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PubMed1989

Iron and learning potential in childhood.

Cognitive function. There is reasonably good evidence that mental and motor developmental test scores are lower among infants with iron deficiency anemia. Although the research on cognitive function in iron deficient older children and adults is sparse and diverse, it suggests that there may be alterations in attentional processes associated with iron deficiency. Iron therapy has not yet been shown effective in completely correcting many of the observed disturbances. Although some aspects of cognitive function seem to change with iron therapy, lower developmental. I.Q., and achievement test scores have still been noted after treatment. The behavioral effects of iron-deficiency anemia may be due to changes in neurotransmission. However, the biochemical bases are not yet completely understood. Noncognitive disturbances. A variety of noncognitive alterations during infant developmental testing has also been observed, including failure to respond to test stimuli, short attention span, unhappiness, increased fearfulness, withdrawal from the examiner, and increased body tension. Exploratory analyses suggest that such behavioral abnormalities may account for poor developmental test performance in infants with iron deficiency anemia. These studies indicate the fruitfulness of examining noncognitive aspects of behavior such as affect, attention, and activity, in addition to specific cognitive processes. Activity and work capacity: There has been a steady accumulation of evidence that iron-deficiency anemia limits maximal physical performance, submaximal endurance, and spontaneous activity in the adult, resulting in diminished work productivity with attendant economic losses. The relative importance of central and peripheral mechanisms underlying these effects, the extent to which anemia or iron deficiency separate from anemia is responsible, and the counterpart in infants and children remain to be established. This essay has examined recent evidence from research on central nervous system biochemistry and from human studies that iron deficiency adversely affects behavior by impairing cognitive function, producing noncognitive disturbances, and limiting activity and work capacity. The body of research taken as a whole provides increasingly persuasive arguments for intensifying efforts to prevent and treat iron deficiency anemia.

Anemia, Hypochromic↗

PubMed1995

A population of wide-field bipolar cells in the rabbit's retina.

We have stained an unusual population of retinal bipolar cells. When the low molecular weight tracer biocytin was injected into the vitreous body of rabbits, it subsequently accumulated in the somata and processes of a population of wide-field bipolar cells. The cells have 2-4 primary dendrites. Their dendritic arbors span a field 50 to 200 microns in diameter. The axonal arbors are sparse and often highly asymmetric. The longest dimension of the axonal arbor ranges from 100 to 300 microns. The cells are moderately evenly spaced. They make up less than 1% of the total population of bipolar cells in the rabbit retina. With the whole population stained, regularities in the spatial arrangement of nearby cells can be recognized. Their dendrites often run to a common point, where they have the appearance of making contact with each other. A similar arrangement is seen for the cells' axonal arbors, so that the whole population is spatially linked in both the outer retina and the inner. The exact nature of the points of conjunction cannot be learned from light microscopy. One possibility is that the processes run together because they contact a common target. If so, the target structures (one in the outer retina and one in the inner) must be sparse. An alternative is that the points of conjunction represent synapses or gap junctions among wide-field bipolars of this type.

Animals↗

PubMed2003

On the choice of a sparse prior.

An emerging paradigm analyses in what respect the properties of the nervous system reflect properties of natural scenes. It is hypothesized that neurons form sparse representations of natural stimuli: each neuron should respond strongly to some stimuli while being inactive upon presentation of most others. For a given network, sparse representations need fewest spikes, and thus the nervous system can consume the least energy. To obtain optimally sparse responses the receptive fields of simulated neurons are optimized. Algorithmically this is identical to searching for basis functions that allow coding for the stimuli with sparse coefficients. The problem is identical to maximizing the log likelihood of a generative model with prior knowledge of natural images. It is found that the resulting simulated neurons share most properties of simple cells found in primary visual cortex. Thus, forming optimally sparse representations is a very compact approach to describing simple cell properties. Many ways of defining sparse responses exist and it is widely believed that the particular choice of the sparse prior of the generative model does not significantly influence the estimated basis functions. Here we examine this assumption more closely. We include the constraint of unit variance of neuronal activity, used in most studies, into the objective functions. We then analyze learning on a database of natural (cat-cam) visual stimuli. We show that the effective objective functions are largely dominated by the constraint, and are therefore very similar. The resulting receptive fields show some similarities but also qualitative differences. Even for coefficient values for which the objective functions are dissimilar, the distributions of coefficients are similar and do not match the priors of the assumed generative model. In conclusion, the specific choice of the sparse prior is relevant, as is the choice of additional constraints, such as normalization of variance.

Algorithms↗

PubMed2000

Coincidence detection in single dendritic spines mediated by calcium release.

Cerebellar long-term depression (LTD) is a calcium-dependent process in which coincident activity of parallel fiber (PF) and climbing fiber (CF) synapses causes a long-lasting decrease in PF synaptic strength onto Purkinje cells. Here we show that pairing CF activation with bursts of PF activity triggers large (>10 microM) calcium signals in Purkinje cell dendrites. When PFs are densely activated, signals span whole dendritic branchlets and are mediated by voltage-dependent calcium entry. When PFs are sparsely activated, however, signals are restricted to single spines and blocked by metabotropic glutamate receptor antagonists. Single-spine signals and sparse-stimulation LTD are also blocked by thapsigargin, indicating that calcium must be released from stores. Single-spine signals and sparse-stimulation LTD are greatest when PF activation precedes the CF activation within 50-200 ms. This timing rule matches the properties of several forms of motor learning, providing a link between behavior and functional properties of cerebellar synaptic plasticity.

Animals↗

PubMed2005

Blind deconvolution of images using optimal sparse representations.

The relative Newton algorithm, previously proposed for quasi-maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind deconvolution of images. Smooth approximation of the absolute value is used as the nonlinear term for sparse sources. In addition, we propose a method of sparsification, which allows blind deconvolution of arbitrary sources, and show how to find optimal sparsifying transformations by supervised learning.

Algorithms↗

PubMed2006

Enhancing text categorization with semantic-enriched representation and training data augmentation.

OBJECTIVE: Acquiring and representing biomedical knowledge is an increasingly important component of contemporary bioinformatics. A critical step of the process is to identify and retrieve relevant documents among the vast volume of modern biomedical literature efficiently. In the real world, many information retrieval tasks are difficult because of high data dimensionality and the lack of annotated examples to train a retrieval algorithm. Under such a scenario, the performance of information retrieval algorithms is often unsatisfactory, therefore improvements are needed. DESIGN: We studied two approaches that enhance the text categorization performance on sparse and high data dimensionality: (1) semantic-preserving dimension reduction by representing text with semantic-enriched features; and (2) augmenting training data with semi-supervised learning. A probabilistic topic model was applied to extract major semantic topics from a corpus of text of interest. The representation of documents was projected from the high-dimensional vocabulary space onto a semantic topic space with reduced dimensionality. A semi-supervised learning algorithm based on graph theory was applied to identify potential positive training cases, which were further used to augment training data. The effects of data transformation and augmentation on text categorization by support vector machine (SVM) were evaluated. RESULTS AND CONCLUSION: Semantic-enriched data transformation and the pseudo-positive-cases augmented training data enhance the efficiency and performance of text categorization by SVM.

Algorithms↗

PubMed2006

Nitric oxide regulates input specificity of long-term depression and context dependence of cerebellar learning.

Recent studies have shown that multiple internal models are acquired in the cerebellum and that these can be switched under a given context of behavior. It has been proposed that long-term depression (LTD) of parallel fiber (PF)-Purkinje cell (PC) synapses forms the cellular basis of cerebellar learning, and that the presynaptically synthesized messenger nitric oxide (NO) is a crucial "gatekeeper" for LTD. Because NO diffuses freely to neighboring synapses, this volume learning is not input-specific and brings into question the biological significance of LTD as the basic mechanism for efficient supervised learning. To better characterize the role of NO in cerebellar learning, we simulated the sequence of electrophysiological and biochemical events in PF-PC LTD by combining established simulation models of the electrophysiology, calcium dynamics, and signaling pathways of the PC. The results demonstrate that the local NO concentration is critical for induction of LTD and for its input specificity. Pre- and postsynaptic coincident firing is not sufficient for a PF-PC synapse to undergo LTD, and LTD is induced only when a sufficient amount of NO is provided by activation of the surrounding PFs. On the other hand, above-adequate levels of activity in nearby PFs cause accumulation of NO, which also allows LTD in neighboring synapses that were not directly stimulated, ruining input specificity. These findings lead us to propose the hypothesis that NO represents the relevance of a given context and enables context-dependent selection of internal models to be updated. We also predict sparse PF activity in vivo because, otherwise, input specificity would be lost.

Action Potentials↗

PubMed2005

Theta oscillations by synaptic excitation in a neocortical circuit model.

Neocortical theta-band oscillatory activity is associated with cognitive tasks involving learning and memory. This oscillatory activity is proposed to originate from the synchronization of interconnected layer V intrinsic bursting (IB) neurons by recurrent excitation. To test this hypothesis, a sparsely connected spiking circuit model based on empirical data was simulated using Hodgkin-Huxley-type bursting neurons and use-dependent depressing synaptic connections. In response to a heterogeneous tonic current stimulus, the model generated coherent and robust oscillatory activity throughout the theta-band (4-12 Hz). These oscillations were not, however, self-sustaining without a driving current, and not dependent on N-methyl-D-aspartate receptor synaptic currents. At realistic connection strengths, synaptic depression was necessary to avoid instability and expanded the basin of attraction for theta oscillations by controlling the gain of recurrent excitation. These results support the hypothesis that IB neuron networks can generate robust and coherent theta-band oscillations in neocortex.

Animals↗

PubMed2000

A model of invariant object recognition in the visual system: learning rules, activation functions, lateral inhibition, and information-based performance measures.

VisNet2 is a model to investigate some aspects of invariant visual object recognition in the primate visual system. It is a four-layer feedforward network with convergence to each part of a layer from a small region of the preceding layer, with competition between the neurons within a layer and with a trace learning rule to help it learn transform invariance. The trace rule is a modified Hebbian rule, which modifies synaptic weights according to both the current firing rates and the firing rates to recently seen stimuli. This enables neurons to learn to respond similarly to the gradually transforming inputs it receives, which over the short term are likely to be about the same object, given the statistics of normal visual inputs. First, we introduce for VisNet2 both single-neuron and multiple-neuron information-theoretic measures of its ability to respond to transformed stimuli. Second, using these measures, we show that quantitatively resetting the trace between stimuli is not necessary for good performance. Third, it is shown that the sigmoid activation functions used in VisNet2, which allow the sparseness of the representation to be controlled, allow good performance when using sparse distributed representations. Fourth, it is shown that VisNet2 operates well with medium-range lateral inhibition with a radius in the same order of size as the region of the preceding layer from which neurons receive inputs. Fifth, in an investigation of different learning rules for learning transform invariance, it is shown that VisNet2 operates better with a trace rule that incorporates in the trace only activity from the preceding presentations of a given stimulus, with no contribution to the trace from the current presentation, and that this is related to temporal difference learning.

Algorithms↗

PubMed2003

Clinical exposure during clinical method attachments in general practice.

BACKGROUND: There has been a significant decline in medical students' clinical experience in hospitals. Hospital-based teaching is struggling to provide medical students with sufficient experience of the common health problems of our industrialized ageing society. Hence, general practice has become an important locus for medical education. Published evidence, however, that students can access appropriate clinical experience in general practice is sparse. OBJECTIVE: To determine students' clinical exposure during clinical and method attachments based in general practice at two medical schools. EDUCATIONAL INITIATIVE: Students were attached to general practice tutors to learn clinical method in internal medicine. METHOD: General practice tutors from two medical schools collected data on age, gender, diagnoses, symptoms and signs of the patients they invited to teaching sessions. RESULTS: The frequency of diagnoses, symptoms and signs seen by medical students are recorded. Students mostly saw patients with chronic illnesses; the commonest diagnoses were ischaemic heart disease and angina. DISCUSSION: Our study has recorded the largest published database of clinical diagnoses, symptoms and signs encountered by students learning clinical method in general practice. It shows that students obtained a wealth of experience with patients with common chronic diseases. Students must also learn in the hospital setting, to experience the presentation of acute illness. The combination of teaching in these two settings is likely to provide the most effective technique to ensure that students encounter the common, acute and chronic conditions that affect patients in the 21st century.

Clinical Clerkship↗

PubMed2026

GiantHost: a domain-adaptive and uncertainty-aware framework for giant virus host prediction.

MOTIVATION: Nucleocytoplasmic large DNA viruses (NCLDVs) play crucial roles in global ecosystems. Although metagenomics has vastly accelerated the discovery of novel NCLDVs, predicting their hosts from fragmented contigs remains a critical bottleneck, with no dedicated end-to-end computational tools currently available. Addressing this gap requires overcoming three fundamental challenges: the extreme scarcity of labeled reference genomes, the severe domain shift between laboratory isolates and diverse environmental metagenomes, and the inability of traditional deterministic models to quantify prediction uncertainty-a crucial requirement for reliable ecological profiling where novel, divergent viruses are prevalent. RESULTS: We present GiantHost, the first NCLDV host prediction tool with domain adaptation and uncertainlty awareness. GiantHost employs a dual-tower neural network to integrate dense genome traits and sparse GVOG profiles, allowing better integration of heterogeneous features. To overcome label scarcity and domain shift, we leverage 1400 environmental viral genomes (GVMAGs) via semi-supervised multi-task learning and Domain Adversarial Neural Networks (DANN), effectively bridging the distributional gap between RefSeq and environmental data. Additionally, GiantHost incorporates Conformal Prediction (CP) to output statistically guaranteed prediction sets rather than overconfident single labels. Evaluated under rigorous genome-level cross-validation, GiantHost demonstrates robust predictive power. Applied to the Tara Ocean dataset, GiantHost successfully captured the vertical stratification of NCLDV hosts-revealing a depth-dependent decline of phytoplankton-infecting viruses and a relative enrichment of Amoebozoa-infecting viruses in the mesopelagic zone. AVAILABILITY: The source code of GiantHost is available via: https://github.com/FuchuanQu/GiantHost.

Giant Viruses↗

PubMed2002

The restricted influence of sparseness of coding on the capacity of familiarity discrimination networks.

Much evidence indicates that the perirhinal cortex is involved in the familiarity discrimination aspect of recognition memory. It has been previously shown under selective conditions that neural networks performing familiarity discrimination can achieve very high storage capacity, being able to deal with many times more stimuli than associative memory networks can in associative recall. The capacity of associative memories for recall has been shown to be highly dependent on the sparseness of coding. However, previous work on the networks of Bogacz et al, Norman and O'Reilly and Sohal and Hasselmo that model familiarity discrimination in the perirhinal cortex has not investigated the effects of the sparseness of encoding on capacity. This paper explores how sparseness of coding influences the capacity of each of these published models and establishes that sparse coding influences the capacity of the different models in different ways. The capacity of the Bogacz et al model can be made independent of the sparseness of coding. Capacity increases as coding becomes sparser for a simplified version of the neocortical part of the Norman and O'Reilly model, whereas capacity decreases as coding becomes sparser for a simplified version of the Sohal and Hasselmo model. Thus in general, and in contrast to associative memory networks, sparse encoding results in little or no advantage for the capacity of familiarity discrimination networks. Hence it may be less important for coding to be sparse in the perirhinal cortex than it is in the hippocampus. Additionally, it is established that the capacities of the networks are strongly dependent on the precise form of the learning rules (synaptic plasticity) used in the network. This finding indicates that the precise characteristics of synaptic plastic changes in the real brain are likely to have major influences on storage capacity.

Animals↗

PubMedDate not supplied

[Unusual reactions to food additives].

The most important symptoms caused by food additives are urticaria and angioedema, but rhinitis, asthma and gastrointestinal disturbances are also reported. Only seldom food additives have been shown to induce symptoms in other organs such central nervous system or joints and with a sparse objective evidence. In this study, we report two cases of unusual reactions to food additives (tartrazine and benzoates) involving mainly the central nervous system (headache, migraine, overactivity, concentration and learning difficulties, depression) and joints (arthralgias), confirmed with diet and double blind challenge. The possible pathogenetic mechanisms are also discussed.

Adolescent↗

PubMedDate not supplied

Policy development in disaster preparedness and management: lessons learned from the January 2001 earthquake in Gujarat, India.

INTRODUCTION: During the last decades, several humanitarian emergencies have occurred, with an increasing number of humanitarian organizations taking part in providing assistance. However, need assessments, medical intelligence, and coordination of the aid often are sparse, resulting in the provision of ineffective and expensive assistance. When an earthquake with the strength of 7.7 on the Richter scale struck the state of Gujarat, India, during the early morning on 26 January 2001, nearly 20,000 persons were killed, nearly 170,000 were injured, and 600,000 were rendered homeless. This study identifies how assigned indicators to measure the level of health care may improve disaster preparedness and management, thus, reducing human suffering. METHODS: During a two-week mission in the disaster area, the disaster relief provided to the disaster-affected population of Gujarat was evaluated. Vulnerability due to climate, geography, culture, religion, gender, politics, and economy, as each affected the outcome, was studied. By assigning indicators to the eight ELEMENTS of the Primary Health Care System as advocated by the World Health Organization (WHO), the level of public health and healthcare services were estimated, an evaluation of the impact of the disaster was conducted, and possible methods for improving disaster management are suggested. Representatives of the major relief organizations involved were interviewed on their relief policies. Strategies to improve disaster relief, such as policy development in the different aspects of public health/primary health care, were sought. RESULTS: Evaluation of the pre-event status of the affected society revealed a complex situation in a vulnerable society with substantial deficiencies in the existing health system that added to the severity of the disaster. Most of the civilian hospitals had collapsed, and army field hospitals provided medical care to most of the patients under primitive conditions using tents. When the foreign field hospitals arrived five to seven days after the earthquake, most of the casualties requiring surgical intervention already had been operated on. Relief provided to the disaster victims had reduced quality for the following reasons: (1) proper public health indicators had not yet been developed; (2) efficient coordination was lacking, (3) insufficient, overestimated, or partly irrelevant relief was provided; (4) relief was delayed because of bureaucracy; and (5) policies on the delivery of disaster relief had not been developed. CONCLUSION: To optimize the effectiveness of limited resources, disaster preparedness and the provision of feasible and necessary aid is of utmost importance. An appropriate, rapid, crisis intervention could be achieved by continual surveillance of the world's situation by a Relief Coordination Center. A panel of experts could evaluate and coordinate the international disaster responses and make use of stored emergency material and emergency teams. A successful disaster response will depend on accurate and relevant medical intelligence and socio-geographical mapping in advance of, during, and after the event(s) causing the disaster. More effective and feasible equipment coordinated with the relief provided by the rest of the world is necessary. If policies and agreements are developed as part of disaster preparedness, on international, bilateral, and national levels, disaster relief may be more relevant, less chaotic, and easier to estimate, thus, bringing improved relief to the disaster victims.

Disaster Planning↗

PubMed2003

Central projections of the saccular and utricular nerves in macaques.

The central projections of the utricular and saccular nerve in macaques were examined using transganglionic labeling of vestibular afferent neurons. In these experiments, biotinylated dextran amine was injected directly into the saccular or utricular neuroepithelium of fascicularis (Macaca fascicularis) or rhesus (Macaca mulatta) monkeys. Two to 5 weeks later, the animals were killed and the peripheral vestibular sensory organs, brainstem, and cerebellum were collected for analysis. The principal brainstem areas of saccular nerve termination were lateral, particularly the spinal vestibular nucleus, the lateral portion of the superior vestibular nucleus, ventral nucleus y, the external cuneate nucleus, and cell group l. The principal cerebellar projection was to the uvula with a less dense projection to the nodulus. Principle brainstem areas of termination of the utricular nerve were the lateral/dorsal medial vestibular nucleus, ventral and lateral portions of the superior vestibular nucleus, and rostral portion of the spinal vestibular nucleus. In the cerebellum, a strong projection was observed to the nodulus and weak projections were present in the flocculus, ventral paraflocculus, bilateral fastigial nuclei, and uvula. Although there is extensive overlap of saccular and utricular projections, saccular inputs to the lateral portions of the vestibular nuclear complex suggest that saccular afferents contribute to the vestibulospinal system. In contrast, the utricular nerve projects more rostrally into areas of known concentration of vestibulo-ocular related cells. Although sparse, the projections of the utricle to the flocculus/ventral paraflocculus suggest a potential convergence with floccular projection inputs from the vestibular brainstem that have been implicated in vestibulo-ocular motor learning.

Afferent Pathways↗

PubMed2007

Relevance of donepezil in enhancing learning and memory in special populations: a review of the literature.

This review discusses the laboratory and clinical research supporting the rationale for the efficacy of donepezil (Aricept USA) in enhancing cognition in autism, Alzheimer disease, Down syndrome, traumatic brain injury, Attention Deficit Hyperactivity Disorder (ADHD), and schizophrenia. While preliminary animal models have shown effective, human studies exclusive of Alzheimer disease are sparse. Although attention and memory are unlikely a sole operation of the cholinergic system, evidence indicates a promising direction for further examination of this hypothesis in autism. Studies that examine changes in operationally defined behaviors and reliable and valid measure of changes in attention and memory are needed.

Alzheimer Disease↗

PubMed2006

Distribution of gonadotropin releasing-hormone-II in the house sparrow brain (Passer domesticus).

In songbirds, three isoforms of gonadotropin-releasing hormone (GnRH) have been reported: chicken GnRH-I (GnRH-I); and -II (GnRH-II); and lamprey GnRH-III (lGnRH-III). In galliformes, the distribution of GnRH-I and -II have been extensively studied. GnRH-I cell bodies are located primarily in the preoptic-septal region and primarily project to the median eminence. GnRH-II cell bodies are located in the midbrain and project to various hypothalamic and extrahypothalamic regions. In songbirds, the distributions of only GnRH-I and lGnRH-III have been thoroughly described. Songbirds differ from galliformes in that they possess specialized neural regions for the learning and production of complex vocalizations, the song-control system. In songbirds lGnRH-III was found within many song nuclei. In this study, we investigated the distribution of GnRH-II in the male house sparrow (Passer domesticus) brain. Our objectives were (1) to determine the distribution of GnRH-II in the male songbird brain and (2) to investigate the presence of GnRH-II in song control nuclei. Our study identified immunoreactive magnocellular GnRH-II cell bodies in the oculomotor region of the mesencephalon and parvicellular cells in the lateral hypothalamus. Also, an extensive network of GnRH-II immunoreactive fibres was observed in hypothalamic nuclei and extrahypothalamic regions. Immunoreactive GnRH-II fibres were most abundant in the preoptic area, ventromedial nucleus, hippocampus and the medial septum. Sparse immunoreactivity was also observed in the mesencephalon and diencephalon. GnRH-II was not identified in any of the song-control nuclei. Unlike lGnRH-III, these data suggest that GnRH-II is not directly involved with song learning, perception or production.

Animals↗

PubMed1996

Differential expression of NADPH diaphorase in functionally distinct prefrontal cortices in the rhesus monkey.

The prefrontal cortex of primates is an integrative centre for sensory, cognitive, mnemonic and emotional processes. The cellular features which contribute to the functional specialization of its subsectors are poorly understood. In this study we determined the distribution of nicotinamide adenine dinucleotide phosphate-diaphorase-positive neurons in structurally and functionally distinct prefrontal cortices in the rhesus monkey. This class of neurons express nitric oxide synthase which is necessary for the production of nitric oxide, a novel neural messenger implicated in learning and memory. The density of diaphorase-positive neurons was approximately four times higher in olfactory areas than in eulaminate areas (areas 9, 10, 12, 46, and 8), and two- to three-times higher in the agranular limbic area PAll than in eulaminate areas. Positive neurons were concentrated in a deep band (layers V and VI), a superficial band (layers II and upper III), and were sparsely distributed in the central, thalamic recipient zone (deep layer III, layer IV and upper V). The highest densities of positive neurons were observed in the white matter where their prevalence followed the opposite trend than in the corresponding overlying cortices. The distribution of diaphorase-positive neurons was correlated with the regional anatomic and functional specialization of prefrontal cortices. Thus, diaphorase-positive neurons were most densely distributed in orbital and then medial prefrontal limbic cortices which have a low cell density and widespread connections. In contrast, positive neurons were comparatively sparse in eulaminate cortices, which have a high cell density and more restricted connections. These findings indicated that the distribution of diaphorase-positive neurons in prefrontal cortices is not random, but is associated with the structural architecture and functional attributes of these cortices. The preponderance of diaphorase-positive neurons in limbic cortices, which have been implicated in learning and memory, is consistent with the idea that nitric oxide may have a role in synaptic plasticity.

Animals↗