Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.

We developed a new method to estimate the spatial extent of summation, the cortical spread, of the local field potential (LFP) throughout all layers of macaque primary visual cortex V1 by taking advantage of the V1 retinotopic map. We mapped multi-unit activity and LFP visual responses with sparse-noise at several cortical sites simultaneously. The cortical magnification factor near the recording sites was precisely estimated by track reconstruction. The new method combined experimental measurements together with a model of signal summation to obtain the cortical spread of the LFP. This new method could be extended to cortical areas that have topographic maps such as S1 or A1, and to cortical areas without functional columnar maps, such as rodent visual cortex. In macaque V1, the LFP was the sum of signals from a very local region, the radius of which was on average 250 microm. The LFP's cortical spread varied across cortical layers, reaching a minimum value of 120 microm in layer 4B. An important functional consequence of the small cortical spread of the LFP is that the visual field maps of LFP and MUA recorded at a single electrode site were very similar. The similar spatial scale of the visual responses, the restricted cortical spread, and their laminar variation led to new insights about the sources and possible applications of the LFP.

Sequential firings with fixed time delays are frequently observed in simultaneous recordings from multiple neurons. Such temporal patterns are potentially indicative of underlying microcircuits and it is important to know when a repeatedly occurring pattern is statistically significant. These sequences are typically identified through correlation counts. In this paper we present a method for assessing the significance of such correlations. We specify the null hypothesis in terms of a bound on the conditional probabilities that characterize the influence of one neuron on another. This method of testing significance is more general than the currently available methods since under our null hypothesis we do not assume that the spiking processes of different neurons are independent. The structure of our null hypothesis also allows us to rank order the detected patterns. We demonstrate our method on simulated spike trains.

The use of large-scale electrophysiology to obtain high spatiotemporal resolution brain recordings (>100 channels) capable of probing the range of neural activity from local field potential oscillations to single-neuron action potentials presents new challenges for data acquisition, storage, and analysis. Our group is currently performing continuous, long-term electrophysiological recordings in human subjects undergoing evaluation for epilepsy surgery using hybrid intracranial electrodes composed of up to 320 micro- and clinical macroelectrode arrays. DC-capable amplifiers, sampling at 32kHz per channel with 18-bits of A/D resolution are capable of resolving extracellular voltages spanning single-neuron action potentials, high frequency oscillations, and high amplitude ultra-slow activity, but this approach generates 3 terabytes of data per day (at 4 bytes per sample) using current data formats. Data compression can provide several practical benefits, but only if data can be compressed and appended to files in real-time in a format that allows random access to data segments of varying size. Here we describe a state-of-the-art, scalable, electrophysiology platform designed for acquisition, compression, encryption, and storage of large-scale data. Data are stored in a file format that incorporates lossless data compression using range-encoded differences, a 32-bit cyclically redundant checksum to ensure data integrity, and 128-bit encryption for protection of patient information.

Receptive fields of sensory neurons in the brain are usually restricted to a portion of the entire stimulus domain. At all levels of the gustatory neuraxis, however, there are many cells that are broadly tuned, i.e., they respond well to each of the basic taste qualities (sweet, sour, salty, and bitter). Although it might seem that this broad tuning precludes a major role for these cells in representing taste space, here we show the opposite--namely, that the tastant-specific temporal aspects (firing rate envelope and spike timing) of their responses enable each cell to represent the entire stimulus domain. Specifically, we recorded the response patterns of cells in the nucleus of the solitary tract (NTS) to representatives of four basic taste qualities and their binary mixtures. We analyzed the temporal aspects of these responses, and used their similarities and differences to construct the taste space represented by each neuron. We found that for the more broadly tuned neurons in the NTS, the taste space is a systematic representation of the entire taste domain. That is, the taste space of these broadly tuned neurons is three dimensional, with basic taste qualities widely separated and binary mixtures placed close to their components. Further, the way that taste quality is represented by the firing rate envelope is consistent across the population of cells. Thus, the temporal characteristics of responses in the population of NTS neurons, especially those that are more broadly tuned, produce a comprehensive and logical representation of the taste world.

We have designed a device for long-term head fixation for use in behaving nonhuman primates that is robust yet minimally invasive and simple to use. This device is a modified version of the halo system that is used in humans for cervical traction and stabilization after spinal column injuries. This device consists of an aluminum halo with four titanium skull pins offset from the halo by aluminum posts. The titanium pins insert onto small segments of cranially reinforcing titanium plate, which are attached to the skull with titanium cortex screws. The surgery involves four scalp incisions, placement of the reinforcing plates, insertion of the pins for attachment of the halo, and incision closure. After the halo is attached, the animal's head can be fixed to a primate chair using a custom-built attachment arm that provides three degrees of adjustability for proper positioning during behavioral tasks. We have installed this device on two Macaque monkeys weighing 7 and 10kg. The halos have been in place on these animals for up to 8 months without signs of discomfort or loss of fixation. Using this method of head fixation, we have been able to track the animals' eye positions with an accuracy of less than two visual degrees while they perform behavioral tasks.

We have developed a reversible system for performing simultaneous recordings from multiple brain areas of trained macaque monkeys. It consists of a near-circular halo fitted around the head of the monkey with 5-10 thin plastic or stainless steel posts that either jut against or are screwed into the skull, respectively. Both methods of implantation of the posts are easily reversible, enabling protracted recordings over many years and training the monkeys in more complex tasks. The former is more useful for shorter periods of recordings (2-4 months) separated by long intervals and the latter for longer periods of recordings at a time (6-12 months). With both systems, essentially the entire scalp is intact, allowing multi-site recordings from a number of dorsal cortical areas, as well as other areas, simultaneously. These recordings are performed through tiny craniotomies of usually less than 2mm diameter, which are fitted with small plastic cones that serve as guide tubes for the microelectrodes. The surgery involved in these procedures is relatively minor compared to classical methods and the implants are also usually free of infections, thus requiring little maintenance of recording chambers.

Cortical motor areas are thought to contribute "higher-order processing," but what that processing might include is unknown. Previous studies of the smooth pursuit-related discharge of supplementary eye field (SEF) neurons have not distinguished activity associated with the preparation for pursuit from discharge related to processing or memory of the target motion signals. Using a memory-based task designed to separate these components, we show that the SEF contains signals coding retinal image-slip-velocity, memory, and assessment of visual motion direction, the decision of whether to pursue, and the preparation for pursuit eye movements. Bilateral muscimol injection into SEF resulted in directional errors in smooth pursuit, errors of whether to pursue, and impairment of initial correct eye movements. These results suggest an important role for the SEF in memory and assessment of visual motion direction and the programming of appropriate pursuit eye movements.

Random dot motion (RDM) displays have emerged as one of the standard stimulus types employed in psychophysical and physiological studies of motion processing. RDMs are convenient because it is straightforward to manipulate the relative motion energy for a given motion direction in addition to stimulus parameters such as the speed, contrast, duration, density, aperture, etc. However, as widely as RDMs are employed so do they vary in their details of implementation. As a result, it is often difficult to make direct comparisons across studies employing different RDM algorithms and parameters. Here, we systematically measure the ability of human subjects to estimate motion direction for four commonly used RDM algorithms under a range of parameters in order to understand how these different algorithms compare in their perceptibility. We find that parametric and algorithmic differences can produce dramatically different performances. These effects, while surprising, can be understood in relationship to pertinent neurophysiological data regarding spatiotemporal displacement tuning properties of cells in area MT and how the tuning function changes with stimulus contrast and retinal eccentricity. These data help give a baseline by which different RDM algorithms can be compared, demonstrate a need for clearly reporting RDM details in the methods of papers, and also pose new constraints and challenges to models of motion direction processing.

When correlation is measured in the presence of noise, its value is decreased. In single-neuron recording experiments, for example, the correlation of selectivity indices in a pair of tasks may be assessed across neurons but, because the number of trials is limited, the measured index values for each neuron will be noisy. This attenuates the correlation. A correction for such attenuation was proposed by Spearman more than 100 years ago, and more recent work has shown how confidence intervals may be constructed to supplement the correction. In this paper, we propose an alternative Bayesian correction. A simulation study shows that this approach can be far superior to Spearman's, both in accuracy of the correction and in coverage of the resulting confidence intervals. We demonstrate the usefulness of this technology by applying it to a set of data obtained from the frontal cortex of a macaque monkey while performing serial order and variable reward saccade tasks. There, the correction results in a substantial increase in the correlation across neurons in the two tasks.