Biomedical subjects

L M Optican

Publications and source records attributed to L M Optican.

At least 37 records · Page 2Linked to original sources

PubMed1992

Role of inferior temporal neurons in visual memory. II. Multiplying temporal waveforms related to vision and memory.

1. In the companion paper we reported on the activity of neurons in the inferior temporal (IT) cortex during a sequential pattern matching task. In this task a sample stimulus was followed by a test stimulus that was either a match or a nonmatch. Many of the neurons encoded information about the patterns of both current and previous stimuli in the temporal modulation of their responses. 2. A simple information processing model of visual memory can be formed with just four steps: 1) encode the current stimulus; 2) recall the code of a remembered stimulus; 3) compare the two codes; 4) and decide whether they are similar or different. The analysis presented in the first paper suggested that some IT neurons were performing the comparison step of visual memory. 3. We propose that IT neurons participate in the comparison of temporal waveforms related to vision and memory by multiplying them together. This product could form the basis of a crosscorrelation-based comparison. 4. We tested our hypothesis by fitting a simple multiplicative model to data from IT neurons. The model generated waveforms in separate memory and visual channels. The waveforms arising from the two channels were then multiplied on a point by point basis to yield the output waveform. The model was fitted to the actual neuronal data by a gradient descent method to find the best fit waveforms that also had the lowest total energy. 5. The multiplicative model fit the neuronal responses quite well. The multiplicative model made consistently better predictions of the actual response waveforms than did an additive model. Furthermore, the fit was better when the actual relationship between the responses and the sample and test stimuli were preserved than when that relationship was randomized. 6. We infer from the superior fit of the multiplicative model that IT neurons are multiplying temporally modulated waveforms arising from separate visual and memory systems in the comparison step of visual memory.

Animals↗

PubMed1992

Saccade-vergence interactions in humans.

1. We recorded eye movements in four normal human subjects during refixations between targets calling for various combinations of saccades and vergence. We confirmed and extended prior observations of 1) transient changes in horizontal ocular alignment during both pure horizontal saccades (relative divergence followed by relative convergence) and pure vertical saccades (usually divergence for upward and convergence for downward saccades); 2) occasional, high-frequency (20-25 Hz), conjugate oscillations along the axis orthogonal to the main saccade; and 3) the speeding up of horizontal vergence by both horizontal and vertical saccades. 2. To interpret these findings, we developed a hypothesis for the generation of vergence to step changes in target depth, both with and without associated saccades. The essential features of this hypothesis are 1) the transient changes in horizontal ocular alignment during pure horizontal saccades reflect asymmetries in the mechanical properties of the lateral and medial rectus muscles causing adduction to lag abduction; 2) pure vergence movements in response to step changes in target depth are generated by a neural network that uses a desired change in vergence position as its input command and instantaneous vergence motor error (the difference between the desired change and the actual change in vergence) to drive vergence premoter neurons; and 3) the facilitation of horizontal vergence by saccades arises from nonlinear interactions in central premotor circuits. 3. The hypothetical network for generating pure vergence to step changes in target depth is analogous in structure to the local feedback model for the generation of saccades and has the same conceptual appeal. With the assumption of a single nonlinearity describing the relationship between a vergence motor error signal and the output of the neurons that generate promoter vergence velocity commands, this model generates pure vergence movements with peak velocity-amplitude relationships and trajectories that closely match those of experimental data. 4. Several types of models are proposed for the central, nonlinear interaction that occurs when saccades and vergence are combined. Common to all models is the idea that omnidirectional pause neurons (OPN), which are thought to gate activity for saccade burst neurons, also gate activity for saccade-related vergence. In one model we hypothesize the existence of a separate class of saccade-related vergence burst neurons, which generate premotor horizontal vergence commands but only during saccades. In a second model we hypothesize separate right eye and left eye saccadic burst neurons that receive not only conjugate, but also equal but oppositely directed vergence error signals.(ABSTRACT TRUNCATED AT 400 WORDS)

Adult↗

PubMed1991

Concurrent processing and complexity of temporally encoded neuronal messages in visual perception.

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.

Animals↗

PubMed1991

Unbiased measures of transmitted information and channel capacity from multivariate neuronal data.

Two measures from information theory, transmitted information and channel capacity, can quantify the ability of neurons to convey stimulus-dependent information. These measures are calculated using probability functions estimated from stimulus-response data. However, these estimates are biased by response quantization, noise, and small sample sizes. Improved estimators are developed in this paper that depend on both an estimate of the sample-size bias and the noise in the data.

Animals↗

PubMed1991

Interactive effects among several stimulus parameters on the responses of striate cortical complex cells.

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)

Analysis of Variance↗

PubMed1991

Lateral geniculate neurons in behaving primates. I. Responses to two-dimensional stimuli.

1. Using behaving monkeys, we studied the visual responses of single neurons in the parvocellular layers of the lateral geniculate nucleus (LGN) to a set of two-dimensional black and white patterns. We found that monkeys could be trained to make sufficiently reliable and stable fixations to enable us to plot and characterize the receptive fields of individual neurons. A qualitative examination of rasters and a statistical analysis of the data revealed that the responses of neurons were related to the stimuli. 2. The data from 5 of the 13 "X-like" neurons in our sample indicated the presence of antagonistic center and surround mechanisms and linear summation of luminance within center and surround mechanisms. We attribute the lack of evidence for surround antagonism in the eight neurons that failed to exhibit center-surround antagonism either to a mismatch between the size of the pixels in the stimuli and the size of the receptive field or to the lack of a surround mechanism (i.e., the type II neurons of Wiesel and Hubel). 3. The data from five other neurons confirm and extend previous reports indicating that the surround regions of X-like neurons can have nonlinearities. The responses of these neurons were not modulated when a contrast-reversing, bipartite stimulus was centered on the receptive field, which suggests a linear summation within the center and surround mechanisms. However, it was frequently the case for these neurons that stimuli of identical pattern but opposite contrast elicited responses of similar polarity, which indicates nonlinear behavior. 4. We found a wide variety of temporal patterns in the responses of individual LGN neurons, which included differences in the magnitude, width, and number of peaks of the initial on-transient and in the magnitude of the later sustained component. These different temporal patterns were repeatable and clearly different for different visual patterns. These results suggest that visual information may be carried in the shape as well as in the amplitude of the response waveform.

Animals↗

PubMed1991

Lateral geniculate neurons in behaving primates. II. Encoding of visual information in the temporal shape of the response.

1. We used the Karhunen-Loève (K-L) transform to quantify the temporal distribution of spikes in the responses of lateral geniculate (LGN) neurons. The basis functions of the K-L transform are a set of waveforms called principal components, which are extracted from the data set. The coefficients of the principal components are uncorrelated with each other and can be used to quantify individual responses. The shapes of each of the first three principal components were very similar across neurons. 2. The coefficient of the first principal component was highly correlated with the spike count, but the other coefficients were not. Thus the coefficient of the first principal component reflects the strength of the response, whereas the coefficients of the other principal components reflect aspects of the temporal distribution of spikes in the response that are uncorrelated with the strength of the response. Statistical analysis revealed that the coefficients of up to 10 principal components were driven by the stimuli. Therefore stimuli govern the temporal distribution as well as the number of spikes in the response. 3. Through the application of information theory, we were able to compare the amount of stimulus-related information carried by LGN neurons when two codes were assumed: first, a univariate code based on response strength alone; and second, a multivariate temporal code based on the coefficients of the first three principal components. We found that LGN neurons were able to transmit an average of 1.5 times as much information using the three-component temporal code as they could using the strength code. 4. The stimulus set we used allowed us to calculate the amount of information each neuron could transmit about stimulus luminance, pattern, and contrast. All neurons transmitted the greatest amount of information about stimulus luminance, but they also transmitted significant amounts of information about stimulus pattern. This pattern information was not a reflection of the luminance or contrast of the pixel centered on the receptive field. 5. In addition to measuring the average amount of information each neuron transmitted about all stimuli, we also measured the amount of information each neuron transmitted about the individual stimuli with both the univariate spike count code and the multivariate temporal code. We then compared the amount of information transmitted per stimulus with the magnitudes of the responses to the individual stimuli. We found that the magnitudes of both the univariate and the multivariate responses to individual stimuli were poorly correlated with the information transmitted about the individual stimuli.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed1991

Lateral geniculate neurons in behaving primates. III. Response predictions of a channel model with multiple spatial-to-temporal filters.

1. For the experiments reported in these papers, we recorded the responses of lateral geniculate (LGN) neurons to a large set of two-dimensional, black and white patterns based on Walsh functions and to a set of test stimuli. In the first two papers we reported that these neurons encode stimulus-related information in both the strength and the shape of the response waveforms and that there are more than two independent components in the response. These results cannot be explained by existing models. This paper provides a model of LGN neurons that not only accounts for the foregoing observations, but also yields predictions confirmed by direct tests. 2. The model represents a neuron as a set of three parallel channels. The input to each channel is an array of pixel luminances. Each channel consists of an input nonlinearity cascaded into a linear spatial-to-temporal filter. The output of each channel is a basic waveform, a principal component. The response of the neuron is the sum of the outputs of the three channels. 3. The model accounted for much of the variance in the coefficients of the first three principal components of the neuronal responses to the set of Walsh stimuli. Using parameters derived from the responses of neurons to the Walsh stimuli only, the model also predicted the responses to "center-surround" annuli of different contrasts and mean luminances, as well as to superpositions of pairs of Walsh patterns. The model made statistically significant predictions of the coefficients of two of the principal components of these responses. 4. After the parameters of the model had been fit to reproduce the responses of neurons to the Walsh stimuli, we found that the input nonlinearity of the model was compressed at both the high and low luminance levels. This compression produced response saturation that closely resembled the response saturation of neurons reported in the first paper in this series. Although not absolutely smooth, the spatial filter for the first channel had a dominant excitatory or inhibitory center and an antagonistic surround. Thus this spatial filter accounted for both the center and the surround structures of previous models of LGN receptive fields. There was greater variety in the structures of the spatial filters for the second and third channels, but none had a center-surround organization. Many of the spatial filters for these higher channels contained oriented ridges or valleys. Other spatial filters were dominated by a bipolar pair of pixels. 5. The model of LGN neurons that we present in this paper represents an extension over previous models in four ways. First, the model is capable of explaining the responses of neurons to a wider range of luminances than previous models. Second, the model is capable of explaining the shapes of the response waveforms as well as their magnitudes. Third, the concept of a single receptive field is extended to a series of spatial-to-temporal filters. Fourth, the model suggests that LGN neurons provide a description of both the brightness and the form of a stimulus in their response waveforms.

Animals↗

PubMed1991

Superior colliculus neurons mediate the dynamic characteristics of saccades.

1. The locus of activity within the superior colliculus (SC) is related to the desired displacement of the eye. Current hypotheses suggest that the location of this locus of activity determines the amplitude of the saccade and that the level of activity at this locus determines eye velocity. We present evidence that suggests that, although the locus determines the amplitude of the saccade, the level of activity in the colliculus encodes dynamic motor error (the difference between desired and current eye displacement). 2. We categorized 86 neurons in the intermediate and deep layers of the superior colliculus of two rhesus monkeys by their activity in relation to the end of saccadic eye movements. In 36% of the cells (n = 31), activity was completely cut off by the end of the saccade (clipped cells). For 53% of cells (n = 46), the major burst of activity ceased by the end of the saccade, but activity continued for 30-100 ms after the end of the movement (partially clipped cells). The remaining 10% of the cells (n = 9) had no clear burst of activity (unclipped cells) but rather had activity that increased gradually before the saccade and then slowly decreased for up to 100 ms after the saccade. These categories were part of a continuum of cell types rather than discrete classes of cells. 3. We first determined whether this new categorization of cells revealed a special relation between the discharge of clipped and partially clipped cells and saccadic amplitude and peak velocity. As expected, we found a steady increase in spike count as saccadic amplitude increased up to the center of the movement field, and an increase in peak spike discharge as peak velocity increased up to a maximum radial eye velocity. Variability in the cell discharge was substantially greater than the variability of saccadic amplitude or peak velocity. We concluded that these single point or averaged measures did not reveal any new functional relationship of these cells. 4. We then examined the relationship of the temporal pattern of discharge of clipped and partially clipped cells to instantaneous changes in radial error and radial velocity. There was a monotonic decay in spike discharge with declining radial error. In contrast, there was a complex, multivalued relationship between spike discharge and radial velocity; collicular cells produced two different values of spike discharge for the same velocity, one during acceleration and the other during deceleration of the eye during a saccade.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed1990

Retinal image motion alone does not control disconjugate postsaccadic eye drift.

1. In these experiments, postsaccadic ocular drift was induced by postsaccadic motion of the visual scene. In the most important case, the scene was moved in one eye but not the other. Six human subjects viewed the interior of a full-field hemisphere filled with a random-dot pattern. During training, eye movements were recorded by the electrooculogram. A computer detected the end of every saccade and immediately moved the pattern horizontally in the same or, in different experiments, in the opposite direction as the saccade. The pattern motion was exponential with an amplitude of 25% of the size of the antecedent saccade and a time constant of 50 ms. Before and after 3-4 h of such training, movements of both eyes were measured simultaneously by the eye coil-magnetic field method while subjects looked between stationary targets for calibration, explored the visual pattern with saccades, or made saccades in the dark to measure the effects of adaptation on postsaccadic ocular drift. The amplitude of this drift was expressed as a percentage of the size of the antecedent saccade. 2. In monocular experiments, subjects viewed the random-dot pattern with one eye. The other eye was patched. With two subjects, the pattern drifted backward in the direction opposite to the saccade; with the third, it drifted onward. The induced ocular drift was exponential, always in the direction to reduce retinal image motion, had zero latency, and persisted in the dark. After training, drift in the dark changed by 6.7% in agreement with our prior study with binocular vision, which produced a change of 6.0%. 3. In a dichoptic arrangement, one eye regarded the moveable random-dot pattern; the other, through mirrors, saw a different random-dot pattern (with similar spacing, contrast, and distance) that was stationary. These visual patterns were not fuseable and did not evoke subjective diplopia. In this case, the induced change in postsaccadic drift in the same three subjects was only 4.8%. In all cases the changes in postsaccadic drift were conjugate--they obeyed Hering's law. 4. Normal human saccades are characterized by essentially no postsaccadic drift in the abducting eye and a pronounced onward drift (approximately 4%) in the adducting eye. After training, this abduction-adduction asymmetry was preserved in the light and dark with monocular or dichoptic viewing, indicating again that all adaptive changes were conjugate. 5. When the subjects viewed the adapting stimulus after training, the zero-latency, postsaccadic drift always increased from levels in the dark.(ABSTRACT TRUNCATED AT 400 WORDS)

Adult↗

PubMed1990

Temporal encoding of two-dimensional patterns by single units in primate primary visual cortex. I. Stimulus-response relations.

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)

Animals↗

PubMed1990

Temporal encoding of two-dimensional patterns by single units in primate primary visual cortex. II. Information transmission.

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.

Analysis of Variance↗

PubMed1989

Visually induced plasticity of postsaccadic ocular drift in normal humans.

1. Five human subjects viewed binocularly the interior of a full-field hemisphere filled with a random-dot pattern. During training, eye movements were recorded by the electrooculogram. A computer detected the end of every saccade and immediately moved the pattern horizontally either in the same or, in different experiments, the opposite direction as the saccade. The motion was exponential, its amplitude was 25% of the horizontal component of the antecedent saccade, and its time constant was either 25, 50, or 100 ms in different experiments. Before and after 2-3 h of this experience, movements of both eyes were measured simultaneously by the eye-coil/magnetic-field method while subjects made saccades across the moveable pattern, looked between stationary targets, or made saccades in the dark, to see the effect of such adaptation on postsaccadic eye movements. 2. After 2-3 h (10,000-20,000 saccades) subjects developed a zero-latency, postsaccadic, ocular drift in the dark in the direction of the pattern motion. Three subjects were trained to backward drift, two to onward drift. Drift amplitude in the dark changed by 6% of the saccade size (range: 2-11%). The drift was exponential with an overall time constant of 108 ms. 3. After training, while viewing the adapting pattern motion, the change in the amplitude of the zero-latency drift was approximately 10% (range: 6.5-14%). 4. Increasing the time constant of the pattern motion produced significant increases in the time constant of the ocular drift. 5. The incidence of dynamic overshoot (a tiny, backward saccade immediately following a main saccade) was idiosyncratic and went up in some subjects and down in others with adaptation. These changes did not seem related to modifications of postsaccadic drift. 6. Normal human saccades are characterized by essentially no postsaccadic drift in the abducting eye and a pronounced onward drift (approximately 4%) in the adducting eye. This adduction-adduction asymmetry is largely preserved through adaptation. Thus the changes in drift were conjugate and conformed to Hering's law of equal (change of) innervation. 7. These results agree with those previously demonstrated in the monkey and can similarly be explained by parametric changes in the pulse, slide, and step of normal saccadic innervation.

Acclimatization↗

PubMed1989

Unilateral pursuit-induced congenital nystagmus.

We describe two patients with a lifelong history of oscillopsia only when following objects moving toward their left side. Neurologic examination was normal except for eye movements. The patients showed nystagmus during any tasks that required visual following toward the left (ie, smooth pursuit, optokinetic nystagmus, and vestibulo-ocular-reflex-suppression), but had no nystagmus during fixation of stationary targets or visual following tasks to the right. Eye-movement recordings showed waveforms during pursuit to the left that were typical of congenital nystagmus.

Adult↗

PubMed1988

Superior colliculus neurons provide the saccadic motor error signal.

Studies of the intermediate layers of the superior colliculus have suggested that it provides a desired change in eye position signal (delta E) for the generation of saccadic eye movements. Recent evidence, however, has shown that some neurons in these layers may be related to the velocity of saccades. We present single cell recordings from the intermediate layers of monkey superior colliculus that are consistent with the hypothesis that many superior colliculus neurons provide instead a motor error signal, em. Our hypothesis about the function of these cells places them inside the local feedback loop controlling the waveform of the saccade.

Animals↗

PubMed1987

Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. I. Response characteristics.

We seek a general approach to determine what stimulus features visual neurons are sensitive to and how those features are represented by the neuron's responses. Because lesions of inferior temporal (IT) cortex interfere with a monkey's ability to perform pattern discrimination tasks we studied IT neurons. Previous single-unit studies have shown that IT neurons sometimes respond more strongly to complex stimuli (brushes, hands, faces) than to simple stimuli (bars, slits, edges). However, it is not known how specific stimulus parameters are represented by responses. We studied the responses of IT neurons in alert behaving monkeys to a large set of two-dimensional black and white patterns. The stimulus set was based on 64 Walsh functions that can be used to represent any picture with a resolution of one part in eight along each of two dimensions. The responses to these stimuli spanned a continuum from inhibition to strong excitation. A statistical test showed that the spike count was determined by which Walsh stimulus was presented. Hence, these stimuli form an adequate set for testing IT neurons. The responses showed temporal modulation of the spike train that could not be represented by a change in the spike count alone. Examples of this modulation were changes in latency, changes in the duration of the response, and alternating periods of excitation and inhibition. This temporal modulation may be important in representing stimulus parameters. The next paper in this series develops a method for quantifying this temporal modulation and shows that it is dependent on the stimulus. The third paper in this series shows that this temporal modulation contains more information about stimulus parameters than is contained in the spike count alone.

Animals↗

PubMed1987

Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. II. Quantification of response waveform.

The purpose of this study was to describe how the responses of neurons in inferior temporal (IT) cortex represent visual stimuli. In the preceding paper we described the responses of IT neurons to a large set of two-dimensional black and white patterns. The responses to different stimuli showed temporal modulation of the spike trains. This paper develops a method for quantifying temporal modulation and shows that the stimulus determines the distribution over time, as well as the number, of spikes in a response. The responses were quantified using an orthogonal set of temporal waveforms called principal components. The principal components related to each neuron were extracted from all the responses of that neuron to all of the stimuli, regardless of which stimulus elicited which response. Each response was then projected onto the set of principal components to obtain a set of coefficients that quantified its temporal modulation. This decomposition produces coefficients that are uncorrelated with each other. Thus each coefficient could be tested individually, with univariate statistics, to determine whether its relation to the stimulus was nonrandom. The waveforms of the principal components are unconstrained and depend only on the responses from which they are derived; hence, they can assume any shape. Nonetheless, the 21 neurons we analyzed all had principal components that belonged to only one of two sets. The two sets could be characterized by their first principal component, which was either phasic or tonic. This suggests that these neurons may use as few as two different mechanisms in generating responses. The first principal component was highly correlated with spike count, and both were driven by the stimulus. Higher principal components were uncorrelated with spike count, yet some of them were also driven by the stimulus. Thus the principal components form a richer description of the stimulus-dependent aspects of a neuronal response than does spike count. Bootstrap tests showed that several principal components (usually 3 or 4) were determined by the stimulus. Since higher principal components were not correlated with the spike count, the stimulus must have determined the distribution of spikes in the response as well as their number. However, it is possible that the number and distribution of spikes are both determined by the same characteristics of the stimulus. In this case, the temporal modulation would be redundant, and a simple univariate measure would be sufficient to characterize the stimulus-response relationship.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed1987

Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. III. Information theoretic analysis.

Ablation and single-unit studies in primates have shown that inferior temporal (IT) cortex is important for pattern discrimination. The first paper in this series suggested that single units in IT cortex of alert monkeys respond to a set of two-dimensional patterns with complex temporal modulation of their spike trains. The second paper quantified the waveform of the modulated responses of IT neurons with principal components and demonstrated that the coefficients of two to four of the principal components were stimulus dependent. Although the coefficients of the principal components are uncorrelated, it is possible that they are not statistically independent. That is, several coefficients could be determined by the same feature of the stimulus, and thus could be conveying the same information. The final part of this study examined this issue by comparing the amount of information about the stimulus that can be conveyed by two codes: a temporal waveform code derived from the coefficients of the first three principal components and a mean rate code derived from the spike count. We considered the neuron to be an information channel conveying messages about stimulus parameters. Previous applications of information theory to neurophysiology have dealt either with the theoretical capacity of neuronal channels or the temporal distribution of information within the spike train. This previous work usually used a general binary code to represent the spike train of a neuron's response. Such a general approach yields no indication of the nature of the neuron's intrinsic coding scheme because it depends only on the timing of spikes in the response. In particular, it is independent of any statistical properties of the responses. Our approach uses the principal components of the response waveform to derive a code for representing information about the stimuli. We regard this code as an indication of the neuron's intrinsic coding scheme, because it is based on the statistical properties of the neuronal responses. We measured how much information about the stimulus was present in the neuron's responses. This transmitted information was calculated for codes based on either the spike count or on the first three principal components of the response waveform. The information transmitted by each of the first three principal components was largely independent of that transmitted by the others. It was found that the average amount of information transmitted by the principal components was about twice as large as that transmitted by the spike count.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗