Search results for "cognitive neuroscience"
showing 10 items of 1135 documents
When the amnestic mild cognitive impairment disappears: characterisation of the memory profile
2009
BACKGROUND/OBJECTIVES: Subjects affected by mild cognitive impairment (MCI) may improve during the observation period. This is the first study investigating qualitative features of memory deficits in subjects affected by reversible MCI [reversible cognitive impairment (RCI)]. METHODS: Baseline cognitive and memory performances of 18 subjects affected by amnestic MCI who had normalized cognitive performances at follow-ups were compared with those of 76 amnestic MCI subjects who still showed impaired cognitive performances at the 24-month follow-up (MCI) and with those of a group of 87 matched control subjects (normal controls). RESULTS: Compared with normal controls the memory deficit in the…
Phoneme processing skills are reflected in children's MMN responses.
2017
Phonological awareness (PA), the core contributor in phoneme processing abilities, has a link to later reading skills in children. However, the associations between PA and neural auditory discrimination are not clear. We used event-related potential (ERP) methodology and neuropsychological testing to monitor the neurocognitive basis of phonological awareness in typically developing children. We measured 5–6-year-old children's (N=70) phoneme processing, word completion and perceptual reasoning skills and compared their test results to their brain responses to phonemic changes, separately for each test. We found that children performing better in Phoneme processing test showed larger mismatc…
The contribution of acetylcholine and dopamine to subprocesses of visual working memory--what patients with amnestic mild cognitive impairment and Pa…
2014
Attentional selection, i.e. filtering out of irrelevant sensory input and information storage are two crucial components of working memory (WM). It has been proposed that the two processes are mediated by different neurotransmitters, namely acetylcholine for attentional selection and dopamine for memory storage. However, this hypothesis has been challenged by others, who for example linked a lack in dopamine levels in the brain to filtering deficits. Here we tested the above mentioned hypothesis in two patient cohorts which either served as a proxy for a cholinergic or a dopaminergic deficit. The first group comprised 18 patients with amnestic mild cognitive impairment (aMCI), the second 22…
DSM-IV Combined Type ADHD Shows Familial Association With Sibling Trait Scores
2008
Contains fulltext : 69060.pdf (Publisher’s version ) (Closed access) Attention deficit hyperactivity disorder (ADHD) is a discrete clinical syndrome characterized by the triad of inattention, hyperactivity, and impulsivity in the context of marked impairments. Molecular genetic studies have been successful in identifying genetic variants associated with ADHD, particularly with DSM-IV inattentive and combined subtypes. Quantitative trait locus (QTL) approaches to linkage and association mapping have yet to be widely used in ADHD research, although twin studies investigating individual differences suggest that genetic liability for ADHD is continuously distributed throughout the population, u…
Predicting domain-specific actions in expert table tennis players activates the semantic brain network.
2018
Motor expertise acquired during long-term training in sports enables top athletes to predict the outcomes of domain-specific actions better than nonexperts do. However, whether expert players encode actions, in addition to the concrete sensorimotor level, also at a more abstract, conceptual level, remains unclear. The present study manipulated the congruence between body kinematics and the subsequent ball trajectory in videos of an expert player performing table tennis serves. By using functional magnetic resonance imaging, the brain activity was evaluated in expert and nonexpert table tennis players during their predictions on the fate of the ball trajectory in congruent versus incongruent…
Action expertise reduces brain activity for audiovisual matching actions: An fMRI study with expert drummers
2011
When we observe someone perform a familiar action, we can usually predict what kind of sound that action will produce. Musical actions are over-experienced by musicians and not by non-musicians, and thus offer a unique way to examine how action expertise affects brain processes when the predictability of the produced sound is manipulated. We used functional magnetic resonance imaging to scan 11 drummers and 11 age- and gender-matched novices who made judgments on point-light drumming movements presented with sound. In Experiment 1, sound was synchronized or desynchronized with drumming strikes, while in Experiment 2 sound was always synchronized, but the natural covariation between sound in…
Long-Term Response to Cholinesterase Inhibitor Treatment Is Related to Functional MRI Response in Alzheimer's Disease.
2015
<b><i>Background:</i></b> Treatment of Alzheimer's disease (AD) with cholinesterase inhibitors (ChEI) enhances cholinergic activity and alleviates clinical symptoms. However, there is variation in the clinical response as well as system level changes revealed by functional MRI (fMRI) studies. <b><i>Methods:</i></b> We investigated 18 newly diagnosed mild AD patients with fMRI using a face recognition task after a single oral dose of rivastigmine, a single dose of placebo and 1-month treatment with rivastigmine. The clinical follow-up took place at 6 and 12 months. <b><i>Results:</i></b> MMSE score difference between bas…
Computational modeling in cognitive science: a manifesto for change.
2012
Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces. For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely made available, accessibility of models to non-programming researchers is essentially non-existent, and even for other modelers, the profusion of source code in a multitude of programming languages, written witho…
Least-squares temporal difference learning based on an extreme learning machine
2014
Abstract Reinforcement learning (RL) is a general class of algorithms for solving decision-making problems, which are usually modeled using the Markov decision process (MDP) framework. RL can find exact solutions only when the MDP state space is discrete and small enough. Due to the fact that many real-world problems are described by continuous variables, approximation is essential in practical applications of RL. This paper is focused on learning the value function of a fixed policy in continuous MPDs. This is an important subproblem of several RL algorithms. We propose a least-squares temporal difference (LSTD) algorithm based on the extreme learning machine. LSTD is typically combined wi…
Statistical criteria for early-stopping of support vector machines
2007
This paper proposes the use of statistical criteria for early-stopping support vector machines, both for regression and classification problems. The method basically stops the minimization of the primal functional when moments of the error signal (up to fourth order) become stationary, rather than according to a tolerance threshold of primal convergence itself. This simple strategy induces lower computational efforts and no significant differences are observed in terms of performance and sparsity.