Activity in layer 2/3 of the mouse primary visual cortex has been shown to depend both on visual input and the mouse’s locomotion. Moreover, this activity is altered by a mismatch between the observed visual flow and the predicted visual flow from ...

The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate for auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the formation and retrieval of ...

We demonstrate a model of chirp-velocity sensitivity in the inferior colliculus (IC) that retains the tuning to amplitude modulation (AM) that was established in earlier models. The mechanism of velocity sensitivity is sequence detection by ...

Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional ...

Theta burst stimulation (TBS) is a form of repetitive transcranial magnetic stimulation (rTMS) with unknown underlying mechanisms and highly variable responses across subjects. To investigate these issues, we developed a simple computational ...

The computational resources of a neuromorphic network model introduced earlier were investigated in the first paper of this series. It was argued that a form of ubiquitous spontaneous local convolution enabled logical gate-like neural motifs to ...

Replicating neural responses observed in biological systems using artificial neural networks holds significant promise in the fields of medicine and engineering. In this study, we employ ultra-fast artificial neurons based on antiferromagnetic (...

We derive a next generation neural mass model of a population of quadratic-integrate-and-fire neurons, with slow adaptation, and conductance-based AMPAR, GABAR and nonlinear NMDAR synapses. We show that the Lorentzian ansatz assumption can be ...

Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between ...

Recent developments in experimental neuroscience make it possible to simultaneously record the activity of thousands of neurons. However, the development of analysis approaches for such large-scale neural recordings have been slower than those ...

Place cells develop spatially-tuned receptive fields during the early stages of novel environment exploration. The generative mechanism underlying these spatially-selective responses remains largely elusive, but has been associated with theta ...

Models of synaptic plasticity have been used to better understand neural development as well as learning and memory. One prominent classic model is the Bienenstock-Cooper-Munro (BCM) model that has been particularly successful in explaining ...

We investigate spontaneous critical dynamics of excitatory and inhibitory (EI) sparsely connected populations of spiking leaky integrate-and-fire neurons with conductance-based synapses. We use a bottom-up approach to derive a single neuron gain ...${}_{\mathit{}}{}_{\mathit{}}$

The stochastic activity of neurons is caused by various sources of correlated fluctuations and can be described in terms of simplified, yet biophysically grounded, integrate-and-fire models. One paradigmatic model is the quadratic integrate-and-...

Type 2 diabetes mellitus (T2DM) is reported to cause widespread changes in brain function, leading to cognitive impairments. Research using resting-state functional magnetic resonance imaging data already aims to understand functional changes in ...

Using the improved memristive Izhikevich neuron model, the effects of autaptic connection as well as electromagnetic induction are studied on the dynamical behavior of neuronal spiking. Using bifurcation analysis for membrane potentials, the ...

To elucidate how the flattening of sensory tuning due to a deficit in tonic inhibition slows motor responses, we simulated a neural network model in which a sensory cortical network (${\mathrm{N}}_{\mathrm{S}}$) and a motor cortical network (${\mathrm{N}}_{\mathrm{M}}$) are reciprocally connected,...${\mathrm{}}_{\mathrm{}}$${\mathrm{}}_{\mathrm{}}$${\mathrm{}}_{\mathrm{}}$${\mathrm{}}_{\mathrm{}}$${\mathrm{}}_{\mathrm{}}$

The brain is believed to operate in part by making predictions about sensory stimuli and encoding deviations from these predictions in the activity of “prediction error neurons.” This principle defines the widely influential theory of predictive ...