Functional organization of temporal frequency selectivity in primate visual cortex

Visual temporal frequency preference shows a distinct cortical architecture using fMRI

Studies of visual temporal frequency preference typically examine frequencies under 20 Hz and measure local activity to evaluate the sensitivity of different cortical areas to variations in temporal frequencies. Most of these studies have not attempted to map preferred temporal frequency within and across visual areas, nor have they explored in detail, stimuli at gamma frequency, which recent research suggests may have potential clinical utility. In this study, we address this gap by using functional magnetic resonance imaging (fMRI) to measure response to flickering visual stimuli varying in frequency from 1 to 40 Hz. We apply stimulation in both a block design to examine task response and a steady-state design to examine functional connectivity. We observed distinct activation patterns between 1 Hz and 40 Hz stimuli. We also found that the correlation between medial thalamus and visual cortex was modulated by the temporal frequency. The modulation functions and tuned frequencies are different for the visual activity and thalamo-visual correlations. Using both fMRI activity and connectivity measurements, we show evidence for a temporal frequency specific organization across the human visual system.

Pinwheel-dipole configuration in cat early visual cortex

In the early visual cortex, information is processed within functional maps whose layouts are thought to underlie visual perception. However, the precise organization of these functional maps as well as their interrelationships remain unsettled. Here, we show that spatial frequency representation in cat early visual cortex exhibits singularities around which the map organizes like an electric dipole potential. These singularities are precisely co-located with singularities of the orientation map: the pinwheel centers. To show this, we used high resolution intrinsic optical imaging in cat areas 17 and 18. First, we show that a majority of pinwheel centers exhibit in their neighborhood both semi-global maximum and minimum in the spatial frequency map (i.e. extreme values of the spatial frequency in a hypercolumn). This contradicts pioneering studies suggesting that pinwheel centers are placed at the locus of a single spatial frequency extremum. Based on an analogy with electromagnetism, we proposed a mathematical model for a dipolar structure, accurately fitting optical imaging data. We conclude that a majority of orientation pinwheel centers form spatial frequency dipoles in cat early visual cortex. Given the functional specificities of neurons at singularities in the visual cortex, it is argued that the dipolar organization of spatial frequency around pinwheel centers could be fundamental for visual processing.

Morphological and neurochemical comparisons between pulvinar and V1 projections to V2

The flow of visual information is clear at the earliest stages: the retina provides the driving (main signature) activity for the lateral geniculate nucleus (LGN), which in turn drives the primary visual cortex (V1). These driving pathways can be distinguished anatomically from other modulatory pathways that innervate LGN and V1. The path of visual information after V1, however, is less clear. There are two primary feedforward projections to the secondary visual cortex (V2), one from the lateral/inferior pulvinar and the other from V1. Because both lateral/inferior pulvinar and V2 cannot be driven visually following V1 removal, either or both of these inputs to V2 could be drivers. Retinogeniculate and geniculocortical projections are privileged over modulatory projections by their layer of termination, their bouton size, and the presence of vesicular glutamate transporter 2 (Vglut2) or parvalbumin (PV). It has been suggested that such properties might also distinguish drivers from modulators in extrastriate cortex. We tested this hypothesis by comparing lateral pulvinar to V2 and V1 to V2 projections with LGN to V1 projections. We found that V1 and lateral pulvinar projections to V2 are similar in that they target the same layers and lack PV. Projections from pulvinar to V2, however, bear a greater similarity to projections from LGN to V1 because of their larger boutons (measured at the same location in V2) and positive staining for Vglut2. These data lend support to the hypothesis that the pulvinar could act as a driver for V2.

Distinct functional organizations for processing different motion signals in V1, V2, and V4 of macaque

Motion perception is qualitatively invariant across different objects and forms, namely, the same motion information can be conveyed by many different physical carriers, and it requires the processing of motion signals consisting of direction, speed, and axis or trajectory of motion defined by a moving object. Compared with the representation of orientation, the cortical processing of these different motion signals within the early ventral visual pathway of the primate remains poorly understood. Using drifting full-field noise stimuli and intrinsic optical imaging, along with cytochrome-oxidase staining, we found that the orientation domains in macaque V1, V2, and V4 that processed orientation signals also served to process motion signals associated with the axis and speed of motion. In contrast, direction domains within the thick stripes of V2 demonstrated preferences that were independent of motion speed. The population responses encoding the orientation and motion axis could be precisely reproduced by a spatiotemporal energy model. Thus, our observation of orientation domains with dual functions in V1, V2, and V4 directly support the notion that the linear representation of the temporal series of retinotopic activations may serve as another motion processing strategy in primate ventral visual pathway, contributing directly to fine form and motion analysis. Our findings further reveal that different types of motion information are differentially processed in parallel and segregated compartments within primate early visual cortices, before these motion features are fully combined in high-tier visual areas.

BOLD responses to different temporal frequency stimuli in the lateral geniculate nucleus and visual cortex: insights into the neural basis of fMRI

The neural basis of the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) remains largely unknown after decades of research. To investigate this issue, the unique property of the temporal frequency tuning that could separate neural input and output in the primary visual cortex was used as a model. During moving grating stimuli of 1, 2, 10 and 20Hz temporal frequencies, we measured 9.4-T BOLD fMRI responses simultaneously in the primary visual cortex of area 17 (A17) and area 18 (A18), and the lateral geniculate nucleus (LGN) of isoflurane-anesthetized cat. Our results showed that preferred temporal frequencies of the BOLD responses for A17, A18 and LGN were 3.1Hz, 4.5Hz and 6.0Hz, respectively, which were comparable to the previously reported electrophysiological data. Additionally, the difference of BOLD response onset time between LGN and A17 was 0.5s, which is 18 times larger than the difference of neural activity onset time between these areas. We then compared the frequency-dependent BOLD fMRI response of A17 with tissue partial pressure of oxygen (pO(2)) and electrophysiological data of the same animal model reported by Viswanathan and Freeman (Nature Neuroscience, 2007). The BOLD tuning curve resembled the low frequency band (<12Hz) of local field potential (LFP) tuning curve rather than spiking activity, gamma band (25-90Hz) of LFP, and tissue pO(2) tuning curves, suggesting that the BOLD fMRI signal relates closer to low frequency LFP.

Neural computation of visual imaging based on Kronecker product in the primary visual cortex

BACKGROUND

What kind of neural computation is actually performed by the primary visual cortex and how is this represented mathematically at the system level? It is an important problem in the visual information processing, but has not been well answered. In this paper, according to our understanding of retinal organization and parallel multi-channel topographical mapping between retina and primary visual cortex V1, we divide an image into orthogonal and orderly array of image primitives (or patches), in which each patch will evoke activities of simple cells in V1. From viewpoint of information processing, this activated process, essentially, involves optimal detection and optimal matching of receptive fields of simple cells with features contained in image patches. For the reconstruction of the visual image in the visual cortex V1 based on the principle of minimum mean squares error, it is natural to use the inner product expression in neural computation, which then is transformed into matrix form.

RESULTS

The inner product is carried out by using Kronecker product between patches and function architecture (or functional column) in localized and oriented neural computing. Compared with Fourier Transform, the mathematical description of Kronecker product is simple and intuitive, so is the algorithm more suitable for neural computation of visual cortex V1. Results of computer simulation based on two-dimensional Gabor pyramid wavelets show that the theoretical analysis and the proposed model are reasonable.

CONCLUSIONS

Our results are: 1. The neural computation of the retinal image in cortex V1 can be expressed to Kronecker product operation and its matrix form, this algorithm is implemented by the inner operation between retinal image primitives and primary visual cortex's column. It has simple, efficient and robust features, which is, therefore, such a neural algorithm, which can be completed by biological vision. 2. It is more suitable that the function of cortical column in cortex V1 is considered as the basic unit of visual image processing (such unit can implement basic multiplication of visual primitives, such as contour, line, and edge), rather than a set of tiled array filter. Fourier Transformation is replaced with Kronecker product, which greatly reduces the computational complexity. The neurobiological basis of this idea is that a visual image can be represented as a linear combination of orderly orthogonal primitive image containing some local feature. In the visual pathway, the image patches are topographically mapped onto cortex V1 through parallel multi-channels and then are processed independently by functional columns. Clearly, the above new perspective has some reference significance to exploring the neural mechanisms on the human visual information processing.

Quantification of optical images of cortical responses for inferring functional maps

Optical imaging of cortical signals enables the mapping of functional organization across large patches of cortex with good spatial resolution. But techniques for the quantitative analysis and interpretation of these images are limited. Frequently the functional architecture of the cortex is inferred from the visible topography of cortical reflectance images averaged or differenced across stimulus conditions and scaled or color-coded for presentation. Such qualitative assessments have sometimes led to divergent conclusions particularly about the organization of spatial and temporal frequency preferences in the primary visual cortex. We applied quantitative methods derived from signal detection theory to objectively interpret optical images. The differential response to any two arbitrary stimuli was represented at each pixel as the probability of discriminating between the two stimuli given the reflectance values at that pixel. These probability maps reduced false alarms and provided better signal-to-noise ratio in fewer trials than difference maps. We applied these methods to optical images of primate primary visual area (V1) obtained in response to sinusoidal gratings of different orientations and spatiotemporal frequencies. Clustering by orientation preference was stronger than that for spatial frequency, whereas clustering by temporal frequency preference was the weakest, largely in agreement with a previous electrophysiological study that quantified the degree of clustering of neurons for various response properties using uniform, quantitative criterion. We suggest that probability maps can extend the applicability of optical imaging to investigations of finer aspects of cortical functional organization through better signal-to-noise ratio and uniform, quantitative criteria for interpretation.