bluuebunny/crossref_metadata_2025_split huggingface dataset:
New directions for research into aging and intelligence: the development of expertise
Authors: Horn John L , Masunaga Hiromi 
Published: November 2023

Abstract
In this article we will review and critically evaluate what is believed, scientifically, about human cognitive capabilities and their development through adulthood. We will then discuss a major concern about this information – what appears to be wrong with it - and put forth some ideas about what is needed to fill in information that is more nearly correct. We will argue that the major thrust in research aimed at understanding the nature of human intelligence (viewed behaviourally) should be directed at understanding capabilities that emerge in adulthood. This argument stems from research findings that, for the most part, have been directed at describing cognitive declines that occur in adulthood. Yet this research has netted evidence of abilities that are maintained or that improve with advancing age. These findings have forced modifications in reductionistic assumptions that the maintenance of human intelligence is determined only by physiological (largely neurological) functions that inevitably decline in adulthood. The findings have led to questions about what, indeed, are the physiological/neurological functions that support expressions of different cognitive abilities: which of these functions are likely to deteriorate over adulthood and why. But most pertinent to the argument of this chapter, the findings have raised anew questions about what human intelligence is – in particular, what is intelligence at its highest level of expression. Here it is reasoned that development (through childhood into adulthood) i directed at realizing that highest level and that probably that apex is reached in adulthood. Thus, the question of what is intelligence becomes one of what is it that emerges in adulthood that is both different from what is called intelligence in childhood and that can be recognized as the sine qua non of human intelligence?
Hippocampal synaptic plasticity: role in spatial learning or the automatic recording of attended experience?
Authors: Morris Richard G M , Frey Uwe 
Published: November 2023

Abstract
This paper outlines a new hypothesis about the function of associative synaptic plasticity in the hippocampal formation, namely that it is essential for what is referred to here as the ‘ automatic recording of attended experience’ . This constitutes one component of a larger episodic memory system involving a number of brain regions (Tulving 1983; Tulving & Schacter 1994) and likely to be implemented by several neurophysiological mechanisms of plasticity. The idea is that this part of the episodic memory system of the brain is automatic in the sense that it cannot be switched off in a voluntary manner, although it can be subject to selective disruption by certain kinds of brain damage. Being automatic, it can potentially record everything to which attention is directed, including context, but this recording may only be of markers that an event has happened at a particular place rather than a detailed encoding of sensory or perceptual information. To operate effectively, such a system needs a mechan¬ ism of neuronal plasticity that can register event-context associations rapidly in a strictly correlational manner, i.e. without regard to their consistency to an organism’ s goal-directed actions.
Hippocampal and parietal involvement in human topographical memory:evidence from functional neuroimaging
Authors: Maguire Eleanor A 
Published: November 2023

Abstract
The ability of humans to orient and navigate successfully in the large-scale spatially-extended environments that constitute the real-world is commonly referred to as topographical orientation. Way-finding is complex and not a unitary process; there are many aspects to it including attentional, perceptual and mnestic components. Topographical disorientation, therefore, can occur because of disturbance to one or more component processes. Occasionally cases of topographical disorientation are reported and are typically described in terms of perceptual or mnestic difficulties, such as perceptual disturbance where there is an agnosia for landmarks and buildings even in well-known surroundings, often found in association with prosopagnosia (Patterson and Zangwill 1944; Landis et al. 1986); or a topographical memory disturbance, where buildings and landmarks can be recognized and recalled, but the memory for their place in space and spatial relationships is dysfunctional (DeRenzi et al. 1977; Habib and Sirigu 1987; Bottini et al. 1990; Maguire et al. 1996a). Some general conclusions about the neural basis of topographical orientation systems can be drawn from the patient literature. Damage to several brain regions can produce topographic deficits of one sort or another.
Parietal cortex and hippocampus: from visual affordances to the world graph
Authors: Arbib Michael A 
Published: November 2023

Abstract
Gibson (1966) observed that the pattern of optic flow, the movement of features across the retina from moment to moment, contains valuable information that could be used to guide navigation through the environment without prior recognition of objects. We adopt Gibson’ s term ‘ affordances’ for parameters for motor interactions signalled by sensory cues without the necessary intervention of ‘ high-level processes’ of object recognition. Neurological data relate human parietal function not only to impairment of a variety of affordances but also to impairment of ‘ cognitive maps’ . Bilateral parietal lobe damage often yields ‘ global spatial disorientation’ (Kase et al. 1977), a symptom complex which involves the three systems whose parietal roles are modelled in this paper: the control of eye movements; the control of the grasping of objects; and the use of ‘ cognitive maps’ in navigation. Some of these deficits can also be seen in relatively pure isolated form.
Visuospatial processing in a pure case of visual-form agnosia
Authors: Milner A David , Dijkerman H Chris , Carey David P 
Published: November 2023

Abstract
Visual form agnosia refers to a variety of apperceptive agnosia in which the patient’ s ability to perceive, discriminate and recognize the shape of objects is grossly impaired (Benson & Greenberg 1969). Detailed case descriptions of such patients have been given by Goldstein & Gelb (1918), Adler (1944), Benson & Greenberg (1969), Landis et al. (1982) and Milner et al. (1991), and extensive experimental studies of their perceptual abilities have been presented by the same authors, as well as by Gelb & Goldstein (1938), Efron (1969), and Campion & Latto (1985). There is a remarkable similarity among these patients, both in their pathology and in their visual symptoms. In all cases the brain damage has been bilateral and in most cases caused by carbon monoxide poisoning, the principal exceptions being the patients of Goldstein & Gelb (missile injury) and Landis et al. (mercury poisoning). Also in all cases the profound deficit in form perception is seen without any appreciable deficit in auditory or tactile perception, and in most cases without any appreciable deficit in other domains of visual perception, including colour, motion, stereopsis and even visual acuity.
Introduction
Authors: Humphreys Glyn W , Duncan John , Treisman Anne 
Published: November 2023

Abstract
Over the past 15 years or so there have been substantial and important developments in the cognitive neuroscience of selective perception and action. We review the role played in these developments by the component disciplines of experimental psychology, neuropsychology, electrophysiology, mathematical and computational modelling, and functional imaging. We argue that interdisciplinary work in this field has played a major part in advancing our understanding, and that there are benefits to be gained from gathering converging evidence at different levels of analysis. We discuss the relations between these arguments and the chapters presented in book.
Neural coding of 3D features of objects for hand action in the parietal cortex of the monkey
Authors: Sakata Hideo , Taira Masato , Kusunoki Makoto , Murata Akira , Tanaka Yi ji , Tsutsui Ken-ichiro 
Published: November 2023

Abstract
In our previous studies of hand manipulation task-related neurons, we found many neurons of the parietal association cortex which responded to the sight of three-dimensional (3D) objects. Most of the task-related neurons in the AIP area (the lateral bank of the anterior intraparietal sulcus) were visually responsive and half of them responded to objects for manipulation. Most of these neurons were selective for the 3D features of the objects. More recently, we have found binocular visual neurons in the lateral bank of the caudal intraparietal sulcus (c-IPS area) that preferentially respond to a luminous bar or plate at a particular orientation in space. We studied the responses of axis-orientation selective (AOS) neurons and surface 01ientation selective (SOS) neurons in this area with stimuli presented on a 3D computer graphics display. The AOS neurons showed a stronger response to elongated stimuli and showed tuning to the orientation of the longitudinal axis. Many of them prefe1Ted a tilted stimulus in depth and appeared to be sensitive to orientation disparity and/or width disparity. The SOS neurons showed a stronger response to a flat than to an elongated stimulus and showed tuning to the 3D orientation of the surface. Their responses increased with the width or length of the stimulus. A considerable number of SOS neurons responded to a square in a random dot stereogram and were tuned to orientation in depth, suggesting their sensitivity to the gradient of disparity. We also found several SOS neurons that responded to a square with tilted or slanted contours, suggesting their sensitivity to orientation disparity and/or width disparity. Area c-IPS is likely to send visual signals of the 3D features of an object to area AIP for the visual guidance of hand actions.
Neuropsychological studies of perception and visuomotor control
Authors: Milner A D 
Published: November 2023

Abstract
According to recent conceptualizations, there are two separate cortical visual systems-each with its own distinctive cortical and subcortical links—and these two systems respectively serve the functions of perception and of motor control. These ideas have been arrived at through a confluence of neuroanatomical, electrophysiological, behavioural, and neuropsychological research. It is proposed that this distinction between two broad purposes of vision and their neural bases can provide useful working procedures for analysing both (i) the nature of visuomotor processing in the normal brain and also (ii) the abnormal patterns of visual processing that are seen in certain neurological conditions.
Sustained attention deficits in time and space
Authors: Robertson Ian H , Manly Tom 
Published: November 2023

Abstract
We review critically the influential framework of attentional systems developed by Posner and Petersen (1990). Their proposal that three independent supramodal attentional control systems exist in the brain-selection, alertness and spatial attention respectively—is examined in the light of evidence accumulated over the last decade. We conclude that while evidence for differentiable supramodal selection and alertness systems is quite strong, the notion of a posterior supramodal spatial attention system centred in the parietal lobes is much V.’eaker. We review evidence showing that unilateral neglect consequent on parietal lesions is both strongly associated with non-lateralized attentional deficits, and strongly modifiable by manipulation of these non-spatial variables. Spatial selective attention may be better conceived of as an emergent property of competition between distributed but integrated representations of objects and space between the two hemispheres. The role of the parietal lobes in spatial selection may be related to the integration of cross¬ modal representations and motor preparation in the organisation of responses towards the environment. But the parietal lobe of the right hemisphere appears to have an additional, but as yet inadequately specified role, in the maintenance of the alert state over time and other non-lateralized aspects of attention.
Random effects models
Authors: Diggle Peter J , Heagerty Patrick J , Liang Kung-yee. , Zeger Scott L 
Published: November 2023

Abstract
Chapter 8 has dealt with marginal models whose regression parameters have population average interpretations. In this chapter we consider random effects models in which the regression coeficients measure the more direct infiuence of explanatory variables on the responses for heterogeneous individuals. Linear models with random effects were discussed in Section 5.2 in the context of a general framework for parametric modelling of correlation in longitudinal data.
Likelihood-based methods for categorical data
Authors: Diggle Peter J , Heagerty Patrick J , Liang Kung-yee. , Zeger Scott L 
Published: November 2023

Abstract
In a study of the natural history of schizophrenia, first-episode patients had disease symptoms recorded monthly for up to 10 years following initial hospitalization (Thara et al., 1994). In studies of the health effects of air pollution, asthmatic children recorded the presence or absence of wheezing each day for approximately 60 days (Yu et al., 2000). To determine whether maternal employment correlates with paediatric care utilization and both maternal stress and childhood illness, daily measurements of maternal stress (yes, no) and childhood illness (yes, no) were recorded for 28 consecutive days (Alexander and Markowitz, 1986). Lunn, et al. (2001) analyse ordinal allergic severity scores collected daily for 3 months on subjects assigned either to placebo or to one of three doses of active drug.
Time-dependent covariates
Authors: Diggle Peter J , Heagerty Patrick J , Liang Kung-yee. , Zeger Scott L 
Published: November 2023

Abstract
One of the main scientific advantages of conducting a longitudinal study is the ability to observe the temporal order of key exposure and outcome events. Specifically, we can determine whether changes in a covariate precede changes in the outcome of interest. Such data provide crucial evidence for a causal role of the exposure (see Chapter 2 in Rothman and Greenland, 1998).
Kinetics analysis of DNA-protein interactions by time-resolved synchrotron X-ray footprinting
Authors: Dhavan Gauri M , Chance Mark R , Brenowitz Michael 
Published: November 2023

Abstract
The binding of proteins to specific sequences of DNA is often the first step in the regulation of cellular events essential to cell function and growth such as transcription, DNA replication, site-specific recombination, and other processes that require DNA binding. The rates at which these protein-DNA complexes assemble is dependent upon the kinetics of each individual binding event as well as additional cooperative interactions between two or more protein molecules required for biological function. The study of the kinetics of association and dissociation of site-specific DNA contact events provides insight into the mechanism by which the complexes are formed and the role of each player in a larger nucleo-protein assembly.
Weyl and Schur Modules
Authors: Boffi Giandomenico , Buchsbaum David A 
Published: November 2023

Abstract
In earlier chapters we introduced a very small dose of representation theory of the general linear group when we discussed, in particular, the hook shapes. In this chapter, we will deal more comprehensively with representations of that group, over an arbitrary commutative ring, R. Our discussion will help place the material in earlier chapters in proper perspective, and will move us forward to some interesting observations relating to determinantal ideals and other matters.
Plants as insect food: not the ideal
Authors: Schoonhoven Louis M , Loon Joop J A van , Dicke Marcel 
Published: November 2023

Abstract
The subject of this Chapter-plants as food for herbivorous insects-touches the heart of insectplant biology. Its theme can be captured in two basic questions. First, what do plants offer to insects by way of nutrition? And second, what do insects need for optimal growth and reproduction? Answering these two questions is seriously hindered by the fact that (1) the chemical composition of plants, as noted before, varies among species in both space and time, and (2) the nutritional requirements of insects vary between species and with developmental stage and environmental conditions.
Functional magnetic resonance imaging (fMRI)
Authors: Honey Garry D , McGuire Phillip K , Bullmore Edward T 
Published: November 2023

Abstract
The first report of localized changes in cerebral blood oxygenation in the occipital cortex following visual stimulation in humans (Belliveau et al. 1991) was of seminal importance to neuropsychiatric research. Only 3 years following this technological development, which enabled non-invasive visualization of in vivo human brain function, the application of the technique was first reported in psychiatric patients (Renshaw et al. 1994; Wenz et al. 1994). This ushered in a new era in functional neuroimaging, and provided a powerful tool in cognitive neuroscience to explore both normal and abnormal brain function, complementing earlier techniques such as positron emission tomography (PET), single-photon emission computed tomography (SPECT), and non-topographic electrophysiological procedures such as electron-cephalography (EEG) and evoked response potentials (ERPs).
Bayesian Treed Generalized Linear Models
Authors: Chipman Hugh A , George Edward I , Mcculloch Roberte.E 
Published: November 2023

Abstract
For the standard regression setup, conventional tree models partition the predictor space into regions where the variable of interest Y, can be approximated by a constant. A treed model extends this idea by allowing a functional relationship between Y and the predictors within each region. As opposed to using a single model to describe the global variation of the response, treed models allow for local modelling across the predictor space. In this paper, we consider treed versions of generalized linear models (GLMs) and propose a Bayesian approach to finding and fitting such models. The potential of this approach is illustrated with a treed Poisson regression.
Bayesian Harmonic Models for Musical Signal Analysis
Authors: Davy Manuel , Godsill Simon J 
Published: November 2023

Abstract
This paper is concerned with the Bayesian analysis of musical signals. The ultimate aim is to use Bayesian hierarchical structures in order to infer quantities at the highest level, including such things as musical pitch, dynamics, timbre, instrument identity, etc. Analysis of real musical signals is complicated by many things, including the presence of transient sounds, noises, and the complex structure of musical pitches in the frequency domain. The problem is truly Bayesian in that there is a wealth of (often subjective) prior knowledge about how musical signals are constructed, which can be exploited in order to achieve more accurate inference about the musical structure. Here we propose developments to an earlier Bayesian model that describes each component “note” at a given time in terms of a fundamental frequency, partials (“harmonics”), and amplitude. This basic model is modified for greater realism to include non-white residuals, time-varying amplitudes and partials “detuned” from the natural linear relationship. The unknown parameters of the new model are simulated using a variable dimension MCMC algorithm, leading to a highly sophisticated analysis tool. We discuss how the models and algorithms can be applied for feature extraction, polyphonic music transcription, source separation, and restoration of musical sources.
Exact Bayesian Inference for a Class of Nonlinear Systems with Application to Robotic Assembly
Authors: Lefebvre Tyne , Gadeyne Klaas , Bruyninckx Herman , Schutter Joris De 
Published: November 2023

Abstract
This paper presents a new finite-dimensional Bayesian filter. The filter calculates the exact analytical expression for the posterior probability density function (pdf) of static systems with any kind of nonlinear measurement equation subject to Gaussian measurement uncertainty. The paper also extends this filter to a limited class of dynamic systems. The filter is applied to the estimation of the inaccurately known position and orientation of two mating parts during autonomous robotic assembly. The sufficient statistics of the posterior pdf are obtained by Kalman Filter formulas, making online estimation possible. Exact finite-dimensional filters exist only for a small class of systems. The best known example is the Kalman Filter for linear systems (i.e., systems for which both the process equation and the measurement equation are linear) with Gaussian uncertainties. In this case, the posterior pdf is a Gaussian represented by its mean and its covariance matrix. Other examples are the filters of Benes (1981), which requires the measurement equation to be linear, and Daum (1988), applicable to a more general class of systems with nonlinear process and measurement equations for which the posterior pdf is any exponential distribution.
Density Modeling and Clustering Using Dirichlet Diffusion Trees
Authors: Neal Radford M 
Published: November 2023

Abstract
I introduce a family of prior distributions over multivariate distributions, based on the use of a “Dirichlet diffusion tree” to generate exchangeable data sets. These priors can be viewed as generalizations of Dirichlet processes and of Dirichlet process mixtures, but unlike simple mixtures, they can capture the hierarchical structure present in many distributions, by means of the latent diffusion tree underlying the data. This latent tree also provides a hierarchical clustering of the data, which, unlike ad hoc clustering methods, comes with probabilistic indications of uncertainty. The relevance of each variable to the clustering can also be determined. Although Dirichlet diffusion trees are defined in terms of a continuoustime process, posterior inference involves only finite-dimensional quantities, allowing computation to be performed by reasonably efficient Markov chain Monte Carlo methods. The methods are demonstrated on problems of modelling a two-dimensional density and of clustering gene expression data.
Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals
Authors: Rasmussen Carl Edward 
Published: November 2023

Abstract
Hybrid Monte Carlo (HMC) is often the method of choice for computing Bayesian integrals that are not analytically tractable. However, the success of this method may require a very large number of evaluations of the (un-normalized) posterior and its partial derivatives. In situations where the posterior is computationally costly to evaluate, this may lead to an unacceptable computational load for HMC. I propose to use a Gaussian Process model of the (log of the) posterior for most of the computations required by HMC. Within this scheme only occasional evaluation of the actual posterior is required to guarantee that the samples generated have exactly the desired distribution, even if the GP model is somewhat inaccurate. The method is demonstrated on a 10 dimensional problem, where 200 evaluations suffice for the generation of 100 roughly independent points from the posterior. Thus, the proposed scheme allows Bayesian treatment of models with posteriors that are computationally demanding, such as models involving computer simulation.