Comparison with baseline clustering techniques. حسب Sayantan Kumar (20208872)

Experimental design. حسب Sam Hall-McMaster (10343795)

Comparison of cue-locked and feedback-locked decoding. حسب Sam Hall-McMaster (10343795)

Subgroup analysis. حسب Sam Hall-McMaster (10343795)

Data and code resources. حسب Sam Hall-McMaster (10343795)

"…These findings point to a possible neural implementation of an adaptive algorithm for generalization across tasks.…"

Validation tests of feature decoding during the associative memory paradigm. حسب Sam Hall-McMaster (10343795)

Comparison of city decoders trained on session one and session two data. حسب Sam Hall-McMaster (10343795)

Validation of the neural decoding pipeline. حسب Sam Hall-McMaster (10343795)

Decoding evidence for policies on each individual test task. حسب Sam Hall-McMaster (10343795)

Choices on individual test tasks were not explained by model-free perseveration. حسب Sam Hall-McMaster (10343795)

Reward outcomes for each combination of task cue and policy in the experiment. حسب Sam Hall-McMaster (10343795)

Post scan feature estimates and confidence ratings. حسب Sam Hall-McMaster (10343795)

Associative memory paradigm used to train the feature decoders. حسب Sam Hall-McMaster (10343795)

Accuracy of the Generalized WTA. حسب Ori Hendler (21262937)

Decoding evidence for feature triplets on test tasks. حسب Sam Hall-McMaster (10343795)

"…This figure shows average decoding evidence for features associated with the more and less rewarding training policies on test trials (y-axis) as a function of brain region (x-axis). Feature information could not be decoded above chance in the four brain regions of interest (corrected <i>p-</i>values > 0.05). …"

Learning dynamics on training tasks. حسب Sam Hall-McMaster (10343795)

Choice behavior on individual test tasks. حسب Sam Hall-McMaster (10343795)

Simulation of Spiral flight. حسب Junhao Wei (6816803)

"…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …"

Population initialized by Pseudo-Random Number. حسب Junhao Wei (6816803)

"…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …"

Population initialized by Good Nodes Set. حسب Junhao Wei (6816803)

"…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …"