Attractor dynamics of spatially correlated neural activity in the limbic system
JJ Knierim, K Zhang - Annual review of neuroscience, 2012 - annualreviews.org
Attractor networks are a popular computational construct used to model different brain
systems. These networks allow elegant computations that are thought to represent a number …
systems. These networks allow elegant computations that are thought to represent a number …
Large-scale neural dynamics: simple and complex
S Coombes - NeuroImage, 2010 - Elsevier
We review the use of neural field models for modelling the brain at the large scales
necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that …
necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that …
Bump attractor dynamics in prefrontal cortex explains behavioral precision in spatial working memory
K Wimmer, DQ Nykamp, C Constantinidis… - Nature …, 2014 - nature.com
Prefrontal persistent activity during the delay of spatial working memory tasks is thought to
maintain spatial location in memory. A'bump attractor'computational model can account for …
maintain spatial location in memory. A'bump attractor'computational model can account for …
Tianjic: A unified and scalable chip bridging spike-based and continuous neural computation
Toward the long-standing dream of artificial intelligence, two successful solution paths have
been paved: 1) neuromorphic computing and 2) deep learning. Recently, they tend to …
been paved: 1) neuromorphic computing and 2) deep learning. Recently, they tend to …
The neuroanatomical ultrastructure and function of a biological ring attractor
DB Turner-Evans, KT Jensen, S Ali, T Paterson… - Neuron, 2020 - cell.com
Neural representations of head direction (HD) have been discovered in many species.
Theoretical work has proposed that the dynamics associated with these representations are …
Theoretical work has proposed that the dynamics associated with these representations are …
Integrated neural dynamics of sensorimotor decisions and actions
Recent theoretical models suggest that deciding about actions and executing them are not
implemented by completely distinct neural mechanisms but are instead two modes of an …
implemented by completely distinct neural mechanisms but are instead two modes of an …
BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming
Elucidating the intricate neural mechanisms underlying brain functions requires integrative
brain dynamics modeling. To facilitate this process, it is crucial to develop a general-purpose …
brain dynamics modeling. To facilitate this process, it is crucial to develop a general-purpose …
Fundamental limits on persistent activity in networks of noisy neurons
Neural noise limits the fidelity of representations in the brain. This limitation has been
extensively analyzed for sensory coding. However, in short-term memory and integrator …
extensively analyzed for sensory coding. However, in short-term memory and integrator …
Stability of working memory in continuous attractor networks under the control of short-term plasticity
Continuous attractor models of working-memory store continuous-valued information in
continuous state-spaces, but are sensitive to noise processes that degrade memory …
continuous state-spaces, but are sensitive to noise processes that degrade memory …
Continuous attractors for dynamic memories
Episodic memory has a dynamic nature: when we recall past episodes, we retrieve not only
their content, but also their temporal structure. The phenomenon of replay, in the …
their content, but also their temporal structure. The phenomenon of replay, in the …