Attractor dynamics in perceptual decision making: from theoretical predictions to psychophysical experiments
- Autores: Genís Prat Ortega
- Directores de la Tesis: Jaime de la Rocha Vázquez (dir. tes.), Alexander Roxin (dir. tes.)
- Lectura: En la Universitat Autònoma de Barcelona ( España ) en 2019
- Idioma: español
- Tribunal Calificador de la Tesis: Jorge Fernando Mejias Palomino (presid.), Alexandre Hyafil (secret.), Gabriela Mochol (voc.)
- Programa de doctorado: Programa de Doctorado en Matemáticas por la Universidad Autónoma de Barcelona
- Materias:
- Enlaces
- Tesis en acceso abierto en: TESEO
- Resumen
From time to time humans and animals must respond to ambiguous stimuli. In the old days, before the creation of the video assistant referee or VAR, football referees had a very hard life. One of the most popular plays in football history is the so-called “La mano de dios” where Maradona used his hand to score a goal in the quarter-final match of the 1986 World Cup. Based on what he saw, the referee incorrectly decided that Maradona had not touched the ball with his hand and Argentina ended up winning the World Cup. The decisions based on sensory evidence (in this case visual) are what we call perceptual decision making.
In this thesis, we studied how the brain makes perceptual decisions in experimental settings where subjects have to make a categorical decision about a certain feature of the presented stimulus. We studied the case where the stimulus was presented for a certain time controlled by the experimenter. During the stimulus presentation, the subjects had to accumulate evidence and, when the stimulus ended, they needed to choose between two possible alternatives. These experiments are typically called 2-alternative forced choice tasks (2AFC).
From a computational point of view, the accumulation of stimulus evidence in 2AFC tasks has been studied intensively in the last decades. Canonical approaches to model this cognitive function are based on diffusion processes that assume bounded or unbounded perfect stimulus evidence accumulation. However, the relationship of such models with the underlying neural circuitry is unclear. Here, we studied the accumulation process in neurobiological models with attractor dynamics. Such models could actually be reduced to a nonlinear diffusion process, which in the case of binary categorizations could be described by a double well model (DWM). Despite the fact that the canonical and the neurobiological models rely on different mechanisms, they could both account for various behavioral aspects such as performance or reaction time.
The first goal of this thesis was to derive behaviourally testable predictions that could determine if attractor dynamics are at play during a 2AFC task or whether alternately the data was more compatible with models that assumed other kind of dynamics (e.g. perfect integration). We found two signatures of attractor dynamics that could be tested in behavioural experiments. Specifically, we found that: 1) The DWM had different integration regimes, which went from transient (primacy) to leaky (recency) accumulation as the magnitude of the stimulus fluctuations (σs) or the stimulus duration (T) increased. 2) Moreover, the DWM had a non-monotonic relation between the accuracy and the magnitude of the stimulus fluctuations.
The second goal of this thesis was to qualitatively and quantitatively test the existence of attractor dynamics in such 2AFC tasks. To this aim, we designed and carried out a new experiment where we systematically modified the magnitude of the stimulus fluctuations. The qualitative analysis of the experimental results was inconclusive because we could not identify obvious signatures of attractor dynamics that allow us to distinguish between different models. However, we quantitatively assessed the attractor dynamics and other plausible neural mechanisms by developing a model-fitting analysis. Preliminary results suggested that attractor dynamics could be important to explain the behavioural results in at least a fraction of subjects.
