Prepulse inhibition predicts spatial working memory performance in the inbred Roman high- and low-avoidance rats and in genetically heterogeneous NIH-HS rats: relevance for studying pre-attentive and cognitive anomalies in schizophrenia

Abstract

Animal models of schizophrenia-relevant symptoms are increasingly important for progress in our understanding of the neurobiological basis of the disorder and for discovering novel and more specific treatments. Prepulse inhibition (PPI) and working memory, which are impaired in schizophrenic patients, are among the symptoms/processes modeled in those animal analogs. We have evaluated whether a genetically-selected rat model, the Roman high-avoidance inbred strain (RHA-I), displays PPI deficits as compared with its Roman low-avoidance (RLA-I) counterpart and the genetically heterogeneous NIH-HS rat stock. We have investigated whether PPI deficits predict spatial working memory impairments (in the Morris water maze; MWM) in these three rat types (Experiment 1), as well as in a separate sample of NIH-HS rats stratified according to their extreme (High, Medium, Low) PPI scores (Experiment 2). The results from Experiment 1 show that RHA-I rats display PPI and spatial working memory deficits compared to both RLA-I and NIH-HS rats. Likewise, in Experiment 2, "Low-PPI" NIH-HS rats present significantly impaired working memory with respect to "Medium-PPI" and "High-PPI" NIH-HS subgroups. Further support to these results comes from correlational, factorial, and multiple regression analyses, which reveal that PPI is positively associated with spatial working memory performance. Conversely, cued learning in the MWM was not associated with PPI. Thus, using genetically-selected and genetically heterogeneous rats, the present study shows, for the first time, that PPI is a positive predictor of performance in a spatial working memory task. These results may have translational value for schizophrenia symptom research in humans, as they suggest that either by psychogenetic selection or by focusing on extreme PPI scores from a genetically heterogeneous rat stock, it is possible to detect a useful (perhaps "at risk") phenotype to study cognitive anomalies linked to schizophrenia.

Keywords: Roman high-avoidance rats; Roman low-avoidance rats; cognitive deficits; genetically heterogeneous rats; prepulse inhibition; schizophrenia-relevant symptoms; schizophreniform rat model; spatial working memory.

Figure 1

(A) Mean prepulse inhibition (± S.E.M.) is shown for the three strains. (B) Mean ± S.E.M. of the “Mean %PPI” averaged for the four prepulse intensities. (C) Mean ± S.E.M. of the startle response in the three blocks of pulse-alone trials: BL(105), initial pulse-alone 10-trial block; PPI(105), second pulse-alone 10-trial block, pseudorandomly administered in combination with presentation of the prepulse-pulse trials; POST(105), the final pulse-alone 5-trial block. ^*p < 0.05 between the indicated groups (LSD tests).

Figure 2

(A) Mean ± S.E.M. of the distance (cm) traveled by the rats of the three strains in the first (T1) and second (T2) trials, averaged for the 3 days. (B) Mean ± S.E.M. of the three differences (i.e., subtractions T1-T2), corresponding to the 3 days, between the first (T1) and the second trials (T2) of the working memory task. (C) Mean ± S.E.M. swimming speed for each trial and strain. ^*p < 0.05, “Strain” effect (One-Way ANCOVA; see text).

Figure 3

(A) Mean ± S.E.M. of the percentage of distance traveled in the periphery in each trial for the three groups. (B) Mean ± S.E.M. of the difference of “percentage of distance traveled in the periphery between T1 and T2 (averaged for the 3 days)” (“Mean %DP T1-T2”). (C) Mean ± S.E.M. of the distance traveled by the rats in each of the 8 trials of the cued task. (D) Mean ± S.E.M. swimming speed in the cued task for each trial. ^*p < 0.05 vs. the other two strains (A,D) or between the groups indicated (B); &, p < 0.05 vs. the RLA-I group (LSD tests following the corresponding significant ANOVA effects).

Figure 4

Linear regressions between %PPI and “working memory” measures (all rats pooled, n = 33). (A) Regression between %PPI75 (predictor variable) and “Mean T1-T2” (dependent variable). (B) Regression between %PPI80 (predictor variable) and “Mean %DP T1-T2” (dependent variable).

Figure 5

(A) Mean ± S.E.M. of the distance (cm) traveled by the three subgroups of NIH-HS rats (selected for their extreme performance in the PPI test) in the first (T1) and second trials (T2), averaged for the 3 days (see text for the criteria followed to build these 3 subgroups). (B) Mean ± S.E.M. of the three differences (i.e., “Mean T1-T2”), corresponding to the 3 days, between the first (T1) and second (T2) trials of the working memory task. (C) Mean ± S.E.M. swimming speed of the NIH-HS sub-groups for each trial. ^*p < 0.05 between the indicated groups (LSD test following significant One-Way ANOVA).

Figure 6

(A) Mean ± S.E.M. of the percentage of distance traveled in the periphery in each trial for the 3 groups of NIH-HS rats. (B) Mean ± S.E.M. of the “difference of percentage of distance traveled in the periphery between T1 and T2 (averaged for the 3 days)” (i.e., “Mean %DP T1-T2”). (C) Mean ± S.E.M. of the distance (cm) traveled by the rats of the three groups in each of the 8 trials of the cued task. (D) Mean ± S.E.M. swimming speed of the NIH-HS sub-groups for each trial. ^*p < 0.05 between the groups indicated (LSD test following significant One-Way ANOVA).