A dynamic sequence of visual processing initiated by gaze shifts.

Animals move their head and eyes as they explore the visual scene. Neural correlates of these movements have been found in rodent primary visual cortex (V1), but their sources and computational roles are unclear. We addressed this by combining head and eye movement measurements with neural recordings in freely moving mice. V1 neurons responded primarily to gaze shifts, where head movements are accompanied by saccadic eye movements, rather than to head movements where compensatory eye movements stabilize gaze. A variety of activity patterns followed gaze shifts and together these formed a temporal sequence that was absent in darkness. Gaze-shift responses resembled those evoked by sequentially flashed stimuli, suggesting a large component corresponds to onset of new visual input. Notably, neurons responded in a sequence that matches their spatial frequency bias, consistent with coarse-to-fine processing. Recordings in freely gazing marmosets revealed a similar sequence following saccades, also aligned to spatial frequency preference. Our results demonstrate that active vision in both mice and marmosets consists of a dynamic temporal sequence of neural activity associated with visual sampling.

Joint coding of visual input and eye/head position in V1 of freely moving mice.

Visual input during natural behavior is highly dependent on movements of the eyes and head, but how information about eye and head position is integrated with visual processing during free movement is unknown, as visual physiology is generally performed under head fixation. To address this, we performed single-unit electrophysiology in V1 of freely moving mice while simultaneously measuring the mouse's eye position, head orientation, and the visual scene from the mouse's perspective. From these measures, we mapped spatiotemporal receptive fields during free movement based on the gaze-corrected visual input. Furthermore, we found a significant fraction of neurons tuned for eye and head position, and these signals were integrated with visual responses through a multiplicative mechanism in the majority of modulated neurons. These results provide new insight into coding in the mouse V1 and, more generally, provide a paradigm for investigating visual physiology under natural conditions, including active sensing and ethological behavior.

Distance estimation from monocular cues in an ethological visuomotor task.

In natural contexts, sensory processing and motor output are closely coupled, which is reflected in the fact that many brain areas contain both sensory and movement signals. However, standard reductionist paradigms decouple sensory decisions from their natural motor consequences, and head-fixation prevents the natural sensory consequences of self-motion. In particular, movement through the environment provides a number of depth cues beyond stereo vision that are poorly understood. To study the integration of visual processing and motor output in a naturalistic task, we investigated distance estimation in freely moving mice. We found that mice use vision to accurately jump across a variable gap, thus directly coupling a visual computation to its corresponding ethological motor output. Monocular eyelid suture did not affect gap jumping success, thus mice can use cues that do not depend on binocular disparity and stereo vision. Under monocular conditions, mice altered their head positioning and performed more vertical head movements, consistent with a shift from using stereopsis to other monocular cues, such as motion or position parallax. Finally, optogenetic suppression of primary visual cortex impaired task performance under both binocular and monocular conditions when optical fiber placement was localized to binocular or monocular zone V1, respectively. Together, these results show that mice can use monocular cues, relying on visual cortex, to accurately judge distance. Furthermore, this behavioral paradigm provides a foundation for studying how neural circuits convert sensory information into ethological motor output.

Dynamics of gaze control during prey capture in freely moving mice.

Many studies of visual processing are conducted in constrained conditions such as head- and gaze-fixation, and therefore less is known about how animals actively acquire visual information in natural contexts. To determine how mice target their gaze during natural behavior, we measured head and bilateral eye movements in mice performing prey capture, an ethological behavior that engages vision. We found that the majority of eye movements are compensatory for head movements, thereby serving to stabilize the visual scene. During movement, however, periods of stabilization are interspersed with non-compensatory saccades that abruptly shift gaze position. Notably, these saccades do not preferentially target the prey location. Rather, orienting movements are driven by the head, with the eyes following in coordination to sequentially stabilize and recenter the gaze. These findings relate eye movements in the mouse to other species, and provide a foundation for studying active vision during ethological behaviors in the mouse.

As you read this sentence, your eyes will move automatically from one word to the next, while your head remains still. Moving your eyes enables you to view each word using your central ­ as opposed to peripheral ­ vision. Central vision allows you to see objects in fine detail. It relies on a specialized area of the retina called the fovea. When you move your eyes across a page, you keep the images of the words you are currently reading on the fovea. This provides the detailed vision required for reading. The same process works for tracking moving objects. When watching a bird fly across the sky, you can track its progress by moving your eyes to keep the bird in the center of your visual field, over the fovea. But the majority of mammals do not have a fovea, and yet are still able to track moving targets. Think of a lion hunting a gazelle, for instance, or a cat stalking a mouse. Even mice themselves can track and capture insect prey such as crickets, despite not having a fovea. And yet, exactly how they do this is unknown. This is particularly surprising given that mice have long been used to study the neural basis of vision. By fitting mice with miniature head-mounted cameras, Michaiel et al. now reveal how the rodents track and capture moving crickets. It turns out that unlike animals with a fovea, mice do not use eye movements to track moving objects. Instead, when a mouse wants to look at something new, it moves its head to point at the target. The eyes then follow and 'land' on the target. In essence, head movements lead the way and the eyes catch up afterwards. These findings are consistent with the idea that mammals with large heads evolved eye movements to overcome the energy costs of turning the head whenever they want to look at something new. For small animals, moving the head is less energetically expensive. As a result, being able to move the eyes independent of the head is unnecessary. Future work could use a combination of behavioral experiments and brain recordings to reveal how visual areas of the brain process what an animal is seeing in real time.

Variation in sequence dynamics improves maintenance of stereotyped behavior in an example from bird song.

Performing a stereotyped behavior successfully over time requires both maintaining performance quality and adapting efficiently to environmental or physical changes affecting performance. The bird song system is a paradigmatic example of learning a stereotyped behavior and therefore is a good place to study the interaction of these two goals. Through a model of bird song learning, we show how instability in neural representation of stable behavior confers advantages for adaptation and maintenance with minimal cost to performance quality. A precise, temporally sparse sequence from the premotor nucleus HVC is crucial to the performance of song in songbirds. We find that learning in the presence of sequence variations facilitates rapid relearning after shifts in the target song or muscle structure and results in decreased error with neuron loss. This robustness is due to the prevention of the buildup of correlations in the learned connectivity. In the absence of sequence variations, these correlations grow, due to the relatively low dimensionality of the exploratory variation in comparison with the number of plastic synapses. Our results suggest one would expect to see variability in neural systems executing stereotyped behaviors, and this variability is an advantageous feature rather than a challenge to overcome.