Interactions between rodent visual and spatial systems during navigation.

Many behaviours that are critical for animals to survive and thrive rely on spatial navigation. Spatial navigation, in turn, relies on internal representations about one's spatial location, one's orientation or heading direction and the distance to objects in the environment. Although the importance of vision in guiding such internal representations has long been recognized, emerging evidence suggests that spatial signals can also modulate neural responses in the central visual pathway. Here, we review the bidirectional influences between visual and navigational signals in the rodent brain. Specifically, we discuss reciprocal interactions between vision and the internal representations of spatial position, explore the effects of vision on representations of an animal's heading direction and vice versa, and examine how the visual and navigational systems work together to assess the relative distances of objects and other features. Throughout, we consider how technological advances and novel ethological paradigms that probe rodent visuo-spatial behaviours allow us to advance our understanding of how brain areas of the central visual pathway and the spatial systems interact and enable complex behaviours.

Redefining sensorimotor mismatch selectivity in the visual cortex.

This Matters Arising Response contains our commentary to the response written by Vasilevskaya et al., 2023, publishing concurrently in Cell Reports, for our recent article "Feature selectivity can explain mismatch signals in mouse visual cortex." We find that results in the response reinforced many of our findings and, further supported by their new results, we argue for the necessity to redefine sensorimotor mismatch selectivity in the mouse visual system.

Walking humans and running mice: perception and neural encoding of optic flow during self-motion.

Locomotion produces full-field optic flow that often dominates the visual motion inputs to an observer. The perception of optic flow is in turn important for animals to guide their heading and interact with moving objects. Understanding how locomotion influences optic flow processing and perception is therefore essential to understand how animals successfully interact with their environment. Here, we review research investigating how perception and neural encoding of optic flow are altered during self-motion, focusing on locomotion. Self-motion has been found to influence estimation and sensitivity for optic flow speed and direction. Nonvisual self-motion signals also increase compensation for self-driven optic flow when parsing the visual motion of moving objects. The integration of visual and nonvisual self-motion signals largely follows principles of Bayesian inference and can improve the precision and accuracy of self-motion perception. The calibration of visual and nonvisual self-motion signals is dynamic, reflecting the changing visuomotor contingencies across different environmental contexts. Throughout this review, we consider experimental research using humans, non-human primates and mice. We highlight experimental challenges and opportunities afforded by each of these species and draw parallels between experimental findings. These findings reveal a profound influence of locomotion on optic flow processing and perception across species. This article is part of a discussion meeting issue 'New approaches to 3D vision'.

Altered low-frequency brain rhythms precede changes in gamma power during tauopathy.

Neurodegenerative disorders are associated with widespread disruption to brain activity and brain rhythms. Some disorders are linked to dysfunction of the membrane-associated protein Tau. Here, we ask how brain rhythms are affected in rTg4510 mouse model of tauopathy, at an early stage of tauopathy (5 months), and at a more advanced stage (8 months). We measured brain rhythms in primary visual cortex in presence or absence of visual stimulation, while monitoring pupil diameter and locomotion to establish behavioral state. At 5 months, we found increased low-frequency rhythms during resting state in tauopathic animals, associated with periods of abnormally increased neural synchronization. At 8 months, this increase in low-frequency rhythms was accompanied by a reduction of power in the gamma range. Our results therefore show that slower rhythms are impaired earlier than gamma rhythms in this model of tauopathy, and suggest that electrophysiological measurements can track the progression of tauopathic neurodegeneration.

Midbrain dopamine neurons signal phasic and ramping reward prediction error during goal-directed navigation.

Goal-directed navigation requires learning to accurately estimate location and select optimal actions in each location. Midbrain dopamine neurons are involved in reward value learning and have been linked to reward location learning. They are therefore ideally placed to provide teaching signals for goal-directed navigation. By imaging dopamine neural activity as mice learned to actively navigate a closed-loop virtual reality corridor to obtain reward, we observe phasic and pre-reward ramping dopamine activity, which are modulated by learning stage and task engagement. A Q-learning model incorporating position inference recapitulates our results, displaying prediction errors resembling phasic and ramping dopamine neural activity. The model predicts that ramping is followed by improved task performance, which we confirm in our experimental data, indicating that the dopamine ramp may have a teaching effect. Our results suggest that midbrain dopamine neurons encode phasic and ramping reward prediction error signals to improve goal-directed navigation.

Functional Organisation of the Mouse Superior Colliculus.

The superior colliculus (SC) is a highly conserved area of the mammalian midbrain that is widely implicated in the organisation and control of behaviour. SC receives input from a large number of brain areas, and provides outputs to a large number of areas. The convergence and divergence of anatomical connections with different areas and systems provides challenges for understanding how SC contributes to behaviour. Recent work in mouse has provided large anatomical datasets, and a wealth of new data from experiments that identify and manipulate different cells within SC, and their inputs and outputs, during simple behaviours. These data offer an opportunity to better understand the roles that SC plays in these behaviours. However, some of the observations appear, at first sight, to be contradictory. Here we review this recent work and hypothesise a simple framework which can capture the observations, that requires only a small change to previous models. Specifically, the functional organisation of SC can be explained by supposing that three largely distinct circuits support three largely distinct classes of simple behaviours-arrest, turning towards, and the triggering of escape or capture. These behaviours are hypothesised to be supported by the optic, intermediate and deep layers, respectively.

Plasticity in visual cortex is disrupted in a mouse model of tauopathy.

Alzheimer's disease and other dementias are thought to underlie a progressive impairment of neural plasticity. Previous work in mouse models of Alzheimer's disease shows pronounced changes in artificially-induced plasticity in hippocampus, perirhinal and prefrontal cortex. However, it is not known how degeneration disrupts intrinsic forms of brain plasticity. Here we characterised the impact of tauopathy on a simple form of intrinsic plasticity in the visual system, which allowed us to track plasticity at both long (days) and short (minutes) timescales. We studied rTg4510 transgenic mice at early stages of tauopathy (5 months) and a more advanced stage (8 months). We recorded local field potentials in the primary visual cortex while animals were repeatedly exposed to a stimulus over 9 days. We found that both short- and long-term visual plasticity were already disrupted at early stages of tauopathy, and further reduced in older animals, such that it was abolished in mice expressing mutant tau. Additionally, visually evoked behaviours were disrupted in both younger and older mice expressing mutant tau. Our results show that visual cortical plasticity and visually evoked behaviours are disrupted in the rTg4510 model of tauopathy. This simple measure of plasticity may help understand how tauopathy disrupts neural circuits, and offers a translatable platform for detection and tracking of the disease.

Feature selectivity can explain mismatch signals in mouse visual cortex.

Sensory experience often depends on one's own actions, including self-motion. Theories of predictive coding postulate that actions are regulated by calculating prediction error, which is the difference between sensory experience and expectation based on self-generated actions. Signals consistent with prediction error have been reported in the mouse visual cortex (V1) when visual flow coupled to running was unexpectedly stopped. Here, we show that such signals can be elicited by visual stimuli uncoupled to an animal running. We record V1 neurons while presenting drifting gratings that unexpectedly stop. We find strong responses to visual perturbations, which are enhanced during running. Perturbation responses are strongest in the preferred orientation of individual neurons, and perturbation-responsive neurons are more likely to prefer slow visual speeds. Our results indicate that prediction error signals can be explained by the convergence of known motor and sensory signals, providing a purely sensory and motor explanation for purported mismatch signals.

Spatial modulation of dark versus bright stimulus responses in the mouse visual system.

A fundamental task of the visual system is to respond to both increases and decreases of luminance with action potentials (ON and OFF responses1-4). OFF responses are stronger, faster, and more salient than ON responses in primary visual cortex (V1) of both cats5,6 and primates,7,8 but in ferrets9 and mice,10 ON responses can be stronger, weaker,11 or balanced12 in comparison to OFF responses. These discrepancies could arise from differences in species, experimental techniques, or stimulus properties, particularly retinotopic location in the visual field, as has been speculated;9 however, the role of retinotopy for ON/OFF dominance has not been systematically tested across multiple scales of neural activity within species. Here, we measured OFF versus ON responses across large portions of visual space with silicon probe and whole-cell patch-clamp recordings in mouse V1 and lateral geniculate nucleus (LGN). We found that OFF responses dominated in the central visual field, whereas ON and OFF responses were more balanced in the periphery. These findings were consistent across local field potential (LFP), spikes, and subthreshold membrane potential in V1, and were aligned with spatial biases in ON and OFF responses in LGN. Our findings reveal that retinotopy may provide a common organizing principle for spatial modulation of OFF versus ON processing in mammalian visual systems.

Organization of feedback projections to mouse primary visual cortex.

Top-down, context-dependent modulation of visual processing has been a topic of wide interest, including in mouse primary visual cortex (V1). However, the organization of feedback projections to V1 is relatively unknown. Here, we investigated inputs to mouse V1 by injecting retrograde tracers. We developed a software pipeline that maps labeled cell bodies to corresponding brain areas in the Allen Reference Atlas. We identified more than 24 brain areas that provide inputs to V1 and quantified the relative strength of their projections. We also assessed the organization of the projections, based on either the organization of cell bodies in the source area (topography) or the distribution of projections across V1 (bias). Projections from most higher visual and some nonvisual areas to V1 showed both topography and bias. Such organization of feedback projections to V1 suggests that parts of the visual field are differentially modulated by context, which can be ethologically relevant for a navigating animal.

Creating and controlling visual environments using BonVision.

Real-time rendering of closed-loop visual environments is important for next-generation understanding of brain function and behaviour, but is often prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source software for the display of virtual or augmented reality, as well as standard visual stimuli. BonVision has been tested on humans and mice, and is capable of supporting new experimental designs in other animal models of vision. As the architecture is based on the open-source Bonsai graphical programming language, BonVision benefits from native integration with experimental hardware. BonVision therefore enables easy implementation of closed-loop experiments, including real-time interaction with deep neural networks, and communication with behavioural and physiological measurement and manipulation devices.

Spatial modulation of visual responses arises in cortex with active navigation.

During navigation, the visual responses of neurons in mouse primary visual cortex (V1) are modulated by the animal's spatial position. Here we show that this spatial modulation is similarly present across multiple higher visual areas but negligible in the main thalamic pathway into V1. Similar to hippocampus, spatial modulation in visual cortex strengthens with experience and with active behavior. Active navigation in a familiar environment, therefore, enhances the spatial modulation of visual signals starting in the cortex.

Mouse Visual Cortex Is Modulated by Distance Traveled and by Theta Oscillations.

The visual responses of neurons in the primary visual cortex (V1) are influenced by the animal's position in the environment [1-5]. V1 responses encode positions that co-fluctuate with those encoded by place cells in hippocampal area CA1 [2, 5]. This correlation might reflect a common influence of non-visual spatial signals on both areas. Place cells in CA1, indeed, do not rely only on vision; their place preference depends on the physical distance traveled [6-11] and on the phase of the 6-9 Hz theta oscillation [12, 13]. Are V1 responses similarly influenced by these non-visual factors? We recorded V1 and CA1 neurons simultaneously while mice performed a spatial task in a virtual corridor by running on a wheel and licking at a reward location. By changing the gain that couples the wheel movement to the virtual environment, we found that ∼20% of V1 neurons were influenced by the physical distance traveled, as were ∼40% of CA1 place cells. Moreover, the firing rate of ∼24% of V1 neurons was modulated by the phase of theta oscillations recorded in CA1 and the response profiles of ∼7% of V1 neurons shifted spatially across the theta cycle, analogous to the phase precession observed in ∼37% of CA1 place cells. The influence of theta oscillations on V1 responses was more prominent in putative layer 6. These results reveal that, in a familiar environment, sensory processing in V1 is modulated by the key non-visual signals that influence spatial coding in the hippocampus.

Two stream hypothesis of visual processing for navigation in mouse.

Vision research has traditionally been studied in stationary subjects observing stimuli, and rarely during navigation. Recent research using virtual reality environments for mice has revealed that responses even in the primary visual cortex are modulated by spatial context - identical scenes presented in different positions of a room can elicit different responses. Here, we review these results and discuss how information from visual areas can reach navigational areas of the brain. Based on the observation that mouse higher visual areas cover different parts of the visual field, we propose that spatial signals are processed along two-streams based on visual field coverage. Specifically, this hypothesis suggests that landmark related signals are processed by areas biased to the central field, and self-motion related signals are processed by areas biased to the peripheral field.

Layer-specific integration of locomotion and sensory information in mouse barrel cortex.

During navigation, rodents continually sample the environment with their whiskers. How locomotion modulates neuronal activity in somatosensory cortex, and how it is integrated with whisker-touch remains unclear. Here, we compared neuronal activity in layer 2/3 (L2/3) and L5 of barrel cortex using calcium imaging in mice running in a tactile virtual reality. Both layers increase their activity during running and concomitant whisking, in the absence of touch. Fewer neurons are modulated by whisking alone. Whereas L5 neurons respond transiently to wall-touch during running, L2/3 neurons show sustained activity. Consistently, neurons encoding running-with-touch are more abundant in L2/3 and they encode the run-speed better during touch. Few neurons across layers were also sensitive to abrupt perturbations of tactile flow during running. In summary, locomotion significantly enhances barrel cortex activity across layers with L5 neurons mainly reporting changes in touch conditions and L2/3 neurons continually integrating tactile stimuli with running.

Coherent encoding of subjective spatial position in visual cortex and hippocampus.

A major role of vision is to guide navigation, and navigation is strongly driven by vision1-4. Indeed, the brain's visual and navigational systems are known to interact5,6, and signals related to position in the environment have been suggested to appear as early as in the visual cortex6,7. Here, to establish the nature of these signals, we recorded in the primary visual cortex (V1) and hippocampal area CA1 while mice traversed a corridor in virtual reality. The corridor contained identical visual landmarks in two positions, so that a purely visual neuron would respond similarly at those positions. Most V1 neurons, however, responded solely or more strongly to the landmarks in one position rather than the other. This modulation of visual responses by spatial location was not explained by factors such as running speed. To assess whether the modulation is related to navigational signals and to the animal's subjective estimate of position, we trained the mice to lick for a water reward upon reaching a reward zone in the corridor. Neuronal populations in both CA1 and V1 encoded the animal's position along the corridor, and the errors in their representations were correlated. Moreover, both representations reflected the animal's subjective estimate of position, inferred from the animal's licks, better than its actual position. When animals licked in a given location-whether correctly or incorrectly-neural populations in both V1 and CA1 placed the animal in the reward zone. We conclude that visual responses in V1 are controlled by navigational signals, which are coherent with those encoded in hippocampus and reflect the animal's subjective position. The presence of such navigational signals as early as a primary sensory area suggests that they permeate sensory processing in the cortex.

Sensation during Active Behaviors.

A substantial portion of our sensory experience happens during active behaviors such as walking around or paying attention. How do sensory systems work during such behaviors? Neural processing in sensory systems can be shaped by behavior in multiple ways ranging from a modulation of responsiveness or sharpening of tuning to a dynamic change of response properties or functional connectivity. Here, we review recent findings on the modulation of sensory processing during active behaviors in different systems: insect vision, rodent thalamus, and rodent sensory cortices. We discuss the circuit-level mechanisms that might lead to these modulations and their potential role in sensory function. Finally, we highlight the open questions and future perspectives of this exciting new field.

Subcortical Source and Modulation of the Narrowband Gamma Oscillation in Mouse Visual Cortex.

Primary visual cortex exhibits two types of gamma rhythm: broadband activity in the 30-90 Hz range and a narrowband oscillation seen in mice at frequencies close to 60 Hz. We investigated the sources of the narrowband gamma oscillation, the factors modulating its strength, and its relationship to broadband gamma activity. Narrowband and broadband gamma power were uncorrelated. Increasing visual contrast had opposite effects on the two rhythms: it increased broadband activity, but suppressed the narrowband oscillation. The narrowband oscillation was strongest in layer 4 and was mediated primarily by excitatory currents entrained by the synchronous, rhythmic firing of neurons in the lateral geniculate nucleus (LGN). The power and peak frequency of the narrowband gamma oscillation increased with light intensity. Silencing the cortex optogenetically did not abolish the narrowband oscillation in either LGN firing or cortical excitatory currents, suggesting that this oscillation reflects unidirectional flow of signals from thalamus to cortex.