Dendritic spikes in apical oblique dendrites of cortical layer 5 pyramidal neurons

Dendritic spikes in layer 5 pyramidal neurons (L5PNs) play a major role in cortical computation. While dendritic spikes have been studied extensively in apical and basal dendrites of L5PNs, whether oblique dendrites, which ramify in the input layers of the cortex, also generate dendritic spikes is unknown. Here we report the existence of dendritic spikes in apical oblique dendrites of L5PNs. In silico investigations indicate that oblique branch spikes are triggered by brief, low-frequency action potential (AP) trains (~40 Hz) and are characterized by a fast sodium spike followed by activation of voltage-gated calcium channels. In vitro experiments confirmed the existence of oblique branch spikes in L5PNs during brief AP trains at frequencies of around 60 Hz. Oblique branch spikes offer new insights into branch-specific computation in L5PNs and may be critical for sensory processing in the input layers of the cortex.

Interneuron Specific Gamma Synchronization Indexes Cue Uncertainty and Prediction Errors in Lateral Prefrontal and Anterior Cingulate Cortex

Inhibitory interneurons are believed to realize critical gating functions in cortical circuits, but it has been difficult to ascertain the content of gated information for well characterized interneurons in primate cortex. Here, we address this question by characterizing putative interneurons in primate prefrontal and anterior cingulate cortex while monkeys engaged in attention demanding reversal learning. We find a subclass of narrow spiking neurons with relative suppressive effects on the local circuit indicating they are inhibitory interneurons. The activity of one subclass of these interneurons prominently indexed area-specific information in their firing rates and in event-triggered (35-45 Hz) gamma band synchronization. Firing rates and gamma synchrony of this interneuron subclass indexed in prefrontal cortex the uncertainty of attention cues, and in anterior cingulate cortex the unexpectedness of outcomes during learning. Computational analysis suggest that these interneuron-specific activity dynamics reflect in prefrontal cortex the gating of expected stimulus values into choice probabilities, and in anterior cingulate cortex the gating of chosen stimulus values and the received rewards into reward prediction errors. These findings elucidate an electrophysiologically characterized interneuron subclass in the primate, that forms gamma synchronous networks in two different areas while realizing an area-specific computation during adaptive goal-directed behavior.

Spatially organized genomic and physiological heterogeneity of the olfactory bulb mitral cell layer

Sensory inputs to the dorsal vs ventral olfactory bulb derive from distinct receptor families, and drive distinct behaviors. To address whether second-order OB neurons and circuits exhibit matching heterogeneity for input-specific readout, we clustered spatial expression profiles of >2,000 genes from the mitral cell layer (MCL). We observed clear dorsal and ventral clusters, together with dorsoventral differences in mitral cell physiology. Bulbar circuits may therefore be tuned for zone-specific computation.

Building and Auto-Tuning Computing Kernels: Experimenting with Boast and Starpu in the Gysela Code

Modeling turbulent transport is a major goal in order to predict confinement performance in a tokamak plasma. The gyrokinetic framework considers a computational domain in five dimensions to look at kinetic issues in a plasma; this leads to huge computational needs. Therefore, optimization of the code is an especially important aspect, especially since coprocessors and complex manycore architectures are foreseen as building blocks for Exascale systems. This project aims to evaluate the applicability of two auto-tuning approaches with the BOAST and StarPU tools on the GYSELA code in order to circumvent performance portability issues. A specific computation intensive kernel is considered in order to evaluate the benefit of these methods. StarPU enables to match the performance and even sometimes outperform the hand-optimized version of the code while leaving scheduling choices to an automated process. BOAST on the other hand reveals to be well suited to get a gain in terms of execution time on four architectures. Speedups in-between 1.9 and 5.7 are obtained on a cornerstone computation intensive kernel.

Computable Throughput and Metastability in a Cellular Automaton Model for Traffic Flow

A cellular automaton model for traffic flow is analyzed. For this model, it is shown that under ergodic initial configurations, the distribution of cars will converge in time to a mixture of free flow and solid blocks. Furthermore, the nature of the free flow and solid block distributions is fully described, thus allowing for a specific computation of throughput in terms of the parameters. The model is also shown to exhibit a hysteresis phenomenon, which is similar to what has been observed on actual highways.

One size fits all? Dialectometry in a small clan-based indigenous society

In many societies, dialectometry has revealed strong correlations between geographic distances and dialect differences (e.g., Gooskens, 2005; Heeringa & Nerbonne, 2001; Nerbonne, 2009, 2010). But what happens when dialectometry is applied to a small, clan-based society such as the indigenous Sui people of rural southwest China? The Sui results show a strong correlation between dialect difference and geographic distance, thus supporting Nerbonne and Kleiweg's (2007) Fundamental Dialectological Postulate. A new culturally specific computation, “rice paddy distance,” also provides a strong correlation with dialect differences. However, the study finds that some dialectometry patterns of larger societies are not “compressible” into small societies such as Sui. Clan exogamy also poses challenges for dialectometry. Nonetheless, the overall results show that basic principles of dialect variation in space can be generalized cross-culturally, even across very different cultures. This paper also suggests a “lower limit” for dialectology, that is, the smallest distance where regional dialectology may be relevant, all other things being equal.

Identification of a Duffing Oscillator under Different Types of Excitation

In many engineering applications the dynamics may significantly be affected by nonlinear effects, which must be accounted for in order to accurately understand and robustly model the dynamics. From a practical point of view, it is very important to solve theinverse problemrelated to system identification and output prediction. In this paper the recently developed Nonlinear Subspace Identification (NSI) method is presented and applied to an oscillator described by the Duffing equation, with different types of excitation including random forces, which are demonstrated to be very suitable for the identification process. The estimates of system parameters are excellent and, as a consequence, the behaviour of the system, including the jump phenomena, is reconstructed to a high level of fidelity. In addition, the possible memory limitations affecting the method are overcome by the development of a novel algorithm, based on a specific computation of the QR factorisation.