Pulse shape discrimination based on the Tempotron: a powerful classifier on GPU

This study introduces the Tempotron, a powerful classifier based on a third-generation neural network model, for pulse shape discrimination. By eliminating the need for manual feature extraction, the Tempotron model can process pulse signals directly, generating discrimination results based on learned prior knowledge. The study performed experiments using GPU acceleration, resulting in over a 500 times speedup compared to the CPU-based model, and investigated the impact of noise augmentation on the Tempotron's performance. Experimental results showed that the Tempotron is a potent classifier capable of achieving high discrimination accuracy. Furthermore, analyzing the neural activity of Tempotron during training shed light on its learning characteristics and aided in selecting the Tempotron's hyperparameters. The dataset used in this study and the source code of the GPU-based Tempotron are publicly available on GitHub at https://github.com/HaoranLiu507/TempotronGPU.Comment: 14 pages,7 figure

(E)-4-Bromo-N′-(2-hydr­oxy-1-naphthyl­methyl­ene)benzohydrazide

The title compound, C18H13BrN2O2, was synthesized by the reaction of 2-hydr­oxy-1-naphthaldehyde with 4-bromo­benzohydrazide. This Schiff base mol­ecule has an E configuration about the C=N bond and is almost planar, the dihedral angle between the mean planes through the substituted benzene ring and the naphthyl system being 6.6 (2)°. There is an intra­molecular O—H⋯N hydrogen bond involving the naphthyl hydr­oxy substituent and the N′ atom of the hydrazide group. In the crystal structure, mol­ecules are linked through inter­molecular N—-H⋯O hydrogen bonds to form chains extending along the b direction

Neuronal representation of working memory in the medial prefrontal cortex of rats

Working memory is a process for short-term active maintenance of information. Behavioral neurophysiological studies in monkeys have demonstrated that the dorsolateral prefrontal cortex (dlPFC) is a key cortical region for working memory. The medial prefrontal cortex (mPFC) in rats is a cortical area similar to the dlPFC in monkeys in terms of anatomical connections, and is also required for behavioral performance on working-memory tasks. However, it is still controversial regarding whether and how mPFC neurons encode working memory. In the present study, we trained rats on a two-choice spatial delayed alternation task in Y maze, a typical working memory task for rodents, and investigated neuronal activities in the mPFC when rats performed the task. Our results show that, (1) inactivation of the mPFC severely impaired the performance of rats on the task, consistent with previous studies showing the importance of the mPFC for working-memory tasks; (2) 93.7% mPFC cells (449 in 479) exhibited changes in spiking frequency that were temporally locked with the task events, some of which, including delay-related cells, were tuned by spatial information; (3) differential delay activities in individual mPFC cells appeared transiently and sequentially along the delay, especially during the early phase of the delay; (4) some mPFC cells showed no change in discharge frequency but exhibited differential synchronization in firing during the delay. The present results suggest that mPFC neurons in rats are involved in encoding working memory, via increasing firing frequency or synchronization