[HTML][HTML] Where is the error? Hierarchical predictive coding through dendritic error computation
Top-down feedback in cortex is critical for guiding sensory processing, which has
prominently been formalized in the theory of hierarchical predictive coding (hPC). However …
prominently been formalized in the theory of hierarchical predictive coding (hPC). However …
Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception
Mechanistic insight is achieved only when experiments are employed to test formal or
computational models. Furthermore, in analogy to lesion studies, phantom perception may …
computational models. Furthermore, in analogy to lesion studies, phantom perception may …
Interoception as modeling, allostasis as control
The brain regulates the body by anticipating its needs and attempting to meet them before
they arise–a process called allostasis. Allostasis requires a model of the changing sensory …
they arise–a process called allostasis. Allostasis requires a model of the changing sensory …
Aligned and oblique dynamics in recurrent neural networks
The relation between neural activity and behaviorally relevant variables is at the heart of
neuroscience research. When strong, this relation is termed a neural representation. There …
neuroscience research. When strong, this relation is termed a neural representation. There …
Constrained predictive coding as a biologically plausible model of the cortical hierarchy
Predictive coding (PC) has emerged as an influential normative model of neural
computation with numerous extensions and applications. As such, much effort has been put …
computation with numerous extensions and applications. As such, much effort has been put …
Computational role of structure in neural activity and connectivity
One major challenge of neuroscience is identifying structure in seemingly disorganized
neural activity. Different types of structure have different computational implications that can …
neural activity. Different types of structure have different computational implications that can …
Optimal noise level for coding with tightly balanced networks of spiking neurons in the presence of transmission delays
Neural circuits consist of many noisy, slow components, with individual neurons subject to
ion channel noise, axonal propagation delays, and unreliable and slow synaptic …
ion channel noise, axonal propagation delays, and unreliable and slow synaptic …
Dendritic predictive coding: A theory of cortical computation with spiking neurons
Top-down feedback in cortex is critical for guiding sensory processing, which has
prominently been formalized in the theory of hierarchical predictive coding (hPC). However …
prominently been formalized in the theory of hierarchical predictive coding (hPC). However …
Geometry of population activity in spiking networks with low-rank structure
L Cimeša, L Ciric, S Ostojic - PLOS Computational Biology, 2023 - journals.plos.org
Recurrent network models are instrumental in investigating how behaviorally-relevant
computations emerge from collective neural dynamics. A recently developed class of models …
computations emerge from collective neural dynamics. A recently developed class of models …
The impact of sparsity in low-rank recurrent neural networks
Neural population dynamics are often highly coordinated, allowing task-related
computations to be understood as neural trajectories through low-dimensional subspaces …
computations to be understood as neural trajectories through low-dimensional subspaces …