A Fundamental Study of Efficiency of Information Processing in Emergency Operations Center

Many of the emergency operations centers that take the initiative in commanding and controlling on disaster response still rely on inefficient manual information processing even though they have ICT systems at hand. This paper reports on 3-year functional exercises in a local government using ICT to improve information processing.

Interactive Effects of DAOA (G72) and Catechol- O-Methyltransferase on Neurophysiology in Prefrontal Cortex

Accumulating evidence indicates that genetic polymorphisms of D-amino acid oxidase activator (DAOA) (M24; rs1421292; T-allele) and catechol-O-methyltransferase (COMT) (Val¹⁵⁸Met; rs4680) likely enhance susceptibility to schizophrenia. Previously, clinical association between DAOA M24 (T-allele) and a functionally inefficient 3-marker COMT haplotype (that included COMT Val¹⁵⁸Met) uncovered epistatic effects on risk for schizophrenia. Therefore, we projected that healthy control subjects with risk genotypes for both DAOA M24 (T/T) and COMT Val¹⁵⁸Met (Val/Val) would produce prefrontal inefficiency, a critical physiological marker of the dorsolateral prefrontal cortex (DLPFC) in schizophrenic patients influenced by both familial and heritable factors. With 3T blood oxygen level dependent functional magnetic resonance imaging data, we analyzed in SPM5 the proposed interaction of DAOA and COMT in 82 healthy volunteers performing an N-back executive working memory paradigm (2-back > 0-back). As predicted, we detected a functional gene x gene interaction between DAOA and COMT in the DLPFC. The neuroimaging findings here of inefficient information processing in the prefrontal cortex seem to echo prior statistical epistasis between risk alleles for DAOA and COMT, albeit within a small sample. These in vivo results suggest that deleterious genotypes for DAOA and COMT might contribute to the pathophysiology of schizophrenia, perhaps through combined glutamatergic and dopaminergic dysregulation.

Fooling Mother Nature: Epigenetics and Novel Treatments for Psychiatric Disorders

Modern formulations of psychiatric disorders hypothesize that mother nature goes awry, causing both genetic and epigenetic disease actions. Genetic disease actions are the consequences of naturally inherited risk genes that have an altered sequence of DNA. This altered DNA sequence theoretically leads to the production of altered gene products in neurons, causing inefficient information processing in various brain circuits, and biasing those circuits towards developing symptoms of a mental illness. Epigenetic disease actions are theorized either to activate risk genes to make an altered gene product or to activate normal genes to make normal gene products but at the wrong time. Epigenetic disease mechanisms theoretically turn normal genes into risk genes by causing normal genes to be expressed in neurons when these genes should be silenced or by causing normal genes to be silenced when they should be expressed.

Methylated Spirits: Epigenetic Hypotheses of Psychiatric Disorders

Our spirits may be regulated by the methylation of our genes. Methylation, acetylation, and other biochemical processes are the molecular switches for turning genes on and off. There is evidence now that certain behaviors, feelings, and psychiatric symptoms may be modified by turning various genes on or off. If classical genetics is the sequence of DNA that is inherited, then epigenetics is a parallel process determining whether a given gene (ie, a sequence of DNA coding for transcription) is expressed into its RNA or is silenced. Epigenetics is now entering psychiatry with the hypothesis that normal genes as well as risk genes can both contribute to a mental disorder. That is, it has long been hypothesized that when “abnormal” genes with an altered sequence of DNA are inherited as risk genes for a mental illness, these risk genes will make an abnormal gene product in neurons, contributing to inefficient information processing in various brain circuits and creating risk for developing a symptom of a mental illness. Now comes the role of epigenetic actions in mental illnesses.

Reading the Tea Leaves: Why Serial Correlation Patterns in Analysts' Forecast Errors are not Evidence of Inefficient Information Processing

We put forward a model in which analysts are uncertain about a firm's earnings process. Faced with the possibility of using a misspecified model, analysts issue forecasts that are robust to model misspecification. We estimate that this mechanism explains approximately 60% of the autocorrelation in analysts' forecast errors. The remainder stems from the cross-sectional variation in mean forecast errors and in analysts' estimation errors of the persistence of earnings growth shocks. Consistent with our model, we find that analysts learn about some features of the earnings process but not others, and this learning reduces, but does not eliminate, the auto- correlation of forecast errors as firms age. Other potential explanations for the autocorrelation of analyst's forecast errors are rejected. Our model of robust forecasting applies not only to analysts' forecasts but to all model-based forecasts.

Cerebellar information processing in relapsing-remitting multiple sclerosis (RRMS).

Recent research has characterized the anatomical connectivity of the cortico-cerebellar system – a large and important fibre system in the primate brain. Within this system, there are reciprocal projections between the prefrontal cortex and Crus II of the cerebellar cortex, which both play important roles in the acquisition and execution of cognitive skills. Here, we propose that this system also plays a particular role in sustaining skilled cognitive performance in patients with Relapsing-Remitting Multiple Sclerosis (RRMS), in whom advancing neuropathology causes increasingly inefficient information processing. We scanned RRMS patients and closely matched healthy subjects while they performed the Paced Auditory Serial Addition Test (PASAT), a demanding test of information processing speed, and a control task. This enabled us to localize differences between conditions that change as a function of group (group-by-condition interactions). Hemodynamic activity in some patient populations with CNS pathology are not well understood and may be atypical, so we avoided analysis strategies that rely exclusively on models of hemodynamic activity derived from the healthy brain, using instead an approach that combined a ‘model-free’ analysis technique (Tensor Independent Component Analysis, TICA) that was relatively free of such assumptions, with a post-hoc ‘model-based’ approach (General Linear Model, GLM). Our results showed group-by-condition interactions in cerebellar cortical Crus II. We suggest that this area may have in role maintaining performance in working memory tasks by compensating for inefficient data transfer associated with white matter lesions in MS.

Cerebellar Information Processing in Relapsing-Remitting Multiple Sclerosis (RRMS)

Recent research has characterized the anatomical connectivity of the cortico-cerebellar system – a large and important fibre system in the primate brain. Within this system, there are reciprocal projections between the prefrontal cortex and Crus II of the cerebellar cortex, which both play important roles in the acquisition and execution of cognitive skills. Here, we propose that this system also plays a particular role in sustaining skilled cognitive performance in patients with Relapsing-Remitting Multiple Sclerosis (RRMS), in whom advancing neuropathology causes increasingly inefficient information processing. We scanned RRMS patients and closely matched healthy subjects while they performed the Paced Auditory Serial Addition Test (PASAT), a demanding test of information processing speed, and a control task. This enabled us to localize differences between conditions that change as a function of group (group-by-condition interactions). Hemodynamic activity in some patient populations with CNS pathology are not well understood and may be atypical, so we avoided analysis strategies that rely exclusively on models of hemodynamic activity derived from the healthy brain, using instead an approach that combined a ‘model-free’ analysis technique (Tensor Independent Component Analysis, TICA) that was relatively free of such assumptions, with a post-hoc ‘model-based’ approach (General Linear Model, GLM). Our results showed group-by-condition interactions in cerebellar cortical Crus II. We suggest that this area may have in role maintaining performance in working memory tasks by compensating for inefficient data transfer associated with white matter lesions in MS.

The Prefrontal Cortex Is Out of Tune in Attention-Deficit/Hyperactivity Disorder

In ADHD, pyramidal neurons in the prefrontal cortex are hypothetically out of tune, causing either deficient signals, excessive noise, or both. Specific malfunctioning brain areas within the prefrontal cortex theoretically mediate the various symptoms of ADHD. Inefficient information processing in related areas of prefrontal cortex may also cause the specific symptoms of the common comorbidities of ADHD, such as bipolar disorder, anxiety disorders, conduct disorder, and oppositional defiant disorder.

Suppressed Negative Information and Future Underperformance*

I present evidence of inefficient information processing in equity markets by documenting that negative information withheld by securities analysts is incorporated in stock prices with a significant delay. I estimate the extent of the withheld negative information based on the proportion of analysts who stop revising their annual earnings forecasts. This measure predicts negative earnings surprises and negative price reaction around earnings announcements. It could also be used to generate profitable trading strategies. I show that institutions tend to sell their stock holdings as my measure of unreported negative news increases, thus ameliorating the mispricing.

The Genetics of Schizophrenia Converge Upon the NMDA Glutamate Receptor

Recent research shows that single genes do not cause schizophrenia, but that multiple “susceptibility” genes each provide a genetic “bias” towards schizophrenia. Each susceptibility gene codes for a subtle molecular abnormality that hypothetically causes inefficient information processing in brain circuits that mediate the symptoms of this disorder. It is therefore not surprising that many of the susceptibility genes that have been identified for schizophrenia are known to regulate neuronal connectivity, synaptogenesis, and N-methyl-D-aspartate (NMDA) glutamate receptor functions. This includes genes for brain-derived neurotrophic factor (BDNF), dysbindin, also known as dystrobrevin-binding protein 1, neuregulin, disrupted in schizophrenia-1 (DISC-1), D-amino acid oxidase activator (DAOA), and regulator of G-protein signaling (RGS4). Hypothetically, converging molecular abnormalities expressed by defective versions of these genes could cause dysregulation of NMDA receptors and NMDA synapses, leading to vulnerability for schizophrenia due to inefficient information processing at glutamate synapses.

Suppressed Negative Information and Future Underperformance

We present evidence of inefficient information processing in equity markets by documenting that negative information withheld by securities analysts is reflected in stock prices with a significant delay. We estimate the extent of the withheld negative information based on the proportion of analysts who stop revising their annual earnings forecasts. This measure predicts negative earnings surprises and negative price reaction around earnings announcements. It could also be used to generate profitable trading strategies. We show that institutions tend to sell their stock holdings as our measure of unreported negative news increases, thus ameliorating the mispricing.

Analyst Disagreement, Forecast Bias and Stock Returns

We present evidence of inefficient information processing in equity markets by documenting that biases in analysts' earnings forecasts are reflected in stock prices. In particular, we show that investors fail to fully account for optimistic bias associated with analyst disagreement. This bias arises for two reasons. First, analysts issue more optimistic forecasts when earnings are uncertain. Second, analysts with sufficiently low earnings expectations who choose to keep quiet introduce an optimistic bias in the mean reported forecast that is increasing in the underlying disagreement. Indicators of the missing negative opinions predict earnings surprises and stock returns. By selling stocks with high analyst disagreement institutions exert correcting pressure on prices.