Effects of long-term visual experience on responses of distinct classes of single units in inferior temporal cortex

Abstract

Primates can learn to recognize a virtually limitless number of visual objects. A candidate neural substrate for this adult plasticity is the inferior temporal cortex (ITC). Using a large stimulus set, we explored the impact that long-term experience has on the response properties of two classes of neurons in ITC: broad-spiking (putative excitatory) cells and narrow-spiking (putative inhibitory) cells. We found that experience increased maximum responses of putative excitatory neurons but had the opposite effect on maximum responses of putative inhibitory neurons, an observation that helps to reconcile contradictory reports regarding the presence and direction of this effect. In addition, we found that experience reduced the average stimulus-evoked response in both cell classes, but this decrease was much more pronounced in putative inhibitory units. This latter finding supports a potentially critical role of inhibitory neurons in detecting and initiating the cascade of events underlying adult neural plasticity in ITC.

Figure 1

Experimental paradigm and spike waveform clustering. (A) Passive fixation task during which 10 stimuli were presented for 200 ms each with a 50 ms interstimulus interval. Familiar and novel stimuli were interleaved. (B) All recorded spike waveforms, aligned by their troughs and labeled according to their cluster membership. (C) Distribution of spike widths (trough-to-peak durations) and the two clusters that emerged from the k-means algorithm. The bars above the distributions show mean ± SD of the respective distributions.

Figure 2

Example neuronal responses to familiar and novel stimuli. (A) – (E) Five representative putative excitatory cells. (F and G) Two representative putative inhibitory cells. In all rows, the column on the far left shows both the mean spike waveform of each cell and the cluster to which the waveform was assigned (blue = broad spike, red = narrow spike). In the middle five columns are plotted the spike density functions (SDFs, spike times convolved with a Gaussian kernel with σ = 20 ms) for the top 5 stimuli from the familiar set (black) and the top 5 stimuli from the novel set (green). These rankings were determined not on the basis of the peak value of the SDF but rather from the spike counts in the interval 75 – 200 ms after stimulus onset, which is shown as a light gray bar abutting the time axis. The insets in these graphs show the actual familiar and novel images eliciting the response. The column on the far right shows each neuron's entire distribution of mean firing rates, sorted according to rank. Again, the mean firing rates were computed from the spike counts in the interval 75 – 200 ms after stimulus onset and the rankings were done independently for the familiar and novel sets. The numbers in the top right of the rank plots show the magnitude of the sparseness metric that was used to quantify single cell selectivity.

Figure 3

Visual experience increases maximum responses of putative excitatory cells but decreases maximum responses of putative inhibitory cells. (A and B) Sliding window analyses (step size = 5 ms, window size = 50 ms) of maximum firing rates to familiar (black) and novel (green) stimulus sets, averaged separately for the putative excitatory (A) and putative inhibitory (B) cells. Shaded regions indicate ±SEM. Tick marks denote the time points at which the differences between the maximum familiar responses and maximum novel responses achieved statistical significance according to a permutation test (p < .05). (C) Distribution of individual cells' responses to the best familiar (x-axis) and best novel (y-axis) stimulus during the early epoch (75 – 200 ms). Each data point represents the activity of a single unit. Cells are color-labeled according to cluster membership (blue, putative excitatory; red, putative inhibitory). Error bars represent mean ± SEM across individual repetitions of the best familiar or best novel stimulus. Histogram in the top right shows the distribution of differences for both subpopulations. Shaded bars show individually significant cases (p < .05, Mann-Whitney test). Arrows denote mean maximum response differences across either the putative excitatory (blue) or inhibitory (red) cells. (D) A magnified view of the plot in (C), emphasizing the distribution of effects in the putative excitatory cells. (E and F) Same as in (C and D) but for the late epoch (200 – 325 ms).

Figure 4

Visual experience decreases average stimulus-evoked responses of putative excitatory and inhibitory cells, particularly in the late phase, but the effect is much larger in putative inhibitory cells. Conventions same as in Figure 4 with the notable exception that the metric of interest is the average, not maximum, response across the 125 familiar or 125 novel stimuli. Error bars in (C) and (D) represent mean ± SEM across the 125 familiar or 125 novel (mean) firing rates. Individually significant cases in histograms of panels C and D were determined with a t-test (p < .05).

Figure 5

Visual experience increases selectivity (sparseness) of putative excitatory and inhibitory cells. Same conventions as in Figures 3 and 4, except that the metric investigated is sparseness across the 125 familiar or 125 novel stimuli. Individually significant cases in histograms of panels C and D were determined with a permutation test (p < .05).

Figure 6

For putative excitatory cells, the experience-dependent increase in maximum response predicts the experience-dependent increase in selectivity (sparseness). The difference between familiar and novel sparseness is plotted as a function of the difference between maximum familiar and maximum novel responses. Each point represents a single putative excitatory unit. Maximum responses and sparseness values were taken from the early epoch (75 – 200 ms).

Figure 7

Putative excitatory and inhibitory units can discriminate between stimuli within the familiar and within the novel sets. (A) Distribution of individual cells' familiar (x-axis) and novel (y-axis) mean pairwise AUC values during the early epoch (75 – 200 ms). Each data point represents the mean pairwise AUC value of a single unit. Cells are color-labeled according to cluster membership (blue, putative excitatory; red, putative inhibitory). Histogram in the top right shows the distribution of AUC differences for both subpopulations. For clarity, all bars are shaded but this does not indicate significance. Arrows denote mean differences across either the putative excitatory (blue) or inhibitory (red) cell class. (B) Same as in (A) but for the late epoch (200 – 325 ms). (C) Relationship between sparseness and mean pairwise AUC value for familiar (black) and novel (green) stimuli during the early epoch (75 – 200 ms). Putative inhibitory units are indicated by open circles. (D) Same as in (C) but for the late epoch (200 – 325 ms).

Figure 8

Schematic representation of experience-dependent firing rate changes in putative excitatory and putative inhibitory units. (A) Firing rates of putative excitatory neurons are arranged in descending order of effectiveness. In this cell class, visual experience increased responses to the most effective stimuli, particularly in the early epoch, and decreased responses to moderately effective stimuli, especially in the late epoch. (B) Same as in (A) but for putative inhibitory units. Visual experience caused a much more widespread and noticeable decline in firing rates of these neurons. This change was most prominent in the late epoch.