Evaluating Visual Cues Modulates Their Representation in Mouse Visual and Cingulate Cortex.

Choosing an action in response to visual cues relies on cognitive processes, such as perception, evaluation, and prediction, which can modulate visual representations even at early processing stages. In the mouse, it is challenging to isolate cognitive modulations of sensory signals because concurrent overt behavior patterns, such as locomotion, can also have brainwide influences. To address this challenge, we designed a task, in which head-fixed mice had to evaluate one of two visual cues. While their global shape signaled the opportunity to earn reward, the cues provided equivalent local stimulation to receptive fields of neurons in primary visual (V1) and anterior cingulate cortex (ACC). We found that mice evaluated these cues within few hundred milliseconds. During this period, ∼30% of V1 neurons became cue-selective, with preferences for either cue being balanced across the recorded population. This selectivity emerged in response to the behavioral demands because the same neurons could not discriminate the cues in sensory control measurements. In ACC, cue evaluation affected a similar fraction of neurons; emerging selectivity, however, was stronger than in V1, and preferences in the recorded population were biased toward the cue promising reward. Such a biased selectivity regime might allow the mouse to infer the promise of reward simply by the overall level of activity. Together, these experiments isolate the impact of task demands on neural responses in mouse cerebral cortex, and document distinct neural signatures of cue evaluation in V1 and ACC.SIGNIFICANCE STATEMENT Performing a cognitive task, such as evaluating visual cues, not only recruits frontal and parietal brain regions, but also modulates sensory processing stages. We trained mice to evaluate two visual cues, and show that, during this task, ∼30% of neurons recorded in V1 became selective for either cue, although they provided equivalent visual stimulation. We also show that, during cue evaluation, mice frequently move their eyes, even under head fixation, and that ignoring systematic differences in eye position can substantially obscure the modulations seen in V1 neurons. Finally, we document that modulations are stronger in ACC, and biased toward the reward-predicting cue, suggesting a transition in the neural representation of task-relevant information across processing stages in mouse cerebral cortex.

Learning Enhances Sensory Processing in Mouse V1 before Improving Behavior.

A fundamental property of visual cortex is to enhance the representation of those stimuli that are relevant for behavior, but it remains poorly understood how such enhanced representations arise during learning. Using classical conditioning in adult mice of either sex, we show that orientation discrimination is learned in a sequence of distinct behavioral stages, in which animals first rely on stimulus appearance before exploiting its orientation to guide behavior. After confirming that orientation discrimination under classical conditioning requires primary visual cortex (V1), we measured, during learning, response properties of V1 neurons. Learning improved neural discriminability, sharpened orientation tuning, and led to higher contrast sensitivity. Remarkably, these learning-related improvements in the V1 representation were fully expressed before successful orientation discrimination was evident in the animals' behavior. We propose that V1 plays a key role early in discrimination learning to enhance behaviorally relevant sensory information.SIGNIFICANCE STATEMENT Decades of research have documented that responses of neurons in visual cortex can reflect the behavioral relevance of visual information. The behavioral relevance of any stimulus needs to be learned, though, and little is known how visual sensory processing changes, as the significance of a stimulus becomes clear. Here, we trained mice to discriminate two visual stimuli, precisely quantified when learning happened, and measured, during learning, the neural representation of these stimuli in V1. We observed learning-related improvements in V1 processing, which were fully expressed before discrimination was evident in the animals' behavior. These findings indicate that sensory and behavioral improvements can follow different time courses and point toward a key role of V1 at early stages in discrimination learning.

Mice Can Use Second-Order, Contrast-Modulated Stimuli to Guide Visual Perception.

Visual processing along the primate ventral stream takes place in a hierarchy of areas, characterized by an increase in both complexity of neuronal preferences and invariance to changes of low-level stimulus attributes. A basic type of invariance is form-cue invariance, where neurons have similar preferences in response to first-order stimuli, defined by changes in luminance, and global features of second-order stimuli, defined by changes in texture or contrast. Whether in mice, a now popular model system for early visual processing, visual perception can be guided by second-order stimuli is currently unknown. Here, we probed mouse visual perception and neural responses in areas V1 and LM using various types of second-order, contrast-modulated gratings with static noise carriers. These gratings differ in their spatial frequency composition and thus in their ability to invoke first-order mechanisms exploiting local luminance features. We show that mice can transfer learning of a coarse orientation discrimination task involving first-order, luminance-modulated gratings to the contrast-modulated gratings, albeit with markedly reduced discrimination performance. Consistent with these behavioral results, we demonstrate that neurons in area V1 and LM are less responsive and less selective to contrast-modulated than to luminance-modulated gratings, but respond with broadly similar preferred orientations. We conclude that mice can, at least in a rudimentary form, use second-order stimuli to guide visual perception. SIGNIFICANCE STATEMENT: To extract object boundaries in natural scenes, the primate visual system does not only rely on differences in local luminance but can also take into account differences in texture or contrast. Whether the mouse, which has a much simpler visual system, can use such second-order information to guide visual perception is unknown. Here we tested mouse perception of second-order, contrast-defined stimuli and measured their neural representations in two areas of visual cortex. We find that mice can use contrast-defined stimuli to guide visual perception, although behavioral performance and neural representations were less robust than for luminance-defined stimuli. These findings shed light on basic steps of feature extraction along the mouse visual cortical hierarchy, which may ultimately lead to object recognition.

Population rate dynamics and multineuron firing patterns in sensory cortex.

Cortical circuits encode sensory stimuli through the firing of neuronal ensembles, and also produce spontaneous population patterns in the absence of sensory drive. This population activity is often characterized experimentally by the distribution of multineuron "words" (binary firing vectors), and a match between spontaneous and evoked word distributions has been suggested to reflect learning of a probabilistic model of the sensory world. We analyzed multineuron word distributions in sensory cortex of anesthetized rats and cats, and found that they are dominated by fluctuations in population firing rate rather than precise interactions between individual units. Furthermore, cortical word distributions change when brain state shifts, and similar behavior is seen in simulated networks with fixed, random connectivity. Our results suggest that similarity or dissimilarity in multineuron word distributions could primarily reflect similarity or dissimilarity in population firing rate dynamics, and not necessarily the precise interactions between neurons that would indicate learning of sensory features.

Spatial integration in mouse primary visual cortex.

Responses of many neurons in primary visual cortex (V1) are suppressed by stimuli exceeding the classical receptive field (RF), an important property that might underlie the computation of visual saliency. Traditionally, it has proven difficult to disentangle the underlying neural circuits, including feedforward, horizontal intracortical, and feedback connectivity. Since circuit-level analysis is particularly feasible in the mouse, we asked whether neural signatures of spatial integration in mouse V1 are similar to those of higher-order mammals and investigated the role of parvalbumin-expressing (PV+) inhibitory interneurons. Analogous to what is known from primates and carnivores, we demonstrate that, in awake mice, surround suppression is present in the majority of V1 neurons and is strongest in superficial cortical layers. Anesthesia with isoflurane-urethane, however, profoundly affects spatial integration: it reduces the laminar dependency, decreases overall suppression strength, and alters the temporal dynamics of responses. We show that these effects of brain state can be parsimoniously explained by assuming that anesthesia affects contrast normalization. Hence, the full impact of suppressive influences in mouse V1 cannot be studied under anesthesia with isoflurane-urethane. To assess the neural circuits of spatial integration, we targeted PV+ interneurons using optogenetics. Optogenetic depolarization of PV+ interneurons was associated with increased RF size and decreased suppression in the recorded population, similar to effects of lowering stimulus contrast, suggesting that PV+ interneurons contribute to spatial integration by affecting overall stimulus drive. We conclude that the mouse is a promising model for circuit-level mechanisms of spatial integration, which relies on the combined activity of different types of inhibitory interneurons.

Neural networks: Explaining animal behavior with prior knowledge of the world.

Animal behavior is both facilitated and constrained by innate knowledge and previous experience of the world. A new study, exploiting the power of recurrent neural networks, has revealed the existence of such structural priors and their impact on animal behavior.

GABAA inhibition controls response gain in visual cortex.

GABA(A) inhibition is thought to play multiple roles in sensory cortex, such as controlling responsiveness and sensitivity, sharpening selectivity, and mediating competitive interactions. To test these proposals, we recorded in cat primary visual cortex (V1) after local iontophoresis of gabazine, the selective GABA(A) antagonist. Gabazine increased responsiveness by as much as 300%. It slightly decreased selectivity for stimulus orientation and direction, often by raising responses to all orientations. Strikingly, gabazine affected neither contrast sensitivity nor cross-orientation suppression, the competition seen when stimuli of different orientation are superimposed. These results were captured by a simple model in which GABA(A) inhibition has the same selectivity as excitation and keeps responses to unwanted stimuli below threshold. We conclude that GABA(A) inhibition in V1 helps enhance stimulus selectivity but is not responsible for competition among superimposed stimuli. It controls the sensitivity of V1 neurons by adjusting their response gain, without affecting their input gain.

The detection of visual contrast in the behaving mouse.

The mouse is becoming a key species for research on the neural circuits of the early visual system. To relate such circuits to perception, one must measure visually guided behavior and ask how it depends on fundamental stimulus attributes such as visual contrast. Using operant conditioning, we trained mice to detect visual contrast in a two-alternative forced-choice task. After 3-4 weeks of training, mice performed hundreds of trials in each session. Numerous sessions yielded high-quality psychometric curves from which we inferred measures of contrast sensitivity. In multiple sessions, however, choices were influenced not only by contrast, but also by estimates of reward value and by irrelevant factors such as recent failures and rewards. This behavior was captured by a generalized linear model involving not only the visual responses to the current stimulus but also a bias term and history terms depending on the outcome of the previous trial. We compared the behavioral performance of the mice to predictions of a simple decoder applied to neural responses measured in primary visual cortex of awake mice during passive viewing. The decoder performed better than the animal, suggesting that mice might not use optimally the information contained in the activity of visual cortex.

Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability.

One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

Robust effects of corticothalamic feedback and behavioral state on movie responses in mouse dLGN.

Neurons in the dorsolateral geniculate nucleus (dLGN) of the thalamus receive a substantial proportion of modulatory inputs from corticothalamic (CT) feedback and brain stem nuclei. Hypothesizing that these modulatory influences might be differentially engaged depending on the visual stimulus and behavioral state, we performed in vivo extracellular recordings from mouse dLGN while optogenetically suppressing CT feedback and monitoring behavioral state by locomotion and pupil dilation. For naturalistic movie clips, we found CT feedback to consistently increase dLGN response gain and promote tonic firing. In contrast, for gratings, CT feedback effects on firing rates were mixed. For both stimulus types, the neural signatures of CT feedback closely resembled those of behavioral state, yet effects of behavioral state on responses to movies persisted even when CT feedback was suppressed. We conclude that CT feedback modulates visual information on its way to cortex in a stimulus-dependent manner, but largely independently of behavioral state.

Temporal dynamics of neuronal modulation during exogenous and endogenous shifts of visual attention in macaque area MT.

Dynamically shifting attention between behaviorally relevant stimuli in the environment is a key condition for successful adaptive behavior. Here, we investigated how exogenous (reflexive) and endogenous (voluntary) shifts of visual spatial attention interact to modulate activity of single neurons in extrastriate area MT. We used a double-cueing paradigm, in which the first cue instructed two macaque monkeys to covertly attend to one of three moving random dot patterns until a second cue, whose unpredictable onset exogenously captured attention, either signaled to shift or maintain the current focus of attention. The neuronal activity revealed correlates of both exogenous and endogenous attention, which could be well distinguished by their characteristic temporal dynamics. The earliest effect was a transient interruption of the focus of endogenous attention by the onset of the second cue. The neuronal signature of this exogenous capture of attention was a short-latency decrease of responses to the stimulus attended so far. About 70 ms later, the influence of exogenous attention leveled off, which was reflected in two concurrent processes: responses to the newly cued stimulus continuously increased because of allocation of endogenous attention, while, surprisingly, there was also a gradual rebound of attentional enhancement of the previously relevant stimulus. Only after an additional 110 ms did endogenous disengagement of attention from this previously relevant stimulus become evident. These patterns of attentional modulation can be most parsimoniously explained by assuming two distinct attentional mechanisms drawing on the same capacity-limited system, with exogenous attention having a much faster time course than endogenous attention.

V1 microcircuits underlying mouse visual behavior.

Visual behavior is based on the concerted activity of neurons in visual areas, where sensory signals are integrated with top-down information. In the past decade, the advent of new tools, such as functional imaging of populations of identified single neurons, high-density electrophysiology, virus-assisted circuit mapping, and precisely timed, cell-type specific manipulations, has advanced our understanding of the neuronal microcircuits underlying visual behavior. Studies in head-fixed mice, where such tools can routinely be applied, begin to provide new insights into the neural code of primary visual cortex (V1) underlying visual perception, and the micro-circuits of attention, predictive processing, and learning.

Visual attention: of features and transparent surfaces.

A recent report by Wannig et al. demonstrated the effects of selectively attending to individual surfaces in transparent motion patterns on neurons in the middle temporal area of awake, behaving monkeys. The study illustrates a highly adaptive and flexible attentional modulation of sensory responses.

Effects of attention on perceptual direction tuning curves in the human visual system.

In sensory neurophysiology, reverse correlation analyses have advanced our understanding of the spatio-temporal structure of receptive fields (RFs) and the tuning properties of individual neurons. Here, we used a psychophysical variant of the motion reverse correlation technique to investigate how visual selective attention influences human perceptual tuning curves for direction of motion. Direction tuning functions were computed by reverse correlating speeded target-present responses of human observers with a random sequence of brief, fully coherent motion impulses. We found that attention enhanced the amplitude of perceptual tuning curves for direction of motion, while tuning width remained unaffected. Furthermore, the full direction tuning profile across time could be well fitted by a separable model of direction and temporal tuning. Attention enhanced both the direction tuning and its temporal profile, without shifts or changes in shape. Thus, attention exerts a multiplicative effect on human perceptual tuning curves for direction of motion. An analysis of second-order correlations revealed a boost in the likelihood of responses to the target direction when it was followed by a motion impulse in the opposite direction. This perceptual effect might be mediated by biphasic neurons that are preferentially activated by a rapid succession of opposite motion directions.

Spatial and feature-based effects of exogenous cueing on visual motion processing.

In two experiments, we investigated the effects of exogenous cueing on visual motion processing. The first experiment shows that the typical pattern of reaction time (RT) effects, namely early facilitation and later inhibition of return (IOR), can be obtained using a color change as exogenous cue and a direction change as target. In the second experiment, we manipulated the validity of the cue independently with respect to location and feature using transparent motion stimuli. Facilitation of RTs with short cue-target interstimulus-intervals (ISIs) was only evident for targets with both the valid location and the valid feature. Furthermore, at longer cue-target intervals, RTs were prolonged for targets at the cued location, irrespective of the cued feature. These results demonstrate spatial and feature-based components of early facilitation and purely spatial IOR.

Feature-based attentional integration of color and visual motion.

In four variants of a speeded target detection task, we investigated the processing of color and motion signals in the human visual system. Participants were required to attend to both a particular color and direction of motion in moving random dot patterns (RDPs) and to report the appearance of the designated targets. Throughout, reaction times (RTs) to simultaneous presentations of color and direction targets were too fast to be reconciled with models proposing separate and independent processing of such stimulus dimensions. Thus, the data provide behavioral evidence for an integration of color and motion signals. This integration occurred even across superimposed surfaces in a transparent motion stimulus and also across spatial locations, arguing against object- and location-based accounts of attentional selection in such a task. Overall, the pattern of results can be best explained by feature-based mechanisms of visual attention.

Effects of locomotion extend throughout the mouse early visual system.

BACKGROUND: Neural responses in visual cortex depend not only on sensory input but also on behavioral context. One such context is locomotion, which modulates single-neuron activity in primary visual cortex (V1). How locomotion affects neuronal populations across cortical layers and in precortical structures is not well understood. RESULTS: We performed extracellular multielectrode recordings in the visual system of mice during locomotion and stationary periods. We found that locomotion influenced activity of V1 neurons with a characteristic laminar profile and shaped the population response by reducing pairwise correlations. Although the reduction of pairwise correlations was restricted to cortex, locomotion slightly but consistently increased firing rates and controlled tuning selectivity already in the dorsolateral geniculate nucleus (dLGN) of the thalamus. At the level of the eye, increases in locomotion speed were associated with pupil dilation. CONCLUSIONS: These findings document further, nonmultiplicative effects of locomotion, reaching earlier processing stages than cortex.

Visual cortical networks: of mice and men.

The visual cortical network consists of a number of specialized areas that are connected in a highly structured way. Understanding the function of this network is a milestone goal of visual neuroscience. This goal is pursued at different levels of description, including large-scale neuroanatomical as well as molecular and cellular perspectives. As a consequence, visual cortical networks are studied with a diverse set of methods across the order of mammalian species, ranging from the human all the way down to the mouse. Remarkable progress has been made at both ends of the spectrum. On the basis of work in humans, the last decade has seen ongoing refinements of the intricate functional organization of the cortical visual network. Neuroimaging studies have opened up the possibility to map individual visual areas, characterize their function and, search for an overarching organizational principle. Meanwhile, the mouse has become a valuable model system for early visual processing. A number of studies have demonstrated that basic response properties observed in higher-order mammals are also present in the mouse, making it possible to apply genetic tools to study visual network function. Here, we discuss the progress in these two fields side-by-side. We summarize new findings that have shaped our current understanding of the human cortical network. In addition, we review recent work that has laid the foundation for a mouse model of visual cortical processing. Although their brains are different, the visual cortical networks of mice and men share structural and functional principles.

Response-level probability effects on reaction time: now you see them, now you don't.

Many reaction time (RT) experiments have tested for response-level probability effects. Their results have been mixed, which is surprising because psychophysiological studies provide clear evidence of motor-level changes associated with an anticipated response. A survey of the designs used in the RT studies reveals many potential problems that could conceal the effects of response probability. We report five new RT experiments testing for response-level probability effects with the most promising of the previous designs-that of Blackman ( 1972 )-and with new designs. Some of these experiments yield evidence of response-level probability effects, but others do not. It appears that response-level probability effects are present primarily in simple tasks with a strong emphasis on response preparation, possibly because participants only expend effort on response preparation in these tasks.