The Interaction of Cue Type and Its Associated Behavioral Response Dissociates the Neural Activity between the Perirhinal and Postrhinal Cortices

Behavioral performance in the VSOM task. A, Behavioral performance (percent correct) was measured separately for each stimulus condition. Performance exceeded the chance level (50%) for all stimuli. No significant performance difference was observed between stimulus conditions. B, Latency measured within the event period was plotted for each stimulus. There was no significant difference in latency. C, Latency was compared between the two choice responses. The nose-poke response required a significantly longer latency compared with the push response. Each dot represents the average of a rat; data are presented as the mean ± standard error of the mean (SEM). **p < 0.01. n.s., Not significant.

Histologic verification of recording sites in the PER and POR. A, Lateral view of the rat brain (top). The PER and POR lie alongside the anterior and posterior strip of the rhinal fissure (marked by arrow). The vertical dash demarcates the boundary (−7.5 mm from bregma) between the PER (purple) and POR (gold). Thionin-stained sections near the boundary between the PER and POR (bottom). The caudal limit of the angular bundle (marked with red arrow) was defined as the border between the PER and POR (Burwell, 2001), which corresponds to −7.5 mm from bregma according to Paxinos and Watson (2009). Lines demarcate the boundaries of the PER or POR. Scale bar, 1 mm. B, Dorsal and ventral borders of the PER and POR were defined based on adjacent myelin-stained (left) and thionin-stained (right) sections. Lines demarcate the boundaries of the PER. Scale bar, 0.5 mm. C, Locations of recording electrodes in the PER and POR are marked in the nearest sections found in the atlas by Paxinos and Watson (2009). Different colors are used to mark electrodes from different rats.

Basic firing properties of neurons in the PER and POR. A, Representative autocorrelograms and waveforms of neurons from the PER and POR. The mean firing rate and spike width of a neuron are indicated below the waveform. Neurons were classified as bursting (top), regular spiking (middle), and unclassified (bottom) based on the study by Barthó et al. (2004). Calibration: amplitude (vertical bar), 100 μV; width (horizontal bar), 500 μs. B, Pie charts showing the proportions of three neuronal categories for the PER (top) and POR (bottom). Regular-spiking neurons were more abundant in the PER, whereas more bursting neurons were present in the POR. The numbers in the parentheses denote the number of neurons. *p < 0.05.

Characteristic firing patterns observed under various task-related conditions in PER and POR neurons. A, Firing rates (FR) under different stimulus types (scene or object) were measured within the event period and compared between the PER and POR. Despite the difference in visual salience, scene and object stimuli evoked similar firing rates in the PER and POR. B, Firing rates for different response conditions (push or nose-poke) were compared between PER and POR. No significant difference was observed in firing rates under different choice responses. Data are presented as the mean ± SEM. n.s., Not significant. C, Firing patterns were examined by plotting the raster plot (i) and spike density functions (ii). In the raster plot, trials were grouped into four stimulus conditions and sorted based on the trial latency of the event period (i.e., from the onset of a stimulus marked with a dotted line to the choice response marked with a gray dot). Spike density functions for each stimulus condition were constructed within the event period based on normalized time bins. Cell 1 preferentially fired to the pebble scene (thick line), while it remained silent to the other stimuli (thin lines). D, The raster plot (i) and spike density functions (ii) of cell 2, which also showed preferential firing patterns for the pebble scene (thick line), but by remaining silent compared with those observed for the other stimuli (thin lines). E, The raster plot (i) and spike density functions (ii) of cell 3 firing for the zebra and owl stimuli (thick lines), which were associated with the same choice response (i.e., nose-poke).

The PER and POR differ in their proportions of response-selective neurons but not stimulus-selective neurons. A, An analytic scheme showing the cell-categorization process. The firing rates of an example neuron from a session were fitted to a GLM using four predictors (or stimuli). In the extended plot of a gray box, the neuron increased its firing rates in trials where the owl object was presented (i.e., trials where the owl predictor had a value of 1). The GLM for the example neuron selected the owl predictor as a significant predictor (solid line), while the other predictors were found to be unsuitable for predicting the firing rates (dotted lines). B, Proportions of cell categories determined by GLM analysis. We categorized neurons based on which predictor was included in a GLM explaining the firing rates of the neuron. Stimulus-selective neurons were those with only one significant predictor in a GLM, implying preferential firing to a specific stimulus. Among stimulus-selective neurons, we further dissociated object- and scene-selective neurons based on which type of predictor (object or scene) was significant. Response-selective neurons were those with two significant predictors that were associated with the same choice response (push or nose-poke). Statistical comparison revealed that there were higher proportions of response-selective neurons in the POR compared with the PER. **p < 0.01. C, Functional categories of all recorded neurons and their anatomic locations. The dotted line represents the border between the PER and POR. Response-selective neurons (marked with green circles) were abundant in relatively posterior regions of the postrhinal cortex. We did not observe any clear functional segregation within regions neighboring the border.

Quantification of selective firing patterns from stimulus- and response-selective cells. A, An example of quantifying selective firing patterns in stimulus-selective neurons. The neuron classified as an object-selective neuron preferentially fired to the phone object (orange solid line). Firing rates for the phone object were designated as Prefer (black solid line), while firing rates for the other stimuli were averaged to be Non-prefer (gray dotted line) firing rates. To define the SI, Cohen’s d was calculated between the firing rates to Prefer and Non-prefer in each time bin and plotted as a heatmap. The SI was taken as the sum of Cohen’s d for all time bins. B, The SI was compared with shuffled data to verify that cell categorization based on GLM matched with averaged firing patterns. Scene- and object-selective neurons in both PER and POR showed higher SI compared with the shuffled data. C, An example of a response-selective neuron and its SI. The example neuron increased its firing in nose-poke trials. Firing rates for the nose-poke condition were averaged to Prefer firing rates, and for the push trials were averaged to Non-prefer firing rates. SI was calculated following the same procedure. D, Response-selective neurons also showed higher SI compared with shuffled data in the PER and POR. E, The SI was compared between regions and categories. Response-selective neurons of the PER and POR showed significantly higher SI compared with scene- and object-selective neurons, regardless of region. F, The explained variance (adjusted R²) obtained from the GLM generated in the previous analysis was compared between regions and categories. The GLM had a significantly higher explained variance for response-selective neurons compared with the other categories. Data are presented as the mean ± SEM. ***p < 0.001, ****p < 0.0001.