Correlation of activity in neighbouring goldfish ganglion cells: relationship between latency and lag.

Abstract

SUMMARY1. Pairs of retinal ganglion cells in the isolated goldfish retina were recorded simultaneously with a single electrode. Repeated flashes of light were delivered to evaluate the response latency of each of the units.2. The cross-correlation histogram for the maintained discharge ofeach pair of cells was examined, and its temporal relationships (lags) were compared with the differences in response latencies of the two units. There was a strong correlation between these measures; however, the differences between latencies were often at least twice as great as the lags.3. The differences between the times to the peaks of the responses of the two units were less reliably related to the lags of the pairs, although the correlation was positive and the differences in time-to-peak generally greater than the lags. The weaker relationship between the difference in time-to-peak and lag than between latency difference and lag is apparently a manifestation of a negative correlation between latency and rise time (from first response to peak). This indicates that cells with a longer latency compensate with a faster rise time.4. There was a negative correlation between the mean maintained rate of a neurone and its response latency. That is, cells with faster maintained discharge rates respond sooner than those with slower maintained rates.5. There was virtually no relationship between the lags or the differences in latency and the differences between the magnitudes of the responses to light. Thus, it is unlikely that differences in latency (or lags) could be attributed to unequal effectiveness of the stimuli for the two units.6. The relationship between differences in latency and lags did not depend on the response categorizations of the two units. Specifically, it did not matter whether the members of the pair were on centre, off centre or on-off centre; neither did it matter whether they were X-like or not-X-like neurones. 7. Consideration of these data leads to the conclusion that there must be 'marked' pathways of differential conduction velocity through the retina.

The Structure of Multi-Neuron Firing Patterns in Primate Retina

“…2 B). This synchronized firing in the absence of time-varying stimulation (also known as "noise correlations") resembles observations in other species and indicates functional connectivity attributable to common inputs and/or reciprocal connections in the retina (Arnett, 1978;Johnsen and Levine, 1983;Mastronarde, 1983b;Meister et al, 1995;DeVries and Baylor, 1997;Brivanlou et al, 1998;Hidaka et al, 2004). Anticorrelation between ON and OFF parasol cells was also observed (data not shown) (Mastronarde, 1983a), but subsequent analysis will be restricted to cells of the same type.…”

“…However, multi-neuron recordings have revealed substantial interactions that cannot be observed with single-neuron recording. For example, retinal ganglion cells (RGCs) exhibit strong stimulus-independent correlated activity; the circuits mediating such correlations and the consequences for visual processing are not fully understood (Arnett, 1978;Johnsen and Levine, 1983;Mastronarde, 1983b;Meister et al, 1995;DeVries and Baylor, 1997;Nirenberg et al, 2001;Schneidman et al, 2003a). Such findings suggest interesting possibilities for circuit function but at the same time raise a major concern: will it be necessary to record from all of the cells in a neural circuit, and analyze all possible interactions, to determine how the circuit works?…”

Common noise in the firing of neighbouring ganglion cells in goldfish retina.

“…One means of tracking down the source is to study statistical dependencies in spike discharge between neighbouring ganglion cells by generating cross-correlation histograms (Perkel, Gerstein & Moore, 1967). With this method, statistical dependencies between ganglion cells have been demonstrated in goldfish (Arnett, 1978;Levine & Johnsen, 1982;Johnsen & Levine, 1983), rabbit (Arnett & Spraker, 1981) and cat retinae (Rodieck, 1967;Mastronarde, 1983a). The type of dependency observed in these studies was related to the functional types of the ganglion cells in the pair; ganglion cells with the same types of centre processes tended to fire in synchrony, while those with complementary centre processes were likely not to fire together.…”

Spike discharge prediction based on neuro-fuzzy system

“…Recording action potentials (spikes) from the neural cells makes it possible to investigate their health, stability, and sensitivity [1] . Different characteristics of the electrical activity of neurons can be considered in the study of neural coding.…”

“…There are many similarities between human and animal brain's neural coding and many studies used animal modeling for investigation the spike discharge [8][9][10][11] . Johnsen and Levine [1] analyzed as follows.…”