Persistent neural firing is of fundamental importance to working memory and other brain functions because it allows information to be held "online" following an input and to be integrated over time. Many models of persistent activity rely on some kind of positive feedback internal to the neural circuit concerned; however, too much feedback causes runaway firing (instability), and too little res...

Spike-timing dependent plasticity (STDP) is an organizing principle of biological neural networks. While synchronous firing of neurons is considered to be an important functional block in the brain, how STDP shapes neural networks possibly toward synchrony is not entirely clear. We examine relations between STDP and synchronous firing in spontaneously firing neural populations. Using coupled he...

Traditionally, insights into neural computation have been furnished by averaged firing rates from many stimulus repetitions or trials. We pursue an analysis of neural response variance to unveil neural computations that cannot be discerned from measures of average firing rate. We analyzed single-neuron recordings from the lateral intraparietal area (LIP), during a perceptual decision-making tas...

Spike timing-dependent synaptic plasticity (STDP) develops neural circuits through close interaction with the firing function of single neurons. Here, we investigate the neuronal firing function dependency of STDP about a single-compartment Hodgkin–Huxley (HH) model neuron and a leaky integrate-and-fire (LIF) model neuron. Computer simulation shows that the development of synaptic strength by s...

The relation between the blood-oxygen-level-dependent (BOLD) signal, which forms the basis of functional magnetic resonance imaging (fMRI), and underlying neural activity is not well understood. We performed high-resolution fMRI in patients scheduled for implantation with depth electrodes for seizure monitoring while they navigated a virtual environment. We then recorded local field potentials ...

We report on deterministic and stochastic evolutions of firing states through a feedforward neural network with Mexican-hat-type connectivity. The prevalence of columnar structures in a cortex implies spatially localized connectivity between neural pools. Although feedforward neural network models with homogeneous connectivity have been intensively studied within the context of the synfire chai...

Patterns of neural firing linked to eye movement decisions show that behavioral decisions are predicted by the differential firing rates of cells coding selected and nonselected stimulus alternatives. These results can be interpreted using models developed in mathematical psychology to model behavioral decisions. Current models assume that decisions are made by accumulating noisy stimulus infor...

We simulated a large scale spiking neural network characterized by an initial developmental phase featuring cell death driven by an excessive firing rate, followed by the onset of spike-timing-dependent synaptic plasticity (STDP), driven by spatiotemporal patterns of stimulation. The network activity stabilized such that recurrent preferred firing sequences appeared along the STDP phase. The an...

The dynamics of microelectrode local field potentials from cortical slice cultures shows critical behavior. A desirable feature of criticality is that information transmission is optimal in this state. We explore a biologically plausible neural net model that can dynamically converge on criticality and that can return to criticality if perturbed away from it. Our model assumes the presence of a...