Given a task goal and some prior knowledge, an observer is able to prepare in advance for sensory events in a way that improves the speed and accuracy of perceptual decisions and subsequent actions. There exists evidence that this preparation, a function of """"""""top-down"""""""" attention, involves transient alterations to the activity of sensory neurons in early (low-level) sensory areas. One common finding is that when attention is deployed to a certain location, visual cortical regions that normally respond to stimuli at that location specifically undergo an enhancement in baseline excitability. However, the finer details of how the patterns of modulation across neurons at various hierarchical levels and with various tuning properties are tailored to facilitate specific perceptual tasks are not yet understood. Adapting preparatory neural states to tasks of varying complexity, difficulty and context is a fundamental higher cognitive ability that is known to be impaired in many brain disorders such as schizophrenia, autism and attention deficit/hyperactivity disorder (ADHD). The goal of this proposal is to develop, validate and apply novel methods to allow us to investigate these details. Building on previous work, we will use electroencephalographic (EEG) steady-state responses to track cortical excitability in visual neurons with specific properties in humans.
In aim 1, we wll exploit well-known geometrical properties of visual cortical anatomy along with simple signal processing principles to derive signals that differentially index striate (V1) versus extrastriate activity. We will then examine the influence of task complexity on the invocation of spatially specific gain modulation in striate and extrastriate cortex. This could potentially reconcile a longstanding controversy surrounding the earliest locus of attention modulation.
In aim 2, we will derive signals indexing neural sensitivity across a range of values of a single feature dimension - orientation - using a field of oriented probe stimuli. We will thus examine the allocation of attentional weights to specific feature values during preparation for visual search, comparing across conditions of fine and coarse target-distracter similarity. This will provide key insight ino context-dependent feature-weighting and how it is accomplished by changes to the sensitivity of early visual cortical neurons. The fulfillment of these two aims will not only bring about new insights into major cognitive problems, but will also establish new procedures that will be of broad utility in the field of cognitive neurophysiology.
This SC2 Pilot project proposal is aimed at understanding how top-down attention to relevant visual locations and features is expressed in patterns of preparatory neuronal modulation in the brain, and how and to what degree these patterns are tailored to the computational demands of the task at hand. Our investigations will use electroencephalographic (EEG) steady-state responses in humans, and will involve novel task manipulations and the establishment of direct links with behavioral performance. The insight we will gain into the flexible, task-specific action of top-down attention in sensory cortex will enhance our understanding of cognitive deficits in several brain disorders including schizophrenia, autism and attention deficit/hyperactivity disorder (ADHD).
| Gebodh, Nigel; Vanegas, M Isabel; Kelly, Simon P (2017) Effects of Stimulus Size and Contrast on the Initial Primary Visual Cortical Response in Humans. Brain Topogr 30:450-460 |
| Vanegas, M Isabel; Blangero, Annabelle; Kelly, Simon P (2015) Electrophysiological indices of surround suppression in humans. J Neurophysiol 113:1100-9 |
| Kelly, Simon P; Vanegas, M Isabel; Schroeder, Charles E et al. (2013) The cruciform model of striate generation of the early VEP, re-illustrated, not revoked: a reply to Ales et al. (2013). Neuroimage 82:154-9 |
| Vanegas, M Isabel; Blangero, Annabelle; Kelly, Simon P (2013) Exploiting individual primary visual cortex geometry to boost steady state visual evoked potentials. J Neural Eng 10:036003 |
