Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Background and Purpose—The authors present an overview of the current evidence and management recommendations for evaluation and treatment of adults with acute ischemic stroke. The intended audienc...

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Guidelines for the Early Management of Patients With Acute Ischemic Stroke A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association

We present a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from a manually labeled training set. This procedure incorporates both geometric information derived from the cortical model, and neuroanatomical convention, as found in the training set. The result is a complete labeling of cortical sulci and gyri. Examples are given from two different training sets generated using different neuroanatomical conventions, illustrating the flexibility of the algorithm. The technique is shown to be comparable in accuracy to manual labeling.

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Automatically Parcellating the Human Cerebral Cortex

We introduce a novel approach for discriminative classification using evolutionary algorithms. We first propose an algorithm to optimize the total loss value using a modified 0-1 loss function in a one-dimensional space for classification. We then extend this algorithm for multi-dimensional classification using an evolutionary algorithm. The proposed evolutionary algorithm aims to find a hyperplane which best classifies instances while minimizes the classification risk. We test particle swarm optimization, evolutionary strategy, and covariance matrix adaptation evolutionary strategy for optimization purpose. Finally, we compare our results with well-established and state-of-the-art classification algorithms, for both binary and multi-class classification, on 19 benchmark classification problems, with and without noise and outliers. Results show that the performance of the proposed algorithm is significantly (t-test) better than all other methods in almost all problems tested. We also show that the proposed algorithm is significantly more robust against noise and outliers comparing to other methods. The running time of the algorithm is within a reasonable range for the solution of real-world classification problems.

Optimal-margin evolutionary classifier.

Mathematical models are becoming increasingly important in magnetic resonance imaging (MRI), as they provide a mechanistic approach for making a link between tissue microstructure and signals acquired using the medical imaging instrument. The Bloch equations, which describes spin and relaxation in a magnetic field, is a set of integer order differential equations with a solution exhibiting mono-exponential behaviour in time. Parameters of the model may be estimated using a non-linear solver, or by creating a dictionary of model parameters from which MRI signals are simulated and then matched with experiment. We have previously shown the potential efficacy of a magnetic resonance fingerprinting (MRF) approach, i.e. dictionary matching based on the classical Bloch equations, for parcellating the human cerebral cortex. However, this classical model is unable to describe in full the mm-scale MRI signal generated based on an heterogenous and complex tissue micro-environment. The time-fractional order Bloch equations has been shown to provide, as a function of time, a good fit of brain MRI signals. We replaced the integer order Bloch equations with the previously reported time-fractional counterpart within the MRF framework and performed experiments to parcellate human gray matter, which is cortical brain tissue with different cyto-architecture at different spatial locations. Our findings suggest that the time-fractional order parameters, {\alpha} and {\beta}, potentially associate with the effect of interareal architectonic variability, hypothetically leading to more accurate cortical parcellation.

Fractional order magnetic resonance fingerprinting in the human cerebral cortex

Reasoning requires initial encoding of the semantic association between premises or assumptions, retrieval of these semantic associations from memory, and recombination of information to draw a logical conclusion. Currently-held beliefs can interfere with the content of the assumptions if not congruent and inhibited. This study aimed to investigate the role of the hippocampus and hippocampal networks during logical reasoning tasks in which the congruence between currently-held beliefs and assumptions varies. Participants of younger and older age completed a series of syllogistic reasoning tasks in which two premises and one conclusion were presented and they were required to decide if the conclusion logically followed the premises. The belief load of premises was manipulated to be either congruent or incongruent with currently-held beliefs. Our whole-brain results showed that older adults recruited the hippocampus during the premise integration stage more than their younger counterparts. Functional connectivity using a hippocampal seed revealed that older, but not younger, adults recruited a hippocampal network that included anterior cingulate and inferior frontal regions when premises were believable. Importantly, this network contributed to better performance in believable inferences, only in older adults group. Further analyses suggested that, in older adults group, the integrity of the left cingulum bundle was associated with the higher correct rejection of believable premises more than unbelievable ones. Using multimodal imaging, this study highlights the importance of the hippocampus during premise integration and supports the compensatory role of the hippocampal network during a logical reasoning task among older adults.

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Role of the hippocampus during logical reasoning and belief bias in aging

The synthesis of titled compounds were achieved in one step using hydroxyl naphthones and substituted cinnamic acids in the presence of a catalytic amount of phosphorus oxychloride. X-ray crystal studies were undertaken for three compounds and the results are presented. Compounds 1 (C22H15F3O3) and 3 (C21H15BrO3) formed a monoclinic crystals while compound 2 (C22H15F3O3) formed a triclinic crystals. The observed space group of these compounds is P21/c and P
 $$ \bar{1} $$
 respectively. The 2-substituted compounds showed identical space group and showed a perpendicular arrangements of each of the substituents to the plane of the naphthyl ring. On the contrary, the 1-substituted cinnamoyal compound showed an orthogonal arrangement to naphthyl ring but the acetyl group was almost planar relative to the naphthyl moiety. The characterization of the structures of the compounds was also accomplished using high-resolution NMR spectroscopic techniques. The synthesis of titled compound was achieved in one step using hydroxyl naphthones and substituted cinnamic acids in the presence of a catalytic amount of phosphorus oxychloride. X-ray crystal studies were undertaken for three compounds and the results are presented. Compounds 1 and 3 formed a monoclinic crystal while compound 2 formed a triclinic crystal. The molecular formulae of compounds are as follows: C22H15F3O3 (1 and 2) and C21H15BrO3(3) . The observed space group of these compounds is P21/c and P1 respectively.

Synthesis and X-Ray Crystal Structure of 1- and 2-Cinnamoyaloxy Acetonaphthones

18 F-radiolabeled diphenyl gallium thiosemicarbazone was prepared by [18 F] fluoride exchange of a nitrato anion under mild conditions. The diphenyl gallium thiosemicarbazone chloride is easily prepared in gram quantities and can be used at room temperature in the presence of oxygen. The corresponding nitrate complex is prepared using silver nitrate in methanol solvent and can be stored under nitrogen for weeks before radiolabeling. The biodistribution of this new tracer was studied in mice using positron emission tomography (PET).

https://espace.library.uq.edu.au/view/UQ:5220d2d/UQ5220d2d_OA.pdf

David C. Reutens

Papers

Optimal-margin evolutionary classifier.

Fractional order magnetic resonance fingerprinting in the human cerebral cortex

Role of the hippocampus during logical reasoning and belief bias in aging

Synthesis and X-Ray Crystal Structure of 1- and 2-Cinnamoyaloxy Acetonaphthones

Synthesis of 18F-radiolabeled diphenyl gallium dithiosemicarbazone using a novel halogen exchange method and in vivo biodistribution