Ferrets as a Model for Higher-Level Visual Motion Processing

Development of Higher-Level Vision: A Network Perspective

Most studies on the development of the visual system have focused on the mechanisms shaping early visual stages up to the level of primary visual cortex (V1). Much less is known about the development of the stages after V1 that handle the higher visual functions fundamental to everyday life. The standard model for the maturation of these areas is that it occurs sequentially, according to the positions of areas in the adult hierarchy. Yet, the existing literature reviewed here paints a different picture, one in which the adult configuration emerges through a sequence of unique network configurations that are not mere partial versions of the adult hierarchy. In addition to studying higher visual development per se to fill major gaps in knowledge, it will be crucial to adopt a network-level perspective in future investigations to unravel normal developmental mechanisms, identify vulnerabilities to developmental disorders, and eventually devise treatments for these disorders.

Ferret as a model system for studying the anatomy and function of the prefrontal cortex: A systematic review

There is a lack of consensus on anatomical nomenclature, standards of documentation, and functional equivalence of the frontal cortex between species. There remains a major gap between human prefrontal function and interpretation of findings in the mouse brain that appears to lack several key prefrontal areas involved in cognition and psychiatric illnesses. The ferret is an emerging model organism that has gained traction as an intermediate model species for the study of top-down cognitive control and other higher-order brain functions. However, this research has yet to benefit from synthesis. Here, we provide a summary of all published research pertaining to the frontal and/or prefrontal cortex of the ferret across research scales. The targeted location within the ferret brain is summarized visually for each experiment, and the anatomical terminology used at time of publishing is compared to what would be the appropriate term to use presently. By doing so, we hope to improve clarity in the interpretation of both previous and future publications on the comparative study of frontal cortex.

The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition

The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.

The Cousa objective: a long-working distance air objective for multiphoton imaging in vivo

Multiphoton microscopy can resolve fluorescent structures and dynamics deep in scattering tissue and has transformed neural imaging, but applying this technique in vivo can be limited by the mechanical and optical constraints of conventional objectives. Short working distance objectives can collide with compact surgical windows or other instrumentation and preclude imaging. Here we present an ultra-long working distance (20 mm) air objective called the Cousa objective. It is optimized for performance across multiphoton imaging wavelengths, offers a more than 4 mm2 field of view with submicrometer lateral resolution and is compatible with commonly used multiphoton imaging systems. A novel mechanical design, wider than typical microscope objectives, enabled this combination of specifications. We share the full optical prescription, and report performance including in vivo two-photon and three-photon imaging in an array of species and preparations, including nonhuman primates. The Cousa objective can enable a range of experiments in neuroscience and beyond.

Hierarchical temporal prediction captures motion processing along the visual pathway

Visual neurons respond selectively to features that become increasingly complex from the eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) neurons prefer moving bars, and those in higher cortical areas favor complex features like moving textures. Previously, we showed that V1 simple cell tuning can be accounted for by a basic model implementing temporal prediction - representing features that predict future sensory input from past input (Singer et al., 2018). Here, we show that hierarchical application of temporal prediction can capture how tuning properties change across at least two levels of the visual system. This suggests that the brain does not efficiently represent all incoming information; instead, it selectively represents sensory inputs that help in predicting the future. When applied hierarchically, temporal prediction extracts time-varying features that depend on increasingly high-level statistics of the sensory input.

Developmental alignment of feedforward inputs and recurrent network activity drives increased response selectivity and reliability in primary visual cortex following the onset of visual experience

Selective and reliable cortical sensory representations depend on synaptic interactions between feedforward inputs, conveying information from lower levels of the sensory pathway, and recurrent networks that reciprocally connect neurons functioning at the same hierarchical level. Here we explore the development of feedforward/recurrent interactions in primary visual cortex of the ferret that is responsible for the representation of orientation, focusing on the feedforward inputs from cortical layer 4 and its relation to the modular recurrent network in layer 2/3 before and after the onset of visual experience. Using simultaneous laminar electrophysiology and calcium imaging we found that in experienced animals, individual layer 4 and layer 2/3 neurons exhibit strongly correlated responses with the modular recurrent network structure in layer 2/3. Prior to experience, layer 2/3 neurons exhibit comparable modular correlation structure, but this correlation structure is missing for individual layer 4 neurons. Further analysis of the receptive field properties of layer 4 neurons in naïve animals revealed that they exhibit very poor orientation tuning compared to layer 2/3 neurons at this age, and this is accompanied by the lack of spatial segregation of ON and OFF subfields, the definitive property of layer 4 simple cells in experienced animals. Analysis of the response dynamics of layer 2/3 neurons with whole-cell patch recordings confirms that individual layer 2/3 neurons in naïve animals receive poorly-selective feedforward input that does not align with the orientation preference of the layer 2/3 responses. Further analysis reveals that the misaligned feedforward input is the underlying cause of reduced selectivity and increased response variability that is evident in the layer 2/3 responses of naïve animals. Altogether, our experiments indicate that the onset of visual experience is accompanied by a critical refinement in the responses of layer 4 neurons and the alignment of feedforward and recurrent networks that increases the selectivity and reliability of the representation of orientation in V1.

Selective representations of texture and motion in mouse higher visual areas

The mouse visual cortex contains interconnected higher visual areas, but their functional specializations are unclear. Here, we used a data-driven approach to examine the representations of complex visual stimuli by L2/3 neurons across mouse higher visual areas, measured using large-field-of-view two-photon calcium imaging. Using specialized stimuli, we found higher fidelity representations of texture in area LM, compared to area AL. Complementarily, we found higher fidelity representations of motion in area AL, compared to area LM. We also observed this segregation of information in response to naturalistic videos. Finally, we explored how receptive field models of visual cortical neurons could produce the segregated representations of texture and motion we observed. These selective representations could aid in behaviors such as visually guided navigation.

Morphological evidence for multiple distinct channels of corticogeniculate feedback originating in mid-level extrastriate visual areas of the ferret

Complementary reciprocal feedforward and feedback circuits connecting the visual thalamus with the visual cortex are essential for visual perception. These circuits predominantly connect primary and secondary visual cortex with the dorsal lateral geniculate nucleus (LGN). Although there are direct geniculocortical inputs to extrastriate visual cortex, whether reciprocal corticogeniculate neurons exist in extrastriate cortex is not known. Here we utilized virus-mediated retrograde tracing to reveal the presence of corticogeniculate neurons in three mid-level extrastriate visual cortical areas in ferrets: PMLS, PLLS, and 21a. We observed corticogeniculate neurons in all three extrastriate areas, although the density of virus-labeled corticogeniculate neurons in extrastriate cortex was an order of magnitude less than that in areas 17 and 18. A cluster analysis of morphological metrics quantified following reconstructions of the full dendritic arborizations of virus-labeled corticogeniculate neurons revealed six distinct cell types. Similar corticogeniculate cell types to those observed in areas 17 and 18 were also observed in PMLS, PLLS, and 21a. However, these unique cell types were not equally distributed across the three extrastriate areas. The majority of corticogeniculate neurons per cluster originated in a single area, suggesting unique parallel organizations for corticogeniculate feedback from each extrastriate area to the LGN. Together, our findings demonstrate direct feedback connections from mid-level extrastriate visual cortex to the LGN, supporting complementary reciprocal circuits at multiple processing stages along the visual hierarchy. Importantly, direct reciprocal connections between the LGN and extrastriate cortex, that bypass V1, could provide a substrate for residual vision following V1 damage.

Development of visual motion integration involves coordination of multiple cortical stages

A central feature of cortical function is hierarchical processing of information. Little is currently known about how cortical processing cascades develop. Here, we investigate the joint development of two nodes of the ferret’s visual motion pathway, primary visual cortex (V1), and higher-level area PSS. In adult animals, motion processing transitions from local to global computations between these areas. We now show that PSS global motion signals emerge a week after the development of V1 and PSS direction selectivity. Crucially, V1 responses to more complex motion stimuli change in parallel, in a manner consistent with supporting increased PSS motion integration. At the same time, these V1 responses depend on feedback from PSS. Our findings suggest that development does not just proceed in parallel in different visual areas, it is coordinated across network nodes. This has important implications for understanding how visual experience and developmental disorders can influence the developing visual system.

From Neurons to Cognition: Technologies for Precise Recording of Neural Activity Underlying Behavior

Understanding how brain activity encodes information and controls behavior is a long-standing question in neuroscience. This complex problem requires converging efforts from neuroscience and engineering, including technological solutions to perform high-precision and large-scale recordings of neuronal activity in vivo as well as unbiased methods to reliably measure and quantify behavior. Thanks to advances in genetics, molecular biology, engineering, and neuroscience, in recent decades, a variety of optical imaging and electrophysiological approaches for recording neuronal activity in awake animals have been developed and widely applied in the field. Moreover, sophisticated computer vision and machine learning algorithms have been developed to analyze animal behavior. In this review, we provide an overview of the current state of technology for neuronal recordings with a focus on optical and electrophysiological methods in rodents. In addition, we discuss areas that future technological development will need to cover in order to further our understanding of the neural activity underlying behavior.

Neuroanatomy and Sampling of Central Projections for the Visual System in Mammals Used in Toxicity Testing

Visual system toxicity may manifest anywhere in the visual system, from the eye proper to the visual brain. Therefore, effective screening for visual system toxicity must evaluate not only ocular structures (ie, eye and optic nerve) but also multiple key brain regions involved in vision (eg, optic tract, subcortical relay nuclei, and primary and secondary visual cortices). Despite a generally comparable pattern across species, the neuroanatomic organization and function of the visual brain in rodents and rabbits exhibit appreciable differences relative to nonrodents. Currently recognized sampling practices for general toxicity studies in animals, which are based on easily discerned external neuroanatomic landmarks and guided by extant stereotaxic brain atlases, typically will permit histopathologic evaluation of many brain centers involved in visual sensation (eg, optic chiasm, optic tract, dorsal lateral geniculate nucleus, primary and secondary visual cortices) and often some subcortical brain nuclei involved in light-modulated nonvisual activities needed for visual attention and orientation (eg, rostral colliculus in quadrupeds, termed the superior colliculus in bipeds; several cranial nerve nuclei). Pathologic findings induced by toxicants in the visual brain centers are similar to those that are produced in other brain regions.

Visual Corticocortical Inputs to Ferret Area 18

Visual cortical areas in the adult mammalian brain are linked by a network of interareal feedforward and feedback circuits. We investigated the topography of feedback projections to ferret (Mustela putorius furo) area 18 from extrastriate areas 19, 21, and Ssy. Our objective was to characterize the anatomical organization of the extrastriate feedback pool to area 18. We also wished to determine if feedback projections to area 18 share similar features as feedback projections to area 17. We injected the tracer cholera toxin B subunit (CTb) into area 18 of adult ferrets to visualize the distribution and pattern of retrogradely labeled cells in extrastriate cortex. We find several similarities to the feedback projection to area 17: (i) Multiple visual cortical areas provide feedback to area 18: areas 19, 21, Ssy, and weaker inputs from posterior parietal and lateral temporal visual areas. Within each area a greater proportion of feedback projections arises from the infragranular than from the supragranular layers. (ii) The cortical area immediately rostral to area 18 provides the greatest proportion of total cortical feedback, and has the greatest peak density of cells providing feedback to area 18. (iii) The spacing (peak cell density and nearest neighbor distances) of cells in extrastriate cortex providing feedback to areas 17 and 18 are similar. However, peak density of feedback cells to area 18 is comparable in the supra- and infragranular layers, whereas peak density of feedback cells to area 17 is higher in the infragranular layers. Another prominent difference is that dorsal area 18 receives a cortical input that area 17 does not: from ventral cortex representing the upper visual field; this appears to be roughly 25% of the feedback input to area 18. Lastly, area 17 receives a greater proportion of cortical feedback from area 21 than from Ssy, whereas area 18 receives more feedback from Ssy than from area 21. While the organization of feedback projections from extrastriate cortex to areas 17 and 18 is broadly similar, the main difference in input topography might arise due to differences in visual field representations of the two areas.

Seasonal weight changes in laboratory ferrets

Ferrets (Mustela putorius furo) are a valuable animal model used in biomedical research. Like many animals, ferrets undergo significant variation in body weight seasonally, affected by photoperiod, and these variations complicate the use weight as an indicator of health status. To overcome this requires a better understanding of these seasonal weight changes. We provide a normative weight data set for the female ferret accounting for seasonal changes, and also investigate the effect of fluid regulation on weight change. Female ferrets (n = 39) underwent behavioural testing from May 2017 to August 2019 and were weighed daily, while housed in an animal care facility with controlled light exposure. In the winter (October to March), animals experienced 10 hours of light and 14 hours of dark, while in summer (March to October), this contingency was reversed. Individual animals varied in their body weight from approximately 700 to 1200 g. However, weights fluctuated with light cycle, with animals losing weight in summer, and gaining weight in winter such that they fluctuated between approximately 80% and 120% of their long-term average. Ferrets were weighed as part of their health assessment while experiencing water regulation for behavioural training. Water regulation superimposed additional weight changes on these seasonal fluctuations, with weight loss during the 5-day water regulation period being greater in summer than winter. Analysing the data with a Generalised Linear Model confirmed that the percentage decrease in weight per week was relatively constant throughout the summer months, while the percentage increase in body weight per week in winter decreased through the season. Finally, we noted that the timing of oestrus was reliably triggered by the increase in day length in spring. These data establish a normative benchmark for seasonal weight variation in female ferrets that can be incorporated into the health assessment of an animal's condition.

Mapping the Architecture of Ferret Brains at Single-Cell Resolution

Mapping the cytoarchitecture of the whole brain can reveal the organizational logic of neural systems. However, this remains a significant challenge, especially for gyrencephalic brains with a large volume. Here we propose an integrated pipeline for generating a cytoarchitectonic atlas with single-cell resolution of the whole brain. To analyze a large-volume brain, we used a modified en-bloc Nissl staining protocol to achieve uniform staining of large-scale brain specimens from ferret (Mustela putorius furo). By combining whole-brain imaging and big data processing, we established strategies for parsing cytoarchitectural information at a voxel resolution of 0.33 μm × 0.33 μm × 1 μm and terabyte-scale data analysis. Using the cytoarchitectonic datasets for adult ferret brain, we identified giant pyramidal neurons in ferret brains and provide the first report of their morphological diversity, neurochemical phenotype, and distribution patterns in the whole brain in three dimensions. This pipeline will facilitate studies on the organization and development of the mammalian brains, from that of rodents to the gyrencephalic brains of ferret and even primates.

Visual Motion and Form Integration in the Behaving Ferret

Ferrets have become a standard animal model for the development of early visual stages. Less is known about higher-level vision in ferrets, both during development and in adulthood. Here, as a step towards establishing higher-level vision research in ferrets, we used behavioral experiments to test the motion and form integration capacity of adult ferrets. Motion integration was assessed by training ferrets to discriminate random dot kinematograms (RDK) based on their direction. Task difficulty was varied systematically by changing RDK coherence levels, which allowed the measurement of motion integration thresholds. Form integration was measured analogously by training ferrets to discriminate linear Glass patterns of varying coherence levels based on their orientation. In all experiments, ferrets proved to be good psychophysical subjects that performed tasks reliably. Crucially, the behavioral data showed clear evidence of perceptual motion and form integration. In the monkey, motion and form integration are usually associated with processes occurring in higher-level visual areas. In a second set of experiments, we therefore tested whether PSS, a higher-level motion area in the ferret, could similarly support motion integration behavior in this species. To this end, we measured responses of PSS neurons to RDK of different coherence levels. Indeed, neurometric functions for PSS were in good agreement with the behaviorally derived psychometric functions. In conclusion, our experiments demonstrate that ferrets are well suited for higher-level vision research.