Introduction: Anethole is the main constituent of Pimpinella anisum L. (anise), a herbaceous annual plant which has several therapeutic effects. In the folk medicine, anise is employed as an antiepileptic drug. Specifically, this study was focused on the cellular effect of anethole, an aromatic compound in essential oils from anise and camphor. Anethole has various physiological effects on t...

Neural information processing may depend importantly on the ability of a network to vary its firing rate continuously in response to continuous changes in its input. In strongly inhibitory networks of oscillating neurons, subsets of neurons that are intrinsically more active can silence the rest of the neural population. If excitatory drive is increased to the whole network, the silenced neuron...

What hippocampal neural firing patterns signal memory and, more importantly, how is this memory code used by associated structures to translate a memory into a decision or action? Candidate hippocampal activity patterns will be discussed including (1) trajectory-specific firing of place cells with place fields on an overlapping segment of two (or more) distinct trajectories (2) prospective firi...

Scale-invariant timing has been observed in a wide range of behavioral experiments. The scale-invariant firing property of recently described time cells provides a possible neural substrate for this behavior. Earlier work proposed a mathematical model that generates scale-invariant time cells based on neurons with long time constants and an approximation of inverse Laplace transform. This paper...

Neurons process and convey information by transforming barrages of synaptic inputs into spiking activity. Synaptic inhibition typically suppresses the output firing activity of a neuron, and is commonly classified as having a subtractive or divisive effect on a neuron’s output firing activity. Subtractive inhibition can narrow the range of inputs that evoke spiking activity by eliminating respo...

Spiking neural networks that have variable connection delays have the interesting property that they are sensitive to both spatial and temporal patterns of input. Each neuron in the network receives input from spatially-distributed input neurons whose precise firing times interact with connection delays to determine whether the neuron can exceed the firing threshold and produce an output. The n...

We now consider the effects of connecting neurons together into networks. To do this, we make use of a description of neural responses that dispenses with individual action potentials and instead describes the inputs and outputs of neurons solely in terms of firing rates. A neuron firing at a rate r will produce an action potential during a short interval of duration ∆t with probability r∆t. Be...

Although previous research into the mechanisms underlying sensory and episodic representations has primarily focused on changes in neural firing rate, more recent evidence suggests that neural oscillations also contribute to these representations. Here, we argue that multiplexed oscillatory power and phase contribute to neural representations at the mesoscopic scale, complementary to neuronal f...

The process of changing the neuronal activity of the brain to acquire rewards in a broad sense is essential for utilizing brain-machine interfaces (BMIs), which is essentially operant conditioning of neuronal activity. Currently, this is also known as neural biofeedback, and it is often referred to as neurofeedback when human brain activity is targeted. In this review, we first illustrate biofe...

We analyze the conditions under which synaptic learning rules based on action potential timing can be approximated by learning rules based on firing rates. In particular, we consider a form of plasticity in which synapses depress when a presynaptic spike is followed by a postsynaptic spike, and potentiate with the opposite temporal ordering. Such differential anti-Hebbian plasticity can be appr...