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Detecting non-adjacent dependencies is the exception rather than the rule.

ABSTRACT: Statistical learning refers to our sensitivity to the distributional properties of our environment. Humans have been shown to readily detect the dependency relationship of events that occur adjacently in a stream of stimuli but processing non-adjacent dependencies (NADs) appears more challenging. In the present study, we tested the ability of human participants to detect NADs in a new Hebb-naming task that has been proposed recently to study regularity detection in a noisy environment. In three experiments, we found that most participants did not manage to extract NADs. These results suggest that the ability to learn NADs in noise is the exception rather than the rule. They provide new information about the limits of statistical learning mechanisms.

SUBMITTER: Tosatto L

PROVIDER: S-EPMC9282578 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Detecting non-adjacent dependencies is the exception rather than the rule.

Tosatto Laure L Bonafos Guillem G Melmi Jean-Baptiste JB Rey Arnaud A

PloS one 20220714 7

Statistical learning refers to our sensitivity to the distributional properties of our environment. Humans have been shown to readily detect the dependency relationship of events that occur adjacently in a stream of stimuli but processing non-adjacent dependencies (NADs) appears more challenging. In the present study, we tested the ability of human participants to detect NADs in a new Hebb-naming task that has been proposed recently to study regularity detection in a noisy environment. In three ...[more]

PMID: 35834512

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Project description:The ability to learn and process sequential dependencies is essential for language acquisition and other cognitive domains. Recent studies suggest that the learning of adjacent (e.g., "A-B") versus nonadjacent (e.g., "A-X-B") dependencies have different cognitive demands, but the neural correlates accompanying such processing are currently underspecified. We developed a sequential learning task in which sequences of printed nonsense syllables containing both adjacent and nonadjacent dependencies were presented. After incidentally learning these grammatical sequences, twenty-one healthy adults (age M = 22.1, 12 females) made familiarity judgments about novel grammatical sequences and ungrammatical sequences containing violations of the adjacent or nonadjacent structure while in a 3T MRI scanner. Violations of adjacent dependencies were associated with increased BOLD activation in both posterior (lateral occipital and angular gyrus) as well as frontal regions (e.g., medial frontal gyrus, inferior frontal gyrus). Initial results indicated no regions showing significant BOLD activations for the violations of nonadjacent dependencies. However, when using a less stringent cluster threshold, exploratory analyses revealed that violations of nonadjacent dependencies were associated with increased activation in subcallosal cortex, paracingulate cortex, and anterior cingulate cortex (ACC). Finally, when directly comparing the adjacent condition to the nonadjacent condition, we found significantly greater levels of activation for the right superior lateral occipital cortex (BA 19) for the adjacent relative to nonadjacent condition. In sum, the detection of violations of adjacent and nonadjacent dependencies appear to involve distinct neural networks, with perceptual brain regions mediating the processing of adjacent but not nonadjacent dependencies. These results are consistent with recent proposals that statistical-sequential learning is not a unified construct but depends on the interaction of multiple neurocognitive mechanisms acting together.

Project description:IntroductionTicks are the most common arthropod vectors of both human and animal diseases in Europe, and the Ixodes ricinus tick species is able to transmit a large number of bacteria, viruses and parasites. Ticks may also be co-infected with several pathogens, with a subsequent high likelihood of co-transmission to humans or animals. However few data exist regarding co-infection prevalences, and these studies only focus on certain well-known pathogens. In addition to pathogens, ticks also carry symbionts that may play important roles in tick biology, and could interfere with pathogen maintenance and transmission. In this study we evaluated the prevalence of 38 pathogens and four symbionts and their co-infection levels as well as possible interactions between pathogens, or between pathogens and symbionts.Methodology/principal findingsA total of 267 Ixodes ricinus female specimens were collected in the French Ardennes and analyzed by high-throughput real-time PCR for the presence of 37 pathogens (bacteria and parasites), by rRT-PCR to detect the presence of Tick-Borne encephalitis virus (TBEV) and by nested PCR to detect four symbionts. Possible multipartite interactions between pathogens, or between pathogens and symbionts were statistically evaluated. Among the infected ticks, 45% were co-infected, and carried up to five different pathogens. When adding symbiont prevalences, all ticks were infected by at least one microorganism, and up to eight microorganisms were identified in the same tick. When considering possible interactions between pathogens, the results suggested a strong association between Borrelia garinii and B. afzelii, whereas there were no significant interactions between symbionts and pathogens.Conclusion/significanceOur study reveals high pathogen co-infection rates in ticks, raising questions about possible co-transmission of these agents to humans or animals, and their consequences to human and animal health. We also demonstrated high prevalence rates of symbionts co-existing with pathogens, opening new avenues of enquiry regarding their effects on pathogen transmission and vector competence.

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Detecting non-adjacent dependencies is the exception rather than the rule.

Publications

Detecting non-adjacent dependencies is the exception rather than the rule.

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