Hebbian changes of excitatory synapses are driven by and further enhance correlations between pre- and postsynaptic activities. Hence, Hebbian plasticity forms a positive feedback loop that can lead to instability in simulated neural networks. To keep activity at healthy, low levels, plasticity must therefore incorporate homeostatic control mechanisms. We find in numerical simulations of recurrent networks with a realistic triplet-based spike-timing-dependent plasticity rule (triplet STDP) that homeostasis has to detect rate changes on a timescale of seconds to minutes to keep the activity stable. We confirm this result in a generic mean-field formulation of network activity and homeostatic plasticity. Our results strongly suggest the existence of a homeostatic regulatory mechanism that reacts to firing rate changes on the order of seconds to minutes.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828150 | PMC |
| http://dx.doi.org/10.1371/journal.pcbi.1003330 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Illustration image style transfer method design based on improved cyclic consistent adversarial network.
PLoS One
January 2025
College of Arts, Anhui Xinhua University, Hefei, China.
To improve the expressiveness and realism of illustration images, the experiment innovatively combines the attention mechanism with the cycle consistency adversarial network and proposes an efficient style transfer method for illustration images. The model comprehensively utilizes the image restoration and style transfer capabilities of the attention mechanism and the cycle consistency adversarial network, and introduces an improved attention module, which can adaptively highlight the key visual elements in the illustration, thereby maintaining artistic integrity during the style transfer process. Through a series of quantitative and qualitative experiments, high-quality style transfer is achieved, especially while retaining the original features of the illustration.
View Article and Find Full Text PDFThis study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, a location known for its complex wind patterns. By using data from a network of six meteorological stations and deep learning techniques, the produced model is capable of predicting wind speed and direction up to 30-minute ahead with 1-minute temporal resolution. The optimized architecture demonstrated robust predictive performance across all forecast horizons.
View Article and Find Full Text PDFEnhancing the visual environment of urban coastal roads through deep learning analysis of street-view images: A perspective of aesthetic and distinctiveness.
PLoS One
January 2025
Academy of Fine Arts, Jiangsu Second Normal University, Nanjing, China.
Urban waterfront areas, which are essential natural resources and highly perceived public areas in cities, play a crucial role in enhancing urban environment. This study integrates deep learning with human perception data sourced from street view images to study the relationship between visual landscape features and human perception of urban waterfront areas, employing linear regression and random forest models to predict human perception along urban coastal roads. Based on aesthetic and distinctiveness perception, urban coastal roads in Xiamen were classified into four types with different emphasis and priorities for improvement.
View Article and Find Full Text PDFEnhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy.
PLoS One
January 2025
School of Economics and Trade, Guangzhou Xinhua University, Dongguan, China.
Stock price prediction is a challenging research domain. The long short-term memory neural network (LSTM) widely employed in stock price prediction due to its ability to address long-term dependence and transmission of historical time signals in time series data. However, manual tuning of LSTM parameters significantly impacts model performance.
View Article and Find Full Text PDFDecoding the elite soccer player's psychological profile.
Proc Natl Acad Sci U S A
January 2025
Center for Psychiatry Research and Center for Cognitive and Computational Neuropsychiatry, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17177, Sweden.
Soccer is arguably the most widely followed sport worldwide, and many dream of becoming soccer players. However, only a few manage to achieve this dream, which has cast a significant spotlight on elite soccer players who possess exceptional skills to rise above the rest. Originally, such attention was focused on their great physical abilities.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!