Faculty Bibliography

Although vector strength (VS) and the Rayleigh tests are widely used to quantify neuronal firing synchrony to cyclic events, their use is valid only for singly peaked, unimodal distributions. In this report, we propose a new method to quantify synchrony, applicable to both unimodal and multimodal distributions. We also propose a statistical test to examine temporal structure under a null hypothesis of no synchrony.

In this report, a method is presented for gaining direct access to cortical areas within the lateral fissure of primates for neuroanatomical tracer injections and electrode array implantation. Compared to areas on the surface of the brain, the anatomical and physiological properties of areas within the fissure are poorly understood. Typically, access to these areas is indirectly achieved by ablating or passing through intervening areas. To enable direct experimental access, a neurosurgical technique was developed in primates whereby the banks of the lateral fissure were retracted with sparing of the vascular network and intervening areas. In some animals, anatomical tracers were directly injected into target fields without contamination of other areas. In others, multichannel electrode arrays were implanted into target areas for chronic recording of neural activity. Since, these techniques could be adapted for exploration of areas within other sulci, the approach represents an important advance in efforts to elucidate the functional organization of the primate cerebral cortex.

The purpose of this study was to compare response properties of two adjacent areas of the marmoset monkey auditory cortex. Multiunit responses to 50 ms tones and broadband noise bursts (BBN) were recorded in the core area, A1, and the caudomedial belt area, CM, of ketamine-anesthetized animals. Neurons in A1 and CM exhibited robust low-threshold short-latency responses to BBN and tones, whereas neurons in adjoining lateral belt areas were poorly responsive or unresponsive to tones and noise. Except for a population of broadly tuned units in CM, the characteristic frequency (CF) could be determined for all recording sites in A1 and CM. Both areas were tonotopically organized and shared a high CF border. Whereas the tonotopic gradient in A1 was smooth and continuous across the field, the gradient in CM was discontinuous, and the intermediate CF range was underrepresented. For BBN stimuli, rate level functions were largely monotonic in A1 and CM. Response profiles were also similar in both areas. As a population, neurons in CM were distinguished from A1 by significantly shorter response latencies, lower thresholds, and broader tuning bandwidth at higher intensities. The results indicated that, while A1 and CM represent anatomically and physiologically distinct areas, their response profiles under anesthesia overlapped considerably compared with the lateral belt areas. Therefore refinements of current models of the primate auditory cortex may be needed to account for differences in organization among the auditory belt areas.

We describe a novel method for estimation of multivariate neuronal receptive fields that is based on least-squares (LS) regression. The method is shown to account for the relationship between the spike train of a given neuron, the activity of other neurons that are recorded simultaneously, and a variety of time-varying features of acoustic stimuli, e.g. spectral content, amplitude, and sound source direction. Vocalization-evoked neuronal responses from the marmoset auditory cortex are used to illustrate the method. Optimal predictions of single-unit activity were obtained by using the recent-time history of the target neuron and the concurrent activity of other simultaneously recorded neurons (R: 0.82 +/- 0.01, approximately 67% of variance). Predictions based on ensemble activity alone (R: 0.63 +/- 0.18) were equivalent to those based on the combination of ensemble activity and spectral features of the vocal calls (R: 0.61 +/- 0.24). This result suggests that all information derived from the spectrogram is embodied in ensemble activity and that there is a high level of redundancy in the marmoset auditory cortex. We also illustrate that the method allows for quantification of relative and shared contributions of each variable (spike train, spectral feature) to predictions of neuronal activity and describe a novel "neurolet" transform that arises from the method and that may serve as a tool for computationally efficient processing of natural sounds.