Strong Orientation Selectivity Research Articles

Bridging the Functional and Wiring Properties of V1 Neurons Through Sparse Coding.

The functional properties of neurons in the primary visual cortex (V1) are thought to be closely related to the structural properties of this network, but the specific relationships remain unclear. Previous theoretical studies have suggested that sparse coding, an energy-efficient coding method, might underlie the orientation selectivity of V1 neurons. We thus aimed to delineate how the neurons are wired to produce this feature. We constructed a model and endowed it with a simple Hebbian learning rule to encode images of natural scenes. The excitatory neurons fired sparsely in response to images and developed strong orientation selectivity. After learning, the connectivity between excitatory neuron pairs, inhibitory neuron pairs, and excitatory-inhibitory neuron pairs depended on firing pattern and receptive field similarity between the neurons. The receptive fields (RFs) of excitatory neurons and inhibitory neurons were well predicted by the RFs of presynaptic excitatory neurons and inhibitory neurons, respectively. The excitatory neurons formed a small-world network, in which certain local connection patterns were significantly overrepresented. Bidirectionally manipulating the firing rates of inhibitory neurons caused linear transformations of the firing rates of excitatory neurons, and vice versa. These wiring properties and modulatory effects were congruent with a wide variety of data measured in V1, suggesting that the sparse coding principle might underlie both the functional and wiring properties of V1 neurons.

Nonblind Image Deblurring via Deep Learning in Complex Field.

Nonblind image deblurring is about recovering the latent clear image from a blurry one generated by a known blur kernel, which is an often-seen yet challenging inverse problem in imaging. Its key is how to robustly suppress noise magnification during the inversion process. Recent approaches made a breakthrough by exploiting convolutional neural network (CNN)-based denoising priors in the image domain or the gradient domain, which allows using a CNN for noise suppression. The performance of these approaches is highly dependent on the effectiveness of the denoising CNN in removing magnified noise whose distribution is unknown and varies at different iterations of the deblurring process for different images. In this article, we introduce a CNN-based image prior defined in the Gabor domain. The prior not only utilizes the optimal space-frequency resolution and strong orientation selectivity of the Gabor transform but also enables using complex-valued (CV) representations in intermediate processing for better denoising. A CV CNN is developed to exploit the benefits of the CV representations, with better generalization to handle unknown noises over the real-valued ones. Combining our Gabor-domain CV CNN-based prior with an unrolling scheme, we propose a deep-learning-based approach to nonblind image deblurring. Extensive experiments have demonstrated the superior performance of the proposed approach over the state-of-the-art ones.

Light-Induced Triplet-Triplet Electron Resonance Spectroscopy.

We present a new technique, light-induced triplet–triplet electron resonance spectroscopy (LITTER), which measures the dipolar interaction between two photoexcited triplet states, enabling both the distance and angular distributions between the two triplet moieties to be determined on a nanometer scale. This is demonstrated for a model bis-porphyrin peptide that renders dipolar traces with strong orientation selection effects. Using simulations and density functional theory calculations, we extract distance distributions and relative orientations of the porphyrin moieties, allowing the dominant conformation of the peptide in a frozen solution to be identified. LITTER removes the requirement of current light-induced electron spin resonance pulse dipolar spectroscopy techniques to have a permanent paramagnetic moiety, becoming more suitable for in-cell applications and facilitating access to distance determination in unmodified macromolecular systems containing photoexcitable moieties. LITTER also has the potential to enable direct comparison with Förster resonance energy transfer and combination with microscopy inside cells.

Digital Gabor filters with MRA structure

Digital Gabor filters are indispensable tools of local time-frequency analysis in signal processing. With strong orientation selectivity, discrete (tight) Gabor frames generated by two-dimensional ...

Digital Gabor filters do generate MRA-based wavelet tight frames

Gabor frames, especially digital Gabor filters, have long been known as indispensable tools for local time–frequency analysis of discrete signals. With strong orientation selectivity, tensor products discrete (tight) Gabor frames also see their applications in image analysis and restoration. However, the lack of multi-scale structures existing in MRA-based wavelet (tight) frames makes discrete Gabor frames less effective on modeling local structures of signals with varying sizes. Indeed, historically speaking, it was the motivation of studying wavelet systems. By applying the unitary extension principle on some most often seen digital Gabor filters (e.g. local discrete Fourier transform and discrete Cosine transform), we are surprised to find out that these digital filter banks generate MRA-based wavelet tight frames in square integrable function space, and the corresponding refinable functions and wavelets can be explicitly given. In other words, the discrete tight frames associated with these digital Gabor filters can be used as the filter banks of MRA wavelet tight frames, which introduce both multi-scale structures and fast cascade implementation of discrete signal decomposition/reconstruction. Discrete tight frames generated by such filters with both wavelet and Gabor structures can see their potential applications in image processing and recovery.

Orientation selectivity in the visual cortex of the nine-banded armadillo.

Orientation selectivity in primary visual cortex (V1) has been proposed to reflect a canonical computation performed by the neocortical circuitry. Although orientation selectivity has been reported in all mammals examined to date, the degree of selectivity and the functional organization of selectivity vary across mammalian clades. The differences in degree of orientation selectivity are large, from reports in marsupials that only a small subset of neurons are selective to studies in carnivores, in which it is rare to find a neuron lacking selectivity. Furthermore, the functional organization in cortex varies in that the primate and carnivore V1 is characterized by an organization in which nearby neurons share orientation preference while other mammals such as rodents and lagomorphs either lack or have only extremely weak clustering. To gain insight into the evolutionary emergence of orientation selectivity, we examined the nine-banded armadillo, a species within the early placental clade Xenarthra. Here we use a combination of neuroimaging, histological, and electrophysiological methods to identify the retinofugal pathways, locate V1, and for the first time examine the functional properties of V1 neurons in the armadillo (Dasypus novemcinctus) V1. Individual neurons were strongly sensitive to the orientation and often the direction of drifting gratings. We uncovered a wide range of orientation preferences but found a bias for horizontal gratings. The presence of strong orientation selectivity in armadillos suggests that the circuitry responsible for this computation is common to all placental mammals.NEW & NOTEWORTHY The current study shows that armadillo primary visual cortex (V1) neurons share the signature properties of V1 neurons of primates, carnivorans, and rodents. Furthermore, these neurons exhibit a degree of selectivity for stimulus orientation and motion direction similar to that found in primate V1. Our findings in armadillo visual cortex suggest that the functional properties of V1 neurons emerged early in the mammalian lineage, near the time of the divergence of marsupials.

Weak orientation and direction selectivity in lateral geniculate nucleus representing central vision in the gray squirrel Sciurus carolinensis.

Classic studies of lateral geniculate nucleus (LGN) and visual cortex (V1) in carnivores and primates have found that a majority of neurons in LGN exhibit a center-surround organization, while V1 neurons exhibit strong orientation selectivity and, in many species, direction selectivity. Recent work in the mouse and the monkey has discovered previously unknown classes of orientation- and direction-selective neurons in LGN. Furthermore, some recent studies in the mouse report that many LGN cells exhibit pronounced orientation biases that are of comparable strength to the subthreshold inputs to V1 neurons. These results raise the possibility that, in rodents, orientation biases of individual LGN cells make a substantial contribution to cortical orientation selectivity. Alternatively, the size and contribution of orientation- or direction-selective channels from LGN to V1 may vary across mammals. To address this question, we examined orientation and direction selectivity in LGN and V1 neurons of a highly visual diurnal rodent: the gray squirrel. In the representation of central vision, only a few LGN neurons exhibited strong orientation or direction selectivity. Across the population, LGN neurons showed weak orientation biases and were much less selective for orientation compared with V1 neurons. Although direction selectivity was weak overall, LGN layers 3abc, which contain neurons that express calbindin, exhibited elevated direction selectivity index values compared with LGN layers 1 and 2. These results suggest that, for central visual fields, the contribution of orientation- and direction-selective channels from the LGN to V1 is small in the squirrel. As in other mammals, this small contribution is elevated in the calbindin-positive layers of the LGN.

Orientation selective DEER measurements on vinculin tail at X-band frequencies reveal spin label orientations

Double electron electron resonance (DEER) spectroscopy has been established as a valuable method to determine distances between spin labels bound to protein molecules. Caused by selective excitation of molecular orientations DEER primary data also depend on the mutual orientation of the spin labels. For a doubly spin labeled variant of the cytoskeletal protein vinculin tail strong orientation selection can be observed already at X-band frequencies, which allows us to reduce the problem to the relative orientation of two molecular axes and the spin–spin axis parameterized by three angles. A full grid search of parameter space reveals that the DEER experiment introduces parameter-space symmetry higher than the symmetry of the spin Hamiltonian. Thus, the number of equivalent parameter sets is twice as large as expected and the relative orientation of the two spin labels is ambiguous. Except for this inherent ambiguity the most probable relative orientation of the two spin labels can be determined with good confidence and moderate uncertainty by global fitting of a set of five DEER experiments at different offsets between pump and observer frequency. The experiment provides restraints on the angles between the z axis of the nitroxide molecular frame and the spin–spin vector and on the dihedral between the two z axes. When using the same type of label at both sites, assignment of the angle restraints is ambiguous and the sign of the dihedral restraint is also ambiguous.

Development of cortical orientation selectivity in the absence of visual experience with contour

Visual cortical neurons are selective for the orientation of lines, and the full development of this selectivity requires natural visual experience after eye opening. Here we examined whether this selectivity develops without seeing lines and contours. Juvenile ferrets were reared in a dark room and visually trained by being shown a movie of flickering, sparse spots. We found that despite the lack of contour visual experience, the cortical neurons of these ferrets developed strong orientation selectivity and exhibited simple-cell receptive fields. This finding suggests that overt contour visual experience is unnecessary for the maturation of orientation selectivity and is inconsistent with the computational models that crucially require the visual inputs of lines and contours for the development of orientation selectivity. We propose that a correlation-based model supplemented with a constraint on synaptic strength dynamics is able to account for our experimental result.

Nanometer-Scale Distance Measurements in Proteins Using Gd3+ Spin Labeling

Methods for measuring nanometer-scale distances between specific sites in proteins are essential for analysis of their structure and function. In this work we introduce Gd(3+) spin labeling for nanometer-range distance measurements in proteins by high-field pulse electron paramagnetic resonance (EPR). To evaluate the performance of such measurements, we carried out four-pulse double-electron electron resonance (DEER) measurements on two proteins, p75ICD and tau(C)14, labeled at strategically selected sites with either two nitroxides or two Gd(3+) spin labels. In analogy to conventional site-directed spin labeling using nitroxides, Gd(3+) tags that are derivatives of dipicolinic acid were covalently attached to cysteine thiol groups. Measurements were carried out on X-band (approximately 9.5 GHz, 0.35 T) and W-band (95 GHz, 3.5 T) spectrometers for the nitroxide-labeled proteins and at W-band for the Gd(3+)-labeled proteins. In the protein p75ICD, the orientations of the two nitroxides were found to be practically uncorrelated, and therefore the distance distribution could as readily be obtained at W-band as at X-band. The measured Gd(3+)-Gd(3+) distance distribution had a maximum at 2.9 nm, as compared to 2.5 nm for the nitroxides. In the protein tau(C)14, however, the orientations of the nitroxides were correlated, and the W-band measurements exhibited strong orientation selection that prevented a straightforward extraction of the distance distribution. The X-band measurements gave a nitroxide-nitroxide distance distribution with a maximum at 2.5 nm, and the W-band measurements gave a Gd(3+)-Gd(3+) distance distribution with a maximum at 3.4 nm. The Gd(3+)-Gd(3+) distance distributions obtained are in good agreement with expectations from structural models that take into account the flexibility of the tags and their tethers to the cysteine residues. These results show that Gd(3+) labeling is a viable technique for distance measurements at high fields that features an order of magnitude sensitivity improvement, in terms of protein quantity, over X-band pulse EPR measurements using nitroxide spin labels. Its advantage over W-band distance measurements using nitroxides stems from an intrinsic absence of orientation selection.

The time course of contrast masking reveals two distinct mechanisms of human surround suppression

When a target in the periphery is surrounded by a matching mask, contrast sensitivity is suppressed, producing elevated thresholds. We explored the time course of this suppression and found clear evidence for two distinct mechanisms: one strong, transient, and monocular, the other weaker, sustained, and dichoptic. We measured thresholds for a 1.3 cpd Gabor target at 8 deg eccentricity surrounded by a large annulus of matching spatial frequency and orientation. We found that surround suppression is very strong (threshold elevated by up to 600%), but that it decreases by about three-fold when stimuli last longer than ∼100 msec. The strong transient component occurs almost instantaneously (< 1 frame delay, 12 msec) irrespective of the separation between target and surround. The transient suppression differs from the sustained suppression in two remarkable ways. First, it does not transfer dichoptically. Second, it occurs even when the surround is of much lower contrast than the target. Both suppression components are tightly tuned to orientation, peaking at target orientation, but not tuned to spatial phase. These results indicate that there are two distinct kinds of surround suppression in human vision. The properties of the weaker sustained mechanism suggest a cortical origin. The neural substrate of the strong transient suppression is much less evident: the absence of dichoptic transfer suggests a subcortical origin, yet the strong orientation selectivity indicates cortex.

The time course of contrast masking reveals two distinct mechanisms of human surround suppression

We explored the time course of surround suppression and found clear evidence for two distinct mechanisms: one strong, transient, and largely monocular, the other weaker, sustained, and binocular. We measured detection thresholds for a Gabor target at 8 deg eccentricity surrounded by a large annulus of matching spatial frequency and orientation. At short stimulus durations surround suppression was very strong, but the suppression strength decreased precipitously for durations longer than approximately 100 msec. The strong transient component did not transfer between the eyes and occurred almost instantaneously (<1 frame delay, 12 msec) irrespective of the separation between target and surround. Both suppression components were tightly tuned to orientation, peaking at target orientation, but neither was tuned to target spatial phase. These results are in good agreement with surround suppression properties measured in macaque V1 neurons. The absence of interocular transfer, the strong orientation selectivity, and the high propagation speed incommensurate with slow horizontal connections in V1 suggest that the transient component of suppression originates between input layers and the subsequent layers in V1.

Neuronal responsiveness in areas 19 and 21a, and the posteromedial lateral suprasylvian cortex of the cat.

Responsiveness to slits and pattern stimuli was quantified in a total of 68 cells sampled in the posterior extreme of the lateral suprasylvian (PS) cortex as response indices. The cells were studied in relationship to their locations in several subareas of the PS cortex, including areas 19 (n = 15) and 21a (n = 32) and the posteromedial lateral suprasylvian cortex (PMLS; n = 21). These subareas were identified based on retrograde labelling from area 17 and also supplemented with photic responsiveness. This analysis revealed that each cortical area contains cells expressing different combinations of stimulus features. Area 19 contained two major groups of cells: (1) those with strong end-stop selectivity combined with moderate orientation or direction selectivity, and (2) those with weak end-stop selectivity combined with strong orientation selectivity. The groups of cells with strong or moderate orientation selectivity showed a strong preference for stripe over visual noise patterns and relatively large modulatory responses to motion of individual stripes. The PMLS contained one major group of cells with strong end-stop and direction selectivities and with poor orientation selectivity. They also showed stronger preference for visual noise than cells in the other cortical areas and rather weak modulatory responses. Area 21a contained only one group of cells with strong orientation selectivity and length summation property rather than end-stop selectivity, and they also lacked direction selectivity. These cells exhibited a strong preference for stripe patterns and moderate or weak modulatory responses. Altogether, these findings indicate that each cortical area is specialized in expressing different stimulus features. The two groups of cells in area 19 may encode the position and motion of discontinuous visual elements such as corners and line ends and continuous elements such as lines and edges. PMLS cells may encode the motion of single elements or associated motion of multiple discontinuous elements such as textures and backgrounds. Area 21a cells may specifically encode the orientation of long, continuous elements such as lines and edges. In support of this view, two types of statistical analyses demonstrated that the combinations of the response properties expressed in individual PS cells are highly correlated with their locations in cortical areas and that the anatomical locations of individual PS cells are reliably predicted from the sets of response indices expressed in these cells.

S-band electron spin echo spectroscopy

Abstract