17 resultados para neural Correlates
em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland
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The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.
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The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.
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Summary
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The purpose of the research is to define practical profit which can be achieved using neural network methods as a prediction instrument. The thesis investigates the ability of neural networks to forecast future events. This capability is checked on the example of price prediction during intraday trading on stock market. The executed experiments show predictions of average 1, 2, 5 and 10 minutes’ prices based on data of one day and made by two different types of forecasting systems. These systems are based on the recurrent neural networks and back propagation neural nets. The precision of the predictions is controlled by the absolute error and the error of market direction. The economical effectiveness is estimated by a special trading system. In conclusion, the best structures of neural nets are tested with data of 31 days’ interval. The best results of the average percent of profit from one transaction (buying + selling) are 0.06668654, 0.188299453, 0.349854787 and 0.453178626, they were achieved for prediction periods 1, 2, 5 and 10 minutes. The investigation can be interesting for the investors who have access to a fast information channel with a possibility of every-minute data refreshment.
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Substance use is one of our most important public health problems. Studying risk factors in a longitudinal study setting helps to identify subgroups of young people at greater risk for substance-use-related problems, and to facilitate targeted prevention efforts. The aim of this thesis was to study childhood predictors and correlates of substance-use-related outcomes among young men in a longitudinal, nationwide birth cohort study. The study population included 10% of all Finnish-speaking boys born in Finland in 1981 (n=2946, 97% of the target population). In 1989, at age eight, valid measures of psychiatric symptoms (Rutter questionnaires and Children’s Depression Inventory) were obtained from parents, teachers and the boys themselves. In 1999, at age 18, boys were reached at their obligatory military call-up (n=2348, 80% of the boys attending the study in 1989). Self-reports of substance use, psychopathology, adaptive functioning (Young Adult Self-Report), and mental health service use were obtained through questionnaires. Information about psychiatric diagnoses from the Military Register (age 18-23 years) and information about offending from the National Police Register (age 16-20 years) were collected in early adulthood (92% of the 1989sample). Boys with childhood conduct, hyperactive, and comorbid conduct-emotional problems had elevated rates of substance use and substance-use-related crime in early adulthood. Depressive symptoms predicted daily smoking, especially among boys of low-educated fathers. Emotional problems predicted lower occurrence of drunkenness-related alcohol use and smoking. Teacher reports on boys’ problem behaviour had the best predictive power for later substance use. At age 18, frequent drunkenness associated with delinquency, smoking and illicit drug use, and having friends. Occasional drunkenness associated with better psychosocial functioning in general compared to boys with frequent drunkenness or without drunkenness-related alcohol use. Illicit drug use without drug offending was not predicted by childhood psychiatric symptoms, but 22% of boys with illicit drug use had a psychiatric diagnosis in early adulthood. Drug offenders, in turn, had psychiatric problems both in childhood and in adulthood. Psychiatric disorders were common among young men with substance-use-related crime. Recidivist crime associated strongly with having a substance use disorder diagnosis according to the Military Register. At age 18, frequent drunkenness was common among boys entering mental health services, but entering substance use treatment was non-existent. According to the findings of this thesis, substance-use-related outcomes accumulate in boys having psychiatric problems both in childhood and in early adulthood. Targeted early interventions in school health care systems, particularly for boys with childhood hyperactive, conduct, and comorbid conduct-emotional problems are recommended. Psychiatric problems and risky behaviours, such as delinquency should always be assessed alongside substance use. Specialized and multidisciplinary care are required for young men who have multiple or complex needs, for instance, for young men with drug offending and recidivist crime. Integrating a substance use treatment perspective with other services where young men are encountered is emphasized.
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Given the structural and acoustical similarities between speech and music, and possible overlapping cerebral structures in speech and music processing, a possible relationship between musical aptitude and linguistic abilities, especially in terms of second language pronunciation skills, was investigated. Moreover, the laterality effect of the mother tongue was examined with both adults and children by means of dichotic listening scores. Finally, two event-related potential studies sought to reveal whether children with advanced second language pronunciation skills and higher general musical aptitude differed from children with less-advanced pronunciation skills and less musical aptitude in accuracy when preattentively processing mistuned triads and music / speech sound durations. The results showed a significant relationship between musical aptitude, English language pronunciation skills, chord discrimination ability, and sound-change-evoked brain activation in response to musical stimuli (durational differences and triad contrasts). Regular music practice may also have a modulatory effect on the brain’s linguistic organization and cause altered hemispheric functioning in those who have regularly practised music for years. Based on the present results, it is proposed that language skills, both in production and discrimination, are interconnected with perceptual musical skills.
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Deflection compensation of flexible boom structures in robot positioning is usually done using tables containing the magnitude of the deflection with inverse kinematics solutions of a rigid structure. The number of table values increases greatly if the working area of the boom is large and the required positioning accuracy is high. The inverse kinematics problems are very nonlinear, and if the structure is redundant, in some cases it cannot be solved in a closed form. If the structural flexibility of the manipulator arms is taken into account, the problem is almost impossible to solve using analytical methods. Neural networks offer a possibility to approximate any linear or nonlinear function. This study presents four different methods of using neural networks in the static deflection compensation and inverse kinematics solution of a flexible hydraulically driven manipulator. The training information required for training neural networks is obtained by employing a simulation model that includes elasticity characteristics. The functionality of the presented methods is tested based on the simulated and measured results of positioning accuracy. The simulated positioning accuracy is tested in 25 separate coordinate points. For each point, the positioning is tested with five different mass loads. The mean positioning error of a manipulator decreased from 31.9 mm to 4.1 mm in the test points. This accuracy enables the use of flexible manipulators in the positioning of larger objects. The measured positioning accuracy is tested in 9 separate points using three different mass loads. The mean positioning error decreased from 10.6 mm to 4.7 mm and the maximum error from 27.5 mm to 11.0 mm.
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Vision affords us with the ability to consciously see, and use this information in our behavior. While research has produced a detailed account of the function of the visual system, the neural processes that underlie conscious vision are still debated. One of the aims of the present thesis was to examine the time-course of the neuroelectrical processes that correlate with conscious vision. The second aim was to study the neural basis of unconscious vision, that is, situations where a stimulus that is not consciously perceived nevertheless influences behavior. According to current prevalent models of conscious vision, the activation of visual cortical areas is not, as such, sufficient for consciousness to emerge, although it might be sufficient for unconscious vision. Conscious vision is assumed to require reciprocal communication between cortical areas, but views differ substantially on the extent of this recurrent communication. Visual consciousness has been proposed to emerge from recurrent neural interactions within the visual system, while other models claim that more widespread cortical activation is needed for consciousness. Studies I-III compared models of conscious vision by studying event-related potentials (ERP). ERPs represent the brain’s average electrical response to stimulation. The results support the model that associates conscious vision with activity localized in the ventral visual cortex. The timing of this activity corresponds to an intermediate stage in visual processing. Earlier stages of visual processing may influence what becomes conscious, although these processes do not directly enable visual consciousness. Late processing stages, when more widespread cortical areas are activated, reflect the access to and manipulation of contents of consciousness. Studies IV and V concentrated on unconscious vision. By using transcranial magnetic stimulation (TMS) we show that when early visual cortical processing is disturbed so that subjects fail to consciously perceive visual stimuli, they may nevertheless guess (above chance-level) the location where the visual stimuli were presented. However, the results also suggest that in a similar situation, early visual cortex is necessary for both conscious and unconscious perception of chromatic information (i.e. color). Chromatic information that remains unconscious may influence behavioral responses when activity in visual cortex is not disturbed by TMS. Our results support the view that early stimulus-driven (feedforward) activation may be sufficient for unconscious processing. In conclusion, the results of this thesis support the view that conscious vision is enabled by a series of processing stages. The processes that most closely correlate with conscious vision take place in the ventral visual cortex ~200 ms after stimulus presentation, although preceding time-periods and contributions from other cortical areas such as the parietal cortex are also indispensable. Unconscious vision relies on intact early visual activation, although the location of visual stimulus may be unconsciously resolved even when activity in the early visual cortex is interfered with.
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Harm Avoidance and Neuroticism are traits that predispose to mental illnesses. Studying them provides a unique way to study predisposition of mental illnesses. Understanding the biological mechanisms that mediate vulnerability could lead to improvement in treatment and ultimately to pre-emptive psychiatry. These personality traits describe a tendency to feel negative emotions such as fear, shyness and worry. Previous studies suggest these traits are regulated by serotonin and opiate pathways. The aim of this thesis was to test the following hypotheses using personality trait measures and positron emission tomography (PET): 1) Brain serotonin transporter density in vivo is associated with Harm Avoidance and Neuroticism traits. 2) μ-opioid receptor binding is associated with Harm Avoidance. In addition, we developed a methodology for studying neurotransmitter interactions in the brain using the opiate and serotonin pathways. 32 healthy subjects who were consistently in either the highest or lowest quartile of the Harm Avoidance trait were recruited from a population-based cohort. Each subject underwent two PET scans, serotonin transporter binding was measured with [11C] MADAM and μ-opioid receptor binding with [11C]carfentanil. We found that the serotonin transporter is not associated with anxious personality traits. However, Harm Avoidance positively correlated with μ-opioid receptor availability. Particularly the tendency to feel shy and the inability to cope with stress were associated μ-opioid receptor availability. We also demonstrated that serotonin transporter binding correlates with μ-opioid receptor binding, suggesting interplay between the two systems. These findings shed light on the neurobiological correlates of personality and have an impact on etiological considerations of affective disorders.
Resumo:
Resultaten påvisade små, men mätbara försämringar i minnes- och verbal förmåga hos personer som haft Parkinsons sjukdom under tre år. Jämfört med en kontrollgrupp uppvisade Parkinsonpatienter avvikande responser i hjärnans elektriska aktivitet under en korttidsminnesuppgift, och de presterade även sämre i olika typer av andra minnesuppgifter. Försämring i en specifik typ av minnesuppgift korrelerade med förminskad volym i höger hjärnhalva. Samband hittades också mellan sämre verbal förmåga och förminskad volym i djupa hjärnstrukturer. Förminskad hjärnvolym har tidigare påvisats hos dementa patienter i senare sjukdomsstadier. Forskningsresultaten bidrar med ny kunskap om kognitiva symptom och deras neurala bakgrund vid Parkinsons sjukdom. De tyder också på att tidig kognitiv funktionsnedsättning kan identifieras, vilket kan bidra till utvecklingen av sjukdomens behandling. Parkinsons sjukdom är den näst vanligaste neurogeriatriska sjukdomen efter Alzheimers sjukdom. Symptomen uppstår som följd av förminskad produktion av hjärnans transmittorämne dopamin. Parkinsons sjukdom har traditionellt betraktats som en progressiv motorisk sjukdom. Ny forskning tyder på att multipla hjärnsystem skadas, vilket resulterar i att även tankeprocesser påverkas. 75-80% uppskattas insjukna i demens 10-15 år efter diagnos, men det kognitiva sjukdomsförloppet och orsaken till demenssymptomen är tillsvidare okänd. I Finland uppskattas ca 10-12 000 personer ha Parkinsons sjukdom, varav ca 3 000 uppskattas ha demens. ----------------------------------------------------------------------------------------------------------------------------------------------------- Tutkimuksessa todettiin lieviä muutoksia muisti- ja kielellisissä toiminnoissa alle kolme vuotta sairastaneilla Parkinson-potilailla. Potilailla havaittiin poikkeavia aivosähkötoiminnan vasteita lyhytkestoista muistia mittaavan tehtävän aikana. Potilaat suoriutuivat myös verrokkiryhmää heikommin useissa muistitehtävissä. Heikentynyt tahaton muisti liittyi pienempään aivokuoren harmaan aineen paikalliseen tilavuuteen. Heikompi kielellinen suoriutuminen liittyi pienempään harmaan aineen tilavuuteen aivojen syvissä rakenteissa. Pienentyneitä aivorakenteiden tilavuuksia on aiemmin todettu dementoituneilla Parkinson-potilailla sairauden myöhemmissä vaiheissa. Tutkimustulokset tuovat uutta tietoa Parkinsonin taudin kognitiivisista oireista ja niiden aivoperäisestä taustasta. Tulosten perusteella on mahdollista tunnistaa jo varhaisia kognitiivisia muutoksia, mikä voi mahdollistaa tehokkaamman hoidon kohdentamisen. Parkinsonin tauti on Alzheimerin taudin jälkeen toiseksi yleisin neurogeriatrinen sairaus. Oirekuva liittyy aivojen dopaminergisen järjestelmän rappeutumiseen. Perinteisesti liikehäiriösairaudeksi luokiteltu sairaus vaurioittaa lukuisia muita aivojärjestelmiä aiheuttaen muutoksia myös mm. ajattelutoiminnoissa. Pitkään sairastaneista 75–80 prosentilla esiintyy dementiaoireita, mutta oireiden syy ja kehityskaari tunnetaan toistaiseksi huonosti. Suomessa on arviolta 10–12 000 Parkinson-potilasta, joista noin 3 000 arvioidaan kärsivän dementiaoireista.
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In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.
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One of the greatest conundrums to the contemporary science is the relation between consciousness and brain activity, and one of the specifi c questions is how neural activity can generate vivid subjective experiences. Studies focusing on visual consciousness have become essential in solving the empirical questions of consciousness. Th e main aim of this thesis is to clarify the relation between visual consciousness and the neural and electrophysiological processes of the brain. By applying electroencephalography and functional magnetic resonance image-guided transcranial magnetic stimulation (TMS), we investigated the links between conscious perception and attention, the temporal evolution of visual consciousness during stimulus processing, the causal roles of primary visual cortex (V1), visual area 2 (V2) and lateral occipital cortex (LO) in the generation of visual consciousness and also the methodological issues concerning the accuracy of targeting TMS to V1. Th e results showed that the fi rst eff ects of visual consciousness on electrophysiological responses (about 140 ms aft er the stimulus-onset) appeared earlier than the eff ects of selective attention, and also in the unattended condition, suggesting that visual consciousness and selective attention are two independent phenomena which have distinct underlying neural mechanisms. In addition, while it is well known that V1 is necessary for visual awareness, the results of the present thesis suggest that also the abutting visual area V2 is a prerequisite for conscious perception. In our studies, the activation in V2 was necessary for the conscious perception of change in contrast for a shorter period of time than in the case of more detailed conscious perception. We also found that TMS in LO suppressed the conscious perception of object shape when TMS was delivered in two distinct time windows, the latter corresponding with the timing of the ERPs related to the conscious perception of coherent object shape. Th e result supports the view that LO is crucial in conscious perception of object coherency and is likely to be directly involved in the generation of visual consciousness. Furthermore, we found that visual sensations, or phosphenes, elicited by the TMS of V1 were brighter than identically induced phosphenes arising from V2. Th ese fi ndings demonstrate that V1 contributes more to the generation of the sensation of brightness than does V2. Th e results also suggest that top-down activation from V2 to V1 is probably associated with phosphene generation. The results of the methodological study imply that when a commonly used landmark (2 cm above the inion) is used in targeting TMS to V1, the TMS-induced electric fi eld is likely to be highest in dorsal V2. When V1 was targeted according to the individual retinotopic data, the electric fi eld was highest in V1 only in half of the participants. Th is result suggests that if the objective is to study the role of V1 with TMS methodology, at least functional maps of V1 and V2 should be applied with computational model of the TMS-induced electric fi eld in V1 and V2. Finally, the results of this thesis imply that diff erent features of attention contribute diff erently to visual consciousness, and thus, the theoretical model which is built up of the relationship between visual consciousness and attention should acknowledge these diff erences. Future studies should also explore the possibility that visual consciousness consists of several processing stages, each of which have their distinct underlying neural mechanisms.
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Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.