Spatial frequency

Psychedelic compounds act upon the serotonergic pathway to generate altered states of consciousness and disrupt normal sensory processing, creating profound perceptual disturbances including visual hallucinations. While psychedelics have recently garnered much attention for their cognitive and therapeutic effects, how psychedelics disrupt sensory processing to evoke hallucinations is not as well characterized. Furthermore, while initial studies have investigated how psychedelics alter visual responses during head-fixation, nothing is known about how they might alter visual processing during ac

The primary visual cortex (V1) directly projects to the superior colliculus (SC) and is believed to provide sensory drive for eye movements. Consistent with this, a majority of saccade-related SC neurons also exhibit short-latency, stimulus-driven visual responses, which are additionally feature-tuned. However, direct neurophysiological comparisons of the visual response properties of the two anatomically-connected brain areas are surprisingly lacking, especially with respect to active looking behaviors. I will describe a series of experiments characterizing visual response properties in prima

…four parameters: the orientation, the spatial frequency (SF), Bθ and Bsf. We analyzed responses from 411 neurons in area 21a, seeking patterns in orientation precision pro

Behavioural states modulate neural activity in cortical and subcortical sensory areas as early as in the superior colliculus (SC) and the retina. To better understand the purpose of behavioural modulation at these early stages of visual processing, we investigated how locomotion affects various visual tuning properties in distinct functional cell types of the mouse retina and SC. We employed two-photon imaging of calcium activity in retinal axon terminals and neurons of the superficial SC (sSC) while mice were head-fixed and able to run at will on a treadmill. Neural activity was recorded in

…Given that preferred spatial frequency (SF) gradually changes from area 17 towards 18 we suspected CC to reflect the ratio of x- and y- cell driven retinogeniculate-cortical inputs. We thus recorded monocular and binocular responses to diff

An appealing hypothesis states that visual neurons in the brain are sensitive to the statistical properties of natural images. Neurophysiology and fMRI studies have tested neural sensitivity to images altered to exhibit either typical or atypical statistics. A general finding is that visual cortical neurons respond more strongly to images with natural statistics, and that this can vary across the visual hierarchy. Convolutional neural networks (CNNs) have achieved human-level performance in vision tasks and have been used as visual cortex models. However, CNN responses to images with altered s

It is well known that sparse coding models trained on natural images learn basis functions whose shapes resemble the receptive fields (RFs) of simple cells in the primary visual cortex (V1). However, few studies have considered how these basis functions develop during training. In particular, it is unclear whether certain types of basis functions emerge more quickly than others, or whether they develop simultaneously. In this work, we train an overcomplete sparse coding model (Sparsenet) on natural images and find that there is indeed order in the development of its basis functions, with lower

…of anesthetized animals can process spatial information in a CtF fashion, shifting their spatial frequency (SF) preference from low (coarse) to high (fine) throughout their response to static grating stimuli. However, many central questions regarding CtF processing, such as whether it occurs in awake behaving mice and potential computational advantages it may provide, remain unexplored. Here

…affect the cells’ sensitivity to the spatial structure of natural scenes. Fitting subunit models to neural responses remains a challenge, as av

Previous work looking at individual differences in face identity processing (FIP) has found that most commonly used lab-based performance assessments are unfortunately not sufficiently sensitive on their own for measuring performance in both the upper and lower tails of the general population simultaneously. So more recently, researchers have begun incorporating multiple testing procedures into their assessments. Still, though, the growing consensus seems to be that at the individual level, there is quite a bit of variability between test scores. The overall consequence of this is that extreme