These observations were confirmed by a significant schedule x lever interaction F1,7 = 4.91, P = 0.024, using a repeated measures ANOVA/MANOVA with schedule manipulation (vehicle and 60 and 360 infusions of amphetamine) and lever.
Delayed presentation of visual signals decreased active lever pressing facilitated by amphetamine, but did not reliably influence inactive lever presses (Fig. 3A; a significant delay x lever interaction, F2,11 = 4.95, P = 0.029).
LI rats continued to display dose-dependent effects of α-flupenthixol infusions into the DLS, while this sensitivity to DLS dopamine receptor blockade now emerged in HI rats (main effect of Dose: F3,15 = 5.23, p =.011 and F3,21 = 4.11, p =.019, respectively, Dose × Lever interaction: F3,15 = 5.20, p =.012 and F3,21 = 3.59, p =.031, respectively).
The tactics of intentional timing and email spoofing as a subconscious lever to invoke interaction are tried and tested methodologies.
In other words, amphetamine could increase the difference in response rates between the two levers by the same proportion, leading to a significant lever x manipulation interaction.
Thus, although dopamine receptor blockade in the DLS was ineffective during the early stage of cocaine seeking (effect of Dose: F3,45 = 1.03, p =.389 and Lever × Dose interaction: F3,45 = 1.06, p =.375), it dose-dependently reduced cocaine seeking when performed at the transition stage (main effect of Dose, F3,45 = 3.41, p =.025; and a Lever × Dose interaction, F3,45 = 3.45, p =.024).
When cue-controlled cocaine seeking was well-established, bilateral DLS α-flupenthixol infusions resulted in an even more pronounced decrease in cocaine-seeking responses measured during the 15-min drug-free interval (main effect of Dose: F3,39 = 9.69, p <.001 and Lever × Dose interaction: F3,39 = 9.01, p <.001).
UHT rats also tended to decrease their lever-press latency more than the control group across phase (LRT = 3.81, 1 df, p = 0.051 (Model 11 in ESM); after controlling for contingency, the identity of the lever pressed, their interaction, treatment and phase).
Although we found a significant interaction between lever and concentration on lever presses, F2,58 = 22.14, P<0.0001 with the ANOVA/MANOVA described above, it is difficult to interpret this interaction.
The other major innovation lever Snap could pull involves interaction with the real world and artificial reality.
Using the triangulation of learning scores, eye tracking data, and video analysis of interaction with the levers, the efficacy of haptic feedback to improve learning was explored.
