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PubMed2001

PET evidence for multiple strategies of categorization.

It is widely held that people use multiple strategies to categorize their experiences in the world. We conducted a pair of neuroimaging experiments to identify the neural correlates of two of these strategies--rule application and exemplar similarity. Participants were instructed to perform either a rule- or an exemplar-based categorization task while changes in cerebral blood flow were measured using positron emission tomography. Patterns of neural activity were consistent with the predictions of cognitive models of rule-versus exemplar-based categorization and with existing neuroscience data. The identification of strategy-specific neural patterns offers future researchers a diagnostic tool for assessing strategy use in other situations.

Adolescent↗
PubMed2005

The need of neuroinformatic approach in functional neurophysiology.

Despite the enormous growth in the number of facts and regularities observed in neuroscience, the current state of the field does not allow their integration in coherent theoretical frameworks. Neuroinformatics is a new research field devoted to development of neuroscience data bases together with computational models and analytical tools for sharing, integration and analysis of experimental data and the advancement of theories of nervous system function. From 1996 the OECD countries promote fostering neuroinformatics by eliminating the barriers that prevent cooperation and by providing incentives to potential participants. This activity was formulated in the Report on Neuroinformatics from The Global Science Forum Neuroinformatics Working Group of the OECD (2002) as well as in several printed publications by the Neuroinformatics group (Amari et al. 2002, Eckersley et al. 2003). This article summarizes the ideas presented in the Report and stresses the importance of analytical and modeling approach to functional neurophysiology.

Electroencephalography↗
PubMed1999

[Practical aspects of realization of a functional MRI].

Functional MRI (fMRI) allows cognitive processes to be studied on an individual basis. fMRI is at the crossing of many fields, such as physiology, MRI physics, cognitive neurosciences, data analysis,.... Hence, it requires the collaboration of inter-disciplinary teams, in which neuroradiologists should play an important role. This article provides an overview of the general principles necessary to conduct fMRI studies on a practical matter (choice of magnetic field, patient set-up and preparation, paradigm design, data acquisition and analysis).

Cognition↗
PubMed2002

Non-curated distributed databases for experimental data and models in neuroscience.

Neuroscience is generating vast amounts of highly diverse data which is of potential interest to researchers beyond the laboratories in which it is collected. In particular, quantitative neuroanatomical data is relevant to a wide variety of areas, including studies of development, aging, pathology and in biophysically oriented computational modelling. Moreover, the relatively discrete and well-defined nature of the data make it an ideal application for developing systems designed to facilitate data archiving, sharing and reuse. At present, the only widely used forms of dissemination are figures and tables in published papers which suffer from inaccessibility and the loss of machine readability. They may also present only an averaged or otherwise selected subset of the available data. Numerous database projects are in progress to address these shortcomings. They employ a variety of architectures and philosophies, each with its own merits and disadvantages. One axis on which they may be distinguished is the degree of top-down control, or curation, involved in data entry. Here we consider one extreme of this scale in which there is no curation, minimal standardization and a wide degree of freedom in the form of records used to document data. Such a scheme has advantages in the ease of database creation and in the equitable assignment of perceived intellectual property by keeping the control of data in the hands of the experts who collected it. It does, however, require a more sophisticated infrastructure than conventional databases since the software must be capable of organizing diverse and differently documented data sets in an effective way. Several components of a software system to provide this infrastructure are now in place. Examples are presented, showing how these tools can be used to archive and publish neuronal morphology data, and how they can give an integrated view of data stored at many different sites.

Animals↗
PubMed2004

E-neuroscience: challenges and triumphs in integrating distributed data from molecules to brains.

Imaging, from magnetic resonance imaging (MRI) to localization of specific macromolecules by microscopies, has been one of the driving forces behind neuroinformatics efforts of the past decade. Many web-accessible resources have been created, ranging from simple data collections to highly structured databases. Although many challenges remain in adapting neuroscience to the new electronic forum envisioned by neuroinformatics proponents, these efforts have succeeded in formalizing the requirements for effective data sharing and data integration across multiple sources. In this perspective, we discuss the importance of spatial systems and ontologies for proper modeling of neuroscience data and their use in a large-scale data integration effort, the Biomedical Informatics Research Network (BIRN).

Animals↗
PubMed2001

The Ligand Gated Ion Channel database: an example of a sequence database in neuroscience.

Multiple comparisons of receptor sequences, or receptor subunit sequences, has proved to be an invaluable tool in modern pharmacological investigations. Although of outstanding importance, general sequence databases suffer from several imperfections due to their size and their non-specificity. Room therefore exists for expert-maintained databases of restricted focus, where knowledge of the research field helps to filter the huge amount of data generated. Accordingly, neuroscientists have designed databases covering several types of proteins, in particular receptors for neurotransmitters. Ligand-gated ion channels are oligomeric transmembrane proteins involved in the fast response to neurotransmitters. All these receptors are formed by the assembly of homologous subunits, and an unexpected wealth of genes coding for these subunits has been revealed during the last two decades. The Ligand Gated Ion Channel database (LGICdb) has been developed to handle this growing body of information. The database aims to provide only one entry for each gene, containing annotated nucleic acid and protein sequences.

Amino Acid Sequence↗
PubMed2004

QIS: A framework for biomedical database federation.

Query Integrator System (QIS) is a database mediator framework intended to address robust data integration from continuously changing heterogeneous data sources in the biosciences. Currently in the advanced prototype stage, it is being used on a production basis to integrate data from neuroscience databases developed for the SenseLab project at Yale University with external neuroscience and genomics databases. The QIS framework uses standard technologies and is intended to be deployable by administrators with a moderate level of technological expertise: It comes with various tools, such as interfaces for the design of distributed queries. The QIS architecture is based on a set of distributed network-based servers, data source servers, integration servers, and ontology servers, that exchange metadata as well as mappings of both metadata and data elements to elements in an ontology. Metadata version difference determination coupled with decomposition of stored queries is used as the basis for partial query recovery when the schema of data sources alters.

Computer Communication Networks↗
PubMed2002

Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury.

OBJECTIVES: To define optimal cerebral perfusion pressure (CPPOPT) in individual head-injured patients using continuous monitoring of cerebrovascular pressure reactivity. To test the hypothesis that patients with poor outcome were managed at a cerebral perfusion pressure (CPP) differing more from their CPPOPT than were patients with good outcome. DESIGN: Retrospective analysis of prospectively collected data. SETTING: Neurosciences critical care unit of a university hospital. PATIENTS: A total of 114 head-injured patients admitted between January 1997 and August 2000 with continuous monitoring of mean arterial blood pressure (MAP) and intracranial pressure (ICP). MEASUREMENTS AND MAIN RESULTS: MAP, ICP, and CPP were continuously recorded and a pressure reactivity index (PRx) was calculated online. PRx is the moving correlation coefficient recorded over 4-min periods between averaged values (6-sec periods) of MAP and ICP representing cerebrovascular pressure reactivity. When cerebrovascular reactivity is intact, PRx has negative or zero values, otherwise PRx is positive. Outcome was assessed at 6 months using the Glasgow Outcome Scale. A total of 13,633 hrs of data were recorded. CPPOPT was defined as the CPP where PRx reaches its minimum value when plotted against CPP. Identification of CPPOPT was possible in 68 patients (60%). In 22 patients (27%), CPPOPT was not found because it presumably lay outside the studied range of CPP. Patients' outcome correlated with the difference between CPP and CPPOPT for patients who were managed on average below CPPOPT (r =.53, p <.001) and for patients whose mean CPP was above CPPOPT (r = -.40, p <.05). CONCLUSIONS: CPPOPT could be identified in a majority of patients. Patients with a mean CPP close to CPPOPT were more likely to have a favorable outcome than those whose mean CPP was more different from CPPOPT. We propose use of the criterion of minimal achievable PRx to guide future trials of CPP oriented treatment in head injured patients.

Adolescent↗
PubMed2024

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Single-Cell Analysis↗
PubMed2023

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Brain organoids↗
PubMedDate not supplied

Integration of behavioral and relaxation approaches into the treatment of chronic pain and insomnia. NIH Technology Assessment Panel on Integration of Behavioral and Relaxation Approaches into the Treatment of Chronic Pain and Insomnia.

OBJECTIVE: To provide physicians with a responsible assessment of the integration of behavioral and relaxation approaches into the treatment of chronic pain and insomnia. PARTICIPANTS: A nonfederal, nonadvocate, 12-member panel representing the fields of family medicine, social medicine, psychiatry, psychology, public health, nursing, and epidemiology. In addition, 23 experts in behavioral medicine, pain medicine, sleep medicine, psychiatry, nursing, psychology, neurology, and behavioral and neurosciences presented data to the panel and a conference audience of 528 during a 1 1/2-day public session. Questions and statements from conference attendees were considered during the open session. Closed deliberations by the panel occurred during the remainder of the second day and the morning of the third day. EVIDENCE: The literature was searched through MEDLINE, and an extensive bibliography of references was provided to the panel and the conference audience. Experts prepared abstracts with relevant citations from the literature. Scientific evidence was given precedence over clinical anecdotal experience. ASSESSMENT PROCESS: The panel, answering predefined questions, developed their conclusions based on the scientific evidence presented in open forum and the scientific literature. The panel composed a draft statement that was read in its entirety and circulated to the experts and the audience for comment. Thereafter, the panel resolved conflicting recommendations and released a revised statement at the end of the conference. The panel finalized the revisions within a few weeks after the conference. CONCLUSIONS: A number of well-defined behavioral and relaxation interventions now exist and are effective in the treatment of chronic pain and insomnia. The panel found strong evidence for the use of relaxation techniques in reducing chronic pain in a variety of medical conditions as well as strong evidence for the use of hypnosis in alleviating pain associated with cancer. The evidence was moderate for the effectiveness of cognitive-behavioral techniques and biofeedback in relieving chronic pain. Regarding insomnia, behavioral techniques, particularly relaxation and biofeedback, produce improvements in some aspects of sleep, but it is questionable whether the magnitude of the improvement in sleep onset and total sleep time are clinically significant.

Behavior Therapy↗
PubMed1994

Computer models of the brain--how far can they take us?

The recent developments in computer capacity and algorithms, together with a tremendous growth of data in neuroscience have dramatically improved the possibilities of modeling and simulating certain brain structures and activities with a considerable degree of realism. Although there is still a long way to go, some claim that we will one day be able to create artificial "brains" with similar capacity to the human brain, perhaps even surpassing it. Here we focus on these perspectives, discussing the potentials and limitations of today's computer models, and how far they might be able to take us.

Brain↗
PubMed1987

Normal sleep: patterns and mechanisms.

In the last three decades, research in the sleep laboratory has decisively contributed to a much deeper knowledge of sleep physiologic and pathologic states. Parallel to clinical research related to sleep disorders, multifaceted basic research has greatly contributed to a better understanding of the mechanisms underlying sleep and wakefulness. This basic research in the realm of the neurosciences integrates data derived from the application of various methodologic approaches. Currently, the prevailing concepts about sleep mechanisms generally favor the idea of a dynamic interaction among systems rather than that of a unidimensional explanation for sleep generation. Examples of these integrative concepts in current sleep research are the revised model of reciprocal interaction for the control of REM sleep and the two-process model comprising the seemingly incompatible homeostatic and circadian sleep mechanisms. In sleep disorders medicine, the prevailing approach is also integrative: findings from the sleep laboratory are considered in conjunction with those from clinical experience in understanding the nature of sleep disorders. Applying this integrative model, physicians in sleep disorders medicine are able to manage patients with sleep disorders comprehensively. Based on an understanding of sleep physiology, clinicians can make the diagnosis of most sleep disorders in the office setting.

Adolescent↗
PubMed2006

How does current care practice influence the experience of a new diagnosis of motor neuron disease? A qualitative study of current guidelines-based practice.

Management during the diagnostic phase of MND is considered an important influence on the patient's further disease course. Guidelines for the management of MND have been developed, but little is known on how recommended practices influence patients' experience of a new diagnosis of MND. We undertook an interview-based study exploring issues surrounding the diagnosis of MND in a sample of consecutive patients recently diagnosed at a neurosciences centre. Data were analysed with Interpretative Phenomenological Analysis (IPA). Thirteen patients were recruited to the study. The major themes identified in descending order were 'Family/carers', 'Communication of the diagnosis', 'Reaction to the diagnosis', 'Physical difficulties', 'Time before diagnosis', 'Information', 'Future', 'Coping with the diagnosis' and 'Formal support'. Communication was perceived satisfactory if handled according to existing guidelines. Physical difficulties impacted considerably on patients' lives. Delays in the diagnostic process appeared in various interviews. Five patients were avoiding information following the diagnosis. Some patients commented on an increasing number of uncoordinated services becoming involved after their diagnosis. This study supports the current international guidelines for MND care around diagnosis from the patients' perspective and underlines the importance of a multi-disciplinary, coordinated approach for patients with MND from diagnosis onwards.

Adult↗
PubMed1994

Advances in managing increased intracranial pressure: a decade of selected research.

There have been tremendous advances in the diagnosis and treatment of increased intracranial pressure in the past decade. The author presents a review of the pathophysiology of intracranial hypertension, incorporating recent data from neuroscience research. Additional investigations that have implications for the nursing care of patients with actual or potential intracranial pressure also are described.

Cerebrospinal Fluid Pressure↗