AIMC Topic: Neuronal Plasticity

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Networks that learn the precise timing of event sequences.

Journal of computational neuroscience
Neuronal circuits can learn and replay firing patterns evoked by sequences of sensory stimuli. After training, a brief cue can trigger a spatiotemporal pattern of neural activity similar to that evoked by a learned stimulus sequence. Network models s...

Robotic Therapy and the Paradox of the Diminishing Number of Degrees of Freedom.

Physical medicine and rehabilitation clinics of North America
There has been remarkable growth in the development and application of robotics to ameliorate or remediate impairment. This growth is associated with a) the understanding that plasticity is a fundamental property of the adult human brain and might be...

Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
The application of biologically inspired methods in design and control has a long tradition in robotics. Unlike previous approaches in this direction, the emerging field of neurorobotics not only mimics biological mechanisms at a relatively high leve...

Impaired dendritic inhibition leads to epileptic activity in a computer model of CA3.

Hippocampus
Temporal lobe epilepsy (TLE) is a common type of epilepsy with hippocampus as the usual site of origin. The CA3 subfield of hippocampus is reported to have a low epileptic threshold and hence initiates the disorder in patients with TLE. This study co...

Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity.

Nano letters
Memristors have been extensively studied for data storage and low-power computation applications. In this study, we show that memristors offer more than simple resistance change. Specifically, the dynamic evolutions of internal state variables allow ...

Short-term plasticity based network model of place cells dynamics.

Hippocampus
Rodent hippocampus exhibits strikingly different regimes of population activity in different behavioral states. During locomotion, hippocampal activity oscillates at theta frequency (5-12 Hz) and cells fire at specific locations in the environment, t...

Self-organization of a recurrent network under ongoing synaptic plasticity.

Neural networks : the official journal of the International Neural Network Society
We investigated the organization of a recurrent network under ongoing synaptic plasticity using a model of neural oscillators coupled by dynamic synapses. In this model, the coupling weights changed dynamically, depending on the timing between the os...

Unravelling the brain resilience following stroke: From injury to rewiring of the brain through pathway activation, drug targets, and therapeutic interventions.

Ageing research reviews
Synaptic plasticity is a neuron's intrinsic ability to make new connections throughout life. The morphology and function of synapses are highly susceptible to any pathological condition. Ischemic stroke is a cerebrovascular event that affects various...

STSF: Spiking Time Sparse Feedback Learning for Spiking Neural Networks.

IEEE transactions on neural networks and learning systems
Spiking neural networks (SNNs) are biologically plausible models known for their computational efficiency. A significant advantage of SNNs lies in the binary information transmission through spike trains, eliminating the need for multiplication opera...

Enhanced neuroplasticity and gait recovery in stroke patients: a comparative analysis of active and passive robotic training modes.

BMC neurology
BACKGROUND: Stroke is a leading cause of long-term disability, with lower limb dysfunction being a common sequela that significantly impacts patients' mobility and quality of life. Robotic-assisted training has emerged as a promising intervention for...