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This paper delves into the increasingly recognized yet complex relationship between air pollution and Neurological Diseases. Although the detrimental effects of air pollution on respiratory and cardiovascular health are well-documented, its impact on neurological and cognitive disorders is an emerging area of concern. In this mini review, we explore the intricate mechanisms by which various air pollutants, such as particulate matter, nitrogen oxides, and polycyclic aromatic hydrocarbons, contribute to neurological pathologies. The focus lies on the role of oxidative stress and inflammation in exacerbating conditions like Alzheimer’s disease and Parkinson’s disease. By unraveling these connections, the paper sheds light on the broader implications of environmental factors on neurological health and underscores the urgent need for policy interventions to mitigate air pollution’s impact on the nervous system.

Investigating frontal EEG asymmetry as a possible biomarker of cognitive control abilities is especially important in ecological contexts such as school and work. We used a novel approach combining judgment performance and hemispheric frontal event-related potential (ERP) P300 asymmetry (fP3As) to evaluate aspects of cognitive control (i.e., repetition and switching) in adolescent females over a two-week ordinary school period. While undergoing electroencephalographic recording, students performed a word-colour “Stroop-like” congruence judgment task during morning and afternoon sessions, on Mondays and Wednesdays. Proportion of incongruence and congruence trials was 75% and 25%, respectively. ERP analysis revealed larger “novelty” right hemispheric fP3As amplitude for infrequent congruence but equivalent or significantly smaller than left hemispheric fP3As amplitude for frequent incongruence. RTs increased with extent of right fP3As shift. Behaviorally, repeat trial pairs (i.e., congruent followed by congruent, incongruent followed by incongruent) generally did not differ by time or day and were associated with near-ceiling accuracy. In contrast, switch trial pairs (i.e., congruent followed by incongruent, incongruent followed by congruent) in the afternoon were slower and associated with lower accuracy at the expected 75% criterion rate (i.e., judging incongruence by default), dropping significantly below 75% in the mornings. Crucially, compared to afternoon, morning fP3As patterns did not change adaptively with switch trial pairs. Although retroactive switching during congruence judgment was affected at all testing times, we conclude it was most impaired in the mornings of both early and mid school weeks, supporting misalignment between adolescent circadian cycle and school start time. We discuss some implications for optimal learning of adolescents at school.

Background & aims: Naturogenic aspects of global warming are amplified by the anthropogenic effects of the persistent exponential global population growth. Urbanization without proper planning escalates serious all-time disease pathologies in vulnerable populations, such as children, through pollution of toxic gases. We illustrate these associations with a retrospective study of respiratory heath in children living in downtown Rome when this dense urban center recorded one of the highest air pollution levels in Europe. Methods: Lung and respiratory function parameters were evaluated from 2006 to 2007 in a cohort of 90 children including two age subgroups (>10 years and

IntroductionShorter and/or disrupted sleep during adolescence is associated with cognitive and mental health risks, particularly in females. We explored the relationship between bedtime behavior patterns co-varying with Social Jet Lag (SJL) and School Start Times (SST) and neurocognitive performance in adolescent female students.MethodsTo investigate whether time of day (morning vs. afternoon), early SSTs and days of the school week can be correlated with neurocognitive correlates of sleep insufficiency, we recruited 24 female students aged 16–18 to report sleep logs, and undergo event-related electroencephalographic recordings on Monday, Wednesday, mornings, and afternoons. Using a Stroop task paradigm, we analyzed correlations between reaction times (RTs), accuracy, time of day, day of week, electroencephalographic data, and sleep log data to understand what relationships may exist.ResultsParticipants reported a 2-h sleep phase delay and SJL. Stroop interference influenced accuracy on Monday and Wednesday similarly, with better performance in the afternoon. For RTs, the afternoon advantage was much larger on Monday than Wednesday. Midline Event-Related Potentials (ERPs) yielded higher amplitudes and shorter latencies on Wednesday morning and Monday afternoon, in time windows related to attention or response execution. A notable exception were delayed ERP latencies on Wednesday afternoon. The latter could be explained by the fact that delta EEG waves tended to be the most prominent, suggesting heightened error monitoring due to accumulating mental fatigue.DiscussionThese findings provide insights into the interaction between SJL and SST and suggest evidence-based criteria for planning when female adolescents should engage in cognitive-heavy school activities such as tests or exams.

Grossberg’s adaptive resonance theory (ART) provides a framework for understanding possible interactions between mental imagery and visual perception. Our purpose was to integrate, within ART, the phenomenological notion of mental image vividness and thus investigate the possible biasing effects of individual differences on visual processing. Using a Vernier acuity task, we tested whether indirect estimation of relative V1 size (small, medium, large) and self-reported vividness, in three subgroups of 53 observers, could predict significant effects of priming, interference, or more extreme Perky effects (negative and positive), which could be induced by imagery, impacting acuity performance. The results showed that small V1 was correlated with priming and/or negative Perky effects independently of vividness; medium V1 was related to interference at low vividness but priming at high vividness; and large V1 was related to positive Perky effects at high vividness but negative Perky effects at low vividness. Our interpretation of ART and related modeling based on ARTSCAN contributes to expanding Grossberg’s comprehensive understanding of how and why individually experienced vividness may drive the differential use of the dorsal and ventral complementary visual processing pathways, resulting in the observed effects of imagery on concurrent perception.

The use of touch for the treatment of psychiatric disorders is increasingly investigated, as it is shown that cognitive symptoms can be improved by various forms of massage. To investigate if the effect of massage is measurable using classical visual event-related potential components (P1, P2, late positive potential (LPP)), we performed a preliminary study on six participants using myofascial induction massage. Participants were shown emotionally valenced or neutral images before and after a 20 min myofascial massage. We found general increases in P2 amplitude following the intervention across all conditions (both neutral and affective), indicating increased attention or salience to visual stimuli. The magnitude of change was visibly larger for unpleasant stimuli, suggesting that visual perception and attention were modulated specifically in response to unpleasant visual images. The LPP showed reductions in amplitude after myofascial massage, suggesting increased emotional modulation following intervention, as a result of possible DMN alterations, consistent with region and function. We conclude that brief myofascial intervention supports other research in the field, finding that physical touch and massage techniques can alter cognition and perception. We posit further research to investigate its future use as an intervention for both physical and cognitive modulation. Importantly, we provide preliminary evidence that the neural processes that resonate with this type of massage involve complex feedforward and backward cortical pathways, of which a significant portion participate in modulating the visual perception of external stimuli.

We examine the challenging “marriage” between computational efficiency and biological plausibility—A crucial node in the domain of spiking neural networks at the intersection of neuroscience, artificial intelligence, and robotics. Through a transdisciplinary review, we retrace the historical and most recent constraining influences that these parallel fields have exerted on descriptive analysis of the brain, construction of predictive brain models, and ultimately, the embodiment of neural networks in an enacted robotic agent. We study models of Spiking Neural Networks (SNN) as the central means enabling autonomous and intelligent behaviors in biological systems. We then provide a critical comparison of the available hardware and software to emulate SNNs for investigating biological entities and their application on artificial systems. Neuromorphics is identified as a promising tool to embody SNNs in real physical systems and different neuromorphic chips are compared. The concepts required for describing SNNs are dissected and contextualized in the new no man’s land between cognitive neuroscience and artificial intelligence. Although there are recent reviews on the application of neuromorphic computing in various modules of the guidance, navigation, and control of robotic systems, the focus of this paper is more on closing the cognition loop in SNN-embodied robotics. We argue that biologically viable spiking neuronal models used for electroencephalogram signals are excellent candidates for furthering our knowledge of the explainability of SNNs. We complete our survey by reviewing different robotic modules that can benefit from neuromorphic hardware, e.g., perception (with a focus on vision), localization, and cognition. We conclude that the tradeoff between symbolic computational power and biological plausibility of hardware can be best addressed by neuromorphics, whose presence in neurorobotics provides an accountable empirical testbench for investigating synthetic and natural embodied cognition. We argue this is where both theoretical and empirical future work should converge in multidisciplinary efforts involving neuroscience, artificial intelligence, and robotics.

This systematic review and meta-analysis of global peer-reviewed neuroimaging findings preliminarily assessed the magnitude of effect sizes (ES) of the influences of family poverty/low socioeconomic status (SES) on children’s neurocognition and whether these were consistently detrimental. The literature search (Web of Science; PUBMED; MEDLINE: PSYCNET; GOOGLE SCHOLAR; SCIENCEDIRECT) included 66 studies from 1988 to 2022; 85% of the studies included were conducted in Western, high-income nations. Bayesian models, corrected by study sizes and variances, revealed ESs were heterogeneous across countries and measurements. Bayesian and standard hypothesis testing indicated high and low SES groups showed similar behavioral performances in neuroimaging-concurrent tasks. Except for Magnetic Resonance Imaging studies, ESs were small-to-intermediate with modest reliability. The strongest ESs were found for attention, mathematical performance, language, and cortical volume, followed by intermediate ESs for reading and socioemotional processes. Differentials in resting activity and connectivity, working memory, and executive functions yielded small effects. A bibliometric analysis showed a significant proportion of the literature attributed neurocognitive deficits to low SES, despite overlooking the under-representativity of non-Western and low-income countries, potential influences of racial/ethnic differences, and measurement sensitivity/specificity discrepancies. To reach United Nations Sustainable Development Goals, policies and interventions should consider regional, structural, or environmental ecologies beyond the individual, critically probing implicit deficit attributions.

We assessed the neurocognitive correlates of auditory executive attention in low socioeconomic status 9–12-year-old children—with and without training in a social music program (OrKidstra). Event-related potentials (ERPs) were recorded during an auditory Go/NoGo task utilizing 1100 Hz and 2000 Hz pure tones. We examined Go trials, which required attention, tone discrimination and executive response control. We measured Reaction Times (RTs), accuracy and amplitude of relevant ERP signatures: N100-N200 complex, P300, and Late Potentials (LP). Children also completed a screening test for auditory sensory sensitivity and the Peabody Picture Vocabulary Test (PPVT-IV) to assess verbal comprehension. OrKidstra children had faster RTs and larger ERP amplitudes to the Go tone. Specifically, compared to their comparison counterparts, they showed more negative-going polarities bilaterally for N1-N2 and LP signatures across the scalp and larger P300s in parietal and right temporal electrodes; some enhancements were lateralized (i.e., left frontal, and right central and parietal electrodes). Because auditory screening yielded no between-group differences, results suggest that music training did not enhance sensory processing but perceptual and attentional skills, possibly shifting from top-down to more bottom-up processes. Findings have implications for socially based music training interventions in school, specifically for socioeconomically disadvantaged children.

This article will explore the expressivity and tractability of vividness, as viewed from the interdisciplinary perspective of the cognitive sciences, including the sub-disciplines of artificial intelligence, cognitive psychology, neuroscience, and phenomenology. Following the precursor work by Benussi in experimental phenomenology, seminal papers by David Marks in psychology and, later, Hector Levesque in computer science, a substantial part of the discussion has been around a symbolic approach to the concept of vividness. At the same time, a similar concept linked to semantic memory, imagery, and mental models has had a long history in cognitive psychology, with new emerging links to cognitive neuroscience. More recently, there is a push towards neural-symbolic representations which allows room for the integration of brain models of vividness to a symbolic concept of vividness. Such works lead to question the phenomenology of vividness in the context of consciousness, and the related ethical concerns. The purpose of this paper is to review the state of the art, advances, and further potential developments of artificial-human vividness while laying the ground for a shared conceptual platform for dialogue, communication, and debate across all the relevant sub-disciplines. Within such context, an important goal of the paper is to define the crucial role of vividness in grounding simulation and modeling within the psychology (and neuroscience) of human reasoning.

In this scoping review, we provide a selective mapping of the global literature on the effects of air pollution on the life-span development of the central nervous system. Our synthesis first defines developmental neurotoxicants and the model effects of particulate matter. We then discuss air pollution as a test bench for neurotoxicants, including animal models, the framework of systemic inflammation in all affected organs of the body, and the cascade effects on the developing brain, with the most prevalent neurological structural and functional outcomes. Specifically, we focus on evidence on magnetic resonance imaging and neurodegenerative diseases, and the links between neuronal apoptosis and inflammation. There is evidence of a developmental continuity of outcomes and effects that can be observed from utero to aging due to severe or significant exposure to neurotoxicants. These substances alter the normal trajectory of neurological aging in a propulsive way towards a significantly higher rate of acceleration than what is expected if our atmosphere were less polluted. The major aggravating role of this neurodegenerative process is linked with the complex action of neuroinflammation. However, most recent evidence learned from research on the effects of COVID-19 lockdowns around the world suggests that a short-term drastic improvement in the air we breathe is still possible. Moreover, the study of mitohormesis and vitagenes is an emerging area of research interest in anti-inflammatory and antidegenerative therapeutics, which may have enormous promise in combatting the deleterious effects of air pollution through pharmacological and dietary interventions.

In the last decade there has been significant growth in the interest and application of using EEG (electroencephalography) outside of laboratory as well as in medical and clinical settings, for more ecological and mobile applications. However, for now such applications have mainly included military, educational, cognitive enhancement, and consumer-based games. Given the monetary and ecological advantages, consumer-grade EEG devices such as the Emotiv EPOC have emerged, however consumer-grade devices make certain compromises of data quality in order to become affordable and easy to use. The goal of this study was to investigate the reliability and accuracy of EPOC as compared to a research-grade device, Brainvision. To this end, we collected data from participants using both devices during three distinct cognitive tasks designed to elicit changes in arousal, valence, and cognitive load: namely, Affective Norms for English Words, International Affective Picture System, and the n-Back task. Our design and analytical strategies followed an ideographic person-level approach (electrode-wise analysis of vincentized repeated measures). We aimed to assess how well the Emotiv could differentiate between mental states using an Event-Related Band Power approach and EEG features such as amplitude and power, as compared to Brainvision. The Emotiv device was able to differentiate mental states during these tasks to some degree, however it was generally poorer than Brainvision, with smaller effect sizes. The Emotiv may be used with reasonable reliability and accuracy in ecological settings and in some clinical contexts (for example, for training professionals), however Brainvision or other, equivalent research-grade devices are still recommended for laboratory or medical based applications.

We bridge two analogous concepts of comorbidity, dyslexia-dyscalculia and reading-mathematical disabilities, in neuroscience and education, respectively. We assessed the cognitive profiles of 360 individuals (mean age 25.79 ± 13.65) with disability in reading alone (RD group), mathematics alone (MD group) and both (comorbidity: MDRD group), with tests widely used in both psychoeducational and neuropsychological batteries. As expected, the MDRD group exhibited reading deficits like those shown by the RD group. The former group also exhibited deficits in quantitative reasoning like those shown by the MD group. However, other deficits related to verbal working memory and semantic memory were exclusive to the MDRD group. These findings were independent of gender, age, or socioeconomic and demographic factors. Through a systematic exhaustive review of clinical neuroimaging literature, we mapped the resulting cognitive profiles to correspondingly plausible neuroanatomical substrates of dyslexia and dyscalculia. In our resulting “probing” model, the complex set of domain-specific and domain-general impairments shown in the comorbidity of reading and mathematical disabilities are hypothesized as being related to atypical development of the left angular gyrus. The present neuroeducational approach bridges a long-standing transdisciplinary divide and contributes a step further toward improved early prediction, teaching and interventions for children and adults with combined reading and math disabilities.

Background: Transcranial direct current stimulation (tDCS) is a safe, tolerable, and acceptable technique in adults. However, there is limited evidence for its safety in youth. Although limited, there are a handful of important empirical articles that have evaluated safety and tolerability outcomes in youth. However, a synthesis of pediatric safety studies is not currently available. Objective: To synthesize objective evidence regarding the safety and tolerability of pediatric tDCS based on the current state of the literature. Methods: Our search and report used PRISMA guidelines. Our method systematically examined investigations purposefully designed to evaluate the safety, tolerability, and acceptability of tDCS in healthy and atypical youth that were submitted to three databases, from the beginning of the database to November 2019. Safety considerations were evaluated by studies utilizing neuroimaging, physiological changes, performance on tasks, and by analyzing reported and objective side effects; tolerability via rate of adverse events; and acceptability via rate of dropouts. Results: We report on 203 sham sessions, 864 active sessions up to 2 mA, and 303 active hours of stimulation in 156 children. A total of 4.4% of the active sessions were in neurotypical controls, with the other 95.6% in clinical subjects. Conclusion: In spite of the fact that the current evidence is sporadic and scarce, the presently reviewed literature provides support for the safety, tolerability, and acceptability, of tDCS in youth for 1–20 sessions of 20 min up to 2 mA. Future pediatric tDCS research is encouraged.

The interest in using non-invasive brain stimulation (NIBS) for the treatment of major depression (MD), including treatment resistant depression, is growing rapidly. The paper by Bennabi and Haffen (Brain Sci. 2018, 8) was an important step towards the formal acceptance of transcranial direct current stimulation (tDCS) as a possible form of therapy. Their review demonstrated favourable support for the beneficial effects of tDCS for MD, coupled with necessary practical considerations, such as its relatively low cost, portability/ease of use in clinical settings, non-invasiveness, and good tolerability. Here, we provide a follow-up to their review and sketch a current update. Means for optimizing tDCS efficacy and potential limitations of current studies are discussed.

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This paper describes continuing research on the building of neurocognitive models of the internal mental and brain processes of children using a novel adapted combination of existing computational approaches and tools, and using electro-encephalographic (EEG) data to validate the models. The guiding working model which was pragmatically selected for investigation was the established and widely used Adaptive Control of Thought-Rational (ACT-R) modeling architecture from cognitive science. The anatomo-functional circuitry covered by ACT-R is validated by MRI-based neuroscience research. The present experimental data was obtained from a cognitive neuropsychology study involving preschool children (aged 4–6), which measured their visual selective attention and word comprehension behaviors. The collection and analysis of Event-Related Potentials (ERPs) from the EEG data allowed for the identification of sources of electrical activity known as dipoles within the cortex, using a combination of computational tools (Independent Component Analysis, FASTICA; EEG-Lab DIPFIT). The results were then used to build neurocognitive models based on Python ACT-R such that the patterns and the timings of the measured EEG could be reproduced as simplified symbolic representations of spikes, built through simplified electric-field simulations. The models simulated ultimately accounted for more than three-quarters of variations spatially and temporally in all electrical potential measurements (fit of model to dipole data expressed as R2 ranged between 0.75 and 0.98; P < 0.0001). Implications for practical uses of the present work are discussed for learning and educational applications in non-clinical and special needs children's populations, and for the possible use of non-experts (teachers and parents).

According to the latest estimates, about 2 billion children around the world are exposed to severe urban outdoor air pollution. Transdisciplinary, multi-method findings from epidemiology, developmental neuroscience, psychology, and pediatrics, show detrimental outcomes associated with pre- and postnatal exposure are found at all ages. Affected brain-related functions include perceptual and sensory information processing, intellectual and cognitive development, memory and executive functions, emotion and self-regulation, and academic achievement. Correspondingly, with the breakdown of natural barriers against entry and translocation of toxic particles in the brain, the most common structural changes are responses promoting neuroinflammation and indicating early neurodegenerative processes. In spite of the gaps in current scientific knowledge and the challenges posed by non-scientific issues that influence policy, the evidence invites the conclusion that urban outdoor air pollution is a serious threat to healthy brain development which may set the conditions for neurodegenerative diseases. Such evidence supports the perspective that urgent strategic precautionary actions, minimizing exposure and attenuating its effects, are needed to protect children and their brain development.

Obesity in youth increases the risk of type 2 diabetes (T2D), and both are risk factors for neurocognitive deficits. Exercise attenuates the risk of obesity and T2D while improving cognitive function. In adults, these benefits are associated with the actions of the brain-derived neurotrophic factor (BDNF), a protein critical in modulating neuroplasticity, glucose regulation, fat oxidation, and appetite regulation in adults. However, little research exists in youth. This study examined the associations between changes in diabetes risk factors and changes in BDNF levels after 6 months of exercise training in adolescents with obesity. The sample consisted of 202 postpubertal adolescents with obesity (70% females) aged 14–18 years who were randomized to 6 months of aerobic and/or resistance training or nonexercise control. All participants received a healthy eating plan designed to induce a 250/kcal deficit per day. Resting serum BDNF levels and diabetes risk factors, such as fasting glucose, insulin, homeostasis model assessment (HOMA-B—beta cell insulin secretory capacity) and (HOMA-IS—insulin sensitivity), and hemoglobin A1c (HbA1c), were measured after an overnight fast at baseline and 6 months. There were no significant intergroup differences on changes in BDNF or diabetes risk factors. In the exercise group, increases in BDNF were associated with reductions in fasting glucose (β = −6.57, SE = 3.37, p=0.05) and increases in HOMA-B (β = 0.093, SE = 0.03, p=0.004) after controlling for confounders. No associations were found between changes in diabetes risk factors and BDNF in controls. In conclusion, exercise-induced reductions in some diabetes risk factors were associated with increases in BDNF in adolescents with obesity, suggesting that exercise training may be an effective strategy to promote metabolic health and increases in BDNF, a protein favoring neuroplasticity. This trial is registered with ClinicalTrials.gov NCT00195858, September 12, 2005 (funded by the Canadian Institutes of Health Research).

We reanalyzed, modeled and simulated Event-Related Potential (ERP) data from 13 healthy children (Mean age = 5.12, Standard Deviation = 0.75) during a computerized visual sustained target detection task. Extending an ERP-based ACT−R (Adaptive Control of Thought−Rational) neurocognitive modeling approach, we tested whether visual sustained selective-set attention in preschool children involves the enhancement of neural response to targets, and it shows key adult-like features (neurofunctional homology). Blinded automatic peaks analysis was conducted on vincentized binned grand ERP averages. Time-course and distribution of scalp activity were detailed through topographic mapping and paths analysis. Reaction times and accuracy were also measured. Adult Magnetic Resonance Imaging-based mapping using ACT−R dipole source modeling and electric-field spiking simulation provided very good fit with the actual ERP data (R2 > 0.70). In most electrodes, between 50 and 400 ms, ERPs concurrent with target presentation were enhanced relative to distractor, without manual response confounds. Triangulation of peak analysis, ACT−R modeling and simulation for the entire ERP epochs up to the moment of manual response (~700 ms, on average) suggested converging evidence of distinct but interacting processes of enhancement and planning for response release/inhibition, respectively. The latter involved functions and structures consistent with adult ERP activity which might correspond to a large-scale network, implicating Dorsal and Ventral Attentional Networks, corticostriatal loops, and subcortical hubs connected to prefrontal cortex top-down working memory executive control. Although preliminary, the present approach suggests novel directions for further tests and falsifiable hypotheses on the origins and development of visual selective attention and their ERP correlates.

We performed a bibliometric analysis of the peer-reviewed literature on vividness between 1900 and 2019 indexed by the Web of Science and compared it with the same analysis of publications on consciousness and mental imagery. While we observed a similarity between the citation growth rates for publications about each of these three subjects, our analysis shows that these concepts rarely overlap (co-occur) in the literature, revealing a surprising paucity of research about these concepts taken together. A disciplinary analysis shows that the field of Psychology dominates the topic of vividness, even though the total number of publications containing that term is small and the concept occurs in several other disciplines such as Computer Science and Artificial Intelligence. The present findings suggest that without a coherent unitary framework for the use of vividness in research, important opportunities for advancing the field might be missed. In contrast, we suggest that an evidence-based framework (such as the bibliometric analytic methods as exemplified here) will help to guide research from all disciplines that are concerned with vividness and help to resolve the challenge of epistemic incommensurability amongst published research in multidisciplinary fields.

Using secondary database analysis, we tested whether the (implicit) familiarity of eliciting noun-cues and the (explicit) vividness of corresponding imagery exerted additive or interactive influences on verbal learning, as measured by the probability of incidental noun recall and image latency times (RTs). Noun-cues with incongruent levels of vividness and familiarity (high/low; low/high, respectively) at encoding were subsequently associated at retrieval with the lowest recall probabilities, while noun-cues related with congruent levels (high/high; low/low) were associated with higher recall probabilities. RTs in the high vividness and high familiarity grouping were significantly faster than all other subsets (low/low, low/high, high/low) which did not significantly differ among each other. The findings contradict: (1) associative theories predicting positive monotonic relationships between memory strength and learning; and (2) non-monotonic plasticity hypothesis (NMPH), aiming at generalizing the non-monotonic relationship between a neuron’s excitation level and its synaptic strength to broad neural networks. We propose a dualistic neuropsychological model of memory consolidation that mimics the global activity in two large resting-state networks (RSNs), the default mode network (DMN) and the task-positive-network (TPN). Based on this model, we suggest that incongruence and congruence between vividness and familiarity reflect, respectively, competition and synergy between DMN and TPN activity. We argue that competition or synergy between these RSNs at the time of stimulus encoding disproportionately influences long term semantic memory consolidation in healthy controls. These findings could assist in developing neurophenomenological markers of core memory deficits currently hypothesized to be shared across multiple psychopathological conditions.

This is a predictive validity study examining the extent to which developmental vulnerability at kindergarten entry (as measured by the Early Development Instrument, EDI) is associated with children's basic skills in 4th grade (as measured by the Foundation Skills Assessment, FSA).Relative risk analysis was performed on a large database linking individual-level EDI ratings to the scores the same children obtained on a provincial assessment of academic skills (FSA--Foundation Skills Assessment) four years later. We found that early vulnerability in kindergarten is associated with the basic skills that underlie populations of children's academic achievement in reading, writing and math, indicating that the Early Development Instrument permits to predict achievement-related skills four years in advance.The EDI can be used to predict children's educational trends at the population level and can help select early prevention and intervention programs targeting pre-school populations at minimum cost.