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Are different kinds of stimuli (for example, different classes of geometric images or naturalistic images) encoded differently by visual cortex, or are the principles of encoding the same for all stimuli? We examine two response properties: (1) the range of spike counts that can be elicited from a neuron in epochs representative of short periods of fixation (up to 400 msec), and (2) the relation between mean and variance of spike counts elicited by different stimuli, that together characterize the information processing capabilities of a neuron using the spike count code. In monkey primary visual cortex (V1) complex cells, we examine responses elicited by static stimuli of four kinds (photographic images, bars, gratings, and Walsh patterns); in area TE of inferior temporal cortex, we examine responses elicited by static stimuli in the sample, nonmatch, and match phases of a delayed match-to-sample task. In each area, the ranges of mean spike counts and the relation between mean and variance of spike counts elicited are sufficiently similar across experimental conditions that information transmission is unaffected by the differences across stimulus set or behavioral conditions [although in 10 of 27 (37%) of the V1 neurons there are statistically significant but small differences, the median difference in transmitted information for these neurons was 0.9%]. Encoding therefore appears to be consistent across experimental conditions for neurons in both V1 and TE, and downstream neurons could decode all incoming signals using a single set of rules.

Interpreting messages encoded in single neuronal responses requires knowing which features of the responses carry information. That the number of spikes is an important part of the code has long been obvious. In recent years, it has been shown that modulation of the firing rate with about 25 ms precision carries information that is not available from the total number of spikes across the whole response. It has been proposed that patterns of exactly timed (1 ms precision) spikes, such as repeating triplets or quadruplets, might carry information that is not available from knowing about spike count and rate modulation. A model using the spike count distribution, the low-pass filtered PSTH (bandwidth below 30 Hz), and, to a small degree, the interspike interval distribution predicts the numbers and types of exactly-timed triplets and quadruplets that are indistinguishable from those found in the data. From this it can be concluded that the coarse (< 30 Hz) sequential correlation structure over time gives rise to the exactly timed patterns present in the recorded spike trains. Because the coarse temporal structure predicts the fine temporal structure, the information carried by the fine temporal structure must be completely redundant with that carried by the coarse structure. Thus, the existence of precisely timed spike patterns carrying stimulus-related information does not imply control of spike timing at precise time scales.

Usually the conditional probabilities needed to calculate transmitted information are estimated directly from empirically measured distributions. Here we show that an explicit model of the relation between response strength (here, spike count) and its variability allows accurate estimates of transmitted information. This method of estimating information is reliable for data sets with nine or more trials per stimulus. We assume that the model characterizes all response distributions, whether observed in a given experiment or not. All stimuli eliciting the same response are considered equivalent. This allows us to calculate the channel capacity, the maximum information that a neuron can transmit given the variability with which it sends signals. Channel capacity is uniquely defined, thus avoiding the difficulty of knowing whether the 'right' stimulus set has been chosen in a particular experiment. Channel capacity increases with increasing dynamic range and decreases as the variance of the signal (noise) increases. Neurons in V1 send more variable signals in a wide dynamic range of spike counts, while neurons in IT send less variable signals in a narrower dynamic range. Nonetheless, neurons in the two areas have similar channel capacities. This suggests that variance is being traded off against dynamic range in coding.

1. We recorded the responses of 37 striate cortical complex cells in fixating monkeys while presenting a set of oriented stimuli that varied in contrast. 2. The two response parameters of strength and latency can be interpreted as a code: the strength defines the stimulus form (here the orientation), and the latency is more a function of the stimulus contrast. 3. Synchronization based on latency could make a strong contribution to the process of organizing the neural responses to different objects, i.e., binding.

The responses of adjacent neurons in inferior temporal (IT) cortex carry signals that are to a large degree independent (Gawne and Richmond, 1993). Adjacent primary visual cortical neurons have similar orientation tuning (Hubel and Wiesel, 1962, 1968), suggesting that their responses might be more redundant than those in IT. We recorded the responses of 26 pairs of adjacent complex cells in the primary visual cortex of two awake monkeys while using both a set of 16 bar-like stimuli, and a more complex set of 128 two-dimensional patterns. Linear regression showed that 40% of the signal variance of one neuron was related to that of the other when the responses to the bar-like stimuli were considered. However, when the responses to the two-dimensional stimuli were included in the analysis, only 19% of the signal variance of one neuron was related to that of the adjacent one, almost exactly the same results as found in IT. An information theoretic analysis gave similar results. We hypothesize that this trend toward independence of information processing by adjacent cortical neurons is a general organizational strategy used to maximize the amount of information carried in local groups.

We perform time-resolved calculations of the information transmitted about visual patterns by neurons in primary visual and inferior temporal cortices. All measurable information is carried in an effective time-varying firing rate, obtained by averaging the neuronal response with a resolution no finer than about 25 ms in primary visual cortex and around twice that in inferior temporal cortex. We found no better way for a neuron receiving these messages to decode them than simply to count spikes for this long. Most of the information tends to be concentrated in one or, more often, two brief packets, one at the very beginning of the response and the other typically 100 ms later. The first packet is the most informative part of the message, but the second one generally contains new information. A small but significant part of the total information in the message accumulates gradually over the entire course of the response. These findings impose strong constraints on the codes used by these neurons.

We have studied the encoding of spatial pattern information by complex cells in the primary visual cortex of awake monkeys. Three models for the conditional probabilities of different stimuli, given the neuronal response, were fit and compared using cross-validation. For our data, a feed-forward neural network proved to be the best of these models. The information carried by a cell about a stimulus set can be calculated from the estimated conditional probabilities. We performed a spatial spectroscopy of the encoding, examining how the transmitted information varies with both the average coarseness of the stimulus set and the coarseness differences within it. We find that each neuron encodes information about many features at multiple scales. Our data do not appear to allow a characterization of these variations in terms of the detection of simple single features such as oriented bars.

We studied the effect of cooling the striate cortex on parvocellular lateral geniculate nucleus (PLGN) neurons in awake monkeys. Cooling the striate cortex produced both facilitation and inhibition of the responses of all neurons, depending on the stimulus presented. Cooling the striate cortex also altered the temporal distribution of spikes in the responses of PLGN neurons. Shannon's information measure revealed that cooling the striate cortex reduced the average stimulus-related information transmitted by all PLGN neurons. The reduction in transmitted information was associated with both facilitation and inhibition of the response. Cooling the striate cortex reduced the amount of information transmitted about all of the stimulus parameters tested: pattern, luminance, spatial contrast, and sequential contrast. The effect of cooling was nearly the same for codes based on the number of spikes in the response as for codes based on their temporal distribution. The reduction in transmitted information occurred because the differences among the responses to different stimuli (signal separation) were reduced, not because the variability of the responses to individual stimuli (noise) was increased. We conclude that one function of corticogeniculate feedback is to improve the ability of PLGN neurons to discriminate among stimuli by enhancing the differences among their responses.

The intrinsic neuronal code that carries visual information and the perceptual mechanism for decoding that information are not known. However, multivariate statistics and information theory show that neurons in four visual areas simultaneously carry multiple, stimulus-related messages by utilizing multiplexed temporal codes. The complexity of these temporal messages increases progressively across the visual system, yet the temporal codes overlap in time. Thus, visual perception may depend on the concurrent processing of multiplexed temporal messages from all visual areas.

1. Although neurons within the visual system are often described in terms of their responses to particular patterns such as bars and edges, they are actually sensitive to many different stimulus features, such as the luminances making up the patterns and the duration of presentation. Many different combinations of stimulus parameters can result in the same neuronal response, raising the problem of how the nervous system can extract information about visual stimuli from such inherently ambiguous responses. It has been shown that complex cells transmit significant amounts of information in the temporal modulation of their responses, raising the possibility that different stimulus parameters are encoded in different aspects of the response. To find out how much information is actually available about individual stimulus parameters, we examined the interactions among three stimulus parameters in the temporally modulated responses of striate cortical complex cells. 2. Sixteen black and white patterns were presented to two awake monkeys at each of four luminance-combinations and five durations, giving a total of 320 unique stimuli. Complex cells were recorded in layers 2 and 3 of striate cortex, with the stimuli centered on the receptive fields as determined by mapping with black and white bars. 3. An analysis of variance (ANOVA) was applied to these data with the three stimulus parameters of pattern, the luminance-combinations, and duration as the independent variables. The ANOVA was repeated with the magnitude and three different aspects of the temporal modulation of the response as the dependent variables. For the 19 neurons studied, many of the interactions between the different stimulus parameters were statistically significant. For some response measures the interactions accounted for more than one-half of the total response variance. 4. We also analyzed the stimulus-response relationships with the use of information theoretical techniques. We defined input codes on the basis of each stimulus parameter alone, as well as their combinations, and output codes on the basis of response strength, and on three measures of temporal modulation, also taken individually and together. Transmitted information was greatest when the response of a neuron was interpreted as a temporally modulated message about combinations of all three stimulus parameters. The interaction terms of the ANOVA suggest that the response of a complex cell can only be interpreted as a message about combinations of all three stimulus parameters.(ABSTRACT TRUNCATED AT 400 WORDS)

1. Previously, we studied how picture information was processed by neurons in inferior temporal cortex. We found that responses varying in both response strength and temporal waveform carried information about briefly flashed stationary black-and-white patterns. Now, we have applied that same paradigm to the study of striate cortical neurons. 2. In this approach the responses to a set of basic black and white pictures were quantified through use of a set of basic waveforms, the principal components (extracted from all the responses of each neuron). We found that the first principal component, which corresponds to the response strength, and others, which correspond to different basic temporal activity patterns, were significantly related to the stimuli, i.e., the stimulus drove both the response strength and its temporal pattern. 3. Our previous study had shown that, when information theory was used to quantify the stimulus-response relation, inferior temporal neurons convey over twice as much information in a response code that includes temporal modulation as in a response code that includes only the response strength. This study shows that striate cortical neurons also carry twice as much information in a temporal code as in a response strength code. Thus single visual neurons at both ends of a cortical processing chain for visual pattern use a multidimensional temporal code to carry stimulus-related information. 4. These results support our multiplex-filter hypothesis, which states that single visual system neurons can be regarded as several simultaneously active parallel channels, each of which conveys independent information about the stimulus.

1. Previously we developed a new approach for investigating visual system neuronal activity in which single neurons are considered to be communication channels transmitting stimulus-dependent codes in their responses. Application of this approach to the stimulus-response relations of inferior temporal (IT) neurons showed that these carry stimulus-dependent information in the temporal modulation as well as in the strength of their responses. IT cortex is a late station in the visual processing stream. Presumably the neuronal properties arise from the properties of the inputs. However, the discovery that IT neuronal spike trains transmit information in stimulus-dependent temporally modulated codes could not be assumed to be true for those earlier stations, so the techniques used in the earlier study were applied to single-striate cortical neurons in the studies reported here. 2. Single-striate cortical neurons were recorded from three awake, fixating rhesus monkeys. The neurons were stimulated by two sets of patterns. The first set was made up of 128 black-and-white patterns based on a complete, orthogonal set of two-dimensional Walsh-Hadamard functions. These stimuli appear as combinations of black-and-white rectangles and squares, and they fully span the range of all possible black-and-white pictures that can be constructed in an 8 x 8 grid. Except for the stimulus that appeared as an all-white or all-black square, each stimulus had equal areas of white and black. The second stimulus set was made up of single bars constructed in the same 8 x 8 grid as the Walsh stimuli. These were presented both as black against a gray background and white against a gray background. The stimuli were centered on the receptive field, and each member of the stimulus set was presented once before any stimulus appeared again. 3. The responses of 21 striate cortical neurons were recorded and analyzed. Two were identified as simple cells and the other 19 as complex cells according to the criteria originally used by Hubel and Wiesel. The stimulus set elicited a wide variety of response strengths and patterns from each neuron. The responses from both the bars and the Walsh set could be used to differentiate and classify simple and complex cells. 4. The responses of both simple and complex cells showed striking stimulus-related strength and temporal modulation. For all of the complex cells there were instances where the responses to a stimulus and its contrast-reversed mate were substantially different in response strength or pattern, or both.(ABSTRACT TRUNCATED AT 400 WORDS)