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1703 STATISTICAL ANALYSIS OF OSCILLATORY NEURONAL ACTIVITIES IN CAT LATERAL GENICULATE NUCLEUS. HIROYUKI ITO. CHARLES M. GRAY, PEDRO MALDONADO. DeDt. of Enaineerinas, Kvoto Sanqvo Univ.,

. . Pvoto 60t JAPAN, Center for Neurohence, Univ. of CallfPrnla, Davis, USA, A large fraction of cell in the visual cortex of the cat display stimulus dependent, 30-60 Hz, oscillatory firing patterns that are often synchronous over a range of spatial scales. Many studies have been carried

out to test the hypothesis that those oscillations result fromintracorticalnetwork and play a functional role invisualinformationprocessing. Ontheotherhand, spontaneous andstimulus-evokedrhythmicactivity also occurs in the lateral geniculate nucleus (LGN). It has been hypothesized that cortical oscillatory activity may be an epiphenomenon of the spontaneous activity in the LGN that originates in the retina. To further test this notion, we have recorded spontaneous and visually-evoked activity in the LGN of anesthetized cats andevaluated the spike trains using correlation and spectral analyses. Our conclusion is the following. A: There are at least two types of oscillatory activities in the LGN. One is spontaneous oscillation that is suppressedbythe visual stimulation and possibly originates in the retina. The other is stimulusinducedoscillationthat is stimulusdependent. B: Therearesynchronousoscillatoryactivities betweenboththelocalsites andthedistantsites (500micronseparation).C: Weconcludethattheoscillatory activities observedinthe LGNareNOTlikelyto causethose observedinthe cortex, because: 1) The frequency ranges are significantly different, 60-90 Hz in the LGN and 30-60 Hz in the cortex. 2) The oscillatory activity observedinthe LGN is highly stable. This contrasts with highly transient nature of the cortical oscillation. 3) The vigorous , stable, spontaneous oscillatoryactivity observedinthe LGNis not observed in the cortex.

1704 LINEAR AND NONLINEAR COLOR PROCESSING IN STRIATE CORTEX OF THE MACAQUE MONKEY. Akitoshi Hanazawa. lkuva Murakami. Hidehiko

. Natl. Inst. for Phvsiol. Sci.. Mvodaiii, Kom u La . ats . b 0 f Neural Control Okazaki 444. Jaoan.

We recorded neuronal responses to various colors in striate cortex of a macaque monkey performing a visual fixation task. We studied color selectivity by using small rectangular stimuli with equiluminant colors distributed evenly on the C.I.E. chromaticity diagram. The question was whether the selective responses to colors were described as linear summation of three types of cone inputs. Out of fifty-four neurons which showed significant visual response, thirty-nine (72%) had a large difference between the maximum and minimum of responses to various colors (> 0.8 of max.). Thirteen of them had color selectivity which fitted well to a model based on an assumption of linear summation (p c 0.01). Most of the other neurons responded selectively to the colors localized on the C.I.E. diagram, e.g. less saturated colors only. Such selectivities probably resulted from some nonlinear processing. These results suggest that striate cortex mediates between linear process in early stage and non-linear process for fine color representation demonstrated in the inferior temporal cortex (Komatsu et al., 1992).

1705 EFFECT OF VISUAL NOISE ON VISUAL RECOGNITION AND NEURONAL RESPONSES IN

MONKEY INFERIOR TEMPORAL CORTEX. MUNETAKA SHIDARA*. ZHENG LIU & BARRY J. RICHMOND.

Neuroscience Sect., Electrotechnical Lab.. l-l-4 Umezono. Tsukuba-shi. Ibaraki 305. Janan* & Lab. of Neuropsychology,

NIMH. Bethesda. MD20892. USA.

We are studying the relation between the effect of noise on visual recognition behavior and inferior temporal (IT)

neuronal responses using a sequential delayed match-to-sample task. We used 8 black and white patterns. The patterns

consisted of 48*48 video monitor pixels. To add noise, we reversed the color of groups of 3*3-pixel dots with probabilities

of 5, 10, 15, 20, and 25%. As expected, the monkey’s rate of responding correctly to the matching stimulus decreased with

higher noise and the reaction time to bar release increased. Visually responsive neurons in IT responded to the specific

patterns with latencies of 90 - 160ms when there was no noise. Neither the latency or the peak amplitude of the neural responses to the matching stimulus changed consistently with increasing noise, showing that the monkeys performance is not

related to these simple measures of neuronal responses.