Note on the coefficient of variations of neuronal spike trains

Large coefficient of variation of inter-spike intervals induced by noise current in the resonate-and-fire model neuron

Neuronal spike variability is a statistical property associated with the noise environment. Considering a linearised Hodgkin-Huxley model, we investigate how large spike variability can be induced in a typical stellate cell when submitted to constant and noise current amplitudes. For low noise current, we observe only periodic firing (active) or silence activities. For intermediate noise values, in addition to only active or inactive periods, we also identify a single transition from an initial spike-train (active) to silence dynamics over time, where the spike variability is low. However, for high noise current, we find intermittent active and silence periods with different values. The spike intervals during active and silent states follow the exponential distribution, which is similar to the Poisson process. For non-maximal noise current, we observe the highest values of inter-spike variability. Our results suggest sub-threshold oscillations as a possible mechanism for the appearance of high spike variability in a single neuron due to noise currents.

Simultaneous Optimization of the Ultrasonic Extraction Method and Determination of the Antioxidant Activities of Hydroxysafflor Yellow A and Anhydrosafflor Yellow B from Safflower Using a Response Surface Methodology

An evaluation of the ultrasonic extraction process and the antioxidant activities of hydroxysafflor yellow A (HSYA) and anhydrosafflor yellow B (AHSYB) from safflower are presented herein. Using response surface methodology (RSM), based on a four-factor-three-level Box–Behnken design (BBD), the extraction parameters, namely, temperature, extraction time, solvent-to-material ratio, and extraction power, were optimized for maximizing the yields of HSYA and AHSYB. The maximum yield was obtained at a temperature of 66 °C with an extraction time of 36 min, solvent-to-material ratio of 16 mL/g, and the extraction power of 150 W, which was adjusted according to the actual conditions. The HSYA and AHSYB contents were determined using high performance liquid chromatography (HPLC). The yield and the comprehensive evaluation value of HSYA and AHSYB were calculated. The antioxidant activities of the extracts were determined using a ferric reducing antioxidant power (FRAP) kit and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity. The results suggested that the safflower extracts possessed obvious ferric reducing and DPPH radical scavenging activities. The antioxidant activity increased with increasing concentration. The results suggested that optimizing the conditions of ultrasonic extraction using RSM can significantly increase the yields of HSYA and AHSYB from safflower. The safflower extracts showed better antioxidant activity. This study can encourage future research on cardiovascular and cerebrovascular diseases.

Fluctuation Scaling of Neuronal Firing and Bursting in Spontaneously Active Brain Circuits

We employed high-density microelectrode arrays to investigate spontaneous firing patterns of neurons in brain circuits of the primary somatosensory cortex (S1) in mice. We recorded from over 150 neurons for 10min in each of eight different experiments, identified their location in S1, sorted their action potentials (spikes), and computed their power spectra and inter-spike interval (ISI) statistics. Of all persistently active neurons, 92% fired with a single dominant frequency - regularly firing neurons (RNs) - from 1 to 8Hz while 8% fired in burst with two dominant frequencies - bursting neurons (BNs) - corresponding to the inter-burst (2-6Hz) and intra-burst intervals (20-160Hz). RNs were predominantly located in layers 2/3 and 5/6 while BNs localized to layers 4 and 5. Across neurons, the standard deviation of ISI was a power law of its mean, a property known as fluctuation scaling, with a power law exponent of 1 for RNs and 1.25 for BNs. The power law implies that firing and bursting patterns are scale invariant: the firing pattern of a given RN or BN resembles that of another RN or BN, respectively, after a time contraction or dilation. An explanation for this scale invariance is discussed in the context of previous computational studies as well as its potential role in information processing.

Information processing in the LGN: a comparison of neural codes and cell types

To understand how anatomy and physiology allow an organism to perform its function, it is important to know how information that is transmitted by spikes in the brain is received and encoded. A natural question is whether the spike rate alone encodes the information about a stimulus (rate code), or additional information is contained in the temporal pattern of the spikes (temporal code). Here we address this question using data from the cat Lateral Geniculate Nucleus (LGN), which is the visual portion of the thalamus, through which visual information from the retina is communicated to the visual cortex. We analyzed the responses of LGN neurons to spatially homogeneous spots of various sizes with temporally random luminance modulation. We compared the Firing Rate with the Shannon Information Transmission Rate , which quantifies the information contained in the temporal relationships between spikes. We found that the behavior of these two rates can differ quantitatively. This suggests that the energy used for spiking does not translate directly into the information to be transmitted. We also compared Firing Rates with Information Rates for X-ON and X-OFF cells. We found that, for X-ON cells the Firing Rate and Information Rate often behave in a completely different way, while for X-OFF cells these rates are much more highly correlated. Our results suggest that for X-ON cells a more efficient "temporal code" is employed, while for X-OFF cells a straightforward "rate code" is used, which is more reliable and is correlated with energy consumption.