The representation of complex images in spatial frequency domains of primary visual cortex

Unification of free energy minimization, spatiotemporal energy, and dimension reduction models of V1 organization: Postnatal learning on an antenatal scaffold

Developmental selection of neurons and synapses so as to maximize pulse synchrony has recently been used to explain antenatal cortical development. Consequences of the same selection process—an application of the Free Energy Principle—are here followed into the postnatal phase in V1, and the implications for cognitive function are considered. Structured inputs transformed via lag relay in superficial patch connections lead to the generation of circumferential synaptic connectivity superimposed upon the antenatal, radial, “like-to-like” connectivity surrounding each singularity. The spatiotemporal energy and dimension reduction models of cortical feature preferences are accounted for and unified within the expanded model, and relationships of orientation preference (OP), space frequency preference (SFP), and temporal frequency preference (TFP) are resolved. The emergent anatomy provides a basis for “active inference” that includes interpolative modification of synapses so as to anticipate future inputs, as well as learn directly from present stimuli. Neurodynamic properties are those of heteroclinic networks with coupled spatial eigenmodes.

A model integrating multiple processes of synchronization and coherence for information instantiation within a cortical area

What is the form of dynamic, e.g., sensory, information in the mammalian cortex? Information in the cortex is modeled as a coherence map of a mixed chimera state of synchronous, phasic, and disordered minicolumns. The theoretical model is built on neurophysiological evidence. Complex spatiotemporal information is instantiated through a system of interacting biological processes that generate a synchronized cortical area, a coherent aperture. Minicolumn elements are grouped in macrocolumns in an array analogous to a phased-array radar, modeled as an aperture, a "hole through which radiant energy flows." Coherence maps in a cortical area transform inputs from multiple sources into outputs to multiple targets, while reducing complexity and entropy. Coherent apertures can assume extremely large numbers of different information states as coherence maps, which can be communicated among apertures with corresponding very large bandwidths. The coherent aperture model incorporates considerable reported research, integrating five conceptually and mathematically independent processes: 1) a damped Kuramoto network model, 2) a pumped area field potential, 3) the gating of nearly coincident spikes, 4) the coherence of activity across cortical lamina, and 5) complex information formed through functions in macrocolumns. Biological processes and their interactions are described in equations and a functional circuit such that the mathematical pieces can be assembled the same way the neurophysiological ones are. The model can be conceptually convolved over the specifics of local cortical areas within and across species. A coherent aperture becomes a node in a graph of cortical areas with a corresponding distribution of information.

BOLD neurovascular coupling does not change significantly with normal aging

Studies of cognitive function that compare the blood oxygenation level dependent (BOLD) signal across age groups often require the assumption that neurovascular coupling does not change with age. Tests of this assumption have produced mixed results regarding the strength of the coupling and its relative time course. Using deconvolution, we found that age does not have a significant effect on the time course of the hemodynamic impulse response function or on the slope of the BOLD versus stimulus duration relationship. These results suggest that in cognitive studies of healthy aging, group differences in BOLD activation are likely due to age-related changes in cognitive-neural interactions and information processing rather than to impairments in neurovascular coupling. Hum Brain Mapp 38:3538-3551, 2017. © 2017 Wiley Periodicals, Inc.

Organization and origin of spatial frequency maps in cat visual cortex

It remains controversial whether and how spatial frequency (SF) is represented tangentially in cat visual cortex. Several models were proposed, but there is no consensus. Worse still, some data indicate that the SF organization previously revealed by optical imaging techniques simply reflects non-stimulus-specific responses. Instead, stimulus-specific responses arise from the homogeneous distribution of geniculo-cortical afferents representing X and Y pathways. To clarify this, we developed a new imaging method allowing rapid stimulation with a wide range of SFs covering more than 6 octaves with only 0.2 octave resolution. A benefit of this method is to avoid error of high-pass filtering methods which systematically under-represent dominant selectivity features near pinwheel centers. We show unequivocally that SF is organized into maps in cat area 17 (A17) and area 18 (A18). The SF organization in each area displays a global anteroposterior SF gradient and local patches. Its layout is constrained to that of the orientation map, and it is suggested that both maps share a common functional architecture. A17 and A18 are bound at the transition zone by another SF gradient involving the geniculo-cortical and the callosal pathways. A model based on principal component analysis shows that SF maps integrate three different SF-dependent channels. Two of these reflect the segregated excitatory input from X and Y geniculate cells to A17 and A18. The third one conveys a specific combination of excitatory and suppressive inputs to the visual cortex. In a manner coherent with anatomical and electrophysiological data, it is interpreted as originating from a subtype of Y geniculate cells.

Quantitative inference of population response properties across eccentricity from motion-induced maps in macaque V1

Interpreting population responses in the primary visual cortex (V1) remains a challenge especially with the advent of techniques measuring activations of large cortical areas simultaneously with high precision. For successful interpretation, a quantitatively precise model prediction is of great importance. In this study, we investigate how accurate a spatiotemporal filter (STF) model predicts average response profiles to coherently drifting random dot motion obtained by optical imaging of intrinsic signals in V1 of anesthetized macaques. We establish that orientation difference maps, obtained by subtracting orthogonal axis-of-motion, invert with increasing drift speeds, consistent with the motion streak effect. Consistent with perception, the speed at which the map inverts (the critical speed) depends on cortical eccentricity and systematically increases from foveal to parafoveal. We report that critical speeds and response maps to drifting motion are excellently reproduced by the STF model. Our study thus suggests that the STF model is quantitatively accurate enough to be used as a first model of choice for interpreting responses obtained with intrinsic imaging methods in V1. We show further that this good quantitative correspondence opens the possibility to infer otherwise not easily accessible population receptive field properties from responses to complex stimuli, such as drifting random dot motions.

Subcortical representation of non-Fourier image features

A fundamental goal of visual neuroscience is to identify the neural pathways representing different image features. It is widely argued that the early stages of these pathways represent linear features of the visual scene and that the nonlinearities necessary to represent complex visual patterns are introduced later in cortex. We tested this by comparing the responses of subcortical and cortical neurons to interference patterns constructed by summing sinusoidal gratings. Although a linear mechanism can detect the component gratings, a nonlinear mechanism is required to detect an interference pattern resulting from their sum. Consistent with in vitro retinal ganglion cell recordings, we found that interference patterns are represented subcortically by cat LGN Y-cells, but not X-cells. Linear and nonlinear tuning properties of LGN Y-cells were then characterized and compared quantitatively with those of cortical area 18 neurons responsive to interference patterns. This comparison revealed a high degree of similarity between the two neural populations, including the following: (1) the representation of similar spatial frequencies in both their linear and nonlinear responses, (2) comparable orientation selectivity for the high spatial frequency carrier of interference patterns, and (3) the same difference in their temporal frequency selectivity for drifting gratings versus the envelope of interference patterns. The present findings demonstrate that the nonlinear subcortical Y-cell pathway represents complex visual patterns and likely underlies cortical responses to interference patterns. We suggest that linear and nonlinear mechanisms important for encoding visual scenes emerge in parallel through distinct pathways originating at the retina.

Whither the hypercolumn?

Among the crowning achievements of Hubel and Wiesel's highly influential studies on primary visual cortex is the description of the cortical hypercolumn, a set of cortical columns with functional properties spanning a particular parameter space. This fundamental concept laid the groundwork for the notion of a modular sensory cortex, canonical cortical circuits and an understanding of visual field coverage beyond simple retinotopy. Surprisingly, the search for and description of analogous hypercolumnar organizations in other cortical areas to date has been limited. In the present work, we have applied the hypercolumn concept to the functional organization of the second visual area, V2. We found it important to separate out the original definition of the hypercolumn from other associated observations and concepts, not all of which are applicable to V2. We present results indicating that, as in V1, the V2 hypercolumns for orientation and binocular interaction (disparity) run roughly orthogonal to each other. We quantified the 'nearest neighbour' periodicities for the hypercolumns for ocular dominance, orientation, colour and disparity, and found a marked similarity in the periodicities of all of these hypercolumns, both across hypercolumn type and across visual areas V1 and V2. The results support an underlying common mechanism that constrains the anatomical extent of hypercolumn systems, and highlight the original definition of the cortical hypercolumn.

The organization of spatial frequency maps measured by cortical flavoprotein autofluorescence

To determine the organization of spatial frequency (SF) preference within cat Area 17, we imaged responses to stimuli with different SFs using optical intrinsic signals (ISI) and flavoprotein autofluorescence (AFI). Previous studies have suggested that neurons cluster based on SF preference, but a recent report argued that SF maps measured with ISI were artifacts of the vascular bed. Because AFI derives from a non-hemodynamic signal, it is less contaminated by vasculature. The two independent imaging methods produced similar SF preference maps in the same animals, suggesting that the patchy organization of SF preference is a genuine feature of Area 17.

Models and Measurements of Functional Maps in V1

The organization of primary visual cortex has been heavily studied for nearly 50 years, and in the last 20 years functional imaging has provided high-resolution maps of its tangential organization. Recently, however, the usefulness of maps like those of orientation and spatial frequency (SF) preference has been called into question because they do not, by themselves, predict how moving images are represented in V1. In this review, we discuss a model for cortical responses (the spatiotemporal filtering model) that specifies the types of cortical maps needed to predict distributed activity within V1. We then review the structure and interrelationships of several of these maps, including those of orientation, SF, and temporal frequency preference. Finally, we discuss tests of the model and the sufficiency of the requisite maps in predicting distributed cortical responses. Although the spatiotemporal filtering model does not account for all responses within V1, it does, with reasonable accuracy, predict population responses to a variety of complex stimuli.