Distributed processing and temporal codes in neuronal networks

The cerebral cortex presents itself as a distributed dynamical system with the characteristics of a small world network. The neuronal correlates of cognitive and executive processes often appear to consist of the coordinated activity of large assemblies of widely distributed neurons. These features require mechanisms for the selective routing of signals across densely interconnected networks, the flexible and context dependent binding of neuronal groups into functionally coherent assemblies and the task and attention dependent integration of subsystems. In order to implement these mechanisms, it is proposed that neuronal responses should convey two orthogonal messages in parallel. They should indicate (1) the presence of the feature to which they are tuned and (2) with which other neurons (specific target cells or members of a coherent assembly) they are communicating. The first message is encoded in the discharge frequency of the neurons (rate code) and it is proposed that the second message is contained in the precise timing relationships between individual spikes of distributed neurons (temporal code). It is further proposed that these precise timing relations are established either by the timing of external events (stimulus locking) or by internal timing mechanisms. The latter are assumed to consist of an oscillatory modulation of neuronal responses in different frequency bands that cover a broad frequency range from <2 Hz (delta) to >40 Hz (gamma) and ripples. These oscillations limit the communication of cells to short temporal windows whereby the duration of these windows decreases with oscillation frequency. Thus, by varying the phase relationship between oscillating groups, networks of functionally cooperating neurons can be flexibly configurated within hard wired networks. Moreover, by synchronizing the spikes emitted by neuronal populations, the saliency of their responses can be enhanced due to the coincidence sensitivity of receiving neurons in very much the same way as can be achieved by increasing the discharge rate. Experimental evidence will be reviewed in support of the coexistence of rate and temporal codes. Evidence will also be provided that disturbances of temporal coding mechanisms are likely to be one of the pathophysiological mechanisms in schizophrenia

Order-Based Representation in Random Networks of Cortical Neurons

The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen

Glucose Amplifies Fatty Acid-Induced Endoplasmic Reticulum Stress in Pancreatic β-Cells via Activation of mTORC1

BACKGROUND: Palmitate is a potent inducer of endoplasmic reticulum (ER) stress in beta-cells. In type 2 diabetes, glucose amplifies fatty-acid toxicity for pancreatic beta-cells, leading to beta-cell dysfunction and death. Why glucose exacerbates beta-cell lipotoxicity is largely unknown. Glucose stimulates mTORC1, an important nutrient sensor involved in the regulation of cellular stress. Our study tested the hypothesis that glucose augments lipotoxicity by stimulating mTORC1 leading to increased beta-cell ER stress. PRINCIPAL FINDINGS: We found that glucose amplifies palmitate-induced ER stress by increasing IRE1alpha protein levels and activating the JNK pathway, leading to increased beta-cell apoptosis. Moreover, glucose increased mTORC1 activity and its inhibition by rapamycin decreased beta-cell apoptosis under conditions of glucolipotoxicity. Inhibition of mTORC1 by rapamycin did not affect proinsulin and total protein synthesis in beta-cells incubated at high glucose with palmitate. However, it decreased IRE1alpha expression and signaling and inhibited JNK pathway activation. In TSC2-deficient mouse embryonic fibroblasts, in which mTORC1 is constitutively active, mTORC1 regulated the stimulation of JNK by ER stressors, but not in response to anisomycin, which activates JNK independent of ER stress. Finally, we found that JNK inhibition decreased beta-cell apoptosis under conditions of glucolipotoxicity. CONCLUSIONS/SIGNIFICANCE: Collectively, our findings suggest that mTORC1 mediates glucose amplification of lipotoxicity, acting through activation of ER stress and JNK. Thus, mTORC1 is an important transducer of ER stress in beta-cell glucolipotoxicity. Moreover, in stressed beta-cells mTORC1 inhibition decreases IRE1alpha protein expression and JNK activity without affecting ER protein load, suggesting that mTORC1 regulates the beta-cell stress response to glucose and fatty acids by modulating the synthesis and activity of specific proteins involved in the execution of the ER stress response. This novel paradigm may have important implications for understanding beta-cell failure in type 2 diabetes

Parallel Computational Subunits in Dentate Granule Cells Generate Multiple Place Fields

A fundamental question in understanding neuronal computations is how dendritic events influence the output of the neuron. Different forms of integration of neighbouring and distributed synaptic inputs, isolated dendritic spikes and local regulation of synaptic efficacy suggest that individual dendritic branches may function as independent computational subunits. In the present paper, we study how these local computations influence the output of the neuron. Using a simple cascade model, we demonstrate that triggering somatic firing by a relatively small dendritic branch requires the amplification of local events by dendritic spiking and synaptic plasticity. The moderately branching dendritic tree of granule cells seems optimal for this computation since larger dendritic trees favor local plasticity by isolating dendritic compartments, while reliable detection of individual dendritic spikes in the soma requires a low branch number. Finally, we demonstrate that these parallel dendritic computations could contribute to the generation of multiple independent place fields of hippocampal granule cells

Lossless Conditional Schema Evolution

Conditional schema changes change the schema of the tuples that satisfy the change condition. When the schema of a relation changes some tuples may no longer fit the current schema. Handling the mismatch between the intended schema of tuples and the recorded schema of tuples is at the core of a DBMS that supports schema evolution. We propose to keep track of schema mismatches at the level of individual tuples, and prove that evolving schemas with conditional schema changes, in contrast to database systems relying on data migration, are lossless when the schema evolves. The lossless property is a precondition for a flexible semantics that allows to correctly answer general queries over evolving schemas. The key challenge is to handle attribute mismatches between the intended and recorded schema in a consistent way. We provide a parametric approach to resolve mismatches according to the needs of the application. We introduce the mismatch extended completed schema (MECS) which records attributes along with their mismatches, and we prove that relations with MECS are lossless