AIMC Topic: Models, Neurological

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On the Computational Complexity of Spiking Neural Membrane Systems with Colored Spikes.

International journal of neural systems
Spiking Neural P Systems are parallel and distributed computational models inspired by biological neurons, emerging from membrane computing and applied to solving computationally difficult problems. This paper focuses on the computational complexity ...

Linking cellular-level phenomena to brain architecture: the case of spiking cerebellar controllers.

Neural networks : the official journal of the International Neural Network Society
Linking cellular-level phenomena to brain architecture and behavior is a holy grail for theoretical and computational neuroscience. Advances in neuroinformatics have recently allowed scientists to embed spiking neural networks of the cerebellum with ...

Heterogeneous quantization regularizes spiking neural network activity.

Scientific reports
The learning and recognition of object features from unregulated input has been a longstanding challenge for artificial intelligence systems. Brains, on the other hand, are adept at learning stable sensory representations given noisy observations, a ...

SpikeCLIP: A contrastive language-image pretrained spiking neural network.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) have emerged as a promising alternative to conventional Artificial Neural Networks (ANNs), demonstrating comparable performance in both visual and linguistic tasks while offering the advantage of improved energy efficie...

Multiscroll hidden attractor in memristive autapse neuron model and its memristor-based scroll control and application in image encryption.

Neural networks : the official journal of the International Neural Network Society
In current neurodynamic studies, memristor models using polynomial or multiple nested composite functions are primarily employed to generate multiscroll attractors, but their complex mathematical form restricts both research and application. To addre...

From social effort to social behavior: An integrated neural model for social motivation.

Neuroscience and biobehavioral reviews
As humans rely on social groups for survival, social motivation is central to behavior and well-being. Here we define social motivation as the effort that initiates and directs behavior towards social outcomes, with the goal of satisfying our fundame...

Toward a Biologically Plausible SNN-Based Associative Memory with Context-Dependent Hebbian Connectivity.

International journal of neural systems
In this paper, we propose a spiking neural network model with Hebbian connectivity for implementing energy-efficient associative memory, whose activity is determined by input stimuli. The model consists of three interacting layers of Hodgkin-Huxley-M...

Neural models for detection and classification of brain states and transitions.

Communications biology
Exploring natural or pharmacologically induced brain dynamics, such as sleep, wakefulness, or anesthesia, provides rich functional models for studying brain states. These models allow detailed examination of unique spatiotemporal neural activity patt...

Scalable Multi-FPGA HPC Architecture for Associative Memory System.

IEEE transactions on biomedical circuits and systems
Associative memory is a cornerstone of cognitive intelligence within the human brain. The Bayesian confidence propagation neural network (BCPNN), a cortex-inspired model with high biological plausibility, has proven effective in emulating high-level ...

RRAM-Based Spiking Neural Network With Target-Modulated Spike-Timing-Dependent Plasticity.

IEEE transactions on biomedical circuits and systems
The spiking neural network (SNN) training with spike timing-dependent plasticity (STDP) for image classification usually requires a lot of neurons to extract representative features and(or) needs an external classifier. Conventional bio-inspired lear...