Kinetic modeling of the generation of 2-and 3-methylbutanal in a heated extract of beef liver

Quantitative control of aroma generation during the Maillard reaction presents great scientific and industrial interest. Although there have been many studies conducted in simplified model systems, the results are difficult to apply to complex food systems, where the presence of other components can have a significant impact. In this work, an aqueous extract of defatted beef liver was chosen as a simplified food matrix for studying the kinetics of the Mallard reaction. Aliquots of the extract were heated under different time and temperature conditions and analyzed for sugars, amino acids, and methylbutanals, which are important Maillard-derived aroma compounds formed in cooked meat. Multiresponse kinetic modeling, based on a simplified mechanistic pathway, gave a good fit with the experimental data, but only when additional steps were introduced to take into account the interactions of glucose and glucose-derived intermediates with protein and other amino compounds. This emphasizes the significant role of the food matrix in controlling the Maillard reaction.

Efficient modeling and inference for event-related fMRI data

Event-related functional magnetic resonance imaging (efMRI) has emerged as a powerful technique for detecting brains' responses to presented stimuli. A primary goal in efMRI data analysis is to estimate the Hemodynamic Response Function (HRF) and to locate activated regions in human brains when specific tasks are performed. This paper develops new methodologies that are important improvements not only to parametric but also to nonparametric estimation and hypothesis testing of the HRF. First, an effective and computationally fast scheme for estimating the error covariance matrix for efMRI is proposed. Second, methodologies for estimation and hypothesis testing of the HRF are developed. Simulations support the effectiveness of our proposed methods. When applied to an efMRI dataset from an emotional control study, our method reveals more meaningful findings than the popular methods offered by AFNI and FSL. (C) 2008 Elsevier B.V. All rights reserved.

The human thalamus processes syntactic and semantic language violations

Numerous linguistic operations have been assigned to cortical brain areas, but the contributions of subcortical structures to human language processing are still being discussed. Using simultaneous EEG recordings directly from deep brain structures and the scalp, we show that the human thalamus systematically reacts to syntactic and semantic parameters of auditorily presented language in a temporally interleaved manner in coordination with cortical regions. In contrast, two key structures of the basal ganglia, the globus pallidus internus and the subthalamic nucleus, were not found to be engaged in these processes. We therefore propose that syntactic and semantic language analysis is primarily realized within cortico-thalamic networks, whereas a cohesive basal ganglia network is not involved in these essential operations of language analysis.

Neural mechanisms of visual object priming: evidence for perceptual and semantic distinctions in fusiform cortex

Previous functional imaging studies have shown that facilitated processing of a visual object on repeated, relative to initial, presentation (i.e., repetition priming) is associated with reductions in neural activity in multiple regions, including fusiforin/lateral occipital cortex. Moreover, activity reductions have been found, at diminished levels, when a different exemplar of an object is presented on repetition. In one previous study, the magnitude of diminished priming across exemplars was greater in the right relative to the left fusiform, suggesting greater exemplar specificity in the right. Another previous study, however, observed fusiform lateralization modulated by object viewpoint, but not object exemplar. The present fMRI study sought to determine whether the result of differential fusiform responses for perceptually different exemplars could be replicated. Furthermore, the role of the left fusiform cortex in object recognition was investigated via the inclusion of a lexical/semantic manipulation. Right fusiform cortex showed a significantly greater effect of exemplar change than left fusiform, replicating the previous result of exemplar-specific fusiform lateralization. Right fusiform and lateral occipital cortex were not differentially engaged by the lexical/semantic manipulation, suggesting that their role in visual object recognition is predominantly in the. C visual discrimination of specific objects. Activation in left fusiform cortex, but not left lateral occipital cortex, was modulated by both exemplar change and lexical/semantic manipulation, with further analysis suggesting a posterior-to-anterior progression between regions involved in processing visuoperceptual and lexical/semantic information about objects. The results are consistent with the view that the right fusiform plays a greater role in processing specific visual form information about objects, whereas the left fusiform is also involved in lexical/semantic processing. (C) 2003 Elsevier Science (USA). All rights reserved.

fMRI delineation of working memory for emotional prosody in the brain: commonalities with the lexico-semantic emotion network

Decoding emotional prosody is crucial for successful social interactions, and continuous monitoring of emotional intent via prosody requires working memory. It has been proposed by Ross and others that emotional prosody cognitions in the right hemisphere are organized in an analogous fashion to propositional language functions in the left hemisphere. This study aimed to test the applicability of this model in the context of prefrontal cortex working memory functions. BOLD response data were therefore collected during performance of two emotional working memory tasks by participants undergoing fMRI. In the prosody task, participants identified the emotion conveyed in pre-recorded sentences, and working memory load was manipulated in the style of an N-back task. In the matched lexico-semantic task, participants identified the emotion conveyed by sentence content. Block-design neuroimaging data were analyzed parametrically with SPM5. At first, working memory for emotional prosody appeared to be right-lateralized in the PFC, however, further analyses revealed that it shared much bilateral prefrontal functional neuroanatomy with working memory for lexico-semantic emotion. Supplementary separate analyses of males and females suggested that these language functions were less bilateral in females, but their inclusion did not alter the direction of laterality. It is concluded that Ross et al.'s model is not applicable to prefrontal cortex working memory functions, that evidence that working memory cannot be subdivided in prefrontal cortex according to material type is increased, and that incidental working memory demands may explain the frontal lobe involvement in emotional prosody comprehension as revealed by neuroimaging studies. (c) 2007 Elsevier Inc. All rights reserved.

How does the brain mediate interpretation of incongruent auditory emotions? The neural response to prosody in the presence of conflicting lexico-semantic cues

We frequently encounter conflicting emotion cues. This study examined how the neural response to emotional prosody differed in the presence of congruent and incongruent lexico-semantic cues. Two hypotheses were assessed: (i) decoding emotional prosody with conflicting lexico-semantic cues would activate brain regions associated with cognitive conflict (anterior cingulate and dorsolateral prefrontal cortex) or (ii) the increased attentional load of incongruent cues would modulate the activity of regions that decode emotional prosody (right lateral temporal cortex). While the participants indicated the emotion conveyed by prosody, functional magnetic resonance imaging data were acquired on a 3T scanner using blood oxygenation level-dependent contrast. Using SPM5, the response to congruent cues was contrasted with that to emotional prosody alone, as was the response to incongruent lexico-semantic cues (for the 'cognitive conflict' hypothesis). The right lateral temporal lobe region of interest analyses examined modulation of activity in this brain region between these two contrasts (for the 'prosody cortex' hypothesis). Dorsolateral prefrontal and anterior cingulate cortex activity was not observed, and neither was attentional modulation of activity in right lateral temporal cortex activity. However, decoding emotional prosody with incongruent lexico-semantic cues was strongly associated with left inferior frontal gyrus activity. This specialist form of conflict is therefore not processed by the brain using the same neural resources as non-affective cognitive conflict and neither can it be handled by associated sensory cortex alone. The recruitment of inferior frontal cortex may indicate increased semantic processing demands but other contributory functions of this region should be explored.

False recognition of abstract versus common objects in older and younger adults: testing the semantic categorization account

Older adults often demonstrate higher levels of false recognition than do younger adults. However, in experiments using novel shapes without preexisting semantic representations, this age-related elevation in false recognition was found to be greatly attenuated. Two experiments tested a semantic categorization account of these findings, examining whether older adults show especially heightened false recognition if the stimuli have preexisting semantic representations, such that semantic category information attenuates or truncates the encoding or retrieval of item-specific perceptual information. In Experiment 1, ambiguous shapes were presented with or without disambiguating semantic labels. Older adults showed higher false recognition when labels were present but not when labels were never presented. In Experiment 2, older adults showed higher false recognition for concrete but not abstract objects. The semantic categorization account was supported.

Inverse problems in dynamic cognitive modeling

Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.

Semantic organization to enhance active learning based on distributed multimedia educational resources

In order to organize distributed educational resources efficiently, to provide active learners an integrated, extendible and cohesive interface to share the dynamically growing multimedia learning materials on the Internet, this paper proposes a generic resource organization model with semantic structures to improve expressiveness, scalability and cohesiveness. We developed an active learning system with semantic support for learners to access and navigate through efficient and flexible manner. We learning resources in an efficient and flexible manner. We provide facilities for instructors to manipulate the structured educational resources via a convenient visual interface. We also developed a resource discovering and gathering engine based on complex semantic associations for several specific topics.

Modeling and simulating a mathematical tool for multi-robot pattern transformation

The work reported in this paper is motivated by the need to investigate general methods for pattern transformation. A formal definition for pattern transformation is provided and four special cases namely, elementary and geometric transformation based on repositioning all and some agents in the pattern are introduced. The need for a mathematical tool and simulations for visualizing the behavior of a transformation method is highlighted. A mathematical method based on the Moebius transformation is proposed. The transformation method involves discretization of events for planning paths of individual robots in a pattern. Simulations on a particle physics simulator are used to validate the feasibility of the proposed method.

Multimodal semantic-associative collateral labelling and indexing of still images

A novel framework for multimodal semantic-associative collateral image labelling, aiming at associating image regions with textual keywords, is described. Both the primary image and collateral textual modalities are exploited in a cooperative and complementary fashion. The collateral content and context based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix, of the visual keywords, A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. Finally, we use Self Organising Maps to examine the classification and retrieval effectiveness of the proposed high-level image feature vector model which is constructed based on the image labelling results.