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Biomedical subjects

Y Yeshurun

Publications and source records attributed to Y Yeshurun.

60 records · Page 4Linked to original sources
PubMed1985

Identification of MGB cells by Volterra kernels. I. Prediction of responses to species specific vocalizations.

The function of CNS sites is frequently explored by an analysis of its input-output relationships. However, such research are often confined to a qualitative and subjective inspection of raw data. System Identification methods can be used to formalize the stimulus--response relations, and one of them, the Volterra approach, is employed here in order to define these relations in the MGB of the squirrel monkey, natural vocalizations being the stimuli. In order to validate the formal representation of the system under study, the predictability power of the model is tested. Having the distances between responses (PSTH) and predicted response quantified, it is found that the predictions made by the model are, in general, "closer" to the actual responses then some arbitrarily chosen responses. It is concluded that there are cells in the MGB that can be characterized by their Volterra kernels, and further research on the cell's functional role can be based on these kernels.

Acoustic Stimulation↗
PubMed1981

Responses of single cells in the medial geniculate body of awake squirrel monkeys.

Response properties of 142 medial geniculate (MGB) cells were investigated in the awake and undrugged squirrel monkey (Saimiri sciureus). Using Jordan's (1973) parcellation of this complex nucleus, cells were assigned to 3 major subdivisions a, b and c MGB and compared for their general characteristics and response properties. b MBG cells had significantly higher rates of spontaneous firing and longer latency periods than a and c MGB cells. With regard to responsiveness to various auditory stimuli, response patterns, and tuning characteristics, cells in all 3 subdivisions were statistically similar and were thus treated as one cell population. About 95% of the cells responded to broadband white noise, steady tone bursts and frequency modulated (FM) tones. Click activated only 69% of the responding cells. Various "through-stimulus" responses comprised about 80% of the responses. Among the tone-sensitive cells, 90% responded with complex patterns, out of which 50% were frequency-dependent. About 62% of the cells (for which tuning properties were determined) were quite broadly tuned (Q10dB less than 2) and had either single or multi-peaked response areas. The other 38% were quite narrowly tuned (Q10dB greater than 2) and had single-peaked, symmetrical or "tailed" response areas. Different inhibitory and excitatory response components of individual cells had different characteristic frequencies and response thresholds. The c MGB, which is tonotopically organized in a latero-medial orientation, appears to be homologous to the cat pars lateralis of the ventral MGB. The tonotopical organization of the b MGB, which is probably homologous to the cat's medial or magnocellular subdivision, is less clear. Most of the cells which were activated by FM tones disclosed "direction sensitivity" with different degrees of pattern complexity. It is suggested that pitch resolution in the MGB is based on spatio-temporal mechanisms.

Acoustic Stimulation↗
PubMed1979

Analysis of recall and recognition in a certain class of adaptive networks.

A general model of adaptive networks which perform recall is analyzed in view of qualitative psychological findings. The assumptions underlying the basic model are few and general in the sense that no specifications of structure or mechanisms of adaptation are imposed. The analysis of the model is towards the addition of various features drawn from the global input-output relations expected from the networks. The memorizing process of recognition is found to be intrinsic to the model, and four of the most prominent relations between the performance of recall and recognition are shown to either exist in model or to be realizable by means of few additional plausible features.

Association Learning↗