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Checkpoint inhibitors targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) have revolutionized cancer therapy across many indications including urothelial carcinoma (UC). Because many patients do not benefit, a better understanding of the molecular mechanisms underlying response and resistance is needed to improve outcomes. We profiled tumors from 2,803 UC patients from four late-stage randomized clinical trials evaluating the PD-L1 inhibitor atezolizumab by RNA sequencing (RNA-seq), a targeted DNA panel, immunohistochemistry, and digital pathology. Machine learning identifies four transcriptional subtypes, representing luminal desert, stromal, immune, and basal tumors. Overall survival benefit from atezolizumab over standard-of-care is observed in immune and basal tumors, through different response mechanisms. A self-supervised digital pathology approach can classify molecular subtypes from H&E slides with high accuracy, which could accelerate tumor molecular profiling. This study represents a large integration of UC molecular and clinical data in randomized trials, paving the way for clinical studies tailoring treatment to specific molecular subtypes in UC and other indications., Competing Interests: Declaration of interests All Genentech-affiliated authors are shareholders in Roche. H.H., S. Mariathasan., and R.B. are listed on a pending patent related to this work. P.G. is consulting for 4D Pharma, Aadi Bioscience, Asieris Pharmaceuticals, Astellas, AstraZeneca, BostonGene, Bristol Myers Squibb, CG Oncology, Dyania Health, Exelixis, Fresenius Kabi, G1 Therapeutics, Genentech, Gilead Sciences, Guardant Health, ImmunityBio, Infinity Pharmaceuticals, Janssen, Lucence, Merck KGaA, Mirati Therapeutics, MSD, Pfizer, PureTech, QED Therapeutics, Regeneron, Roche, Seattle Genetics, Silverback Therapeutics, Strata Oncology, UroGen Pharma, and receives institutional research funding from ALX Oncology, Acrivon Therapeutics, Bavarian Nordic, Bristol Myers Squibb, Clovis Oncology, Debiopharm Group, G1 Therapeutics, Gilead Sciences, GSK, Merck KGaA, Mirati Therapeutics, MSD, Pfizer, QED Therapeutics. E. Sokol. is an employee at Foundation Medicine and a shareholder in Roche. M.D.G. receives research funding from Bristol Myers Squibb, Novartis, Dendreon, Astra Zeneca, Merck, Genentech, and acts as Advisory Board/Consultant for Bristol Myers Squibb, Merck, Genentech, AstraZeneca, Pfizer, EMD Serono, SeaGen, Janssen, Numab, Dragonfly, GlaxoSmithKline, Basilea, UroGen, Rappta Therapeutics, Alligator, Silverback, Fujifilm, Curis, Gilead, Bicycle, Asieris, Abbvie, Analog Devices, Veracyte. T.P. receives honararia and research funding from Roche, Astellas, Seagen, MSD, Merck-Serono, BMS, Pfizer, Ipsen, AZ, Johnson and johnson, Mashup-Media, Exelixis, Eisai, Natera, FMI, Novartis, Bayer. J. Rosenberg is a Consultant for Aadi Bioscience; Alligator Bioscience; Astellas; AstraZeneca Pharmaceuticals LP; Boehringer Ingelheim Pharmaceuticals Inc; Bristol-Myers Squibb Company; Century Therapeutics Inc; EMD Serono Inc; Emergence Therapeutics; Genentech, a member of the Roche Group; Gilead Sciences Inc; Imvax Inc; Jiangsu Hengrui Medicine Co Ltd; Eli Lilly; Merck; Mirati Therapeutics Inc; Pfizer Inc; Seagen Inc; Tyra Biosciences, has Grant/Research support from Seagen Inc, Genentech/Roche, Astellas, Acrivon and receives honoraria from Pfizer Inc, EMD-Serono Inc, MJH Life Sciences, Research to Practice, Clinical Care Options. M.S.v.d.H. receives research funding from Bristol Myers Squibb, AstraZeneca, 4SC and Roche, and consultancy fees from Bristol Myers Squibb, Roche, Merck Sharp & Dohme, Merck, AstraZeneca, Pfizer, Janssen and Seattle Genetics, which were all paid to the Netherlands Cancer Institute., (Copyright © 2024 Elsevier Inc. All rights reserved.)

While our understanding of the way single neurons process chromatic stimuli in the early visual pathway has advanced significantly in recent years, we do not yet know how these cells interact to form stable representations of hue. Drawing on physiological studies, we offer a dynamical model of how the primary visual cortex tunes for color, hinged on intracortical interactions and emergent network effects. After detailing the evolution of network activity through analytical and numerical approaches, we discuss the effects of the model's cortical parameters on the selectivity of the tuning curves. In particular, we explore the role of the model's thresholding nonlinearity in enhancing hue selectivity by expanding the region of stability, allowing for the precise encoding of chromatic stimuli in early vision. Finally, in the absence of a stimulus, the model is capable of explaining hallucinatory color perception via a Turing-like mechanism of biological pattern formation., (© 2023 Massachusetts Institute of Technology.)

In 1972-1973 Wilson and Cowan introduced a mathematical model of the population dynamics of synaptically coupled excitatory and inhibitory neurons in the neocortex. The model dealt only with the mean numbers of activated and quiescent excitatory and inhibitory neurons, and said nothing about fluctuations and correlations of such activity. However, in 1997 Ohira and Cowan, and then in 2007-2009 Buice and Cowan introduced Markov models of such activity that included fluctuation and correlation effects. Here we show how both models can be used to provide a quantitative account of the population dynamics of neocortical activity.We first describe how the Markov models account for many recent measurements of the resting or spontaneous activity of the neocortex. In particular we show that the power spectrum of large-scale neocortical activity has a Brownian motion baseline, and that the statistical structure of the random bursts of spiking activity found near the resting state indicates that such a state can be represented as a percolation process on a random graph, called directed percolation.Other data indicate that resting cortex exhibits pair correlations between neighboring populations of cells, the amplitudes of which decay slowly with distance, whereas stimulated cortex exhibits pair correlations which decay rapidly with distance. Here we show how the Markov model can account for the behavior of the pair correlations.Finally we show how the 1972-1973 Wilson-Cowan equations can account for recent data which indicates that there are at least two distinct modes of cortical responses to stimuli. In mode 1 a low intensity stimulus triggers a wave that propagates at a velocity of about 0.3 m/s, with an amplitude that decays exponentially. In mode 2 a high intensity stimulus triggers a larger response that remains local and does not propagate to neighboring regions.

Objectives: We describe the development, implementation, and evaluation of a model to pre-emptively select patients for genotyping based on medication exposure risk., Study Design and Setting: Using deidentified electronic health records, we derived a prognostic model for the prescription of statins, warfarin, or clopidogrel. The model was implemented into a clinical decision support (CDS) tool to recommend pre-emptive genotyping for patients exceeding a prescription risk threshold. We evaluated the rule on an independent validation cohort and on an implementation cohort, representing the population in which the CDS tool was deployed., Results: The model exhibited moderate discrimination with area under the receiver operator characteristic curves ranging from 0.68 to 0.75 at 1 and 2 years after index dates. Risk estimates tended to underestimate true risk. The cumulative incidences of medication prescriptions at 1 and 2 years were 0.35 and 0.48, respectively, among 1,673 patients flagged by the model. The cumulative incidences in the same number of randomly sampled subjects were 0.12 and 0.19, and in patients over 50 years with the highest body mass indices, they were 0.22 and 0.34., Conclusion: We demonstrate that prognostic algorithms can guide pre-emptive pharmacogenetic testing toward those likely to benefit from it., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect of heparin treatment resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. No genome-wide evaluations have been performed to identify potential genetic influences on HIT. Here, we performed a genome-wide association study (GWAS) and candidate gene study using HIT cases and controls identified using electronic medical records (EMRs) coupled to a DNA biobank and attempted to replicate GWAS associations in an independent cohort. We subsequently investigated influences of GWAS-associated single nucleotide polymorphisms (SNPs) on PF4/heparin antibodies in non-heparin treated individuals. In a recessive model, we observed significant SNP associations (odds ratio [OR] 18.52; 95% confidence interval [CI] 6.33-54.23; p=3.18×10(-9)) with HIT near the T-Cell Death-Associated Gene 8 (TDAG8). These SNPs are in linkage disequilibrium with a missense TDAG8 SNP. TDAG8 SNPs trended toward an association with HIT in replication analysis (OR 5.71; 0.47-69.22; p=0.17), and the missense SNP was associated with PF4/heparin antibody levels and positive PF4/heparin antibodies in non-heparin treated patients (OR 3.09; 1.14-8.13; p=0.02). In the candidate gene study, SNPs at HLA-DRA were nominally associated with HIT (OR 0.25; 0.15-0.44; p=2.06×10(-6)). Further study of TDAG8 and HLA-DRA SNPs is warranted to assess their influence on the risk of developing HIT.

Unlabelled: Measurements of neuronal signals during human seizure activity and evoked epileptic activity in experimental models suggest that, in these pathological states, the individual nerve cells experience an activity driven depolarization block, i.e. they saturate. We examined the effect of such a saturation in the Wilson-Cowan formalism by adapting the nonlinear activation function; we substituted the commonly applied sigmoid for a Gaussian function. We discuss experimental recordings during a seizure that support this substitution. Next we perform a bifurcation analysis on the Wilson-Cowan model with a Gaussian activation function. The main effect is an additional stable equilibrium with high excitatory and low inhibitory activity. Analysis of coupled local networks then shows that such high activity can stay localized or spread. Specifically, in a spatial continuum we show a wavefront with inhibition leading followed by excitatory activity. We relate our model simulations to observations of spreading activity during seizures., Electronic Supplementary Material: The online version of this article (doi:10.1186/s13408-015-0019-4) contains supplementary material 1.

The last decade has seen an exponential growth in the quantity of clinical data collected nationwide, triggering an increase in opportunities to reuse the data for biomedical research. The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-for-service custom services, and tools built atop the data layer to assist researchers across the enterprise. Providing resources dedicated to research initiatives benefits not only the research community, but also clinicians, patients and institutional leadership. This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others assembling similar services and infrastructure., (Copyright © 2014 Elsevier Inc. All rights reserved.)

We derive generalized spin models for the development of feedforward cortical architecture from a Hebbian synaptic learning rule in a two layer neural network with nonlinear weight constraints. Our model takes into account the effects of lateral interactions in visual cortex combining local excitation and long range effective inhibition. Our approach allows the principled derivation of developmental rules for low-dimensional feature maps, starting from high-dimensional synaptic learning rules. We incorporate the effects of smooth nonlinear constraints on net synaptic weight projected from units in the thalamic layer (the fan-out) and on the net synaptic weight received by units in the cortical layer (the fan-in). These constraints naturally couple together multiple feature maps such as orientation preference and retinotopic organization. We give a detailed illustration of the method applied to the development of the orientation preference map as a special case, in addition to deriving a model for joint pattern formation in cortical maps of orientation preference, retinotopic location, and receptive field width. We show that the combination of Hebbian learning and center-surround cortical interaction naturally leads to an orientation map development model that is closely related to the XY magnetic lattice model from statistical physics. The results presented here provide justification for phenomenological models studied in Cowan and Friedman (Advances in neural information processing systems 3, 1991), Thomas and Cowan (Phys Rev Lett 92(18):e188101, 2004) and provide a developmental model realizing the synaptic weight constraints previously assumed in Thomas and Cowan (Math Med Biol 23(2):119-138, 2006).

Routine integration of genotype data into drug decision making could improve patient safety, particularly if many relevant genetic variants can be assayed simultaneously before prescribing the target drug. The frequency of opportunities for pharmacogenetic prescribing and the potential adverse events (AEs) mitigated are unknown. We examined the frequency with which 56 medications with known outcomes influenced by variant alleles were prescribed in a cohort of 52,942 medical home patients at Vanderbilt University Medical Center (VUMC). Within a 5-year window, we estimated that 64.8% (95% confidence interval (CI): 64.4-65.2%) of individuals were exposed to at least one medication with an established pharmacogenetic association. Using previously published results for six medications with severe, well-characterized, genetically linked AEs, we estimated that 383 events (95% CI, 212-552) could have been prevented with an effective preemptive genotyping program. Our results suggest that multiplexed, preemptive genotyping may represent an efficient alternative approach to current single-use ("reactive") methods and may also improve safety.

Objective: Tacrolimus, an immunosuppressive drug widely prescribed in kidney transplantation, requires therapeutic drug monitoring due to its marked interindividual pharmacokinetic variability and narrow therapeutic index. Previous studies have established that CYP3A5 rs776746 is associated with tacrolimus clearance, blood concentration, and dose requirement. The importance of other drug absorption, distribution, metabolism, and elimination (ADME) gene variants has not been well characterized., Methods: We used novel DNA biobank and electronic medical record resources to identify ADME variants associated with tacrolimus dose requirement. Broad ADME genotyping was performed on 446 kidney transplant recipients, who had been dosed to a steady state with tacrolimus. The cohort was obtained from Vanderbilt's DNA biobank, BioVU, which contains linked deidentified electronic medical record data. Genotyping included Affymetrix drug-metabolizing enzymes and transporters Plus (1936 polymorphisms), custom Sequenom Massarray iPLEX Gold assay (95 polymorphisms), and ancestry-informative markers. The primary outcome was tacrolimus dose requirement defined as blood concentration to dose ratio., Results: In analyses, which adjusted for race and other clinical factors, we replicated the association of tacrolimus blood concentration to dose ratio with CYP3A5 rs776746 (P=7.15×10), and identified associations with nine variants in linkage disequilibrium with rs776746, including eight CYP3A4 variants. No NR1I2 variants were significantly associated. Age, weight, and hemoglobin were also significantly associated with the outcome. In final models, rs776746 explained 39% of variability in dose requirement and 46% was explained by the model containing clinical covariates., Conclusion: This study highlights the utility of DNA biobanks and electronic medical records for tacrolimus pharmacogenomic research.

Objective: DNA biobanks linked to comprehensive electronic health records systems are potentially powerful resources for pharmacogenetic studies. This study sought to develop natural-language-processing algorithms to extract drug-dose information from clinical text, and to assess the capabilities of such tools to automate the data-extraction process for pharmacogenetic studies., Materials and Methods: A manually validated warfarin pharmacogenetic study identified a cohort of 1125 patients with a stable warfarin dose, in which 776 patients were managed by Coumadin Clinic physicians, and the remaining 349 patients were managed by their providers. The authors developed two algorithms to extract weekly warfarin doses from both data sets: a regular expression-based program for semistructured Coumadin Clinic notes; and an advanced weekly dose calculator based on an existing medication information extraction system (MedEx) for narrative providers' notes. The authors then conducted an association analysis between an automatically extracted stable weekly dose of warfarin and four genetic variants of VKORC1 and CYP2C9 genes. The performance of the weekly dose-extraction program was evaluated by comparing it with a gold standard containing manually curated weekly doses. Precision, recall, F-measure, and overall accuracy were reported. Associations between known variants in VKORC1 and CYP2C9 and warfarin stable weekly dose were performed with linear regression adjusted for age, gender, and body mass index., Results: The authors' evaluation showed that the MedEx-based system could determine patients' warfarin weekly doses with 99.7% recall, 90.8% precision, and 93.8% accuracy. Using the automatically extracted weekly doses of warfarin, the authors successfully replicated the previous known associations between warfarin stable dose and genetic variants in VKORC1 and CYP2C9.

Networks of neurons produce diverse patterns of oscillations, arising from the network's global properties, the propensity of individual neurons to oscillate, or a mixture of the two. Here we describe noisy limit cycles and quasi-cycles, two related mechanisms underlying emergent oscillations in neuronal networks whose individual components, stochastic spiking neurons, do not themselves oscillate. Both mechanisms are shown to produce gamma band oscillations at the population level while individual neurons fire at a rate much lower than the population frequency. Spike trains in a network undergoing noisy limit cycles display a preferred period which is not found in the case of quasi-cycles, due to the even faster decay of phase information in quasi-cycles. These oscillations persist in sparsely connected networks, and variation of the network's connectivity results in variation of the oscillation frequency. A network of such neurons behaves as a stochastic perturbation of the deterministic Wilson-Cowan equations, and the network undergoes noisy limit cycles or quasi-cycles depending on whether these have limit cycles or a weakly stable focus. These mechanisms provide a new perspective on the emergence of rhythmic firing in neural networks, showing the coexistence of population-level oscillations with very irregular individual spike trains in a simple and general framework.

Neuronal avalanches are a form of spontaneous activity widely observed in cortical slices and other types of nervous tissue, both in vivo and in vitro. They are characterized by irregular, isolated population bursts when many neurons fire together, where the number of spikes per burst obeys a power law distribution. We simulate, using the Gillespie algorithm, a model of neuronal avalanches based on stochastic single neurons. The network consists of excitatory and inhibitory neurons, first with all-to-all connectivity and later with random sparse connectivity. Analyzing our model using the system size expansion, we show that the model obeys the standard Wilson-Cowan equations for large network sizes ( neurons). When excitation and inhibition are closely balanced, networks of thousands of neurons exhibit irregular synchronous activity, including the characteristic power law distribution of avalanche size. We show that these avalanches are due to the balanced network having weakly stable functionally feedforward dynamics, which amplifies some small fluctuations into the large population bursts. Balanced networks are thought to underlie a variety of observed network behaviours and have useful computational properties, such as responding quickly to changes in input. Thus, the appearance of avalanches in such functionally feedforward networks indicates that avalanches may be a simple consequence of a widely present network structure, when neuron dynamics are noisy. An important implication is that a network need not be "critical" for the production of avalanches, so experimentally observed power laws in burst size may be a signature of noisy functionally feedforward structure rather than of, for example, self-organized criticality.

Clinical research often requires extracting detailed drug information, such as medication names and dosages, from Electronic Health Records (EHR). Since medication information is often recorded as both structured and unstructured formats in the EHR, extracting all the relevant drug mentions and determining the daily dose of a medication for a selected patient at a given date can be a challenging and time-consuming task. In this paper, we present an automated approach using natural language processing to calculate daily doses of medications mentioned in clinical text, using tacrolimus as a test case. We evaluated this method using data sets from four different types of unstructured clinical data. Our results showed that the system achieved precisions of 0.90-1.00 and recalls of 0.81-1.00.

We analyze neocortical dynamics using field theoretic methods for non-equilibrium statistical processes. Assuming the dynamics is Markovian, we introduce a model that describes both neural fluctuations and responses to stimuli. We show that at low spiking rates, neocortical activity exhibits a dynamical phase transition which is in the universality class of directed percolation (DP). Because of the high density and large spatial extent of neural interactions, there is a "mean field" region in which the effects of fluctuations are negligible. However as the generation and decay of spiking activity becomes balanced, there is a crossover into the critical fluctuation driven DP region, consistent with measurements in neocortical slice preparations. From the perspective of theoretical neuroscience, the principal contribution of this work is the formulation of a theory of neural activity that goes beyond the mean-field approximation and incorporates the effects of fluctuations and correlations in the critical region. This theory shows that the scaling laws found in many measurements of neocortical activity, in anesthetized, normal and epileptic neocortex, are consistent with the existence of DP and related phase transitions at a critical point. It also shows how such properties lead to a model of the origins of both random and rhythmic brain activity.

A mean field approach to the population activity of cortical neurons is used to provide a possible mechanism for the generation of geometric visual hallucinations. As was previously investigated, competition between short-range excitation and longer-range inhibition in the connectivity profile of neurons provides the difference of length scales necessary for spontaneous symmetry breaking in the form of the Turing mechanism to generate patterns of activity. This approach is expanded in order to be able to incorporate additional details of the cortical circuitry, namely that neurons are also weakly connected at long ranges to other neurons sharing a particular preference for a stimulus feature such as orientation, spatial frequency, motion, color or disparity. Since the layout of cortical feature maps is approximately crystalline, one can apply a study of nonlinear dynamics similar to the analysis of wave propagation in a crystalline lattice to demonstrate how the spatial pattern formed through the Turing instability can be pinned to the geometric layout of various feature preferences. The specific feature map used in the study presented here is that of orientation preference, although the model can be extended to include additional features. The perturbation analysis is analogous to solving the Schrödinger equation in a weak periodic potential. Competition between the local isotropic connections which produce patterns of activity via the Turing mechanism and the weaker patchy lateral connections that depend on a neuron's particular set of feature preferences create long wavelength affects analogous to commensurate-incommensurate transitions found in fluid systems under a spatially periodic driving force. Using the retinocortical map, spontaneously formed activity patterns generated by the model can then be overlayed on the feature maps to construct the corresponding image in the visual field. We thus describe a new approach that allows the incorporation of some of the above features into a comprehensive account of the origins of hallucinations.

It is shown that a form of the Wilson-Cowan equations representing large-scale activity in interacting neural populations can implement a form of the Retinex algorithm for color vision. It has also been shown recently that a color enhancement algorithm closely related to Retinex can be derived from a variational principle. It follows that a variational principle exists for equations of Wilson-Cowan type. Thus the Wilson-Cowan equations are the Euler-Lagrange solution of the minimization of an energy functional. This result suggests many interesting neural applications.

A well-defined stochastic theory for neural activity, which permits the calculation of arbitrary statistical moments and equations governing them, is a potentially valuable tool for theoretical neuroscience. We produce such a theory by analyzing the dynamics of neural activity using field theoretic methods for nonequilibrium statistical processes. Assuming that neural network activity is Markovian, we construct the effective spike model, which describes both neural fluctuations and response. This analysis leads to a systematic expansion of corrections to mean field theory, which for the effective spike model is a simple version of the Wilson-Cowan equation. We argue that neural activity governed by this model exhibits a dynamical phase transition which is in the universality class of directed percolation. More general models (which may incorporate refractoriness) can exhibit other universality classes, such as dynamic isotropic percolation. Because of the extremely high connectivity in typical networks, it is expected that higher-order terms in the systematic expansion are small for experimentally accessible measurements, and thus, consistent with measurements in neocortical slice preparations, we expect mean field exponents for the transition. We provide a quantitative criterion for the relative magnitude of each term in the systematic expansion, analogous to the Ginsburg criterion. Experimental identification of dynamic universality classes in vivo is an outstanding and important question for neuroscience.

Of 1200 palliative care patients, 28 received palliative sedation. They were more likely than patients without palliative sedation to have an Eastern Cooperative Oncology Group performance status of at least 3, a cancer diagnosis, an expected survival of weeks or less, to have been monitored by the palliative care team for at least 1 week, to have delirium as the cause of decreased communication, to have dyspnea as a non-pain symptom, and to be less able to communicate symptoms. Almost 90% received palliative sedation for at least 24 hours for a median of 3 days (range, 0 to 24 days). Home patients received palliative sedation longer. Symptoms were controlled in 82% and improved in the rest. Sedation developed in 79% but was not required for symptom control in 5. Patient survival from palliative care consultation was a median of 8 days (range, 0 to 32 days).

Context: Compared with DNA microarray technology, relatively little information is available concerning the special requirements, design influences, and implementation strategies of data systems for tissue microarray technology. These issues include the requirement to accommodate new and different data elements for each new project as well as the need to interact with pre-existing models for clinical, biological, and specimen-related data., Objective: To design and implement a flexible, scalable tissue microarray data storage and management system that could accommodate information regarding different disease types and different clinical investigators, and different clinical investigation questions, all of which could potentially contribute unforeseen data types that require dynamic integration with existing data., Design: The unpredictability of the data elements combined with the novelty of automated analysis algorithms and controlled vocabulary standards in this area require flexible designs and practical decisions. Our design includes a custom Java-based persistence layer to mediate and facilitate interaction with an object-relational database model and a novel database schema. User interaction is provided through a Java Servlet-based Web interface., Results: Cruella has become an indispensable resource and is used by dozens of researchers every day. The system stores millions of experimental values covering more than 300 biological markers and more than 30 disease types. The experimental data are merged with clinical data that has been aggregated from multiple sources and is available to the researchers for management, analysis, and export., Conclusion: Cruella addresses many of the special considerations for managing tissue microarray experimental data and the associated clinical information. A metadata-driven approach provides a practical solution to many of the unique issues inherent in tissue microarray research, and allows relatively straightforward interoperability with and accommodation of new data models.

The most prominent feature of mammalian striate cortex (V1) is the spatial organization of response preferences for the position and orientation of elementary visual stimuli. Models for the formation of cortical maps of orientation and 'retinotopic' position typically rely on a combination of Hebbian or correlation-based synaptic plasticity, and constraints on the distribution of synaptic weights. We consider a simplified model of orientation and retinotopic specificity based on the geometry of the feed-forward synaptic weight distribution from an 'unoriented' layer of cells to a first weakly oriented layer. We model the feed-forward weight distribution as a system of planar Gaussian receptive fields each elongated in the direction matching the preferred orientation of the postsynaptic cell. Under the constraint of presynaptic weight normalization (each cell in the oriented layer receives the same net synaptic weight) and a uniform retinotopic map (displacement of centres of mass of receptive fields in the unoriented layer is strictly proportional to the displacement of the corresponding cells in the oriented layer), we find that imposing a pattern of orientation preference forces the system to violate postsynaptic weight normalization (each cell in the unoriented layer no longer sends forth the same net synaptic weight). We study this deviation from uniformity of the postsynaptic weight, and find that the deviation has a distinct form in the vicinity of the 'pinwheel' singularities of the orientation map. We show that uniform synaptic coverage of the unoriented layer can be restored by introducing a distortion in the retinotopic locations of the receptive fields. We calculate, to first order in the relative elongation of the receptive fields, the retinotopic distortion vector field. Both the pattern of postsynaptic weight non-uniformity and the corrective retinotopic distortion vector field fail to possess the reflection symmetry commonly assumed to relate orientation singularities with topological index +/- pi. Hence, we show that 'right-handed' and 'left-handed' orientation singularities are funda-mentally distinct anatomical structures when full 2D synaptic architecture is taken into account. Finally, we predict specific patterns of retinotopic distortion that should obtain in the vicinity of +/- pi-fold orientation singularities, if uniform pre- and post-synaptic weight constraints are strongly enforced.

The mammalian visual cortex maps retinal position (retinotopy) and orientation preference (OP) across its surface. Simultaneous measurements in vivo suggest that positive correlation exists between the location of dislocations in these two maps, contradicting the predictions of classical dimension reduction models. Model symmetries exert a significant influence on pattern development. However, classical models for cortical map formation have inappropriate symmetry properties. By applying equivariant bifurcation theory we derive symmetry induced, model independent coupling of the OP and retinotopic maps and show that this coupling replicates observations.

Defining financial parameters of palliative care (PC) is important for providing sustainable programming. In our study, we evaluated hospital length of stay (LOS) and charges for the first 164 inpatient PC consultations performed by the Advanced Illness Assistance (AIA) team at Blount Memorial Hospital (BMH). These AIA patients had a median LOS of 11 days (range, 3-114 days), mean total charges per patient of 65,795 dollars, and mean daily charges of 3,809 dollars. Higher mean daily charges (p = 2.74 E-08, chi-square) were associated with patients who received consultation because of nonphysical symptom reasons. Patients were followed in PC consultation (AIA follow-up days) for a median of five days (range, 1-48), and had mean daily charges of 3,117 dollars. These mean daily charges were 414 dollars less than the charges for the five days prior to PC consultation (pre-AIA days) (p = 0.04, t-test). There was a significant decrease in laboratory and imaging charges during AIA follow-up (p = 0.04, t-test). The study included a reference group of patients whose information was obtained retrospectively from the BMH Atlas (MediQual, Marlborough, MA) database. These reference group patients were hospitalized at BMH during the same time, but they were not seen by the AIA team. The reference group was matched by Diagnosis Related Group (DRG), Admission Severity Grade (ASG), and disposition to the AIA patients. The Atlas patients had a shorter median LOS of six days (range, 1-105 days), and significantly greater mean daily charges of 4,105 dollars (p = 0.006, t-test) compared with AIA patients. Mean daily charges decreased for Atlas patients, as their day of discharge approached (p < 0.001). Estimates of potential charge savings were calculated in two ways: 1) by evaluating the effect of decreasing the LOS of Atlas patients with long LOS (more than seven days) to the level of AIA patients with long LOS, and 2) by comparing the actual mean patient charges during AIA follow-up with using the pre-AIA mean daily charges during the AIA follow-up period and correcting for the effect of decreasing charges that occurred as discharge approached. The estimated savings achieved by decreasing long LOS were more than 100,000 dollars per year, and estimated savings achieved using AIA follow-up charges were more than 1,801,930 dollars per year.

This paper reports the first year's experience of a consultative, interdisciplinary, integrated palliative medicine program in a community hospital system. Prospective data collection was performed on 308 consecutive consultations. A computer database was developed and used to analyze demographics, reason for consultation, complexity of medical problems, current medications and allergies, physical suffering, spiritual concerns, personal and family concerns, consult recommendations, and mortality. In addition, data were collected on patient rating of the severity of physical symptoms, pain, spiritual suffering, and personal and family suffering; this data also was analyzed using the database. Cancer was the most frequent diagnosis (34 percent) and pain the most common reason for consultation (43 percent). Population medians were identified as follows: five (range, 1 to 10) acute medical problems; three (range, 1 to 10) chronic medical problems; and one (range, 0 to 10) medication allergy/intolerance. Patients were taking a median of 10 (range, 0 to 29) medications, including a median of two analgesics. Eighty percent could communicate concerning physical symptoms and had a median of two (range, 0 to 7) bothersome symptoms, with pain the most frequent. Fifty percent or fewer could rate physical suffering, pain, hope, spiritual suffering, or personal/family suffering using a 0 to 10 scale at consultation. Individual patient ratings provided over time for physical suffering, pain, hope, spiritual suffering, and personal/family suffering were available for less than 25 percent. A median of eight recommendations was made for each consultation, with medication changes suggested for 84 percent. For those known to have died, the median survival from time of consultation to death was 11 days.

A theory is presented of the way in which the hypercolumns in primary visual cortex (V1) are organized to detect important features of visual images, namely local orientation and spatial-frequency. Given the existence in V1 of dual maps for these features, both organized around orientation pinwheels, we constructed a model of a hypercolumn in which orientation and spatial-frequency preferences are represented by the two angular coordinates of a sphere. The two poles of this sphere are taken to correspond, respectively, to high and low spatial-frequency preferences. In Part I of the paper, we use mean-field methods to derive exact solutions for localized activity states on the sphere. We show how cortical amplification through recurrent interactions generates a sharply tuned, contrast-invariant population response to both local orientation and local spatial frequency, even in the case of a weakly biased input from the lateral geniculate nucleus (LGN). A major prediction of our model is that this response is non-separable with respect to the local orientation and spatial frequency of a stimulus. That is, orientation tuning is weaker around the pinwheels, and there is a shift in spatial-frequency tuning towards that of the closest pinwheel at non-optimal orientations. In Part II of the paper, we demonstrate that a simple feed-forward model of spatial-frequency preference, unlike that for orientation preference, does not generate a faithful representation when amplified by recurrent interactions in V1. We then introduce the idea that cortico-geniculate feedback modulates LGN activity to generate a faithful representation, thus providing a new functional interpretation of the role of this feedback pathway. Using linear filter theory, we show that if the feedback from a cortical cell is taken to be approximately equal to the reciprocal of the corresponding feed-forward receptive field (in the two-dimensional Fourier domain), then the mismatch between the feed-forward and cortical frequency representations is eliminated. We therefore predict that cortico-geniculate feedback connections innervate the LGN in a pattern determined by the orientation and spatial-frequency biases of feed-forward receptive fields. Finally, we show how recurrent cortical interactions can generate cross-orientation suppression.

A mathematical model of interacting hypercolumns in primary visual cortex (V1) is presented that incorporates details concerning the geometry of local and long-range horizontal connections. Each hypercolumn is modeled as a network of interacting excitatory and inhibitory neural populations with orientation and spatial frequency preferences organized around a pair of pinwheels. The pinwheels are arranged on a planar lattice, reflecting the crystalline-like structure of cortex. Local interactions within a hypercolumn generate orientation and spatial frequency tuning curves, which are modulated by horizontal connections between different hypercolumns on the lattice. The symmetry properties of the local and long-range connections play an important role in determining the types of spontaneous activity patterns that can arise in cortex.

Purpose: (a) To report the medical complexity of cancer and noncancer patients receiving palliative medicine (PM) consultation at a tertiary medical center and (b) to describe the consult recommendations madefor this group., Patients and Methods: Prospective data collection was performed on all consultations (cancer, n = 175; noncancer, n = 35) done by first author (JDC) as a PM fellow at the Cleveland Clinic Foundation between July 1998 and April 1999. A computer database was used to query for demographics, complexity of medical problems, current medications, mortality, symptoms, nursing problems, and consult recommendations., Results: A median of three (range, 0-12) acute medical problems and three (range, 0-16) chronic medical problems were identified for each patient. Patients were taking a median of six medications (range, 0-20). They had a median of five symptoms (range, 0-13) with pain (73 percent) being most common, followed by weakness (40 percent) and shortness of breath (40 percent). Cancer patients were twice as likely to have more than five symptoms (48 percent versus 23 percent) (chi-square = 0.006). The most common nursing problems were ambulation or fall risk (15 percent) and skin integrity (11 percent). A median of five (range, 1-11) management recommendations were made as part of each consultation. These included medication changes in 81 percent, nonmedication changes in 53 percent, andfollow-up services in 100 percent. The median survivalfrom the time of consultation for the known dead was 29 days with 65 percent living more than 14 days., Conclusion: Multiple recommendations were made with most patients surviving long enough potentially to benefit. Consultation in palliative medicine is a sophisticated intervention involving considerable acuity and complexity of care.

Terminally ill patients want assurance that their symptoms will be controlled as death approaches. Most patients can have a peaceful death with standard palliative care. Some patients approaching death, however, have refractory symptoms such as pain, dyspnea, nausea, and agitated delirium. Palliative sedation (PS), the use of medications to induce sedation in order to control refractory symptoms near death, is a therapeutic option for these patients. The reported frequency of PS use varies greatly, ranging from 5% to 52% of the terminally ill. One concern with PS is its effect on survival. Data suggest that PS does not lead to immediate death, with the median time to death after initiating PS being greater than 1 to 5 days. A number of medications have been used for PS, but midazolam is most commonly reported. PS is distinct from euthanasia because the intent of PS is relief from suffering without death as a required outcome.

Many observers see geometric visual hallucinations after taking hallucinogens such as LSD, cannabis, mescaline or psilocybin; on viewing bright flickering lights; on waking up or falling asleep; in "near-death" experiences; and in many other syndromes. Klüver organized the images into four groups called form constants: (I) tunnels and funnels, (II) spirals, (III) lattices, including honeycombs and triangles, and (IV) cobwebs. In most cases, the images are seen in both eyes and move with them. We interpret this to mean that they are generated in the brain. Here, we summarize a theory of their origin in visual cortex (area V1), based on the assumption that the form of the retino-cortical map and the architecture of V1 determine their geometry. (A much longer and more detailed mathematical version has been published in Philosophical Transactions of the Royal Society B, 356 [2001].) We model V1 as the continuum limit of a lattice of interconnected hypercolumns, each comprising a number of interconnected iso-orientation columns. Based on anatomical evidence, we assume that the lateral connectivity between hypercolumns exhibits symmetries, rendering it invariant under the action of the Euclidean group E(2), composed of reflections and translations in the plane, and a (novel) shift-twist action. Using this symmetry, we show that the various patterns of activity that spontaneously emerge when V1's spatially uniform resting state becomes unstable correspond to the form constants when transformed to the visual field using the retino-cortical map. The results are sensitive to the detailed specification of the lateral connectivity and suggest that the cortical mechanisms that generate geometric visual hallucinations are closely related to those used to process edges, contours, surfaces, and textures.

A mathematical theory of interacting hypercolumns in primary visual cortex (V1) is presented that incorporates details concerning the anisotropic nature of long-range lateral connections. Each hypercolumn is modeled as a ring of interacting excitatory and inhibitory neural populations with orientation preferences over the range 0 to 180 degrees. Analytical methods from bifurcation theory are used to derive nonlinear equations for the amplitude and phase of the population tuning curves in which the effective lateral interactions are linear in the amplitudes. These amplitude equations describe how mutual interactions between hypercolumns via lateral connections modify the response of each hypercolumn to modulated inputs from the lateral geniculate nucleus; such interactions form the basis of contextual effects. The coupled ring model is shown to reproduce a number of orientation-dependent and contrast-dependent features observed in center-surround experiments. A major prediction of the model is that the anisotropy in lateral connections results in a nonuniform modulatory effect of the surround that is correlated with the orientation of the center.

A dynamical model of orientation and spatial frequency tuning in a cortical hypercolumn is presented. The network topology is taken to be a sphere whose poles correspond to orientation pinwheels associated with high and low spatial frequency domains, respectively. Recurrent interactions within the sphere generate a tuned response via an SO3 symmetry breaking mechanism.

This paper reviews the reported use of nonopioid medications for terminal sedation. To provide a summary of the available literature, an electronic database search was performed. Thirteen series and 1 4 case reports were identified. Various symptoms, including agitation, pain, and confusion, required terminal sedation. Eleven drugs were used in 342 patients. Most patients were also treated with concurrent opioids and received terminal sedation in an inpatient hospice unit. Midazolam was the most common sedative employed. A good response--defined as adequate sedation--ranged between 75% and 100%. The median time to death following the introduction of terminal sedation was greater than 1 day. No agent appears to have superior efficacy or limiting toxicity.

This paper is concerned with a striking visual experience: that of seeing geometric visual hallucinations. Hallucinatory images were classified by Klüver into four groups called form constants comprising (i) gratings, lattices, fretworks, filigrees, honeycombs and chequer-boards, (ii) cobwebs, (iii) tunnels, funnels, alleys, cones and vessels, and (iv) spirals. This paper describes a mathematical investigation of their origin based on the assumption that the patterns of connection between retina and striate cortex (henceforth referred to as V1)-the retinocortical map-and of neuronal circuits in V1, both local and lateral, determine their geometry. In the first part of the paper we show that form constants, when viewed in V1 coordinates, essentially correspond to combinations of plane waves, the wavelengths of which are integral multiples of the width of a human Hubel-Wiesel hypercolumn, ca. 1.33-2 mm. We next introduce a mathematical description of the large-scale dynamics of V1 in terms of the continuum limit of a lattice of interconnected hypercolumns, each of which itself comprises a number of interconnected iso-orientation columns. We then show that the patterns of interconnection in V1 exhibit a very interesting symmetry, i.e. they are invariant under the action of the planar Euclidean group E(2)-the group of rigid motions in the plane-rotations, reflections and translations. What is novel is that the lateral connectivity of V1 is such that a new group action is needed to represent its properties: by virtue of its anisotropy it is invariant with respect to certain shifts and twists of the plane. It is this shift-twist invariance that generates new representations of E(2). Assuming that the strength of lateral connections is weak compared with that of local connections, we next calculate the eigenvalues and eigenfunctions of the cortical dynamics, using Rayleigh-Schrödinger perturbation theory. The result is that in the absence of lateral connections, the eigenfunctions are degenerate, comprising both even and odd combinations of sinusoids in straight phi, the cortical label for orientation preference, and plane waves in r, the cortical position coordinate. 'Switching-on' the lateral interactions breaks the degeneracy and either even or else odd eigenfunctions are selected. These results can be shown to follow directly from the Euclidean symmetry we have imposed. In the second part of the paper we study the nature of various even and odd combinations of eigenfunctions or planforms, the symmetries of which are such that they remain invariant under the particular action of E(2) we have imposed. These symmetries correspond to certain subgroups of E(2), the so-called axial subgroups. Axial subgroups are important in that the equivariant branching lemma indicates that when a symmetrical dynamical system becomes unstable, new solutions emerge which have symmetries corresponding to the axial subgroups of the underlying symmetry group. This is precisely the case studied in this paper. Thus we study the various planforms that emerge when our model V1 dynamics become unstable under the presumed action of hallucinogens or flickering lights. We show that the planforms correspond to the axial subgroups of E(2), under the shift-twist action. We then compute what such planforms would look like in the visual field, given an extension of the retinocortical map to include its action on local edges and contours. What is most interesting is that, given our interpretation of the correspondence between V1 planforms and perceived patterns, the set of planforms generates representatives of all the form constants. It is also noteworthy that the planforms derived from our continuum model naturally divide V1 into what are called linear regions, in which the pattern has a near constant orientation, reminiscent of the iso-orientation patches constructed via optical imaging. The boundaries of such regions form fractures whose points of intersection correspond to the well-known 'pinwheels'. To complete the study we then investigate the stability of the planforms, using methods of nonlinear stability analysis, including Liapunov-Schmidt reduction and Poincaré-Lindstedt perturbation theory. We find a close correspondence between stable planforms and form constants. The results are sensitive to the detailed specification of the lateral connectivity and suggest an interesting possibility, that the cortical mechanisms by which geometric visual hallucinations are generated, if sited mainly in V1, are closely related to those involved in the processing of edges and contours.

Orientation tuning in a ring of pulse-coupled integrate-and-fire (IF) neurons is analyzed in terms of spontaneous pattern formation. It is shown how the ring bifurcates from a synchronous state to a non-phase-locked state whose spike trains are characterized by clustered but irregular fluctuations of the interspike intervals (ISIs). The separation of these clusters in phase space results in a localized peak of activity as measured by the time-averaged firing rate of the neurons. This generates a sharp orientation tuning curve that can lock to a slowly rotating, weakly tuned external stimulus. Under certain conditions, the peak can slowly rotate even to a fixed external stimulus. The ring also exhibits hysteresis due to the subcritical nature of the bifurcation to sharp orientation tuning. Such behavior is shown to be consistent with a corresponding analog version of the IF model in the limit of slow synaptic interactions. For fast synapses, the deterministic fluctuations of the ISIs associated with the tuning curve can support a coefficient of variation of order unity.

Most terminally ill patients experience symptoms that require treatment as death approaches. The most common symptoms are pain (5% to 51%), dyspnea (28%), oral and respiratory secretions (25%), nausea and vomiting (10% to 14%), confusion (10%), myoclonus (12%), and bowel and bladder problems (over 20%). These symptoms can be well controlled in up to 90% of individuals with appropriate communication; emotional, spiritual, and social support; noninvasive clinical evaluation; and therapy focused on symptom palliation. Types of drugs that are important in symptom control include opioids, co-analgesics, anxiolytics, and anticholinergics. To be effective, these medications must be readily available for use and often need to be given by a non-oral route.

We propose a model for the lateral connectivity of orientation-selective cells in the visual cortex. We study the properties of the input signal to the visual cortex and find new statistical structures that have not been processed in the retino-geniculate pathway. Using the idea that the system performs redundancy reduction of the incoming signals, we derive the lateral connectivity that will achieve this for a set of orientation-selective local circuits, as well as the complete spatial structure of a network composed of such circuits. We compare the results with various physiological measurements.

The spike timing reliability of Aplysia motoneurons stimulated by repeated presentation of periodic or aperiodic input currents is investigated. Two properties of the input are varied, the frequency content and the relative amplitude of the fluctuations to the mean (expressed as the coefficient of variation: CV). It is shown that, for small relative amplitude fluctuations (CV approximately 0.05-0.15), the reliability of spike timing is enhanced if the input contains a resonant frequency equal to the firing rate of the neuron in response to the DC component of the input. This resonance-related enhancement in reliability decreases as the relative amplitude of the fluctuations increases (CV-->1). Similar results were obtained for a leaky integrate-and-fire neuronal model, suggesting that these effects are a general property of encoders that combine a threshold with a leaky integrator. These observations suggest that, when the magnitude of input fluctuations is small, changes in the power spectrum of the current fluctuations or in the spike discharge rate can have a pronounced effect on the ability of the neuron to encode a time-varying input with reliably timed spikes.

Exploiting local stability, we show what neuronal characteristics are essential to ensure that coherent oscillations are asymptotically stable in a spatially homogeneous network of spiking neurons. Under standard conditions, a necessary and, in the limit of a large number of interacting neighbors, also sufficient condition is that the postsynaptic potential is increasing in time as the neurons fire. If the postsynaptic potential is decreasing, oscillations are bound to be unstable. This is a kind of locking theorem and boils down to a subtle interplay of axonal delays, postsynaptic potentials, and refractory behavior. The theorem also allows for mixtures of excitatory and inhibitory interactions. On the basis of the locking theorem, we present a simple geometric method to verify the existence and local stability of a coherent oscillation.

Visually evoked potentials (VEPs) were recorded during simple motor reaction time (RT) experiments using spatially localized, contrast modulated visual stimuli. VEPs were averaged in groups, called "subensembles," depending on the speed of the subject's motor response. To a specific visual stimulus, the VEP response time of a subensemble covaries with motor response latency according to the same linear relationship found to describe conventionally averaged VEPs and RTs over a wide range of stimuli.

Spatially localized, contrast modulated visual stimuli evoke a monophasic, inion negative scalp potential (VEP) which can be recorded simultaneously with motor responses in simple reaction time experiments. VEP response time and median motor response latency are linearly related over a wide range of stimuli. We interpret our results to suggest that VEPs and motor response latencies arise from a common sensory system with different thresholds for detection and reaction. A model is introduced to predict detection thresholds from VEP response times which are usually more robust measures than VEP amplitudes.