A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
., Kujala & Näätänen, 2010) . According to Dweck's (2006) definition, mindsets are beliefs that individuals hold about their most basic qualities and abilities. ...doi:10.4236/psych.2016.79125 fatcat:or74nx7eb5hw3edndst5ls2y6a
Figure adapted from Kujala et al. (2004) . Fig. 5. ... ., 1978; Nä ä tä nen, 1990; Nä ä tä nen and Winkler, 1999; Kujala et al., 2007) . ...doi:10.1016/j.biopsycho.2009.03.010 pmid:19482230 fatcat:ffux27pl5ffa3iflhesfeajjgi
Event-related brain potentials (ERP) were recorded to two spoken words, / paeti / and / peti /. The vowel difference between the two words results in a semantical difference in Finnish, but not in Hungarian, in which / ae / and / e / are perceived as allophones of the same vowel /´/. As a consequence, native Hungarian speakers, who had not studied Finnish before being tested, could not categorize the two word stimuli. In the main experiment, native Hungarian speakers, who fluently spokedoi:10.1016/s0926-6410(03)00205-2 pmid:14561466 fatcat:ja5t34i6hrab5evhkmxonczu6m
more »... were presented with two oddball sequences in which / paeti / was the frequent standard stimulus, / peti / the infrequent deviant. In addition, very rare target words were also included. In one condition, the targets were Hungarian words, whereas in the other, they were Finnish words. The participants' sense of being in two different language environments was further encouraged by having separate experimenters conducting the two conditions, one speaking with the subjects only in Hungarian, the other only in Finnish. Language context had no effect on the mismatch negativity ERP component elicited by the deviant word stimuli. This result suggests that language context does not affect the pre-attentive detection of auditory deviance. (I. Winkler). regular feature of the preceding sound sequence. Thus, 0926-6410 / 03 / $ -see front matter
., 2013; Kujala and Näätänen, 2001 ) may aid the interpretation of our ISC results. ...doi:10.1101/677674 fatcat:pfltlyelpvhvvo6n2assrvpx7y
High-dimensional collections of 0-1 data occur in many applications. The attributes in such data sets are typically considered to be unordered. However, in many cases there is a natural total or partial order ≺ underlying the variables of the data set. Examples of variables for which such orders exist include terms in documents, courses in enrollment data, and paleontological sites in fossil data collections. The observations in such applications are flat, unordered sets; however, the data setsdoi:10.1145/956750.956768 dblp:conf/kdd/GionisKM03 fatcat:smtbwqmr3vdm3fvzllsyl67zui
more »... respect the underlying ordering of the variables. By this we mean that if A ≺ B ≺ C are three variables respecting the underlying ordering ≺, and both of variables A and C appear in an observation, then, up to noise levels, variable B also appears in this observation. Similarly, if A1 ≺ A2 ≺ · · · ≺ A l−1 ≺ A l is a longer sequence of variables, we do not expect to see many observations for which there are indices i < j < k such that Ai and A k occur in the observation but Aj does not. In this paper we study the problem of discovering fragments of orders of variables implicit in collections of unordered observations. We define measures that capture how well a given order agrees with the observed data. We describe a simple and efficient algorithm for finding all the fragments that satisfy certain conditions. We also discuss the sometimes necessary postprocessing for selecting only the best fragments of order. Also, we relate our method with a sequencing approach that uses a spectral algorithm, and with the consecutive ones problem. We present experimental results on some real data sets
However, activity related to semantic priming for spoken words was also found in a fMRI study when the subjects were engaged in a demanding visual task (Rämä, Relander, Carlson, Salonen, & Kujala, 2006 ...doi:10.1162/jocn.2009.21127 pmid:18823236 fatcat:lftu2ckrzfgkvl7qxdtcfn5ata
Citation: Partanen E, Kujala T, Tervaniemi M, Huotilainen M (2013) Prenatal Music Exposure Induces Long-Term Neural Effects. PLoS ONE 8(10): e78946. ...doi:10.1371/journal.pone.0078946 pmid:24205353 pmcid:PMC3813619 fatcat:jhmkm7naw5egnn543wde4rg2iq
A unique feature of human communication system is our ability to rapidly acquire new words and build large vocabularies. However, its neurobiological foundations remain largely unknown. In an electrophysiological study optimally designed to probe this rapid formation of new word memory circuits, we employed acoustically controlled novel word-forms incorporating native and non-native speech sounds, while manipulating the subjects' attention on the input. We found a robust index of neurolexicaldoi:10.1016/j.neuroimage.2015.05.098 pmid:26074199 fatcat:4m2yjejti5dmnommbh7ysbkk2a
more »... mory-trace formation: a rapid enhancement of the brain's activation elicited by novel words during a short (~30 min) perceptual exposure, underpinned by fronto-temporal cortical networks, and, importantly, correlated with behavioural learning outcomes. Crucially, this neural memory trace build-up took place regardless of focused attention on the input or any pre-existing or learnt semantics. Furthermore, it was found only for stimuli with native-language phonology, but not for acoustically closely matching non-native words. These findings demonstrate a specialised cortical mechanism for rapid, automatic and phonology-dependent formation of neural word memory circuits.
(Two of these F values have earlier been reported by Pulvermu¨ller, Kujala, et al., 2001 , as part of results of their experiment 1.) ... In recent studies (Korpilahti, Krause, Holopainen, & Lang, 2001; Pulvermu¨ller, Kujala, et al., 2001; Shtyrov & Pulvermu¨ller, 2002) , an oddball paradigm was used to record the mismatch negativity (MMN ...doi:10.1111/j.1469-8986.2003.00135.x pmid:14693005 fatcat:cvzdgjv3pbbn5gdnmmf4hg7whi
Developmental dyslexia is characterised as an inability to read fluently. Apart from literacy problems, dyslexics have other language difficulties including inefficient speech encoding and deficient novel word learning. Yet, the neural mechanisms underlying these impairments are largely unknown. We tracked online formation of neural memory traces for a novel spoken word-form in dyslexic and normalreading children by recording the brain's electrophysiological response dynamics in a passivedoi:10.1038/s41598-018-31211-0 pmid:30143722 fatcat:pqwhyeyforbxxl433lfmomhuzm
more »... tual exposure session. Crucially, no meaning was assigned to the new word-form nor was there any task related to the stimulus, enabling us to explore the memory-trace formation of a purely phonological form in the absence of any short-term or working memory demands. Similar to previously established neural index of rapid word learning in adults, the control children demonstrated an early brain response enhancement within minutes of exposure to the novel word-form that originated in frontal cortices. Dyslexic children, however, lacked this neural enhancement over the entire course of exposure. Furthermore, the magnitude of the rapid neural enhancement for the novel word-form was positively associated with reading and writing fluency. This suggests that the rapid neural learning mechanism for online acquisition of novel speech material is associated with reading skills. Furthermore, the deficient online learning of novel words in dyslexia, consistent with poor rapid adaptation to familiar stimuli, may underlie the difficulty of learning to read. Developmental dyslexia, a specific reading impairment accompanied by compromised spelling and writing, is one of the most prevalent learning disorders, affecting 5-17% of children with normal IQ and educational possibilities 1,2 . Deficit in phonological processing is widely considered as the underlying cause of dyslexia 3,4 . According to one view, phonological forms (such as words) are poorly constructed in dyslexia; they are inaccurate and incomplete in their segmental organisation 5,6 , implying inefficient memory encoding in the first place. Underdeveloped phonological word-forms may hinder successful phonology-to-orthography mapping that is necessary in reading and writing. Yet, the neural mechanisms behind learning of novel linguistic representations in dyslexia are not understood. Word learning studies in dyslexia primarily employ acquisition of a novel word-form (merely the sound of the word) in association with another, already familiar word or with a visual referent which provide the meaning of the new word. It is, however, imperative to disentangle these two factors with respect to their contribution into the learning deficit. The evidence so far indicates a learning impairment specific to novel phonological forms, with fluent acquisition of semantic and visual associations 7-14 . These studies could not establish, however, whether it is specifically the stage of initial memory encoding, retrieval, or production of the newly learnt word that produces the difficulty. Some evidence suggests that the origin of impaired learning in dyslexia stems from the perceptual encoding level 15 . This account postulates that dyslexics do not benefit from stimulus-specific repetition, unlike normal readers who form "a perceptual anchor" and automatically link subsequent repetitions to it    (note that somewhat similar phonological deficits have been found in SLI 19 although it is important to differentiate SLI from dyslexia). In similar vein, findings of impaired implicit learning of both novel auditory categories 20 and motor sequences in dyslexia 21,22 corroborate the notion that repetition does not facilitate learning in dyslexia as much as it does in normally reading individuals. In the context of word learning, it remains unknown whether it is particularly the failure to benefit from repetitions at the perceptual level (found for both linguistic and non-linguistic stimuli) that slows down the word encoding process, or whether other neural processes underlie the difficulty.
., 2007; Kujala and Näätänen, 2010) . From educators' perspective, neuroscientific research is seldom directly applicable in the assessment of remedial interventions. ... Kujala et al. (2001) presented dyslexics with an intervention with nonlinguistic audiovisual training, including matching a sequence of non-speech sounds with a sequence of visual shapes. ... Citation: Ylinen S and Kujala T (2015) Neuroscience illuminating the influence of auditory or phonological intervention on language-related deficits. Front. ...doi:10.3389/fpsyg.2015.00137 pmid:25741305 pmcid:PMC4330793 fatcat:5zuk37dejbdhzgfuzkqztmq7ka
Kujala et al., 2007) . The mean amplitudes were statistically analysed using a Group (2) × Time window (2) × Electrode (6) Repeated Measures analysis of variance (ANOVA). ... ., in shorter vs. longer reaction times and in preattentive neural processing native-likeness is connected with responses having shorter latencies and larger amplitudes (Kujala & Näätänen, 2010) . ...doi:10.1016/j.ijpsycho.2012.10.003 pmid:23069274 fatcat:pcnxvi2c6ba3rce25fu6mzxcde
For stimulus presentation, we utilized the so-called optimum or multifeature paradigm (Kujala, Tervaniemi, & Schroger, 2007; Näätänen, Pakarinen, Rinne, & Takegata, 2004) , which can accommodate up to ... acoustically matched word and pseudoword stimuli and found an increased MMN response whenever the deviant stimulus was a meaningful word (Shtyrov, Pihko, & Pulvermüller, 2005; Pulvermüller, Shtyrov, Kujala ...doi:10.1162/jocn.2009.21292 pmid:19580394 fatcat:7i3qwiwouzcklli2r6d4ou3kra
Changes in the temporal properties of the speech signal provide important cues for phoneme identification. An impairment or inability to detect such changes may adversely affect one's ability to understand spoken speech. The difference in meaning between the Finnish words tuli (fire) and tuuli (wind), for example, lies in the difference between the duration of the vowel /u/. Detecting changes in the temporal properties of the speech signal, therefore, is critical for distinguishing betweendoi:10.1016/s0378-5955(04)00016-4 pmid:15051135 fatcat:wlqqhn6rfnhevcwlxx6i7aouru
more »... mes and identifying words. In the current study, we tested whether detection of changes in speech sounds, in native Finnish speakers, would vary as a function of the position within the word that the informational changes occurred (beginning, middle, or end) by evaluating how length contrasts in segments of three-syllable Finnish pseudo-words and their acoustic correlates were discriminated. We recorded a combination of cortical components of event-related brain potentials (MMN, N2b, P3b) along with behavioral measures of the perception of the same sounds. It was found that speech sounds were not processed differently than non-speech sounds in the early stages of auditory processing indexed by MMN. Differences occurred only in later stages associated with controlled processes. The effects of position and attention on speech and non-speech stimuli are discussed.
An event-related potential (ERP) protocol is described that can be used to investigate those sound-evoked neural processes that may be implicated in disrupting immediate memory. Conventional electroencephalogram (EEG) is recorded during the performance of a task that involves ignoring irrelevant sounds while trying to hold in memory lists of numbers. Specific bioelectric measures are made to prevent the contamination of recordings by the movements of articulators. An approach is also outlineddoi:10.1016/j.brainresprot.2004.11.001 pmid:15721813 fatcat:r3eut6nbonahlmsosgrjob5zn4
more »... ich controls the timing of ERP components to sounds with different envelopes. Using this approach, it has been shown that the neural processes involved in the elicitation of the auditory N1 ERP response may be involved in the disruption of memory for serial order produced by irrelevant sound. D 2004 Published by Elsevier B.V. Theme: Neural basis of behavior Topic: Cognition
« Previous Showing results 1 — 15 out of 133 results