107 research outputs found
Young Children with ASD Use Lexical and Referential Information During On-line Sentence Processing
Research with adults and older children indicates that verb biases are strong influences on listeners’ interpretations when processing sentences, but they can be overruled. In this paper, we ask two questions: (i) are children with Autism Spectrum Disorder (ASD) who are high functioning sensitive to verb biases like their same age typically developing peers?, and (ii) do young children with ASD and young children with typical development (TD) override strong verb biases to consider alternative interpretations of ambiguous sentences? Participants were aged 5–9 years (mean age 6.65 years): children with ASD who were high functioning and children with TD. In task 1, biasing and neutral verbs were included (e.g., eat cake versus move cake). In task 2, the focus was on whether the prepositional phrase occurring with an instrument biasing verb (e.g., ‘Chop the tree with the axe’) was interpreted as an instrument even if the named item was an implausible instrument (e.g., candle in ‘Cut the cake with the candle’). Overall, the results showed similarities between groups but the ASD group was generally slower. In task 1, both groups looked at the named object faster in the biasing than the non-biasing condition, and in the biasing condition the ASD group looked away from the target more quickly than the TD group. In task 2, both groups identified the target in the prepositional phrase. They were more likely to override the verb instrument bias and consider the alternative (modification) interpretation in the implausible condition (e.g., looking at the picture of a cake with a candle on it’). Our findings indicate that children of age 5 years and above can use context to override verb biases. Additionally, an important component of the sentence processing mechanism is largely intact for young children with ASD who are high functioning. Like children with TD, they draw on verb semantics and plausibility in integrating information. However, they are likely to be slower in processing the language they hear. Based on previous findings of associations between processing speed and cognitive functioning, the implication is that their understanding will be negatively affected, as will their academic outcomes
Postrelease movement and habitat selection of translocated pine martens Martes martes
This is the final version. Available from Wiley via the DOI in this record. Monitoring postrelease establishment and movement of animals is important in evaluating conservation translocations. We translocated 39 wild pine martens Martes martes (19 females, 20 males) from Scotland to Wales. We released them into forested areas with no conspecifics in 2015, followed by a second release in 2016, alongside the previously released animals. We used radio-tracking to describe postrelease movement and habitat selection. Six martens (15%) were not re-encountered during the tracking period, of which four undertook long-distance dispersal. For the remaining individuals, we characterized two phases of movement, “exploration” followed by “settlement,” that differed between releases. In the first release, martens remained in exploration phase for a mean of 14.5 days (SE = 3.9 days) and settled at a mean distance of 8.7 km (SE = 1.8 km) from release sites, whereas martens released in year two, alongside resident conspecifics, traveled away from release sites at a faster rate, settling sooner, at a mean of 6.6 days (SE = 1.8 days), but further, at a mean distance of 14.0 km (SE = 1.7 km) from release sites. Animals released in year one did not exhibit habitat preferences overall but within forests they favored recently felled areas, whereas animals released in year two showed strong selection for forested habitat but did not discriminate between forest types. The presence of conspecifics appeared influential for settlement and site fidelity of translocated martens and was associated with more rapid but more distant dispersal of the later cohort. Releases of animals in close proximity appeared to promote site fidelity and rapid establishment of ranges in the recipient environment.University of ExeterVincent Wildlife TrustThe Woodland TrustThe Forestry CommissionCollege of Life and Environmental Sciences of the University of ExeterNatural Resources Wale
Augmented Reality for the assessment of children's spatial memory in real settings
Short-term memory can be defined as the capacity for holding a small amount of information in mind in an active state for a short period of time. There are no available, specific, and adapted instruments to study the development of memory and spatial orientation in people while they are moving. In this paper, we present the ARSM (Augmented Reality Spatial Memory) task, the first Augmented Reality task that involves a user's movement to assess spatial short-term memory in healthy children. The experimental procedure of the ARSM task was designed to assess the children s skill to retain visuospatial information. They were individually asked to remember the real place where augmented reality objects were located. The children (N=76) were divided into two groups: preschool (5-6 year olds) and primary school (7-8 year olds). We found a significant improvement in ARSM task performance in the older group. The correlations between scores for the ARSM task and traditional procedures were significant. These traditional procedures were the Dot Matrix subtest for the assessment of visuospatial short-term memory of the computerized AWMA-2 battery and a parent s questionnaire about a child s everyday spatial memory. Hence, we suggest that the ARSM task has high verisimilitude with spatial short-term memory skills in real life. In addition, we evaluated the ARSM task s usability and perceived satisfaction. The study revealed that the younger children were more satisfied with the ARSM task. This novel instrument could be useful in detecting visuospatial short-term difficulties that affect school academic achievementFunded by the Spanish Government (MINECO) and European Regional Development Fund (FEDER) in the CHILDMNEMOS project TIN2012-37381-C02-01, Gobierno de Aragon (Dpt. Industria e Innovacion), Fondo Social Europeo, Fundacion Universitaria Antonio Gargallo and Obra Social Ibercaja. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Juan, M.; Mendez Lopez, M.; Pérez Hernández, E.; Albiol Pérez, S. (2014). Augmented Reality for the assessment of children's spatial memory in real settings. PLoS ONE. 9(12):113751-113771. https://doi.org/10.1371/journal.pone.0113751S113751113771912Linn, M. C., & Petersen, A. C. (1985). Emergence and Characterization of Sex Differences in Spatial Ability: A Meta-Analysis. Child Development, 56(6), 1479. doi:10.2307/1130467Simmons, F. R., Willis, C., & Adams, A.-M. (2012). Different components of working memory have different relationships with different mathematical skills. Journal of Experimental Child Psychology, 111(2), 139-155. doi:10.1016/j.jecp.2011.08.011Alloway, T. P., & Alloway, R. G. (2010). Investigating the predictive roles of working memory and IQ in academic attainment. Journal of Experimental Child Psychology, 106(1), 20-29. doi:10.1016/j.jecp.2009.11.003Bavin, E. L., Wilson, P. H., Maruff, P., & Sleeman, F. (2005). Spatio‐visual memory of children with specific language impairment: evidence for generalized processing problems. International Journal of Language & Communication Disorders, 40(3), 319-332. doi:10.1080/13682820400027750Szucs, D., Devine, A., Soltesz, F., Nobes, A., & Gabriel, F. (2013). Developmental dyscalculia is related to visuo-spatial memory and inhibition impairment. Cortex, 49(10), 2674-2688. doi:10.1016/j.cortex.2013.06.007Mammarella, I. C., & Cornoldi, C. (2013). An analysis of the criteria used to diagnose children with Nonverbal Learning Disability (NLD). Child Neuropsychology, 20(3), 255-280. doi:10.1080/09297049.2013.796920Alloway TP (2007) Automated Working Memory Assessment. London: The Psychological Corporation.Oades, R. D., & Isaacson, R. L. (1978). The development of food search behavior by rats: The effects of hippocampal damage and haloperidol. Behavioral Biology, 24(3), 327-337. doi:10.1016/s0091-6773(79)90184-6Morris, R. (1984). Developments of a water-maze procedure for studying spatial learning in the rat. Journal of Neuroscience Methods, 11(1), 47-60. doi:10.1016/0165-0270(84)90007-4Olton, D. S. (1987). The radial arm maze as a tool in behavioral pharmacology. Physiology & Behavior, 40(6), 793-797. doi:10.1016/0031-9384(87)90286-1Méndez-López, M., Méndez, M., López, L., & Arias, J. L. (2009). Sexually dimorphic c-Fos expression following spatial working memory in young and adult rats. Physiology & Behavior, 98(3), 307-317. doi:10.1016/j.physbeh.2009.06.006Munoz M, Morris RGM (2009) Episodic memory in animals. In:Squire LR editor. New Encyclopedia of Neuroscience. Oxford: Academic Press. pp.1173–1182.SHORE, D. I., STANFORD, L., MACINNES, W. J., KLEIN, R. M., & BROWN, R. E. (2001). Of mice and men: Virtual Hebb-Williams mazes permit comparison of spatial learning across species. Cognitive, Affective, & Behavioral Neuroscience, 1(1), 83-89. doi:10.3758/cabn.1.1.83Astur, R. S., Taylor, L. B., Mamelak, A. N., Philpott, L., & Sutherland, R. J. (2002). Humans with hippocampus damage display severe spatial memory impairments in a virtual Morris water task. Behavioural Brain Research, 132(1), 77-84. doi:10.1016/s0166-4328(01)00399-0Astur, R. S., Tropp, J., Sava, S., Constable, R. T., & Markus, E. J. (2004). Sex differences and correlations in a virtual Morris water task, a virtual radial arm maze, and mental rotation☆. Behavioural Brain Research, 151(1-2), 103-115. doi:10.1016/j.bbr.2003.08.024Sturz, B. R., & Bodily, K. D. (2010). Encoding of variability of landmark-based spatial information. Psychological Research, 74(6), 560-567. doi:10.1007/s00426-010-0277-4Cánovas, R., García, R. F., & Cimadevilla, J. M. (2011). Effect of reference frames and number of cues available on the spatial orientation of males and females in a virtual memory task. Behavioural Brain Research, 216(1), 116-121. doi:10.1016/j.bbr.2010.07.026Cimadevilla, J. M., Cánovas, R., Iribarne, L., Soria, A., & López, L. (2011). A virtual-based task to assess place avoidance in humans. Journal of Neuroscience Methods, 196(1), 45-50. doi:10.1016/j.jneumeth.2010.12.026Cheng, K. (1986). A purely geometric module in the rat’s spatial representation. Cognition, 23(2), 149-178. doi:10.1016/0010-0277(86)90041-7Burgess, N., Maguire, E. A., Spiers, H. J., & O’Keefe, J. (2001). A Temporoparietal and Prefrontal Network for Retrieving the Spatial Context of Lifelike Events. NeuroImage, 14(2), 439-453. doi:10.1006/nimg.2001.0806Burgess, N., Maguire, E. A., & O’Keefe, J. (2002). The Human Hippocampus and Spatial and Episodic Memory. Neuron, 35(4), 625-641. doi:10.1016/s0896-6273(02)00830-9Passolunghi, M. C., & Mammarella, I. C. (2011). Selective Spatial Working Memory Impairment in a Group of Children With Mathematics Learning Disabilities and Poor Problem-Solving Skills. Journal of Learning Disabilities, 45(4), 341-350. doi:10.1177/0022219411400746Thomas, E., Reeve, R., Fredrickson, A., & Maruff, P. (2011). Spatial memory and executive functions in children. Child Neuropsychology, 17(6), 599-615. doi:10.1080/09297049.2011.567980SPOONER, D., & PACHANA, N. (2006). Ecological validity in neuropsychological assessment: A case for greater consideration in research with neurologically intact populations. Archives of Clinical Neuropsychology, 21(4), 327-337. doi:10.1016/j.acn.2006.04.004Juan, M. C., Alcaniz, M., Monserrat, C., Botella, C., Banos, R. M., & Guerrero, B. (2005). Using Augmented Reality to Treat Phobias. IEEE Computer Graphics and Applications, 25(6), 31-37. doi:10.1109/mcg.2005.143Furió, D., González-Gancedo, S., Juan, M.-C., Seguí, I., & Costa, M. (2013). The effects of the size and weight of a mobile device on an educational game. Computers & Education, 64, 24-41. doi:10.1016/j.compedu.2012.12.015Juan MC, Furió D, Alem L, Ashworth P, Cano J (2011) ARGreenet and BasicGreenet: Two mobile games for learning how to recycle. Proceedings of the 19th International Conference on Computer Graphics, Visualization and Computer Vision. pp.25–32.Furió, D., González-Gancedo, S., Juan, M.-C., Seguí, I., & Rando, N. (2013). Evaluation of learning outcomes using an educational iPhone game vs. traditional game. Computers & Education, 64, 1-23. doi:10.1016/j.compedu.2012.12.001Albrecht, U.-V., Folta-Schoofs, K., Behrends, M., & von Jan, U. (2013). Effects of Mobile Augmented Reality Learning Compared to Textbook Learning on Medical Students: Randomized Controlled Pilot Study. Journal of Medical Internet Research, 15(8), e182. doi:10.2196/jmir.2497Liu, P.-H. E., & Tsai, M.-K. (2012). Using augmented-reality-based mobile learning material in EFL English composition: An exploratory case study. British Journal of Educational Technology, 44(1), E1-E4. doi:10.1111/j.1467-8535.2012.01302.xBaddeley AD (1986) Working memory. Oxford: Clarendon Press.Alloway TP (2012) Working Memory Assessment. Second Edi. London: Pearson Assessment.Kamphaus KW, Perez-Hernandez E, Sanchez-Sanchez F (2014) Cuestionario de Evaluación Clínica de la Memoria. In press. Madrid: TEA Ediciones.Smith, A. D., Gilchrist, I. D., & Hood, B. M. (2005). Children’s Search Behaviour in Large-Scale Space: Developmental Components of Exploration. Perception, 34(10), 1221-1229. doi:10.1068/p5270Piccardi, L., Palermo, L., Leonzi, M., Risetti, M., Zompanti, L., D’Amico, S., & Guariglia, C. (2014). The Walking Corsi Test (WalCT): A Normative Study of Topographical Working Memory in a Sample of 4- to 11-Year-Olds. The Clinical Neuropsychologist, 28(1), 84-96. doi:10.1080/13854046.2013.863976Gathercole, S. E., Pickering, S. J., Ambridge, B., & Wearing, H. (2004). The Structure of Working Memory From 4 to 15 Years of Age. Developmental Psychology, 40(2), 177-190. doi:10.1037/0012-1649.40.2.177Best, J. R., & Miller, P. H. (2010). A Developmental Perspective on Executive Function. Child Development, 81(6), 1641-1660. doi:10.1111/j.1467-8624.2010.01499.xBianchini, F., Incoccia, C., Palermo, L., Piccardi, L., Zompanti, L., Sabatini, U., … Guariglia, C. (2010). Developmental topographical disorientation in a healthy subject. Neuropsychologia, 48(6), 1563-1573. doi:10.1016/j.neuropsychologia.2010.01.025Iaria, G., & Barton, J. J. S. (2010). Developmental topographical disorientation: a newly discovered cognitive disorder. Experimental Brain Research, 206(2), 189-196. doi:10.1007/s00221-010-2256-9Lowe, P. A., Mayfield, J. W., & Reynolds, C. R. (2003). Gender differences in memory test performance among children and adolescents. Archives of Clinical Neuropsychology, 18(8), 865-878. doi:10.1093/arclin/18.8.865Barnfield, A. M. C. (1999). Development of Sex Differences in Spatial Memory. Perceptual and Motor Skills, 89(1), 339-350. doi:10.2466/pms.1999.89.1.339Alloway, T. P., Gathercole, S. E., Kirkwood, H., & Elliott, J. (2009). The working memory rating scale: A classroom-based behavioral assessment of working memory. Learning and Individual Differences, 19(2), 242-245. doi:10.1016/j.lindif.2008.10.003Injoque-Ricle, I., Calero, A. D., Alloway, T. P., & Burin, D. I. (2011). Assessing working memory in Spanish-speaking children: Automated Working Memory Assessment battery adaptation. Learning and Individual Differences, 21(1), 78-84. doi:10.1016/j.lindif.2010.09.012Jones, A., Scanlon, E., Tosunoglu, C., Morris, E., Ross, S., Butcher, P., & Greenberg, J. (1999). Contexts for evaluating educational software. Interacting with Computers, 11(5), 499-516. doi:10.1016/s0953-5438(98)00064-2Mayes, J. ., & Fowler, C. . (1999). Learning technology and usability: a framework for understanding courseware. Interacting with Computers, 11(5), 485-497. doi:10.1016/s0953-5438(98)00065-4Squires, D., & Preece, J. (1999). Predicting quality in educational software: Interacting with Computers, 11(5), 467-483. doi:10.1016/s0953-5438(98)00063-0Sun, P.-C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202. doi:10.1016/j.compedu.2006.11.007Lee, S. J., Srinivasan, S., Trail, T., Lewis, D., & Lopez, S. (2011). Examining the relationship among student perception of support, course satisfaction, and learning outcomes in online learning. The Internet and Higher Education, 14(3), 158-163. doi:10.1016/j.iheduc.2011.04.001Lyons KE, Zelazo PD (2011) Monitoring, metacognition, and executive function: elucidating the role of self-reflection in the development of self-regulation. In:Benson Jeditor. Advances in Child Development and Behavior. Burlington: Academic Press. pp.379–412
A gestural repertoire of 1-2year old human children : in search of the ape gestures
This project was made possible with the generous financial help of the Baverstock Bequest to the Psychology and Neuroscience Department at the University of St Andrews.When we compare human gestures to those of other apes, it looks at first like there is nothing much to compare at all. In adult humans, gestures are thought to be a window into the thought processes accompanying language, and sign languages are equal to spoken language with all of its features. While some research firmly emphasises the difference between human gestures and those of other apes, the question about whether there are any commonalities has rarely been investigated, and is mostly confined to pointing gestures. The gestural repertoires of nonhuman ape species have been carefully studied and described with regard to their form and function – but similar approaches are much rarer in the study of human gestures. This paper applies the methodology commonly used in the study of nonhuman ape gestures to the gestural communication of human children in their second year of life. We recorded (n=13) children’s gestures in a natural setting with peers and caregivers in Germany and Uganda. Children employed 52 distinct gestures, 46 (89%) of which are present in the chimpanzee repertoire. Like chimpanzees, they used them both singly, and in sequences; and employed individual gestures flexibly towards different goals.Publisher PDFPeer reviewe
Online processing of sentences containing noun modification in young children with high-functioning autism
Background: There is variability in the language of children with autism, even those who are high functioning. However, little is known about how they process language structures in real time, including how they handle potential ambiguity, and whether they follow referential constraints. Previous research with older autism spectrum disorder (ASD) participants has shown that these individuals can use context to access rapidly the meaning of ambiguous words. The severity of autism has also been shown to influence the speed in which children with ASD access lexical information. Aims: To understand more about how children with ASD process language in real time (i.e., as it unfolds). The focus was the integration of information and use of referential constraints to identify a referent named in a sentence. Methods & Procedures: We used an eye-tracking task to compare performance between young, high-functioning children with autism (HFA) and children with typical development (TD). A large sample of 5–9-year-old children (mean age = 6;8 years), 48 with HFA and 56 with TD participated; all were attending mainstream schools. For each item participants were shown a display of four images that differed in two dimensions. Each sentence contained an adjective and noun that restricted the choice from four to two (the target and competitor), followed by a prepositional phrase (e.g., the blue square with dots); this added modifying information to provide a unique description of the target. We calculated looking time at the target, the competitor and the two distractors for each 200 ms time interval as children processed the sentence and looked at the display. Generalized estimating equations were used to carry out repeated-measures analyses on the proportion of looking time to target and competitor and time to fixate to target. Outcomes & Results: Children in both groups (HFA and TD) looked at the target and competitor more than at the distractors following the adjective and noun and following the modifying information in the prepositional phrase more at the target. However, the HFA group was significantly slower in both phases and looked proportionally less at the target. Across the sample, IQ and language did not affect the results; however, age and attention had an impact. The older children showed an advantage in processing the information as did the children with higher attention scores. Conclusions & Implications: The HFA group took longer than the TD group to integrate the disambiguating information provided in the course of processing a sentence and integrate it with the visual information, indicating that for the ASD group incremental processing was not as advanced as for children with ASD, and they were less sensitive to referential conventions. Training for young children with ASD on the use of referential conventions and available contextual clues may be of benefit to them in understanding the language they hear
Young Children with ASD Use Lexical and Referential Information During On-line Sentence Processing
Research with adults and older children indicates that verb biases are strong influences on listeners' interpretations when processing sentences, but they can be overruled. In this paper, we ask two questions: (i) are children with Autism Spectrum Disorder (ASD) who are high functioning sensitive to verb biases like their same age typically developing peers?, and (ii) do young children with ASD and young children with typical development (TD) override strong verb biases to consider alternative interpretations of ambiguous sentences? Participants were aged 5-9 years (mean age 6.65 years): children with ASD who were high functioning and children with TD. In task 1, biasing and neutral verbs were included (e.g., eat cake versus move cake). In task 2, the focus was on whether the prepositional phrase occurring with an instrument biasing verb (e.g., 'Chop the tree with the axe') was interpreted as an instrument even if the named item was an implausible instrument (e.g., candle in 'Cut the cake with the candle'). Overall, the results showed similarities between groups but the ASD group was generally slower. In task 1, both groups looked at the named object faster in the biasing than the non-biasing condition, and in the biasing condition the ASD group looked away from the target more quickly than the TD group. In task 2, both groups identified the target in the prepositional phrase. They were more likely to override the verb instrument bias and consider the alternative (modification) interpretation in the implausible condition (e.g., looking at the picture of a cake with a candle on it'). Our findings indicate that children of age 5 years and above can use context to override verb biases. Additionally, an important component of the sentence processing mechanism is largely intact for young children with ASD who are high functioning. Like children with TD, they draw on verb semantics and plausibility in integrating information. However, they are likely to be slower in processing the language they hear. Based on previous findings of associations between processing speed and cognitive functioning, the implication is that their understanding will be negatively affected, as will their academic outcomes
- …