Motor recovery after stroke is related to neural plasticity, which involves developing new neuronal interconnections, acquiring new functions, and compensating for impairment. However, neural plasticity is impaired in the stroke-affected hemisphere. Therefore, it is important that motor recovery therapies facilitate neural plasticity to compensate for functional loss. Stroke rehabilitation prog...

Neural plasticity is emerging as a fundamental and critical mechanism of neuronal function, which allows the brain to receive information and make the appropriate adaptive responses to subsequent related stimuli. Elucidation of the molecular and cellular mechanisms underlying neural plasticity is a major goal of neuroscience research, and significant advances have been made in recent years. The...

Motor recovery after stroke involves developing new neural connections, acquiring new functions, and compensating for impairments. These processes are related to neural plasticity. Various novel stroke rehabilitation techniques based on basic science and clinical studies of neural plasticity have been developed to aid motor recovery. Current research aims to determine whether using combinations...

A large body of evidence suggests that neural plasticity contributes to learning and disease. Recent studies suggest that cortical map plasticity is typically a transient phase that improves learning by increasing the pool of task-relevant responses. Here, I discuss a new perspective on neural plasticity and suggest how plasticity might be targeted to reset dysfunctional circuits. Specifically,...

The human brain can create new neural pathways and create novel memories. Neuronal connections and cortical maps are continuously remodeled by experience (Johansson, 2000). The brain has the capacity to undergo activity-dependent functional and morphological remodeling via mechanisms of plasticity (Bruel-Jungerman, Davis &Laroche, 2007). There are two major types of neural plasticity: functiona...

Several types of neural plasticity must be perfectly orchestrated for a proper functioning of biological neural networks. In this work we present a computer simulation of the Alzheimer's Disease, taking into account one of the most accepted models of Alzheimer's Disease: the calcium dysregulation hypothesis. According to Cudmore and Turrigiano calcium dysregulation alters the shifting dynamic o...

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network t...

We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP) and Spike Timing Dependent Delay Plasticity (STDDP). We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2(26) (64M) synaptic ...

We review a body of theoretical and experimental research on the interactions of homeostatic and Hebbian plasticity, starting from a puzzling observation: While homeostasis of synapses found in experiments is slow, homeostasis of synapses in most mathematical models is rapid, or even instantaneous. Even worse, most existing plasticity models cannot maintain stability in simulated networks with ...

Throughout development, the nervous system produces patterned spontaneous activity. Research over the past two decades has revealed a core group of mechanisms that mediate spontaneous activity in diverse circuits. Many circuits engage several of these mechanisms sequentially to accommodate developmental changes in connectivity. In addition to shared mechanisms, activity propagates through devel...