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Active tuberculosis (TB) in solid organ transplant (SOT) recipients most commonly occurs due to reactivation of latent infection and is associated with poor clinical outcomes, including allograft loss and death. National transplant societies, including the American Society of Transplantation, recommend screening for latent TB prior to transplant, with treatment in the peritransplant setting to reduce the subsequent risk of TB reactivation. Though screening is traditionally conducted using laboratory-based assays, such as the QuantiFERON-TB Gold, false negatives may occur in SOT candidates due to anergy from end-stage organ dysfunction, highlighting the need for a multimodal diagnostic approach. In this case series, we describe the clinical characteristics and outcomes of 3 SOT recipients at the University of Pennsylvania with negative pretransplant QuantiFERON-TB Gold testing who subsequently developed active TB in the posttransplant setting, contributing to a growing body of knowledge regarding this challenging population. Each patient experienced a complicated clinical course that arose in part from the lack of diagnosis of TB prior to transplant. Because all had epidemiologic risk factors for TB, the findings of our study highlight the need for more individualized approaches to pretransplant TB screening.

Nursing homes and long-term care facilities represent highly vulnerable environments for respiratory disease outbreaks, such as coronavirus disease 2019 (COVID-19). We describe a COVID-19 outbreak in a nursing home that was rapidly contained by using a universal testing strategy of all residents and nursing home staff.

Biologic agents are effective treatments for rheumatoid arthritis but are associated with important risks, including severe infections. Tumor Necrosis Factor (TNF) α inhibitors are known to increase the risk of systemic fungal infections such as disseminated histoplasmosis. Abatacept is a biologic agent with a mechanism different from that of TNFα inhibitors: It suppresses cellular immunity by competing for the costimulatory signal on antigen-presenting cells. The risk of disseminated histoplasmosis for patients on abatacept is not known. We report a case of abatacept-associated disseminated histoplasmosis and review the known infectious complications of abatacept. While the safety of resuming biologic agents following treatment for disseminated histoplasmosis is also not known, abatacept is recommended over TNFα inhibitors for rheumatoid arthritis patients with a prior serious infection. We discuss the evidence supporting this recommendation and discuss alternative treatments for rheumatoid arthritis patients with a history of a serious infection.

Clathrin-mediated endocytosis (CME) is the best-studied pathway by which cells selectively internalize molecules from the plasma membrane and surrounding environment. Previous live-cell imaging studies using ectopically overexpressed fluorescent fusions of endocytic proteins indicated that mammalian CME is a highly dynamic but inefficient and heterogeneous process. In contrast, studies of endocytosis in budding yeast using fluorescent protein fusions expressed at physiological levels from native genomic loci have revealed a process that is very regular and efficient. To analyse endocytic dynamics in mammalian cells in which endogenous protein stoichiometry is preserved, we targeted zinc finger nucleases (ZFNs) to the clathrin light chain A and dynamin-2 genomic loci and generated cell lines expressing fluorescent protein fusions from each locus. The genome-edited cells exhibited enhanced endocytic function, dynamics and efficiency when compared with previously studied cells, indicating that CME is highly sensitive to the levels of its protein components. Our study establishes that ZFN-mediated genome editing is a robust tool for expressing protein fusions at endogenous levels to faithfully report subcellular localization and dynamics.

Understanding the regulatory logic of a eukaryotic promoter requires the elucidation of the regulatory elements within that promoter. Current experimental or computational methods to discover regulatory motifs within a promoter can be labor intensive and may miss redundant, unprecedented or weakly activating elements. We have developed an unbiased combinatorial approach to rapidly identify new upstream activating sequences (UASs) in a promoter. This approach couples nonhomologous random recombination with an in vivo screen to efficiently identify UASs and does not rely on preconceived hypotheses about promoter regulation or on similarity to known activating sequences. We validated this method using the unfolded protein response (UPR) in yeast and were able to identify both known and potentially novel UASs involved in the UPR. One of the new UASs discovered using this approach implicates Crz1 as a possible activator of Hac1, a transcription factor involved in the UPR. This method has several advantages over existing methods for UAS discovery including its speed, potential generality, sensitivity and lack of false positives and negatives.

In electroencephalography (EEG) and event related potentials (ERP), localizing the electrical sources at the origin of scalp potentials (inverse problem) imposes, in a first step, the computation of scalp potential distribution from the simulation of sources (forward problem). This article proposes an alternative method for mimicing both the electrical and geometrical properties of the head, including brain, skull, and scalp tissue with resistors. Two resistor mesh models have been designed to reproduce the three-sphere reference model (analytical model). The first one (spherical resistor mesh) closely mimics the geometrical and electrical properties of the analytical model. The second one (cubic resistor mesh) is designed to conveniently handle anatomical data from magnetic resonance imaging. Both models have been validated, in reference to the analytical solution calculated on the three-sphere model, by computing the magnification factor and the relative difference measure. Results suggest that the mesh...

In a previous event-related fMRI study, we showed that the left occipitotemporal cortex was specifically involved in the abstract categorization of visually presented alphabetic symbols. Here, we duplicate the fMRI study by measuring visual event-related potentials to verify whether the left posterior cortex supports the processing of graphemic representations at a perceptual, prelexical level. N170 amplitudes elicited by the categorically ambiguous stimulus 'O' were about twice as small in the left as in the right occipitotemporal region, and comparable to that of other letters on the left, and to that of other geometric figures on the right. The side asymmetry suggests that a graphemic module is unilaterally implemented in the left hemisphere, where it automatically processes heteromorphic representations that do not depend on the physical characteristics of the signal, whereas the difference in amplitude suggests that this left graphemic module is in series with, precedes and does not transmit information to, or inhibits a general shape-analysis module.

Carbonic anhydrase II (CAII) is a zinc metalloenzyme that catalyzes the hydration of CO2 to yield bicarbonate and a proton. N-(4-Sulfamylbenzoyl)benzylamine (SBB) is a tight-binding inhibitor of hu...

To address the question of the existence of a phonetic module for speech perception, event-related potentials were recorded using a 32 channel system in subjects performing a detection task where the target was the ambiguous, noise-like phoneme /f/ presented either among syllables (speech context) or among environmental sounds (non-speech context). Significant context effects were observed on the N2/P3 complex elicited by the target. In particular, a well localized N2b (250-280 ms) appeared at the left temporoparietal sites on the difference wave between contexts as the result of an enhanced negativity when the target was presented among non-speech stimuli. These findings suggest the involvement of the left temporoparietal region in autonomous, modular processes of speech perception.

Freeman's investigations on the olfactory bulb of the rabbit showed that its signal dynamics was chaotic, and that recognition of a learned stimulus is linked to a dimension reduction of the dynamics attractor. In this paper we address the question whether this behavior is specific of this particular architecture, or if it is a general property. We study the dynamics of a non-convergent recurrent model-the random recurrent neural networks. In that model a mean-field theory can be used to analyze the autonomous dynamics. We extend this approach with various observations on significant changes in the dynamical regime when sending static random stimuli. Then we propose a Hebb-like learning rule, viewed as a self-organization dynamical process inducing specific reactivity to one random stimulus. We numerically show the dynamics reduction during learning and recognition processes and analyze it in terms of dynamical repartition of local neural activity.

Rasamsonia argillacea (formerly known as Geosmithia argillacea ) is a fungus recently recognized as a pathogen of immunocompromised patients. Here we report the first case of Rasamsonia infection in an immunocompetent host, presenting as a pulmonary and aortic graft infection. Its morphological similarity to nonpathogenic Penicillium species delayed the diagnosis and initiation of appropriate treatment.

The dynamical behaviour of a very general model of neural networks with random asymmetric synaptic weights is investigated in the presence of random thresholds. Using mean-field equations, the bifurcations of the fixed points and the change of regime when varying control parameters are established. Different areas with various regimes are defined in the parameter space. Chaos arises generically by a quasi-periodicity route.

Chaos in nervous system is a fascinating but controversial field of investigation. To approach the role of chaos in the real brain, we theoretically and numerically investigate the occurrence of chaos inartificial neural networks. Most of the time, recurrent networks (with feedbacks) are fully connected. This architecture being not biologically plausible, the occurrence of chaos is studied here for a randomly diluted architecture. By normalizing the variance of synaptic weights, we produce a bifurcation parameter, dependent on this variance and on the slope of the transfer function, that allows a sustained activity and the occurrence of chaos when reaching a critical value. Even for weak connectivity and small size, we find numerical results in accordance with the theoretical ones previously established for fully connected infinite sized networks. The route towards chaos is numerically checked to be a quasi-periodic one, whatever the type of the first bifurcation is. Our results suggest that such high-dimensional networks behave like low-dimensional dynamical systems.

We investigate the dynamical behaviour of neural networks with asymmetric synaptic weights, in the presence of random thresholds. We inspect low gain dynamics before using mean-field equations to study the bifurcations of the fixed points and the change of regime that occurs when varying control parameters. We infer different areas with various regimes summarized by a bifurcation map in the parameter space. We numerically show the occurence of chaos that arises generically by a quasi-periodicity route. We then discuss some features of our system in relation with biological observations such as low firing rates and refractory periods.

The occurrence of chaos in recurrent neural networks is supposed to depend on the architecture and on the synaptic coupling strength. It is studied here for a randomly diluted architecture. We produce a bifurcation parameter independent of the connectivity that allows a sustained activity and the occurrence of chaos when reaching a critical value. Even for weak connectivity and small size, we find numerical results in accordance with the theoretical ones previously established for fully connected infinite sized networks. Moreover the route towards chaos is numerically checked to be a quasiperiodic one, whatever the type of the first bifurcation is. In the discussion, we connect these results to some recent theoretical results about highly diluted networks. Hints are provided for further investigations to elicit the role of chaotic dynamics in the cognitive processes of the brain.

QSAR has been used to elucidate the origin of the hydrophobicity and binding affinity of a small library of fluoroaromatic inhibitors of F131V carbonic anhydrase II. Our analysis predicted the presence of a twisted amide conformation for several bound inhibitors, which we confirmed crystallographically. We also determined that the hydrophobicity of the inhibitors as a whole results from the fragment hydrophobicities of their fluorobenzyl rings, corrected for field effects and the presence of an intramolecular F.H contact in solution. The loss of this interaction on binding to the enzyme makes the affinity sensitive to the same terms, but with the opposite dependence on the F.H contact. In the case of the four inhibitors bound as twisted amides, this F.H contact must be retained to some extent in the bound state in order for their affinities to be consistent with our QSAR analysis of the entire set of 17 molecules.

Chaos theory is a rapidly growing field. As a technical term, "chaos" refers to deterministic but unpredictable processes being sensitively dependent upon initial conditions. Neurobiological models and experimental results are very complicated and some research groups have tried to pursue the "neuronal chaos". Babloyantz's group has studied the fractal dimension (d) of electroencephalograms (EEG) in various physiological and pathological states. From deep sleep (d = 4) to full awakening (d8), a hierarchy of "strange" attractors paralles the hierarchy of states of consciousness. In epilepsy (petit mal), despite the turbulent aspect of a seizure, the attractor dimension was near to 2. In Creutzfeld-Jacob disease, the regular EEG activity corresponded to an attractor dimension less than the one measured in deep sleep. Is it healthy to be chaotic? An "active desynchronisation" could be favourable to a physiological system. Rapp's group reported variations of fractal dimension according to particular tasks. During a mental arithmetic task, this dimension increased. In another task, a P300 fractal index decreased when a target was identified. It is clear that the EEG is not representing noise. Its underlying dynamics depends on only a few degrees of freedom despite yet it is difficult to compute accurately the relevant parameters. What is the cognitive role of such a chaotic dynamics? Freeman has studied the olfactory bulb in rabbits and rats for 15 years. Multi-electrode recordings of a few mm2 showed a chaotic hierarchy from deep anaesthesia to alert state. When an animal identified a previously learned odour, the fractal dimension of the dynamics dropped off (near limit cycles).(ABSTRACT TRUNCATED AT 250 WORDS)

This paper presents a correlative study between phonological and semantic verbal fluency performances and SPECT data obtained at rest in a group of dementia of Alzheimer type (DAT) patients. In both verbal fluency tasks, normals were superior to DAT patients, but in the majority of our patients, phonological verbal fluency appeared more resistant than semantic verbal fluency. The only significant result we found was between good performances on semantic verbal fluency and relative preserved left anterior cerebral blood flow. Results are discussed first in terms of cognitive strategies required for verbal fluency and second in terms of predominant lateralized hypoperfusion in relation with both verbal fluency tasks.

Investigation on oil-mineral aggregate (OMA) formation in ice-covered waters was conducted by the Canadian Coast Guard (CCG). Different tests were performed in large basins using Heidrun oil and calcite to determine the efficiency of the OMA formation in these conditions. The main objectives of the experiments were (1) to validate oil droplets (OD) and OMA formation in ice-covered waters for different turbulence levels, (2) to investigate the type and size of OMAs formed, and (3) to help identify performance indicators of the OMA process in these conditions. The results have shown that OD and OMA formation is initiated when the stirring action upsets the water surface in the basin. The majority of the OMAs formed were droplet OMAs and their sizes related to the energy level and to the ice type. The sur-face flow pattern with and without ice was characterised using a particle image velocimetry (PIV) method. The results have shown the circu-lation pattern of surface currents is modified due to the ice blocks. The energy damping and a significant reduction in current intensity were the most evident effects consequential to the presence of ice.

The laboratory evolution of enzymes with tailor-made DNA cleavage specificities would represent new tools for manipulating genomes and may enhance our understanding of sequence-specific DNA recognition by nucleases. Below we describe the development and successful application of an efficient in vivo positive and negative selection system that applies evolutionary pressure either to favor the cleavage of a desired target sequence or to disfavor the cleavage of nontarget sequences. We also applied a previously described in vitro selection method to reveal the comprehensive substrate specificity profile of the wild-type I-SceI homing endonuclease. Together these tools were used to successfully evolve mutant I-SceI homing endonucleases with altered DNA cleavage specificities. The most highly evolved enzyme cleaves the target mutant DNA sequence with a selectivity that is comparable to wild-type I-SceI's preference for its cognate substrate.

Humans are fast and accurate at performing an animal categorization task with natural photographs briefly flashed centrally. Here, this central categorization task is compared to a three position task in which photographs could appear randomly either centrally, or at 3.6 degrees eccentricity (right or left) of the fixation point. A mild behavioral impairment was found with peripheral stimuli with no evidence in support of hemispheric superiority; but enlarging the window of spatial attention to three possible stimuli locations had no behavioral cost on the processing of central images. Performance in the central categorization task has been associated with a large difference between the potentials evoked to target and non-target correct trials, starting about 150 ms after stimulus onset on frontal sites. Present results show that this activity originates within extrastriate visual cortices and probably reflects perceptual stimuli differences processed within areas involved in object recognition. Latencies, slopes, and peak amplitudes of this differential activity were invariant to stimulus position and attentional load. Stimulus location uncertainty and lateralization did not affect speed of visual processing.

A spherical head model based on a resistor mesh is presented. Each resistor corresponds to the conducting electrical properties of a tissue volume. A current dipole is simulated by an electrical current source connected between two nodes in this mesh. The direct problem is solved and the accuracy of this model is evaluated in comparison with the analytical solution. The results show that the resistor mesh provides correct potential and scalp current density values. The model structure makes it easy to introduce conductivity heterogeneities such as stroke and skull anisotropy. First trials of an inverse method are also presented.

The translation of nucleic acid libraries into corresponding synthetic compounds would enable selection and amplification principles to be applied to man-made molecules. We used multistep DNA-templated organic synthesis to translate libraries of DNA sequences, each containing three “codons,” into libraries of sequence-programmed synthetic small-molecule macrocycles. The resulting DNA-macrocycle conjugates were subjected to in vitro selections for protein affinity. The identity of a single macrocycle possessing known target protein affinity was inferred through the sequence of the amplified DNA template surviving the selection. This work represents the translation, selection, and amplification of libraries of nucleic acids encoding synthetic small molecules rather than biological macromolecules.

Most of the neuroimaging studies that have shown visual category-specific activations or categorization effects have been based on a subtractive approach. In the present study, we investigated, by means of EEG, not only the net result of the categorization but also the dynamics of the process. Subjects had to perform a target detection task throughout an image set of distractors belonging to six categories: letters, geometrical figures, faces, tools, structured textures and Asiatic characters. Multivariate analyses were performed on the responses to the non-target stimuli according to their category. Categorical neural responses were only obtained on P2 latencies and N2 amplitudes. This result suggests that there are no differences in the first stage of the implicit categorization of the distractors (visual analysis and proximal stimulus representation elaboration from 100 to 220 ms) and that differences appear between 220 and 280 ms (matching to structural representations). Over-learned stimuli (e.g. letters) elicited the shortest P2 latency, contrasting with unknown categories (e.g. Asiatic characters) that revealed the longest P2 latencies and flattened N2 waves. Categorical differences indicate that the more a subject knows about an object, the less cognitive resources are used. In conclusion, our results suggest that a reduction in neural activity could reflect an improved accuracy in cognitive and cortical processing.

We have developed a genetic method to determine the active orientation of dimeric transmembrane protein helices. The bovine papillomavirus E5 protein, a 44-amino acid homodimeric protein that appears to traverse membranes as a left-handed coiled-coil, transforms fibroblasts by binding and activating the platelet-derived growth factor (PDGF) beta receptor. A heterologous dimerization domain was used to force E5 monomers to adopt all seven possible symmetric coiled-coil registries relative to one another within the dimer. Focus formation assays demonstrated that dimerization of the E5 protein is required for transformation and identified a single preferred orientation of the monomers. The essential glutamine residue at position 17 resided in the dimer interface in this active orientation. The active chimera formed complexes with the PDGF beta receptor and induced receptor tyrosine phosphorylation. We also identified E5-like structures that underwent non-productive interactions with the receptor.

[figure: see text] Linear free energy relationships between binding affinity and hydrophobicity for a library of fluoroaromatic inhibitors of F131V carbonic anhydrase II (CA) implicate three modes of interaction. X-ray crystal structures suggest that F131 interacts with fluoroaromatic inhibitors, while P202, on the opposite side of the active site cleft, serves as the site of the hydrophobic contact in the case of the F131V mutant. 2-Fluorinated compounds bind more tightly, perhaps due to the field effect of the nearby fluorine on the acidity of the amide proton.

[formula: see text] Complexes formed between fluorobenzene and N-methylformamide or benzene have been used as models of the interaction of fluoroaromatic drugs with carbonic anhydrase II. These structures have been investigated via ab initio and density functional methods, including HF, B3LYP, and MP2 procedures. The results of the calculations are consistent with the hypothesis, suggested originally by experimental X-ray crystal structures of the drug-receptor complexes, that favorable fluorine-hydrogen interactions affect binding affinity.

[formula: see text] A library of fluoroaromatic inhibitors of carbonic anhydrase has been found to bind in a manner dependent on both hydrophobicity and the pattern of substitution of the fluoroaromatic ring. All of the compounds in the library bind to the protein with Kd < 3 nM. We have inferred two distinct binding modes from our data, which suggest two types of interactions that should be considered when designing fluorinated drugs.

Today, cognitive functions are considered to be the offspring of the activity of large-scale networks of functionally interconnected cerebral regions. The interpretation of cerebral activation data provided by functional imaging has therefore recently moved to the search for the effective connectivity of activated regions, which aims at understanding the role of anatomical links in the activation propagation. Our assumption is that only causal connectivity can offer a real understanding of the links between brain and mind. Causal connectivity is based on the anatomical connection pattern, the information processing within cerebral regions and the causal influences that connected regions exert on each other. In our approach, the information processing within a region is implemented by a causal network of functional primitives, which are the interpretation of integrated biological properties. Our choice of a qualitative representation of information reflects the fact that cerebral activation data are only the approximate view, provided by imaging techniques, of the real cerebral activity. This explicit modeling approach allows the formulation and the simulation of functional and physiological assumptions about activation data. Two alternative models explaining results of the striate cortex activation described by Fox and Raichle (Fox PT, Raichle ME (1984) J. Neurophysiol 51:1109-1120; Fox PT, Raichle ME (1985) Ann Neurol 17:303-305) are provided as an example of our approach.

The importance of machine translation (MT) in the stream of text-handling processes has become readily apparent in many current production settings as well as in research programs such as the Translingual Information Detection, Extraction, and Summarization (TIDES) program. The MT Proficiency Scale project has developed a means of baselining the inherent "tolerance" that a text-handling task has for raw MT output, and thus how good the output must be in order to be of use to that task. This method allows for a prediction of how useful a particular system can be in a text-handling process stream, whether in integrated, MT-embedded processes, or less integrated user-intensive processes.

Two experiments were conducted to address whether a left hemispheric bias would be observed for categorical processing in both ‘what’ and ‘where’ systems (experiment 1) while a reverse bias would characterize coordinate processing whatever the systems (experiment 2). Young normal subjects were tested using divided visual field tasks. The results of experiment 1 indicated that subjects made categorical judgments in both what and where systems faster when stimuli are presented to the left hemisphere. The results of experiment 2 showed a significant interaction between visual field and difficulty of processing coordinate relationships. Indeed, a left-hemisphere advantage was observed when the task required easy processing whereas a right-hemisphere advantage was noted for difficult distinctions either in location (where system) or in lightness (what system). The left-hemisphere advantage we observed for categorization in both systems confirms the Kosslyn’s hypothesis (1989) for the where system and suggests that the same left-hemisphere advantage also exists for the what system. Concerning coordinate processing, our findings highlight the influence of processing difficulty on the hemispheric lateralization and evidence a right hemispheric advantage for difficult coordinate processing and a left hemispheric advantage for easy coordinate processing. The results are discussed in terms of possible link between on the one hand difficulty and coordinate processing, and easiness and categorization on the other hand.

Using a habituation-recovery paradigm adapted to functional magnetic resonance imaging, we investigated the brain responses to syllables and tones in six right-handed male subjects. We opposed a standard condition (STD) in which the subjects were listening to homogeneous sequences of four identical stimuli, to a deviant condition (DEV) in which the fourth stimulus of the sequence differed in pitch or spectral content for tones and in the initial stop consonant for syllables. The corresponding runs alternated four rest periods with two STD and two DEV conditions. In addition to a marked rightward asymmetry in the primary and secondary auditory cortex for tones and a right inferior frontal activation for the tone condition where the deviant had increased spectral content, the experiment revealed differential activations in the left posterior superior temporal gyrus and in the left supramarginal gyrus. Activations within the left posterior superior temporal gyrus were observed for the DEV condition with tones and for the STD and DEV conditions with syllables. Activation within the inferior part of the left supramarginal gyrus was only observed for the DEV condition with syllables. The analysis of the decreases and increases in the BOLD signal across the STD, DEV, and rest conditions suggests that the left posterior superior temporal gyrus is implicated in the preattentive change detection of acoustic changes in speech as well as nonspeech stimuli, whereas the left supramarginal gyrus is more specifically engaged in the detection of changes in phonological units.

Previous PET results identified distinct neural systems involved with phonology (vicinity of the left sylvian fissure) and lexical semantics (left inferior temporal, left superior frontal, bilateral inferior parietal regions). In the time domain, the phonological task was thought to involve serial parsing of pseudowords, whereas the lexical semantic task would correspond to probabilistic automated access to meaning. Auditory event-related potentials (ERPs) elicited by the same tasks were explored on 32 channels in 12 male volunteers. Subjects had to categorize as target a second element of a pair of pseudo-words or words if a preceding target was detected in the first element. Depending on the absence/presence of target in the first element, a RELEASE condition and a HOLD condition were distinguished. RELEASE and HOLD ERPs split earlier in the semantic task than in the phonological task (300 versus 412 ms after SOT, respectively), although words lasted longer than pseudo-words. Corresponding paired t test maps showed a predominance of differences over left perisylvian regions for the phonological task and posterior bilateral regions for the semantic task. Underlying generators were investigated using BESA (Scherg, 1990) with global task ERPs. Six dipoles—constrained according to PET clusters—brought residual variance down to 0.36%, from 364 to 565 ms after SOT, in both tasks. Relative dipole amplitudes suggested a left-sided functional asymmetry for phonology. These results support the hypothesis of left perisylvian serial processing for phonology contrasting with bihemispheric parallel access for semantics and substantiates BESA for temporally tackling cognitive processes. r 1998 Academic Press

Although extraordinarily complexes, the mental processes can be regarded as products of the neuronal dynamical system. In this context, biological observations make it possible to emit the conjecture that recognition of a form or a stimulus leads to a reduction of neuronal dynamics. This paper proposes a generic model for the study of such dynamics by learning random stimuli. We implement a Hebb-like learning rule, which reinforces the innovation in a network stimulated by a random input. The network learns to react specifically to one or more learned inputs. An estimation of the networks reactivity after learning brings encouraging results in terms of capacity. Then the question of dynamical coding is evoked in terms of limit cycles associated to specific patterns.

Freeman’s investigations on the olfactory bulb of the rabbit showed that its dynamics was chaotic, and that recognition of a learned pattern is linked to a dimension reduction of the dynamics on a much simpler attractor (near limit cycle). We adress here the question wether this behaviour is specific of this particular architecture or if this kind of behaviour observed is an important property of chaotic neural network using a Hebb- like learning rule. In this paper, we use a mean-field theoretical statement to determine the spontaneous dynamics of an assymetric recurrent neural network. In particular we determine the range of random weight matrix for which the network is chaotic. We are able to explain the various changes observed in the dynamical regime when sending static random patterns. We propose a Hebb-like learning rule to store a pattern as a limit cycle or strange attractor. We numerically show the dynamics reduction of a finite-size chaotic network during learning and recognition of a pattern. Though associative learning is actually performed the low storage capacity of the system leads to the consideration of more realistic architecture.

We have developed in vitro selections for DNA-linked synthetic small molecules with protein binding affinity and specificity. These selections require only generally accessible equipment, offer high degrees of enrichment of active molecules from mixtures of predominantly inactive species, can be applied to a variety of unrelated proteins, and require approximately 108-fold less material than existing synthetic molecule screening methods. Iterating these selections multiplies the net enrichment of active molecules, enabling enormous overall enrichment factors exceeding 106 to be achieved. Further, the selections can be adapted to select for binding specificity in addition to binding affinity. The application of methods described in this work may play a key role in the discovery of desired molecules from DNA-templated synthetic libraries.

A protocol of formal lexical evocation (words beginning with a letter) and semantic evocation was applied to 168 normal subjects evenly distributed on the basis of three factors (sex, three age classes and two levels of education). Correct answers, their distribution within the allotted time (proportions of correct answers in four thirty-second periods) and errors were analysed globally and in relation to the said factors. Level of education had a decisive influence in all tests; age had no influence on performance in formal evocation, whereas the subjects in the middle age class presented the best performance in semantic evocation. Distribution of the answers over time was unrelated to any of the factors considered. Errors were related to age in half the test.

Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives stimulating spatiotemporal signals, and the secondary layer is a fully connected random recurrent network. This secondary layer spontaneously displays complex chaotic dynamics. All connections have a constant time delay. We use for our experiments a Hebbian (covariance) learning rule. This rule slowly modifies the weights under the influence of a periodic stimulus. The effect of learning is twofold: (i) it simplifies the secondary-layer dynamics, which eventually stabilizes to a periodic orbit; and (ii) it connects the secondary layer to the primary layer, and realizes a feedback from the secondary to the primary layer. This feedback signal is added to the incoming signal, and matches it (i.e., the secondary layer performs a one-step prediction of the forthcoming stimulus). After learning, a resonant behavior can be observed: the system resonates with familiar stimuli, which activates a feedback signal. In particular, this resonance allows the recognition and retrieval of partial signals, and dynamic maintenence of the memory of past stimuli. This resonance is highly sensitive to the temporal relationships and to the periodicity of the presented stimuli. When we present stimuli which do not match in time or space, the feedback remains silent. The number of different stimuli for which resonant behavior can be learned is analyzed. As with Hopfield networks, the capacity is proportional to the size of the second, recurrent layer. Moreover, the high capacity displayed allows the implementation of our model on real-time systems interacting with their environment. Such an implementation is reported in the case of a simple behavior-based recognition task on a mobile robot. Finally, we present some functional analogies with biological systems in terms of autonomy and dynamic binding, and present some hypotheses on the computational role of feedback connections.

Single photon emission computed tomography was used to measure regional cerebral blood flow in six normal subjects and 12 patients with Parkinson's disease, before and after acute oral administration of levodopa. The drug induced a significant increase in cerebral blood flow both in controls and patients. Before levodopa, there was no significant difference between the groups, either in flow values or in their pattern. The clinical effects of levodopa were not related to the hemodynamic changes. The results suggest that measuring the flow response to levodopa is not appropriate to demonstrate variations in central dopaminergic receptor sensitivity in man.