Neuronal nonlinearity explains greater visual spatial resolution for darks than lights

Astronomers and physicists noticed centuries ago that visual spatial resolution is higher for dark than light stimuli, but the neuronal mechanisms for this perceptual asymmetry remain unknown. Here we demonstrate that the asymmetry is caused by a neuronal nonlinearity in the early visual pathway. We show that neurons driven by darks (OFF neurons) increase their responses roughly linearly with luminance decrements, independent of the background luminance. However, neurons driven by lights (ON neurons) saturate their responses with small increases in luminance and need bright backgrounds to approach the linearity of OFF neurons. We show that, as a consequence of this difference in linearity, receptive fields are larger in ON than OFF thalamic neurons, and cortical neurons are more strongly driven by darks than lights at low spatial frequencies. This ON/OFF asymmetry in linearity could be demonstrated in the visual cortex of cats, monkeys, and humans and in the cat visual thalamus. Furthermore, in the cat visual thalamus, we show that the neuronal nonlinearity is present at the ON receptive field center of ON-center neurons and ON receptive field surround of OFF-center neurons, suggesting an origin at the level of the photoreceptor. These results demonstrate a fundamental difference in visual processing between ON and OFF channels and reveal a competitive advantage for OFF neurons over ON neurons at low spatial frequencies, which could be important during cortical development when retinal images are blurred by immature optics in infant eyes.Light and dark stimuli are separately processed by ON and OFF channels in the retina and visual thalamus. Surprisingly, although most textbooks assume that ON and OFF visual responses are balanced throughout the visual system, recent studies have identified a pronounced overrepresentation of the OFF visual responses in primary visual cortex (area V1) (1–3). This recent discovery resonates with pioneering studies by Galilei (4) and von Helmholtz (5) who noticed that visual spatial resolution was higher for dark than light stimuli. Galilei (4) related the difference in resolution to the observation that a light patch on a dark background appears larger than the same sized dark patch on a light background, an illusion that von Helmholtz (5) named the “irradiation illusion.” Although this illusion has been studied in the past (6, 7), its underlying neuronal mechanisms remain unknown. It has been suggested that the perceived size differences could be caused by the light scatter in the optics of the eye followed by a neuronal nonlinearity (6, 7), but there are no neuronal measurements of a nonlinearity that fits the explanation. Previous studies revealed differences in response linearity between ON and OFF retinal ganglion cells (8, 9) and horizontal cells (10). However, a main conclusion from these studies was that ON retinal ganglion cells were roughly linear and less rectified than OFF retinal ganglion cells (8, 9), which is exactly the opposite of what would be needed to explain the irradiation illusion. Moreover, it remains unclear if ON/OFF retinal differences in response linearity and response gain propagate from retina to visual cortex. To investigate the neuronal mechanisms of the irradiation illusion, we recorded neuronal activity in the visual thalamus and cortex of anesthetized cats, local field potentials in awake monkeys, and visually evoked potentials in humans. We show that OFF neurons in thalamus and cortex increase their responses roughly linearly with luminance contrast, independently of the background luminance. In contrast, ON neurons saturate their responses with small increases in luminance, and approach the linearity of the OFF neurons only on bright backgrounds that make ON responses weaker. We also show that a simple model that uses an early retinal nonlinearity can explain several seemingly unrelated ON/OFF spatial asymmetries, including the difference in spatial resolution between darks and lights, the spatial frequency dependence of OFF dominance in visual cortex, and the difference in receptive field size between ON and OFF retinal ganglion cells. Moreover, because the asymmetry between ON and OFF neurons is present both at the receptive field center and surround of thalamic neurons, our results strongly suggest that it originates at the level of photoreceptors.     

An uncommon neuronal class conveys visual signals from rods and cones to retinal ganglion cells

Neurons in the central nervous system (CNS) are distinguished by the neurotransmitter types they release, their synaptic connections, morphology, and genetic profiles. To fully understand how the CNS works, it is critical to identify all neuronal classes and reveal their synaptic connections. The retina has been extensively used to study neuronal development and circuit formation. Here, we describe a previously unidentified interneuron in mammalian retina. This interneuron shares some morphological, physiological, and molecular features with retinal bipolar cells, such as receiving input from photoreceptors and relaying visual signals to retinal ganglion cells. It also shares some features with amacrine cells (ACs), particularly Aii-ACs, such as their neurite morphology in the inner plexiform layer, the expression of some AC-specific markers, and possibly the release of the inhibitory neurotransmitter glycine. Thus, we unveil an uncommon interneuron, which may play an atypical role in vision.

Photons entering the eye are detected by photoreceptors and processed through a set of function-specific synaptic pathways in the retina. The structural basis of these pathways are the synaptic connections among five major classes of retinal neurons: photoreceptors, horizontal cells (HCs), bipolar cells (BCs), amacrine cells (ACs), and retinal ganglion cells (RGCs) (1–3). Two fundamental features of the vertebrate retina’s visual signal processing are the functional separation of scotopic and photopic vision (4–6) and the segregation of increment and decrement luminance signals into ON and OFF pathways (3, 7).The functional separation of scotopic and photopic vision starts at rod and cone photoreceptors and remains separated at BCs through specific synaptic connections from rods to rod BCs and cones to cone BCs (3, 5, 8, 9). The segregation of increment and decrement luminance signals starts at BCs, where glutamate released from cones activates ionotropic glutamate receptors on the OFF cone BCs resulting in depolarization of the cell membrane potential (10). In contrast, glutamate activates a metabotropic glutamate receptor, mGluR6, on the rod BCs and ON cone BCs resulting in hyperpolarization of these cells (11–16). This sign reversing and nonreversing action of glutamate on the ON and OFF BCs separates the increment and decrement luminance signals into ON and OFF pathways, which remain segregated throughout the visual system (8, 17, 18). In the retina, BCs are thought to be the only interneuron to relay visual signals from photoreceptors to RGCs, and they are the primary excitatory driver for RGCs (19–22). All BCs have a dendrite in the outer plexiform layer (OPL) and axons in the inner plexiform layer (IPL), except for a recently identified monopolar interneuron (23). Additionally, it is commonly assumed that all BC types have been identified in the mouse retina (7, 22, 24).Another interneuron class, ACs, does not receive direct synaptic input from photoreceptors but from BCs and other ACs (3, 25–28). In mice, there are roughly 60 different AC types. Most ACs act as inhibitory interneurons by releasing GABA or glycine onto BCs, ACs, and RGCs, except for a few glutamatergic and cholinergic AC types, which are also GABAergic cells (3, 23, 29–36). Additionally, a small fraction of interplexiform ACs release dopamine (37–39) and GABA (40) as their neurotransmitters, possibly onto BCs, HCs, and photoreceptors, to conduct synaptic signals from the inner retina to the outer retina.Identifying each of the retinal cell classes and understanding their synaptic connections is crucial for understanding how the retina processes visual signals. While all the major retinal classes are believed to be defined, we identified a previously undescribed retinal interneuron. This interneuron shares fundamental morphological, physiological, and molecular features with BCs, such as having neurites that ramify in the OPL to receive synaptic inputs from photoreceptors and neurites that project into the IPL to synapse with RGCs. Additionally, this interneuron expresses several common AC markers, and its neurites ramify throughout the entire IPL to synapse with neurons in both ON and OFF IPL. This interneuron may also release the inhibitory neurotransmitter glycine in both the inner and outer retina, in addition to releasing glutamate in the IPL. This atypical retinal interneuron opens the possibility of an anomalous retinal neuron class.     

A theory of direction selectivity for macaque primary visual cortex

This paper offers a theory for the origin of direction selectivity (DS) in the macaque primary visual cortex, V1. DS is essential for the perception of motion and control of pursuit eye movements. In the macaque visual pathway, neurons with DS first appear in V1, in the Simple cell population of the Magnocellular input layer 4Cα. The lateral geniculate nucleus (LGN) cells that project to these cortical neurons, however, are not direction selective. We hypothesize that DS is initiated in feed-forward LGN input, in the summed responses of LGN cells afferent to a cortical cell, and it is achieved through the interplay of 1) different visual response dynamics of ON and OFF LGN cells and 2) the wiring of ON and OFF LGN neurons to cortex. We identify specific temporal differences in the ON/OFF pathways that, together with item 2, produce distinct response time courses in separated subregions; analysis and simulations confirm the efficacy of the mechanisms proposed. To constrain the theory, we present data on Simple cells in layer 4Cα in response to drifting gratings. About half of the cells were found to have high DS, and the DS was broadband in spatial and temporal frequency (SF and TF). The proposed theory includes a complete analysis of how stimulus features such as SF and TF interact with ON/OFF dynamics and LGN-to-cortex wiring to determine the preferred direction and magnitude of DS.

This paper proposes a solution to a longstanding question in visual neuroscience, namely, the origin of direction selectivity (DS) in the visual cortex of macaque monkeys. Motion perception is a vital visual capability well developed in primates. As perceiving motion requires perceiving the direction in which a target moves, DS, the ability of visual neurons to sense the direction of movement, is essential for motion perception (1) and for the control of pursuit eye movements (2). For these reasons, understanding DS is an important first step toward understanding how the cortex processes motion signals.DS in cortical neurons was first documented in the cat (3). Since then, it has been found in neurons all along the visual dorsal stream (an area associated with motion processing) in primates like macaque monkeys (4–7), whose vision is like that of humans. Neurons with DS are, in fact, present across species; they are widespread among visual mammals, an experimental fact that testifies to their biological significance.In the visual pathway of macaques, DS appears first in the primary visual cortex (V1), in the Simple cell population of the input layer 4Cα (8). These neurons provide feed-forward direction-selective signals to subsequent cortical layers and brain regions in the dorsal pathway. Thus, to discover the origin of DS, one is led to examining how neurons in layer 4Cα acquire their DS—and that is where it gets interesting: The neurons that provide visual signals to layer 4Cα, the Magnocellular cells in the lateral geniculate nucleus (LGN), are not direction selective (9–12). Yet many of the cells in the input layer of V1 to which they project are direction selective. A fundamental scientific question, therefore, is how 4Cα neurons acquire their DS. That is the question we would like to answer in this paper.Although many papers have been written on DS since its discovery over half a century ago, and there is continued interest in the subject (13–16), no satisfactory mechanistic explanation for the origin of DS in primate cortex has been proposed before now: Early conceptual models of how DS may arise, such as the Reichardt multiplier (17) or the motion energy model (18), were not concerned with biological mechanisms. Later work proposed neural mechanisms for the motion energy model (19), but they are not sufficient for explaining DS in primate cortex. See Discussion for comparisons of different model mechanisms.It is widely accepted that the DS computation requires spatiotemporal inseparability (STI); that is, different subregions of the receptive field have different time courses of response (18, 20, 21). What were lacking were biological mechanisms that could produce STI, and a clear understanding of how DS depends on the interaction between STI and the spatial and temporal character of the visual stimulus. These are the issues we address in this paper.We hypothesize that a plausible biological mechanism is the interplay between 1) the different dynamics of ON and OFF LGN cells and 2) the specific wiring that connects ON and OFF cells to V1. Item 2 refers here to the well-known fact that OFF and ON LGN cells are wired to segregated V1 receptive field subregions (3, 22, 23). Our main contribution is item 1: We identify, in Results, dynamic differences in the ON/OFF pathways that, together with item 2, produce distinct response time courses in separated receptive-field subregions. The mechanisms we propose are biologically grounded, and, as we show, they are sufficient for initiating DS in the feed-forward LGN input to cortical cells.To constrain our theory, we present experimental results on the responses of macaque 4Cα Simple cells to drifting gratings. Most Simple cells we recorded in 4Cα were unambiguously direction selective, preferring, consistently, the same direction over their entire visible ranges of spatial frequency (SF) and temporal frequency (TF); about half of the cells had high DS. Our data reveal also an important characteristic of neurons with DS, namely, the approximate invariance of DS with SF and TF. Explaining the broadband character of DS (in TF and SF) is a challenge for all previous theories. Our theory includes a complete analysis of how stimulus features like SF and TF interact with ON/OFF dynamics and LGN-to-cortex wiring to explain the broadband character of DS. The theoretical predictions are in good agreement with data.With regard to broader implications, although the theory as described in this paper is specifically about DS, an important message is that, when combining information from multiple channels, slight biases in their temporal filters can greatly enhance the capability of a system. Thus, it may be possible to exploit the temporal axis further in the processing of biological and nonbiological signals, especially in the neural processing of sensory inputs and, possibly, in computer vision.     

Hierarchical timescales in the neocortex: Mathematical mechanism and biological insights

A cardinal feature of the neocortex is the progressive increase of the spatial receptive fields along the cortical hierarchy. Recently, theoretical and experimental findings have shown that the temporal response windows also gradually enlarge, so that early sensory neural circuits operate on short timescales whereas higher-association areas are capable of integrating information over a long period of time. While an increased receptive field is accounted for by spatial summation of inputs from neurons in an upstream area, the emergence of timescale hierarchy cannot be readily explained, especially given the dense interareal cortical connectivity known in the modern connectome. To uncover the required neurobiological properties, we carried out a rigorous analysis of an anatomically based large-scale cortex model of macaque monkeys. Using a perturbation method, we show that the segregation of disparate timescales is defined in terms of the localization of eigenvectors of the connectivity matrix, which depends on three circuit properties: 1) a macroscopic gradient of synaptic excitation, 2) distinct electrophysiological properties between excitatory and inhibitory neuronal populations, and 3) a detailed balance between long-range excitatory inputs and local inhibitory inputs for each area-to-area pathway. Our work thus provides a quantitative understanding of the mechanism underlying the emergence of timescale hierarchy in large-scale primate cortical networks.

The brain is organized with a delicate structure to integrate and process both spatial and temporal information received from the external world. For spatial information processing, neurons along cortical visual pathways possess increasingly large spatial receptive fields, and its underlying mechanism has been understood as neurons in higher-level visual areas receive input from many neurons with smaller receptive fields in lower-level visual areas, thereby aggregating information across space (1). More recently, a computational model (2) revealed that the timescale over which neural integration occurs also gradually increases from area to area along the cortical hierarchy. The model was based on the anatomically measured directed- and weighted-interareal connectivity of the macaque cortex (3) and incorporated heterogeneity of synaptic excitation calibrated by spine count per pyramidal neuron (4). It has been observed that the decay times increased progressively along the cortical hierarchy when signals propagate in the network, and the temporal hierarchy could change dynamically in response to different types of sensory inputs (e.g., different hierarchy of timescales for somatosensory input versus visual input) (2). By manipulating parameters of the model, simulation results further demonstrated that both within and between regions of anatomical properties could affect the hierarchy of timescales in neuronal population activity (2). A hierarchy of temporal receptive windows is functionally desirable, so that the circuit dynamics operate on short timescales in early sensory areas to encode and process rapidly changing external stimuli, whereas parietal and frontal areas can accumulate information over a relatively long period of time in decision-making and other cognitive processes (5, 6).Despite the accumulating evidence in support of timescale hierarchy across cortical areas in mice (7, 8), monkeys (9–15), and humans (16–23), its underlying mechanism remains unclear. In particular, since interareal connections are dense, with roughly 65% of all possible connections present in the macaque cortex (3) and even higher connection density in the mouse cortex (24), what circuit properties are required to ensure that dynamical modes with disparate time constants are spatially localized? How do intraareal anatomical properties determine the intrinsic timescale of each area, and how do these intrinsic timescales remain to be segregated rather than mixed up in the presence of dense interareal connections? In this work, we addressed these questions by a mathematical analysis of the model (2). Using a perturbation method, we identified key required conditions, in particular a detailed excitation–inhibition balance for long-distance interareal connections that is experimentally testable.     

Harvesting entropy and quantifying the transition from noise to chaos in a photon-counting feedback loop

Many physical processes, including the intensity fluctuations of a chaotic laser, the detection of single photons, and the Brownian motion of a microscopic particle in a fluid are unpredictable, at least on long timescales. This unpredictability can be due to a variety of physical mechanisms, but it is quantified by an entropy rate. This rate, which describes how quickly a system produces new and random information, is fundamentally important in statistical mechanics and practically important for random number generation. We experimentally study entropy generation and the emergence of deterministic chaotic dynamics from discrete noise in a system that applies feedback to a weak optical signal at the single-photon level. We show that the dynamics transition from shot noise to chaos as the photon rate increases and that the entropy rate can reflect either the deterministic or noisy aspects of the system depending on the sampling rate and resolution.Continuous variables and dynamical equations are often used to model systems whose time evolution is composed of discrete events occurring at random times. Examples include the flow of ions across cell membranes (1), the dynamics of large populations of neurons (2), the birth and death of individuals in a population (3), traffic flow on roads (4), the trading of securities in financial markets (5, 6), infection and transmission of disease (7), and the emission and detection of photons (8). We can identify two sources of unpredictability in these systems: the noise associated with the underlying random occurrences that comprise these signals, which are often described by a Poisson process, and the macroscopic dynamics of the system, which may be chaotic. When both effects are present, the macroscopic dynamics can alter the statistics of the noise, and the small-scale noise can in turn feed the large-scale dynamics. This can lead to subtle and nontrivial effects including stochastic resonance and coherence resonance (9, 10). Dynamical unpredictability and complexity are quantified by Lyapunov exponents and dimensionality, whereas shot noise is characterized by statistical metrics like average rate, variance, and signal-to-noise ratio. Characterizing the unpredictability of a system with both large-scale dynamics and small-scale shot noise remains an important challenge in many disciplines including statistical mechanics and information security.Many cryptographic applications, including public key encryption (11), use random numbers. Because the unpredictability of these numbers is essential, physical processes are sometimes used as a source of random numbers (12–25). Physical random number generators are usually tested using the National Institute of Standards and Technology (26) and Diehard (27) test suites, which assess their ability to produce bits that are free of bias and correlation. These tests are an excellent assessment of the performance of a physical random number generator in practical situations but leave an important and fundamental problem unaddressed. Deterministic postprocessing procedures, such as hash functions (25), are often used to remove bias and correlation. Because these procedures are algorithmic and reproducible, they cannot in principle increase the entropy rate of a bit stream. Thus, the reliability of a physical random number generator depends on an accurate assessment of the entropy rate of physical process that generated the numbers (28). It remains difficult to assess the unpredictability of a system based on physical principles.Evaluation of entropy rates from an information-theoretic perspective is also centrally important in statistical mechanics (29–36). One might expect that the unpredictability of a system with both small-scale shot noise and large-scale chaotic dynamics would depend on the scale at which it is observed. In many systems, the dependence of the entropy rate on the resolution, ε, and the sampling interval, τ, can reflect the physical origin of unpredictability (37–40). This dependence has been studied experimentally in Brownian motion, RC circuits, and Rayleigh–Bénard convection (34, 35, 37, 41, 42).Here, we present an experimental exploration and numerical model of entropy production in a photon-counting optoelectronic feedback oscillator. Optoelectronic feedback loops that use analog detectors and macroscopic optical signals produce rich dynamics whose timescales and dimensionality are highly tunable (43–47). Our system applies optoelectronic feedback to a weak optical signal that is measured by a photon-counting detector. The dynamic range of this system (eight orders of magnitude in timescale and a factor of 256 in photon rate) allows us to directly observe the transition from shot noise-dominated behavior to a low-dimensional chaotic attractor with increasing optical power—a transition that, to our knowledge, has never been observed experimentally. We show that the entropy rate can reflect either the deterministic or stochastic aspects of the system, depending on the sampling rate and measurement resolution, and describe the importance of this observation for physical random number generation.     

Elevated intraocular pressure decreases response sensitivity of inner retinal neurons in experimental glaucoma mice

Glaucoma is the second leading cause of blindness in the United States and the world, characterized by progressive degeneration of the optic nerve and retinal ganglion cells (RGCs). Glaucoma patients exhibit an early diffuse loss of retinal sensitivity followed by focal loss of RGCs in sectored patterns. Recent evidence has suggested that this early sensitivity loss may be associated with dysfunctions in the inner retina, but detailed cellular and synaptic mechanisms underlying such sensitivity changes are largely unknown. In this study, we use whole-cell voltage-clamp techniques to analyze light responses of individual bipolar cells (BCs), AII amacrine cells (AIIACs), and ON and sustained OFF alpha-ganglion cells (ONαGCs and sOFFαGCs) in dark-adapted mouse retinas with elevated intraocular pressure (IOP). We present evidence showing that elevated IOP suppresses the rod ON BC inputs to AIIACs, resulting in less sensitive AIIACs, which alter AIIAC inputs to ONαGCs via the AIIAC→cone ON BC→ONαGC pathway, resulting in lower ONαGC sensitivity. The altered AIIAC response also reduces sOFFαGC sensitivity via the AIIAC→sOFFαGC chemical synapses. These sensitivity decreases in αGCs and AIIACs were found in mice with elevated IOP for 3–7 wk, a stage when little RGC or optic nerve degeneration was observed. Our finding that elevated IOP alters neuronal function in the inner retina before irreversible structural damage occurs provides useful information for developing new diagnostic tools and treatments for glaucoma in human patients.Glaucoma is a leading cause of irreversible blindness in the United States and the world (1, 2), and is characterized by optic nerve cupping (thinning of the neuroretinal rim at the optic nerve head) and progressive optic nerve and retinal ganglion cell (RGC) degeneration as well as functional deficit revealed by psychophysical tests (3, 4). Although factors causing the eventual RGC death and blindness remain controversial (1, 5–8), increasing evidence from human patients and animal models has shown that the disease is associated with an early mild diffuse loss of retinal sensitivity or inner retinal response decrease (9–14). Although it is unclear whether these functional changes are a prelude or even causal to RGC death and blindness, elucidating the underlying synaptic and cellular mechanisms for such sensitivity/response decline will nevertheless provide novel insights pertaining to early detection and treatment of human glaucoma.Multiple risk factors are associated with glaucomatous diseases, among which elevated intraocular pressure (IOP) is widely accepted as the most significant for both disease onset and progression (2, 15). Because high IOP (H-IOP) is an important risk factor, many experimental animal models of elevated IOP have been developed in multiple species including monkeys, rats, and mice (16–22). Most experiments performed in animal models have focused on anatomical and histopathological analyses of RGC death, axon loss, and changes to axonal projections to higher visual centers in the brain (23–25). Only a few studies have attempted to address whether function and light sensitivity of retinal neurons are affected. Some reports have suggested a possible but inconclusive involvement of amacrine cells (26, 27). A recent study examining the scotopic threshold responses (STRs) in an elevated IOP mouse model generated by the microbead occlusion method (28) has suggested that the voltage gains (ratio of post/presynaptic signals) of the negative STR [possibly representing AII amacrine cell (AIIAC) responses (29)] and positive STR [possibly representing ON GC responses (30)] are both reduced at stages before morphological changes or RGC death occurs (12). However, no changes in single RGC or their presynaptic bipolar cell (BC)/AIIAC responses have been reported in experimental glaucoma models. Studies using electroretinogram, STR, and optic nerve recording techniques lack the power to identify or establish cellular and synaptic sites of retinal dysfunction (27, 31, 32), leaving a disabling gap preventing us from knowing how elevated IOP affects light responses of individual retinal neurons. In this study, we fill this gap by using whole-cell voltage-clamp techniques to study light responses of individual alpha-RGCs (αGCs) and AIIACs, as well as their presynaptic BCs, in two experimental glaucoma mouse models.It has been shown that light responses of mammalian AIIACs are mediated by rod bipolar cell (DBC_R) inputs via a 6,7-dinitroquinoxaline-2,3-dione (DNQX)–sensitive glutamatergic synapse and certain types of cone depolarizing bipolar cell [DBC_R/MC; ON bipolar cells with mixed rod and M-cone inputs (33), or B6-7] input via a connexin36 (Cx36)-dependent electrical synapse (34–36). AIIACs are perhaps the most sensitive (with the lowest response threshold) neurons in the mouse retina (37, 38), and thus they send highly sensitive output signals to postsynaptic neurons such as certain types of cone hyperpolarizing bipolar cells [HBC_R/MCs; OFF bipolar cells with mixed rod and M-cone inputs (39), or B1-2] and OFF GCs (37, 40). ON and sustained OFF alpha-GCs (ONαGCs and sOFFαGCs) are two primary types of GCs in the mouse retina, and their synaptic circuitries include many major types of mammalian BCs and ACs (40–42). By studying the effects of elevated IOP on these GCs and their presynaptic neurons, we will be able to gain insights into general mechanisms underlying inner retina dysfunction in glaucoma. ONαGCs and sOFFαGCs exhibit characteristic morphology (large somas and dendritic trees) and light response signatures (40). ONαGCs have no or very little spike activity in darkness, increased spikes in light, inward light-evoked cation current (ΔI_C; mediated by DBC_R/MC inputs), and outward light-evoked chloride current (ΔI_Cl; mediated by AC inputs) (40, 43). sOFFαGCs exhibit maintained spike activity in darkness, sustained decrease of spikes in light, outward ΔI_C (mediated by HBC_R/MC inputs), and outward ΔI_Cl (mediated by AIIAC/AC inputs) (40, 44). Fig. 1 is a schematic diagram of synaptic connections between ONαGCs/sOFFαGCs and their primary presynaptic neurons: DBC_Rs, DBC_R/MCs, HBC_R/MCs, and AIIACs (key synapses are labeled 1–5 in the figure; see below). In this report, we analyzed light responses of these retinal neurons in treated mice (in which H-IOP was induced; Materials and Methods) and compared them with the corresponding responses measured in nontreated mice with normal IOP (n-IOP).Open in a separate windowFig. 1.Schematic diagram of major synaptic connections in the ON and OFF α-ganglion pathways in the mouse retina. Green, rods and rod BCs; blue, M cones and mixed rod/M-cone BCs; orange, AIIACs; gray, αGCs; arrows, chemical synapses (red, glutamatergic; blue, glycinergic; +, sign-preserving; −, sign-inverting); zigzag (red), electrical synapses. a, sublamina a; b, sublamina b; GCL, ganglion cell layer; INL, inner nuclear layer; IPL, inner plexiform layer; OPL, outer plexiform layer; PRL, photoreceptor layer. Synapses directly relevant to this study are marked with numbers in circles: 1: DBC_R→AIIAC glutamatergic; 2: DBC_C↔AIIAC electrical; 3: DBC_R/MC/HBC_R/MC→ONαGC/sOFFαGC glutamatergic; 4: AIIAC→HBC_R/MC glycinergic; and 5: AIIAC→sOFFαGC glycinergic.     

Receptive field focus of visual area V4 neurons determines responses to illusory surfaces

Illusory figures demonstrate the visual system’s ability to infer surfaces under conditions of fragmented sensory input. To investigate the role of midlevel visual area V4 in visual surface completion, we used multielectrode arrays to measure spiking responses to two types of visual stimuli: Kanizsa patterns that induce the perception of an illusory surface and physically similar control stimuli that do not. Neurons in V4 exhibited stronger and sometimes rhythmic spiking responses for the illusion-promoting configurations compared with controls. Moreover, this elevated response depended on the precise alignment of the neuron’s peak visual field sensitivity (receptive field focus) with the illusory surface itself. Neurons whose receptive field focus was over adjacent inducing elements, less than 1.5° away, did not show response enhancement to the illusion. Neither receptive field sizes nor fixational eye movements could account for this effect, which was present in both single-unit signals and multiunit activity. These results suggest that the active perceptual completion of surfaces and shapes, which is a fundamental problem in natural visual experience, draws upon the selective enhancement of activity within a distinct subpopulation of neurons in cortical area V4.Visual illusions are valuable stimuli for studying the neural basis of visual processing because they reveal the brain’s internal mechanisms for interpreting sensory input. Illusory figures, for example, exploit the visual system’s capacity to construct contours, shapes, and surfaces despite the lack of a continuous physical border (1, 2). Illusory figures are perceived by a range of phylogenetically diverse species, including monkeys, cats, owls, and bees, pointing to perceptual completion as a fundamental aspect of natural vision (3).Neural correlates of illusory figures have been found in a wide range of brain areas. Recordings in monkeys revealed that illusory figures evoke spiking responses from neurons in visual areas as early as V1 and V2 and as late as the inferotemporal cortex (4–9). Neuroimaging studies in humans similarly found responses to illusory figures throughout visual cortex (10–13).Several theoretical models postulate mechanisms of illusory figure perception (14–19). A common feature of these models is spatial integration of the inducing elements combined with an active interpolation to complete the surface. These processes are frequently assigned to neurons in midlevel areas, whose receptive fields are large enough to cover separate elements yet sensitive enough to distinguish between local features such as orientation, curvature, and colinearity (20, 21). A range of evidence suggests that visual area V4 in particular may play an active role in surface completion. First, the receptive fields of V4 neurons are large by comparison with V1 and V2 receptive fields and are therefore able to integrate information across spatially separated stimulus components (22). Second, psychophysical studies demonstrate that the perception of certain similar illusory figures varies over visual space in a manner consistent with the retinotopy of V4 (23, 24). Third, both human (10–13) and nonhuman primate (25) functional imaging studies reveal responses to illusory contours and surfaces in area V4. Fourth, ablation of area V4 in the macaque selectively impairs performance on discrimination tasks that involve illusory contours (26).Here we investigate the neural representation of illusory surfaces in macaque area V4 using Kanizsa patterns known to give rise to the perception of illusory surfaces. Illusion-promoting patterns elicited electrophysiological responses that were often rhythmic and were significantly enhanced in their firing rate compared with physically similar control patterns that did not promote the illusion. This enhancement depended critically on the spatial alignment of the illusory surface with the point of peak V4 receptive field sensitivity, or “RF focus.” Only neurons with receptive fields focused on the illusory surface showed elevated responses to the illusory surface, whereas those with receptive fields focused on the inducing elements did not. This effect was observed for neurons whose receptive fields, as defined by conventional mapping techniques, were several degrees in size and overlapped with both the illusory surface and the inducer elements. These observations suggest that V4 neurons play an active role in the representation of illusory surfaces and are sensitive to stimulus details much finer than would be predicted based on receptive field size alone.     

Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers

Visual search is a workhorse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed a search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified “feature columns” which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4’s superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.

Throughout cortex, sensory information is organized into maps. This phenomenon is readily observable in visual cortex where maps organize information in both the radial (e.g., within cortical columns) and tangential (e.g., across a cortical area) dimensions (1–4). Importantly, sensory information attributed to these maps is malleable. For example, selective attention is linked to profound changes in neural activity organizing sensory information in both space and time (5–34).In visual cortex, cortical columnar microcircuits comprise many neurons that respond to the same location of visual space and similar stimulus features. For example, primary visual cortex (V1) features “orientation columns” consisting of neurons sharing response preference for the same stimulus orientation (35, 36) and “ocular dominance columns” consisting of neurons that preferentially respond to the same eye (37). Similar columnar organization for feature selectivity has been described across many other visual cortical areas, including area V2 (36, 38, 39), area V3 (40), middle temporal area (area MT) (41–43), and inferotemporal cortex (44–46). Midlevel visual cortical area V4, a well-studied area contributing to attentional modulation, follows suit with columnar organization of visual responses and feature preferences (44, 47–53). Yet, we do not know the extent to which attention impacts feature preferences along columns. While canonical microcircuit models of cortex predict laminar differences for attentional modulation [e.g., feedback-recipient extragranular layers modulating before granular layers (54–56)], how this modulation interacts with columnar feature selectivity is largely unknown.We sought to determine the spatiotemporal profile of feature preferences within the V4 laminar microcircuit during attentional selection. To address this question, we performed neurophysiological recordings along V4 layers in monkeys performing an attention-demanding pop-out search task. We identified feature columns demonstrating homogeneous feature preference along cortical depth. When the search array item presented in the column’s receptive field (RF) was unattended, the upper cortical layers were most selective. However, when attended, feature selectivity in the deep layers enhanced the most, resulting in overall strongest feature selectivity in both extragranular compartments. We further found that the enhancement of feature selectivity associated with attention was rhythmically gated in the beta range. While beta activity was measurable across both unattended and attended conditions, rhythmic gating of feature selectivity was only present with attention. Moreover, beta power modulating the neural response was predictive of response time (RT), suggesting a link between attentional gating and behavior. Synaptic currents revealed the beta rhythm originates in superficial cortical layers, which is compatible with top-down influence.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Synergistic regulation of nonbinary molecular switches by protonation and light

We report a molecular switching ensemble whose states may be regulated in synergistic fashion by both protonation and photoirradiation. This allows hierarchical control in both a kinetic and thermodynamic sense. These pseudorotaxane-based molecular devices exploit the so-called Texas-sized molecular box (cyclo[2]-(2,6-di(1H-imidazol-1-yl)pyridine)[2](1,4-dimethylenebenzene); 1⁴⁺, studied as its tetrakis-PF₆ ⁻ salt) as the wheel component. Anions of azobenzene-4,4′-dicarboxylic acid (2H⁺•2) or 4,4′-stilbenedicarboxylic acid (2H⁺•3) serve as the threading rod elements. The various forms of 2 and 3 (neutral, monoprotonated, and diprotonated) interact differently with 1⁴⁺, as do the photoinduced cis or trans forms of these classic photoactive guests. The net result is a multimodal molecular switch that can be regulated in synergistic fashion through protonation/deprotonation and photoirradiation. The degree of guest protonation is the dominating control factor, with light acting as a secondary regulatory stimulus. The present dual input strategy provides a complement to more traditional orthogonal stimulus-based approaches to molecular switching and allows for the creation of nonbinary stimulus-responsive functional materials.

Multifactor regulation of biomolecular machines is essential to their ability to carry out various biological functions (1 –11). Construction of artificial molecular devices with multifactor regulation features may allow us to understand and simulate biological systems more effectively (12 –31). However, creating and controlling such synthetic constructs remains challenging (16, 32 –37). Most known systems involving multifactor regulation, including most so-called molecular switches and logic devices (38 –43), have been predicated on an orthogonal strategy wherein the different control factors that determine the distribution of accessible states do not affect one another (20, 44 –56). However, in principle, a greater level of control can be achieved by using two separate regulatory inputs that operate in synergistic fashion. Ideally, this could lead to hierarchical control where different states are specifically accessed by means of appropriately selected nonorthogonal inputs. However, to our knowledge, only a limited number of reports detailing controlled hierarchical systems have appeared (57). Furthermore, the balance between specific effects (e.g., kinetics vs. thermodynamics) under conditions of stimulus regulation is still far from fully understood (54). There is thus a need for new systems that can provide further insights into the underlying design determinants. Here we report a set of pseudorotaxane molecular shuttles that act as multimodal chemical switches subject to hierarchical control.     

Single nanoparticle detection using split-mode microcavity Raman lasers

Ultrasensitive nanoparticle detection holds great potential for early-stage diagnosis of human diseases and for environmental monitoring. In this work, we report for the first time, to our knowledge, single nanoparticle detection by monitoring the beat frequency of split-mode Raman lasers in high-Q optical microcavities. We first demonstrate this method by controllably transferring single 50-nm–radius nanoparticles to and from the cavity surface using a fiber taper. We then realize real-time detection of single nanoparticles in an aqueous environment, with a record low detection limit of 20 nm in radius, without using additional techniques for laser noise suppression. Because Raman scattering occurs in most materials under practically any pump wavelength, this Raman laser-based sensing method not only removes the need for doping the microcavity with a gain medium but also loosens the requirement of specific wavelength bands for the pump lasers, thus representing a significant step toward practical microlaser sensors.Stimulated Raman scattering holds great potential for various photonic applications, such as label-free high-sensitivity biomedical imaging (1) and for extending the wavelength range of existing lasers (2), as well as for generating ultra-short light pulses (3). In high Q microcavities (4), stimulated Raman scattering, also called Raman lasing, has been experimentally demonstrated to possess ultra-low thresholds (5–12), due to the greatly increased light density in microcavities (13). Such microcavity Raman lasers hold great potential for sensing applications. In principle, Raman lasing initially occurs in the two initially degenerate counter propagating traveling cavity modes. These two modes couple to each other due to backscattering when a nanoscale object binds to the cavity surface. For a sufficiently strong coupling, in which the photon exchange rate between the two initial modes becomes larger than the rates of all of the loss mechanisms in the system, two new split cavity modes form (14–18) and lase simultaneously. Thus, by monitoring the beat frequency of the split-mode Raman lasers, ultrasensitive nanoparticle detection can be realized.In this work, we report, to our knowledge, the first experimental demonstration of single nanoparticle detection using split-mode microcavity Raman lasers. The sensing principle is first demonstrated in air, by controllably binding or removing single 50-nm-radius polystyrene (PS) nanoparticles to and from the cavity surface using a fiber taper (19) and measuring the changes in the beat frequency of the two split Raman lasers. Real-time single nanoparticle detection is then performed in an aqueous environment by monitoring the discrete changes in beat frequency of the Raman lasers, and a detection limit of 20 nm in particle radius is realized. This microcavity Raman laser sensing method holds several advantages. On the one hand, the beat frequency of the Raman lasers, which corresponds to the mode splitting (18), is inherently immune to many noise sources, such as laser frequency noise and thermal noise (including that induced both by the environmental temperature fluctuations and by probe laser heating), which are the main noise sources in sensing systems using the mode shift mechanism (20–30). Over the last few years, significant effort has been made to suppress the laser frequency noise in the mode-shift detection method, such as by using a reference interferometer (27) and by performing backscattering detection with frequency locking techniques (28, 29), but both approaches involve a substantial increase in the complexity of the sensing systems. On the other hand, the intrinsic Raman gain in the cavity provides a perfect means to compensate for the cavity mode loss and thus to lower the detection limit compared with passive mode splitting methods (18, 31–34). Without the need for doping the microcavities with a gain medium (35–37), the fabrication complexity of microcavities is also greatly reduced, and no specific wavelength bands of the pump lasers are required.     

Self-assembly of alkynylplatinum(II) terpyridine amphiphiles into nanostructures via steric control and metal–metal interactions

A series of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing the hydrophilic oligo(para-phenylene ethynylene) with two 3,6,9-trioxadec-1-yloxy chains was designed and synthesized. The mononuclear alkynylplatinum(II) terpyridine complex was found to display a very strong tendency toward the formation of supramolecular structures. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would lead to the formation of nanotubes or helical ribbons. These desirable nanostructures were found to be governed by the steric bulk on the platinum(II) terpyridine moieties, which modulates the directional metal−metal interactions and controls the formation of nanotubes or helical ribbons. Detailed analysis of temperature-dependent UV-visible absorption spectra of the nanostructured tubular aggregates also provided insights into the assembly mechanism and showed the role of metal−metal interactions in the cooperative supramolecular polymerization of the amphiphilic platinum(II) complexes.Square-planar d⁸ platinum(II) polypyridine complexes have long been known to exhibit intriguing spectroscopic and luminescence properties (1–54) as well as interesting solid-state polymorphism associated with metal−metal and π−π stacking interactions (1–14, 25). Earlier work by our group showed the first example, to our knowledge, of an alkynylplatinum(II) terpyridine system [Pt(tpy)(C ≡ CR)]⁺ that incorporates σ-donating and solubilizing alkynyl ligands together with the formation of Pt···Pt interactions to exhibit notable color changes and luminescence enhancements on solvent composition change (25) and polyelectrolyte addition (26). This approach has provided access to the alkynylplatinum(II) terpyridine and other related cyclometalated platinum(II) complexes, with functionalities that can self-assemble into metallogels (27–31), liquid crystals (32, 33), and other different molecular architectures, such as hairpin conformation (34), helices (35–38), nanostructures (39–45), and molecular tweezers (46, 47), as well as having a wide range of applications in molecular recognition (48–52), biomolecular labeling (48–52), and materials science (53, 54). Recently, metal-containing amphiphiles have also emerged as a building block for supramolecular architectures (42–44, 55–59). Their self-assembly has always been found to yield different molecular architectures with unprecedented complexity through the multiple noncovalent interactions on the introduction of external stimuli (42–44, 55–59).Helical architecture is one of the most exciting self-assembled morphologies because of the uniqueness for the functional and topological properties (60–69). Helical ribbons composed of amphiphiles, such as diacetylenic lipids, glutamates, and peptide-based amphiphiles, are often precursors for the growth of tubular structures on an increase in the width or the merging of the edges of ribbons (64, 65). Recently, the optimization of nanotube formation vs. helical nanostructures has aroused considerable interests and can be achieved through a fine interplay of the influence on the amphiphilic property of molecules (66), choice of counteranions (67, 68), or pH values of the media (69), which would govern the self-assembly of molecules into desirable aggregates of helical ribbons or nanotube scaffolds. However, a precise control of supramolecular morphology between helical ribbons and nanotubes remains challenging, particularly for the polycyclic aromatics in the field of molecular assembly (64–69). Oligo(para-phenylene ethynylene)s (OPEs) with solely π−π stacking interactions are well-recognized to self-assemble into supramolecular system of various nanostructures but rarely result in the formation of tubular scaffolds (70–73). In view of the rich photophysical properties of square-planar d⁸ platinum(II) systems and their propensity toward formation of directional Pt···Pt interactions in distinctive morphologies (27–31, 39–45), it is anticipated that such directional and noncovalent metal−metal interactions might be capable of directing or dictating molecular ordering and alignment to give desirable nanostructures of helical ribbons or nanotubes in a precise and controllable manner.Herein, we report the design and synthesis of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing hydrophilic OPEs with two 3,6,9-trioxadec-1-yloxy chains. The mononuclear alkynylplatinum(II) terpyridine complex with amphiphilic property is found to show a strong tendency toward the formation of supramolecular structures on diffusion of diethyl ether in dichloromethane or dimethyl sulfoxide (DMSO) solution. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would result in nanotubes or helical ribbons in the self-assembly process. To the best of our knowledge, this finding represents the first example of the utilization of the steric bulk of the moieties, which modulates the formation of directional metal−metal interactions to precisely control the formation of nanotubes or helical ribbons in the self-assembly process. Application of the nucleation–elongation model into this assembly process by UV-visible (UV-vis) absorption spectroscopic studies has elucidated the nature of the molecular self-assembly, and more importantly, it has revealed the role of metal−metal interactions in the formation of these two types of nanostructures.     

Two-dimensional electronic–vibrational sum frequency spectroscopy for interactions of electronic and nuclear motions at interfaces

Interactions of electronic and vibrational degrees of freedom are essential for understanding excited-states relaxation pathways of molecular systems at interfaces and surfaces. Here, we present the development of interface-specific two-dimensional electronic–vibrational sum frequency generation (2D-EVSFG) spectroscopy for electronic–vibrational couplings for excited states at interfaces and surfaces. We demonstrate this 2D-EVSFG technique by investigating photoexcited interface-active (E)-4-((4-(dihexylamino) phenyl)diazinyl)-1-methylpyridin-1- lum (AP3) molecules at the air–water interface as an example. Our 2D-EVSFG experiments show strong vibronic couplings of interfacial AP3 molecules upon photoexcitation and subsequent relaxation of a locally excited (LE) state. Time-dependent 2D-EVSFG experiments indicate that the relaxation of the LE state, S₂, is strongly coupled with two high-frequency modes of 1,529.1 and 1,568.1 cm⁻¹. Quantum chemistry calculations further verify that the strong vibronic couplings of the two vibrations promote the transition from the S₂ state to the lower excited state S₁. We believe that this development of 2D-EVSFG opens up an avenue of understanding excited-state dynamics related to interfaces and surfaces.

Electronic and vibrational degrees of freedom are the most important physical quantities in molecular systems at interfaces and surfaces. Knowledge of interactions between electronic and vibrational motions, namely electronic–vibrational couplings, is essential to understanding excited-states relaxation pathways of molecular systems at interfaces and surfaces. Many excited-states relaxation processes occur at interfaces and surfaces, including charge transfer, energy transfer, proton transfer, proton-coupled electron transfer, configurational dynamics, and so on (1–11). These relaxation processes are intimately related to the electronic–vibrational couplings at interfaces and surfaces. Strong electronic–vibrational couplings could promote nonadiabatic evolution of excited potential energy and thus, facilitate chemical reactions or intramolecular structural changes of interfacial molecules (10, 12, 13). Furthermore, these interactions of electronic and vibrational degrees of freedom are subject to solvent environments (e.g., interfaces/surfaces with a restricted environment of unique physical and chemical properties) (9, 14, 15). Despite the importance of interactions of electronic and vibrational motions, little is known about excited-state electronic–vibrational couplings at interfaces and surfaces.Interface-specific electronic and vibrational spectroscopies enable us to characterize the electronic and vibrational structures separately. As interface-specific tools, second-order electronic sum frequency generation (ESFG) and vibrational sum frequency generation (VSFG) spectroscopies have been utilized for investigating molecular structure, orientational configurations, chemical reactions, chirality, static potential, environmental issues, and biological systems at interfaces and surfaces (16–52). Recently, structural dynamics at interfaces and surfaces have been explored using time-resolved ESFG and time-resolved VSFG with a visible pump or an infrared (IR) pump thanks to the development of ultrafast lasers (6–9, 13–15, 49, 53–61). Doubly resonant sum frequency generation (SFG) has been demonstrated to probe both electronic and vibration transitions of interfacial molecular monolayer (15, 62–71). This frequency-domain two-dimensional (2D) interface/surface spectroscopy could provide information regarding electronic–vibrational coupling of interfacial molecules. However, contributions from excited states are too weak to be probed due to large damping rates of vibrational states in excited states (62, 63). As such, the frequency-domain doubly resonant SFG is used only for electronic–vibrational coupling of electronic ground states. Ultrafast interface-specific electronic–vibrational spectroscopy could allow us to gain insights into how specific nuclear motions drive the relaxation of electronic excited states. Therefore, development of interface-specific electronic–vibrational spectroscopy for excited states is needed.In this work, we integrate the specificity of interfaces and surfaces into the capabilities of ultrafast 2D spectroscopy for dynamical electronic–vibrational couplings in excited states of molecules; 2D interface-specific spectroscopies are analogous to those 2D spectra in bulk that spread the information contained in a pump−probe spectrum over two frequency axes. Thus, one can better interpret congested one-dimensional signals. Two-dimensional vibrational sum frequency generation (2D-VSFG) spectroscopy was demonstrated a few year ago (72–74). Furthermore, heterodyne 2D-VSFG spectroscopy using middle infrared (mid-IR) pulse shaping and noncollinear geometry 2D-VSFG experiments have also been developed to study vibrational structures and dynamics at interfaces (31, 75–78). Recently, two-dimensional electronic sum frequency generation (2D-ESFG) spectroscopy has also been demonstrated for surfaces and interfaces (79). On the other hand, bulk two-dimensional electronic–vibrational (2D-EV) spectroscopy has been extensively used to investigate the electronic relaxation and energy transfer dynamics of molecules, biological systems, and nanomaterials (80–90). The 2D-EV technique not only provides electronic and vibrational interactions between excitons or different excited electronic states of systems but also, identifies fast nonradiative transitions through nuclear motions in molecules, aggregations, and nanomaterials. However, an interface-specific technique for two-dimensional electronic–vibrational sum frequency generation (2D-EVSFG) spectroscopy has yet to be developed.Here, we present the development of 2D-EVSFG spectroscopy for the couplings of electronic and nucleic motions at interfaces and surfaces. The purpose of developing 2D-EVSFG spectroscopy is to bridge the gap between the visible and IR regions to reveal how structural dynamics for photoexcited electronic states are coupled with vibrations at interfaces and surfaces. As an example, we applied this 2D-EVSFG experimental method to time evolution of electronic–vibrational couplings at excited states of interface-active molecules at the air–water interface.     

An image-computable model of how endogenous and exogenous attention differentially alter visual perception

Attention alters perception across the visual field. Typically, endogenous (voluntary) and exogenous (involuntary) attention similarly improve performance in many visual tasks, but they have differential effects in some tasks. Extant models of visual attention assume that the effects of these two types of attention are identical and consequently do not explain differences between them. Here, we develop a model of spatial resolution and attention that distinguishes between endogenous and exogenous attention. We focus on texture-based segmentation as a model system because it has revealed a clear dissociation between both attention types. For a texture for which performance peaks at parafoveal locations, endogenous attention improves performance across eccentricity, whereas exogenous attention improves performance where the resolution is low (peripheral locations) but impairs it where the resolution is high (foveal locations) for the scale of the texture. Our model emulates sensory encoding to segment figures from their background and predict behavioral performance. To explain attentional effects, endogenous and exogenous attention require separate operating regimes across visual detail (spatial frequency). Our model reproduces behavioral performance across several experiments and simultaneously resolves three unexplained phenomena: 1) the parafoveal advantage in segmentation, 2) the uniform improvements across eccentricity by endogenous attention, and 3) the peripheral improvements and foveal impairments by exogenous attention. Overall, we unveil a computational dissociation between each attention type and provide a generalizable framework for predicting their effects on perception across the visual field.

Endogenous and exogenous spatial attention prioritize subsets of visual information and facilitate their processing without concurrent eye movements (1–3). Selection by endogenous attention is goal-driven and adapts to task demands, whereas exogenous attention transiently and automatically orients to salient stimuli (1–3). In most visual tasks, both types of attention typically improve visual perception similarly [e.g., acuity (4–6), visual search (7, 8), perceived contrast (9–11)]. Consequently, models of visual attention do not distinguish between endogenous and exogenous attention (e.g., refs. 12–19). However, stark differences also exist. Each attention type differentially modulates neural responses (20, 21) and fundamental properties of visual processing, including temporal resolution (22, 23), texture sensitivity (24), sensory tuning (25), contrast sensitivity (26), and spatial resolution (27–34).The effects of endogenous and exogenous attention are dissociable during texture segmentation, a visual task constrained by spatial resolution [reviews (1–3)]. Whereas endogenous attention optimizes spatial resolution to improve the detection of an attended texture (32–34), exogenous attention reflexively enhances resolution even when detrimental to perception (27–31, 34). Extant models of attention do not explain these well-established effects.Two main hypotheses have been proposed to explain how attention alters spatial resolution. Psychophysical studies ascribe attentional effects to modulations of spatial frequency (SF) sensitivity (30, 33). Neurophysiological (13, 35, 36) and neuroimaging (37, 38) studies bolster the idea that attention modifies spatial profiles of neural receptive fields (RFs) (2). Both hypotheses provide qualitative predictions of attentional effects but do not specify their underlying neural computations.Differences between endogenous and exogenous attention are well established in segmentation tasks and thus provide an ideal model system to uncover their separate roles in altering perception. Texture-based segmentation is a fundamental process of midlevel vision that isolates regions of local structure to extract figures from their background (39–41). Successful segmentation hinges on the overlap between the visual system’s spatial resolution and the levels of detail (i.e., SF) encompassed by the texture (39, 41, 42). Consequently, the ability to distinguish between adjacent textures varies as resolution declines toward the periphery (43–46). Each attention type differentially alters texture segmentation, demonstrating that their effects shape spatial resolution [reviews (1–3)].Current models of texture segmentation do not explain performance across eccentricity and the distinct modulations by attention. Conventional models treat segmentation as a feedforward process that encodes the elementary features of an image (e.g., SF and orientation), transforms them to reflect the local structure (e.g., regions of similarly oriented bars), and then pools across space to emphasize texture-defined contours (39, 41, 47). Few of these models account for variations in resolution across eccentricity (46, 48, 49) or endogenous (but not exogenous) attentional modulations (18, 50). All others postulate that segmentation is a “preattentive” (42) operation whose underlying neural processing is impervious to attention (39, 41, 46–49).Here, we develop a computational model in which feedforward processing and attentional gain contribute to segmentation performance. We augment a conventional model of texture processing (39, 41, 47). Our model varies with eccentricity and includes contextual modulation within local regions in the stimulus via normalization (51), a canonical neural computation (52). The defining characteristic of normalization is that an individual neuron is (divisively) suppressed by the summed activity of neighboring neurons responsive to different aspects of a stimulus. We model attention as multiplicative gains [attentional gain factors (15)] that vary with eccentricity and SF. Attention shifts sensitivity toward fine or coarse spatial scales depending on the range of SFs enhanced.Our model is image-computable, which allowed us to reproduce behavior directly from grayscale images used in psychophysical experiments (6, 26, 27, 29–33). The model explains three signatures of texture segmentation hitherto unexplained within a single computational framework (Fig. 1): 1) the central performance drop (CPD) (27–34, 43–46) (Fig. 1A), that is, the parafoveal advantage of segmentation over the fovea; 2) the improvements in the periphery and impairments at foveal locations induced by exogenous attention (27–32, 34) (Fig. 1B); and 3) the equivalent improvements across eccentricity by endogenous attention (32–34) (Fig. 1C).Open in a separate windowFig. 1.Signatures of texture segmentation. (A) CPD. Shaded region depicts the magnitude of the CPD. Identical axis labels are omitted in B and C. (B) Exogenous attention modulation. Exogenous attention improves segmentation performance in the periphery and impairs it near the fovea. (C) Endogenous attention modulation. Endogenous attention improves segmentation performance across eccentricity.Whereas our analyses focused on texture segmentation, our model is general and can be applied to other visual phenomena. We show that the model predicts the effects of attention on contrast sensitivity and acuity, i.e., in tasks in which both endogenous and exogenous attention have similar or differential effects on performance. To preview our results, model comparisons revealed that normalization is necessary to elicit the CPD and that separate profiles of gain enhancement across SF (26) generate the effects of exogenous and endogenous attention on texture segmentation. A preferential high-SF enhancement reproduces the impairments by exogenous attention due to a shift in visual sensitivity toward details too fine to distinguish the target at foveal locations. The transition from impairments to improvements in the periphery results from exogenous attentional gain gradually shifting to lower SFs that are more amenable for target detection. Improvements by endogenous attention result from a uniform enhancement of SFs that encompass the target, optimizing visual sensitivity for the attended stimulus across eccentricity.     

Thermodynamics of formation of coffinite,USiO4

Coffinite, USiO₄, is an important U(IV) mineral, but its thermodynamic properties are not well-constrained. In this work, two different coffinite samples were synthesized under hydrothermal conditions and purified from a mixture of products. The enthalpy of formation was obtained by high-temperature oxide melt solution calorimetry. Coffinite is energetically metastable with respect to a mixture of UO₂ (uraninite) and SiO₂ (quartz) by 25.6 ± 3.9 kJ/mol. Its standard enthalpy of formation from the elements at 25 °C is −1,970.0 ± 4.2 kJ/mol. Decomposition of the two samples was characterized by X-ray diffraction and by thermogravimetry and differential scanning calorimetry coupled with mass spectrometric analysis of evolved gases. Coffinite slowly decomposes to U₃O₈ and SiO₂ starting around 450 °C in air and thus has poor thermal stability in the ambient environment. The energetic metastability explains why coffinite cannot be synthesized directly from uraninite and quartz but can be made by low-temperature precipitation in aqueous and hydrothermal environments. These thermochemical constraints are in accord with observations of the occurrence of coffinite in nature and are relevant to spent nuclear fuel corrosion.In many countries with nuclear energy programs, spent nuclear fuel (SNF) and/or vitrified high-level radioactive waste will be disposed in an underground geological repository. Demonstrating the long-term (10⁶–10⁹ y) safety of such a repository system is a major challenge. The potential release of radionuclides into the environment strongly depends on the availability of water and the subsequent corrosion of the waste form as well as the formation of secondary phases, which control the radionuclide solubility. Coffinite (1), USiO₄, is expected to be an important alteration product of SNF in contact with silica-enriched groundwater under reducing conditions (2–8). It is also found, accompanied by thorium orthosilicate and uranothorite, in igneous and metamorphic rocks and ore minerals from uranium and thorium sedimentary deposits (2, 4, 5, 8–16). Under reducing conditions in the repository system, the uranium solubility (very low) in aqueous solutions is typically derived from the solubility product of UO₂. Stable U(IV) minerals, which could form as secondary phases, would impart lower uranium solubility to such systems. Thus, knowledge of coffinite thermodynamics is needed to constrain the solubility of U(IV) in natural environments and would be useful in repository assessment.In natural uranium deposits such as Oklo (Gabon) (4, 7, 11, 12, 14, 17, 18) and Cigar Lake (Canada) (5, 13, 15), coffinite has been suggested to coexist with uraninite, based on electron probe microanalysis (EPMA) (4, 5, 7, 11, 13, 17, 19, 20) and transmission electron microscopy (TEM) (8, 15). However, it is not clear whether such apparent replacement of uraninite by a coffinite-like phase is a direct solid-state process or occurs mediated by dissolution and reprecipitation.The precipitation of USiO₄ as a secondary phase should be favored in contact with silica-rich groundwater (21) [silica concentration >10⁻⁴ mol/L (22, 23)]. Natural coffinite samples are often fine-grained (4, 5, 8, 11, 13, 15, 24), due to the long exposure to alpha-decay event irradiation (4, 6, 25, 26) and are associated with other minerals and organic matter (6, 8, 12, 18, 27, 28). Hence the determination of accurate thermodynamic data from natural samples is not straightforward. However, the synthesis of pure coffinite also has challenges. It appears not to form by reacting the oxides under dry high-temperature conditions (24, 29). Synthesis from aqueous solutions usually produces UO₂ and amorphous SiO₂ impurities, with coffinite sometimes being only a minor phase (24, 30–35). It is not clear whether these difficulties arise from kinetic factors (slow reaction rates) or reflect intrinsic thermodynamic instability (33). Thus, there are only a few reported estimates of thermodynamic properties of coffinite (22, 36–40) and some of them are inconsistent. To resolve these uncertainties, we directly investigated the energetics of synthetic coffinite by high-temperature oxide melt solution calorimetry to obtain a reliable enthalpy of formation and explored its thermal decomposition.