The SSVEP tracks attention, not consciousness, during perceptual filling-in

Research on the neural basis of conscious perception has almost exclusively shown that becoming aware of a stimulus leads to increased neural responses. By designing a novel form of perceptual filling-in (PFI) overlaid with a dynamic texture display, we frequency-tagged multiple disappearing targets as well as their surroundings. We show that in a PFI paradigm, the disappearance of a stimulus and subjective invisibility is associated with increases in neural activity, as measured with steady-state visually evoked potentials (SSVEPs), in electroencephalography (EEG). We also find that this increase correlates with alpha-band activity, a well-established neural measure of attention. These findings cast doubt on the direct relationship previously reported between the strength of neural activity and conscious perception, at least when measured with current tools, such as the SSVEP. Instead, we conclude that SSVEP strength more closely measures changes in attention.</p

Tecnologías para la adaptación al usuario en interfaces cerebro-máquina basados en potenciales visuales evocados

Máster en Investigación e Innovación en las Tecnologías de la Información y de las ComunicacionesEn los últimos años la aplicación de nuevas tecnologías en el campo de la Neurociencia y la Medicina en general ha tenido y sigue teniendo un importante papel en su desarrollo. Gracias a ello la comunicación entre los sistemas electrónicos y las personas se ha visto incrementado. Por ello, las interfaces cerebro máquina (BCI), que son sistemas electrónicos capaces de registrar ondas cerebrales mediante un electroencefalograma (EEG), pueden ser de gran utilidad a personas con deficiencias motoras. Muchos son los esfuerzos de grupos científicos por mejorar estos sistemas no invasivos y que son considerados como la pieza clave para el desarrollo de prótesis. A pesar de los esfuerzos, no se consigue alcanzar la robustez necesaria como para que su implementación sea de uso diario. Este proyecto se va a centrar en un tipo de señales EEG denominadas potenciales evocados visualmente de estado estacionario (SSVEP) y que son una respuesta del cerebro a un estímulo visual externo que parpadea a una determinada frecuencia y fase. Gracias al trabajo previo en el Grupo de Neurocomputación Biológica (GNB), se va utilizar un sistema BCI basado en estímulos mediante LEDs. La aportación de este trabajo será la creación de una plataforma Software que permita a un usuario realizar estimulaciones y la detección de señales SSVEPS para diversos estudios científicos que consideran la adaptación al usuario. Para ello, el usuario podrá determinar cuáles son las mejores frecuencias, fases y electrodos del sujeto a estudiar, es decir, se desea descubrir la mejor adaptación al usuario usando un sistema BCI seleccionando estos parámetros. Para facilitar su integración se ha optado por tecnologías recientes, QT y Python, estimulación con LEDs y una metodología de detección de SSVEPs conocida como el Análisis de la correlación Canónica (CCA). Finalmente un sistema de puntuación implementado en esta plataforma permitirá al usuario de determinar si las adaptaciones son compatibles ente sí en el marco de estudio

Neural Correlates of Gain Control in Drosophila and Humans

Previous research has shown that visual sensitivity in human epilepsy patients is abnormal – characterized by increased responses at high contrast levels. These abnormalities have been linked to changes in neuronal gain control. Using animal models to study these changes is a useful approach. In this thesis, we used a steady-state visually evoked potential (SSVEP) technique similar to that used in humans to study photoreceptor-level and neuronal gain control in wild type (w-) Drosophila across a range of ages. We then compared these responses to those obtained from Drosophila carrying the kcc potassium channel mutation that renders young flies susceptible to light and shock-induced seizures. By taking into account the age and temperature dependence of the mutant (kccDHS1) flies, we were able to identify increased neural activity that recovers to the normal profile as they get older. We also found that these kccDHS1 flies are hypersensitive to light, particularly when young. These two findings are consistent with the fact that the level of the KCC protein increases with age. In addition, we found that kccDHS1 flies generate high frequency oscillations in their ERGs in response (50 – 100 Hz) to abrupt light onsets and offsets – a phenomenon that might be linked to abnormal changes in the gain control of neuronal feedback circuits. Studying visual abnormalities in Drosophila can reveal important information but eventually we need to link any visual abnormalities observed in animal models to humans. We therefore, attempted to measure subtle changes in gain control in humans due to adaptation, and at the same time make use of the human mental ability to measure another measure of gain control, attention, using an fMRI technique. Although our data did not show any interaction between adaptation and attention, it suggests that attention in early visual pathways largely affects the level of suppression in non-stimulated regions around the adaptor rather than responses to the probe itself. This is a manipulation that links to our work on adaptation in Drosophila in Chapter 6. Overall, the results presented in this thesis showed that fly models of epilepsy can be useful for studying changes in visual gain control, and showed that this work might be extended to humans

The role of neural oscillations in the visual system and their relation to conscious perception

Neural oscillations are intrinsically linked with attention, vigilance and featural sensitivity and therefore often associated with visual perception. However, the neural oscillation literature remains conflicted on several issues. Here, I describe four experiments investigating these conflicts using a variety of experimental and analysis techniques. We first explored the relationship between the inhibitory neurotransmitter GABA and gamma frequency oscillations in the rodent visual cortex. We found no evidence that synaptic and extrasynaptic GABA concentration altered gamma oscillations, suggesting that GABAergic inhibition cannot be linked directly to GABA concentration and instead depend on postsynaptic receptor kinetics. The second chapter examined how spontaneous alpha activity related to performance in an orientation discrimination task. Alpha amplitude was a significant predictor of reaction time but not task accuracy. The results suggested that alpha can modulate visual perception through top-down mechanisms. Interestingly, we also found that the relationship between alpha activity and task accuracy was determined by the subject’s task expertise. The third chapter examined how exogenous rhythms (generated by chromatic gratings) within visual cortex may interact with ongoing endogenous oscillations. Univariate analysis of single EEG channels revealed significantly higher endogenous power during chromatic than achromatic stimulation. An additional multivariate classifier showed distinct patterns of activity at very high frequencies, suggesting phase coupling between exogenous and endogenous signals. This finding was extended in the final chapter, which examined the neural correlates of rapid chromatic stimulation. Robust BOLD responses were found even when stimuli flickered above the consciously perceptible frequency, indicating that the temporal filtering stage limiting perception is later than V4. Additionally, chromatic preference in ‘colour area’ V4 was strongly dependent on stimulus frequency