IntroductionDeep brain stimulation is an effective treatment for advanced Parkinson’s disease with the targeting bilateral subthalamic nucleus or globus pallidus internus. So far, detailed studies on the efficacy of unilateral STN-DBS for motor symptoms have been reported, but few studies have been conducted on unilateral GPi-DBS.Materials and MethodsSeventeen patients with Parkinson’s disease who underwent unilateral GPi-DBS were selected. We conducted comparison analyses between scores obtained 6–42 months pre- and postoperatively using the following measurement tools: the Movement Disorder Society Unified Parkinson’s (...) Disease Rating Scale part III, the Hoehn and Yahr stage, the presence/absence of dyskinesia, Mini-Mental State Examination, Frontal Assessment Battery, Geriatric Depression Scale, levodopa equivalent dose, and cerebral blood flow by single photon emission computed tomography. Patient backgrounds were compared between four cohorts with favorable and unfavorable postoperative outcome.ResultsSignificant improvement was observed postoperatively in the following: total MDS-UPDRS Part III scores during the off period, contralateral scores, ipsilateral scores, and axial scores. Similarly, the Hoehn and Yahr stages during the off period, and GDS also showed significant decrease. In contrast, LED, MMSE, and FAB remained unchanged while the number of patients who scored positive for dyskinesia decreased by 40%. Abnormal cerebral blood flow preoperatively seen in the cerebral cortex had normalized in the total score-based good responder cohort. In the ipsilateral score-based good responder cohort, cerebral blood flow increased in the contralateral frontal lobe including in the premotor cortex, contralateral to the DBS. Compared to the poor responders, postoperative good responders demonstrated significantly higher preoperative MMSE scores.DiscussionUnilateral GPi-DBS therapy was effective in improving contralateral, ipsilateral, and axial motor symptoms of patients with advanced PD; in particular, it was found to be especially beneficial in PwPD whose cognitive function was unimpaired; the treatment efficacy rivaled that of bilateral counterparts up till at least 6 months postoperatively. Finally, normalization of preoperative abnormalities in cerebral blood flow and increased cerebral blood flow in the contralateral frontal lobe indicated the beneficial potential of this therapy on ipsilateral motor symptoms. (shrink)

The chapters published in this volume developed from presentations, and their associated discussions at a conference organised by the Scottish Branch of the British Psychological Society, held at Rothesay, Isle of Bute, Scotland in September 1987. The goal of the conference was to bring together workers across a wide area of neuropsychological research to discuss recent technological advances, developments in assessment and rehabilitation, and to address theoretical issues of current interest. Thus, the chapters in this book include contributions on the (...) use of Magnetic Resonance Imaging and Single Photon Emission Computed Tomography in neuropsychological research, studies of hemi spheric specialisation and cooperation, alcoholic and Alzheimer type dementia, prosopagnosia and facial processing, the assessment, management and rehabilitation of memory problems, the assessment of premorbid intellectual status and issues in developmental neuropsychology. Many of those engaged in research and clinical practice in neuropsychology encounter a range of topic at least as wide as this in their professional lives. The opportunity for researchers and clinicians to discuss some of the key issues in the field was invaluable and we hope that readers gain as much from the material presented here as the participants did from the meeting itself. (shrink)

Precise and timely diagnosis of Parkinson’s disease is important to control its progression among subjects. Currently, a neuroimaging technique called dopaminergic imaging that uses single photon emission computed tomography (SPECT) with 123I-Ioflupane is popular among clinicians for detecting Parkinson’s disease in early stages. Unlike other studies, which consider only low-level features like gray matter, white matter, or cerebrospinal fluid, this study explores the non-linear relation between different biomarkers (SPECT + biological) using deep learning and multivariate logistic regression. Striatal (...) binding ratios are obtained using 123I-Ioflupane SPECT scans from four brain regions which are further integrated with five biological biomarkers to increase the diagnostic accuracy. Experimental results indicate that this investigated approach can differentiate subjects with 100% accuracy. The obtained results outperform the ones reported in the literature. Furthermore, logistic regression model has been developed for estimating the Parkinson’s disease onset probability. Such models may aid clinicians in diagnosing this disease. (shrink)

Stiff Person Syndrome is a rare autoimmune disorder associated with antibodies against glutamic acid decarboxylase, the key enzyme in γ -aminobutyric acid synthesis. In order to investigate the role of cerebral benzodiazepinereceptor binding in SPS, we performed [ 11 C]flumazenil positron emission tomography in a female patient with SPS compared to nine healthy controls. FMZ is a radioligand to the postsynaptic central benzodiazepine receptor which is co-localized with the GABA-A receptor. In the SPS patient, we found a global reduction (...) of cortical FMZ binding. In addition, distinct local clusters of reduced radiotracer binding were observed. These data provide first in vivo evidence for a reduced postsynaptic GABA-A receptor availability which may reflect the loss of GABAergic neuronal inhibition in SPS. (shrink)

Informed consent has become the most obvious instantiation of patient autonomy in contemporary medicine, though as a practice it does not encompass all spheres of medicine. While diagnostic radiological procedures carry some risk due to the use of radiation, there is no standardized practice of informed consent in the United States. The authors describe the ethical justification of informed consent, the legal background surrounding it, and a brief history of radiology and radiological protection. They ultimately argue that informed consent should (...) become a common practice in computed tomography given the risks involved due to radiation exposure, especially considering the overuse of this technology, since it respects patient autonomy. (shrink)

Preoperative diagnosis of gastric cancer and primary gastric lymphoma is challenging and has important clinical significance. Inspired by the inductive reasoning learning of the human brain, transfer learning can improve diagnosis performance of target task by utilizing the knowledge learned from the other domains (source domain). However, most studies focus on single-source transfer learning and may lead to model performance degradation when a large domain shift exists between the single-source domain and target domain. By simulating the multi-modal information learning and (...) transfer mechanism of human brain, this study designed a multisource transfer learning feature extraction and classification framework, which can enhance the prediction performance of the target model by using multisource medical data (domain). First, this manuscript designs a feature extraction network that takes the maximum mean difference based on the Wasserstein distance as an adaptive measure of probability distribution and extracts the domain-specific invariant representations between source and target domain data. Then, aiming at the random generation of parameters bringing uncertainties to prediction accuracy and generalization ability of extreme learning machine network, the 1-norm regularization is used to implement sparse constraints of the output weight matrix and improve the robustness of the model. Finally, some experiments are carried out on the data of two medical centers. The experimental results show that the area under curves (AUCs) of the method are 0.958 and 0.929 in the two validation cohorts, respectively. The method in this manuscript can provide doctors with a better diagnostic reference, which has certain practical significance. (shrink)

Transfer learning can improve the robustness of deep learning in the case of small samples. However, when the semantic difference between the source domain data and the target domain data is large, transfer learning easily introduces redundant features and leads to negative transfer. According the mechanism of the human brain focusing on effective features while ignoring redundant features in recognition tasks, a brain-like classification method based on adaptive feature matching dual-source domain heterogeneous transfer learning is proposed for the preoperative aided (...) diagnosis of lung granuloma and lung adenocarcinoma for patients with solitary pulmonary solid nodule in the case of small samples. The method includes two parts: (1) feature extraction and (2) feature classification. In the feature extraction part, first, By simulating the feature selection mechanism of the human brain in the process of drawing inferences about other cases from one instance, an adaptive selected-based dual-source domain feature matching network is proposed to determine the matching weight of each pair of feature maps and each pair of convolution layers between the two source networks and the target network, respectively. These two weights can, respectively, adaptive select the features in the source network that are conducive to the learning of the target task, and the destination of feature transfer to improve the robustness of the target network. Meanwhile, a target network based on diverse branch block is proposed, which made the target network have different receptive fields and complex paths to further improve the feature expression ability of the target network. Second, the convolution kernel of the target network is used as the feature extractor to extract features. In the feature classification part, an ensemble classifier based on sparse Bayesian extreme learning machine is proposed that can automatically decide how to combine the output of base classifiers to improve the classification performance. Finally, the experimental results (the AUCs were 0.9542 and 0.9356, respectively) on the data of two center data show that this method can provide a better diagnostic reference for doctors. (shrink)

This paper aims to trace individual as well as collective aspects of ‘sight styles’ in diagnostic computed tomography. Radiologists need to efficiently translate the visualized data from the living human body into a reliable and significant diagnosis. During this process, their visual thinking and the created images are incorporated into a complex network of other visualizations, communication strategies, professional traditions, and (tacit) visual knowledge. To investigate the interplay of collective as well as individual dimensions of diagnostic seeing, the concept (...) of ‘sight collective’ (Sehkollektiv) is developed. On the one hand, this concept is based on critical reading of Ludwik Fleck’s epistemological writings and his notions of thought collective (Denkkollektiv) and thought style (Denkstil). On the other hand, it is tested by means of qualitative empirical studies in a radiological university clinic (participatory observations and informal interviews). By employing this approach, the paper traces the collective foundations of a certain diagnostic sight. Moreover, it shows how the individual abilities of radiologists to perform stylized seeing rely remarkably on software-based interactions with the processed images and on tacit dimensions of visual knowledge. (shrink)

Tools are needed to benchmark carbon emissions and pledges against criteria of equity and fairness. However, standard economic approaches, which use a transparent optimization framework, ignore equity. Models that do include equity benchmarks exist, but often use opaque methodologies. Here we propose a utilitarian benchmark computed in a transparent optimization framework, which could usefully inform the equity benchmark debate. Implementing the utilitarian benchmark, which we see as ethically minimal and conceptually parsimonious, in two leading climate–economy models allows for calculation (...) of the optimal allocation of future emissions. We compare this optimum with historical emissions and initial nationally determined contributions. Compared with cost minimization, utilitarian optimization features better outcomes for human development, equity and the climate. Peak temperature is lower under utilitarianism because it reduces the human development cost of global mitigation. Utilitarianism therefore is a promising inclusion to a set of benchmarks for future explorations of climate equity. (shrink)

The neural substrates of context effects in word perception are still largely unclear. Interhemispheric priming phenomena in word recognition, typically observed in normal subjects, are absent in commissurotomized patients. This suggests that callosal fibers may provide contextual integration. In addition, certain characteristics of human frontal cortical fields subserving sensorimotor learning, as investigated by positron emission tomography, provide evidence for contextual integration not confined to the visual system. This supports the notion of common aspects of cortical computations in different cerebral (...) areas. (shrink)

Cavity-induced changes in atomic spontaneous emission rates are often interpreted in terms of quantum electrodynamical zero-point field fluctuations. A completely classical method of computing this effect in terms of the unquantized normal mode structure of the cavity is presented here. Upon applying the result to a classical dipole radiating between parallel mirrors, we obtain the same cavity correction as that for atomic spontaneous emission in such a cavity. The theory is then compared with a recent experiment in the (...) radio-frequency domain. (shrink)

One recursively enumerable real α dominates another one β if there are nondecreasing recursive sequences of rational numbers (a[n] : n ∈ ω) approximating α and (b[n] : n ∈ ω) approximating β and a positive constant C such that for all n, C(α − a[n]) ≥ (β − b[n]). See [R. M. Solovay, Draft of a Paper (or Series of Papers) on Chaitin’s Work, manuscript, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, 1974, p. 215] and [G. J. (...) Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. We show that every recursively enumerable random real dominates all other recursively enumerable reals. We conclude that the recursively enumerable random reals are exactly the Ω-numbers [G. J. Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. Second, we show that the sets in a universal Martin-Lof test for randomness have random measure, and every recursively enumerable random number is the sum of the measures represented in a universal Martin-Lof test. (shrink)

Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network (...) predict individual differences found on intelligence and reasoning tasks. We describe this network as the Parieto-Frontal Integration Theory (P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs. (shrink)

Since its conception nearly 20 years ago, Logic Programming - the idea of using logic as a programming language - has been developed to the point where it now plays an important role in areas such as database theory, artificial intelligence and software engineering. However, there are still many challenging research issues to be addressed and the UK branch of the Association for Logic Programming was set up to provide a forum where the flourishing research community could discuss important issues (...) of Logic Programming which were often by-passed at the large international conferences. This volume contains the twelve papers which were presented at the ALPUK's 3rd conference which was held in Edinburgh, 10-12 April 1991. The aim of the conference was to give a broad but detailed technical insight into the work currently being done in this field, both in the UK and by researchers as far afield as Canada and Bulgaria. The breadth of interest in this area of Computer Science is reflected in the range of the papers which cover - amongst other areas - massively parallel implementation, constraint logic programming, circuit modelling, algebraic proof of program properties, deductive databases, specialised editors and standardisation. The resulting volume gives a good overview of the current progress being made in the field and will be of interest to researchers and students of any aspects of logic programming, parallel computing or database techniques and management. (shrink)

This book constitutes the strictly refereed post-workshop proceedings of the 11th International Workshop on Computer Science Logic, CSL '97, held as the 1997 Annual Conference of the European Association on Computer Science Logic, EACSL, in Aarhus, Denmark, in August 1997. The volume presents 26 revised full papers selected after two rounds of refereeing from initially 92 submissions; also included are four invited papers. The book addresses all current aspects of computer science logics and its applications and thus presents the state (...) of the art in the area. (shrink)

During the past decade, screening tests using computed tomography have disseminated into practice and been marketed to patients despite neither conclusive evidence nor professional agreement about their efficacy and cost-effectiveness at the population level. This phenomenon raises questions about physicians' professional roles and responsibilities within the setting of medical innovation, as well as the appropriate scope of patient autonomy and access to unproven screening technology. This article explores how physicians ought to respond when new screening examinations that lack conclusive (...) evidence of overall population benefit emerge in the marketplace and are requested by individual patients. To this end, the article considers the nature of evidence and how it influences decision-making for screening at both the public policy and individual patient levels. We distinguish medical and ethical differences between screening recommended for a population and screening considered on an individual patient basis. Finally, we discuss specific cases to explore how evidence, patient risk factors and preferences, and physician judgment ought to balance when making individual patient screening decisions. (shrink)

This volume explores how functional brain imaging techniques like positron emission tomography have influenced cognitive studies. The first chapter outlines efforts to relate human thought and cognition in terms of great books from the late 1800s through the present. Chapter 2 describes mental operations as they are measured in cognitive science studies. It develops a framework for relating mental operations to activity in nerve cells. In Chapter 3, the PET method is reviewed and studies are presented that use PET (...) to map the striate cortex and to activate extrastriate motion, color, and form areas. Chapter 4 shows how top down processes involving attention can lead to activation of these same areas in the detection of targets, visual search, and visual imagery. This chapter reveals complex networks of activations. Chapters 5 and 6 deal with the presentation of words. Chapter 5 illustrates PET studies of the anatomy of visual word processing and shows how the circuitry used for generating novel uses of words changes as the task becomes automated. Chapter 6 applies high density electrical recording to explore these activations in real time and to show how a constant anatomy can be reprogrammed by task instructions to produce and perform different cognitive tasks. Chapter 7 shows how studies of brain lesions and PET converge on common networks underlying attentional functions such as visual orienting, target detection, and maintenance of the alert state. Chapters 8 and 9 apply the network approach to examine normal development of attention in infants and pathological conditions resulting from brain damage, and psychiatric pathologies of depression, schizophrenia, and attention deficit disorder. In Chapter 10, new developments such as functional MRI are discussed in terms of future developments and integration of cognitive neuroscience. (shrink)

“ Tripping through ” is an invitation to plunge into the invisible relationships of hard and soft computer matter through sensuous mediation. The projects outlined are designed to provoke and capture the specific behavior of individual computer components through the use of appropriate software fragments. If one approaches a digital apparatus with a transducer that transforms electromagnetic fields into acoustic waves, the analytical sphere is changed into concrete acoustical phenomena and enters the world of sensation (electromagnetic emissions can be picked (...) using induction microphones and output as acoustic signals. A suitable example is a Monacor telephone adapter AC-71/3,5MM). In choreographies for software and computer parts, these become actors in noise pieces for and in computers. Machine noises can be mediated for the public. They reveal the activity of computer programs in the widest sense and the activity of the computers or computer parts they are running on. The time and space of computer processes and memory span different levels of reality during “ runtime. ” Software being processed within this system of coordinates creates its own temporal and spatial dimensions, which are staged for an audience to provide a sensual experience: that of logic encountering the physical world. (shrink)

In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and (...) the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment. (shrink)

Positron emission tomography is a frontiermedical technology that, in contrast to the othercomputer-assisted technologies providing anatomicalpictures, produces functional images. I argue that PETalso opens up an avenue for shifting from images back toanalysis of measurements. Admittedly, quantification of functionrequires structural constraints. I coined the emerginginterpretational framework quantitative anatomyin an attempt to conceptualize the PET merger betweenmeasuring and imaging, the two competing meansmedicine uses to examine the human body. Anatomyjustifies interpretations that fit the existingknowledge of a larger clinical audience, whilestatistical (...) data possess an unexplored potential tointroduce mathematical rigor in the evaluation offunction, but are still a black box for the majorityof clinicians. This epistemological change is beingcarried out by PET users in action as well as indiscourse. (shrink)

The method of positron emission tomography illustrates the circular logic popular in subtractive neuroimaging and linear reductive cognitive psychology. Both require that strictly feed-forward, modular, cognitive components exist, before the fact, to justify the inference of particular components from images after the fact. Also, both require a "true" componential theory of cognition and laboratory tasks, before the fact, to guarantee reliable choices for subtractive contrasts. None of these possibilities are likely. Consequently, linear reductive analysis has failed to yield general, (...) reliable, componential accounts. (shrink)

In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and (...) the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment. (shrink)

The method of positron emission tomography (PET imaging) illustrates the circular logic popular in subtractive neuroimaging and linear reductive cognitive psychology. Both require that strictly feed-forward, modular, cognitive components exist, before the fact, to justify the inference of particular components from images (or other observables) after the fact. Also, both require a "true" componential theory of cognition and laboratory tasks, before the fact, to guarantee reliable choices for subtractive contrasts. None of these possibilities are likely. Consequently, linear reductive analysis (...) has failed to yield general, reliable, componential accounts. (shrink)

The method of positron emission tomography illustrates the circular logic popular in subtractive neuroimaging and linear reductive cognitive psychology. Both require that strictly feed-forward, modular, cognitive components exist, before the fact, to justify the inference of particular components from images after the fact. Also, both require a "true" componential theory of cognition and laboratory tasks, before the fact, to guarantee reliable choices for subtractive contrasts. None of these possibilities are likely. Consequently, linear reductive analysis has failed to yield general, (...) reliable, componential accounts. (shrink)

The method of positron emission tomography illustrates the circular logic popular in subtractive neuroimaging and linear reductive cognitive psychology. Both require that strictly feed-forward, modular, cognitive components exist, before the fact, to justify the inference of particular components from images after the fact. Also, both require a "true" componential theory of cognition and laboratory tasks, before the fact, to guarantee reliable choices for subtractive contrasts. None of these possibilities are likely. Consequently, linear reductive analysis has failed to yield general, (...) reliable, componential accounts. (shrink)

Using positron emission tomography (PET) and regional cerebral blood flow (rCBF) measurements, we investigated the cerebral correlates of consciousness in a sequence learning task through a novel application of the Process Dissociation Procedure, a behavioral paradigm that makes it possible to separately assess conscious and unconscious contributions to performance. Results show that the metabolic response in the anterior cingulate / mesial prefrontal cortex (ACC / MPFC) is exclusively and specifically correlated with the explicit component of performance during recollection of (...) a learned sequence. This suggests a significant role for the ACC / MPFC in the explicit processing of sequential material.  2003 Elsevier Science B.V. All rights reserved. (shrink)

Using positron emission tomography (PET) and regional cerebral blood flow (rCBF) measurements, we investigated the cerebral correlates of consciousness in a sequence learning task through a novel application of the Process Dissociation Procedure, a behavioral paradigm that makes it possible to separately assess conscious and unconscious contributions to performance. Results show that the metabolic response in the anterior cingulate / mesial prefrontal cortex (ACC / MPFC) is exclusively and specifically correlated with the explicit component of performance during recollection of (...) a learned sequence. This suggests a significant role for the ACC / MPFC in the explicit processing of sequential material.  2003 Elsevier Science B.V. All rights reserved. (shrink)