LM2007 2.3

LM2007 is a software tool developed by Gunnar Sommestad for simulating the behaviour of large networks of leaky integrate-and-fire neurons.

LM2007 stands for "LeakyMap 2007," which reflects the fact that it is a newer version of a similar program called LeakyMap that Sommestad had previously developed.

Researchers in the field of computational neuroscience and related disciplines can benefit from using LM2007 to simulate neural activity and investigate complex phenomena such as synchrony, oscillations, and noise.

Flexible connectivity: Users can define different types of connections between neurons, including distance-based, random, or topological. Configurable neuronal models: Users can choose from a range of neuronal models with different dynamics and parameters, or even create their own custom models. Dynamic visualization: The program provides real-time visual feedback on the network activity, allowing users to observe the emergence of patterns and collective behavior.

LM2007 is freely available for download from Sommestad's website. Users can also access the source code and contribute to its development.

LM2007 is not a general-purpose neural simulator, as it focuses mainly on leaky integrate-and-fire models and does not include some advanced features found in other tools. Additionally, users may encounter performance issues when simulating large networks or complex models.

The program has a user-friendly interface and provides a detailed documentation, but users need a solid understanding of neural dynamics and programming skills to make the most out of it.

Yes, LM2007 can be a valuable tool for teaching computational neuroscience to undergraduate or graduate students, as it allows them to explore different scenarios and test hypotheses in a flexible and interactive environment.

LM2007 has been applied in various studies investigating topics such as network synchronization, working memory, sensory processing, and plasticity, among others. It has also been used to develop new models and theories about neural function and dysfunction.

Other popular neural simulators include NEURON, NEST, Brian, and PyNN, among others. Each tool has its strengths and weaknesses depending on the specific research question and application.