RESUMEN
Laboratory data from conflict tasks, e.g. Simon and Eriksen tasks, reveal differences in response time distributions under different experimental conditions. Only recently have evidence accumulation models successfully reproduced these results, in particular the challenging delta plots with negative slopes. They accomplish this with explicit temporal dependencies in their structure or activation functions. In this work, we introduce an alternative approach to the modeling of decision-making in conflict tasks exclusively based on inhibitory dynamics within a dual-route architecture. We consider simultaneous automatic and controlled drift diffusion processes, with the latter inhibiting the former. Our proposed Dual-Route Evidence Accumulation Model (DREAM) achieves equivalent performance to previous works in fitting experimental response time distributions despite having no time-dependent functions. The model can reproduce conditional accuracy functions and delta plots with positive and negative slopes. The implications of these results, including an interpretation of the parameters and potential links to perceptual representations, are discussed. We provide Python code to fit DREAM to experimental data. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09990-8.
RESUMEN
Context-dependent computation is a relevant characteristic of neural systems, endowing them with the capacity of adaptively modifying behavioral responses and flexibly discriminating between relevant and irrelevant information in a stimulus. This ability is particularly highlighted in solving conflicting tasks. A long-standing problem in computational neuroscience, flexible routing of information, is also closely linked with the ability to perform context-dependent associations. Here we present an extension of a context-dependent associative memory model to achieve context-dependent decision-making in the presence of conflicting and noisy multi-attribute stimuli. In these models, the input vectors are multiplied by context vectors via the Kronecker tensor product. To outfit the model with a noisy dynamic, we embedded the context-dependent associative memory in a leaky competing accumulator model, and, finally, we proved the power of the model in the reproduction of a behavioral experiment with monkeys in a context-dependent conflicting decision-making task. At the end, we discuss the neural feasibility of the tensor product and made the suggestive observation that the capacities of tensor context models are surprisingly in alignment with the more recent experimental findings about functional flexibility at different levels of brain organization.
Asunto(s)
EncéfaloRESUMEN
Surgical site infection (SSI) is an important cause of morbidity after orthotopic liver transplantation (OLT). Perioperative antibiotic prophylaxis is one of the main modifiable risk factors. We prospectively investigated the epidemiology, risk factors, and prognosis of SSI in a cohort of 167 OLT. Two different schedules of antibiotic SSI prophylaxis were compared. Fifty-six episodes of SSI were included (0.34 episodes/patient). The SSI incidence among patients who received cefazolin and amoxicillin-clavulanate did not differ. Bacteria caused all episodes. The most common pathogen was Escherichia coli (21.25%), among which 47% were extended-spectrum beta-lactamase producers. The only risk factor for SSI was antibiotic therapy before OLT. Patients with SSI had a longer hospital and intensive care unit stay (P<0.05), but survival did not differ. In conclusion, SSI has a high incidence despite antibiotic perioperative prophylaxis; therefore, an integral perspective of SSI and a multifactorial approach other than antimicrobial prophylaxis are needed to prevent it.