Physiology seminars

Many animals are highly visual. They view their world through photoreceptors sensitive to different wavelengths of light. Animal survival and optimal behavioral performance may select for varying photoreceptor sensitivities depending on animal habitat or visual tasks. Our goal is to understand what drives visual diversity from both an evolutionary and molecular perspective. The group of more than 2000 cichlid fish species are an ideal system for examining such diversity. Cichlid are a colorful group of fresh water fishes. They have undergone adaptive radiation throughout Africa and the new world and occur in rivers and lakes that vary in water clarity. They are also behaviorally complex, having diverse behaviors for foraging, mate choice and even parental care. As a result, cichlids have highly diverse visual systems with cone sensitivities shifting by 30-90 nm between species. Although this group has seven cone opsin genes, individual species differ in which subset of the cone opsins they express. Some species show developmental shifts in opsin expression, switching from shorter to longer wavelength opsins through ontogeny. Other species modify that developmental program to express just one of the sets, causing the large sensitivity differences. Cichlids are therefore natural mutants for opsin expression. We have used cichlid diversity to explore the relationship between visual sensitivities and ecology. We have also exploited the genomic power of the cichlid system to identify genes and mutations that cause opsin expression shifts. Ultimately, our goal is to learn how different cichlid species see the world and whether differences matter. Behavioral experiments suggest they do indeed use color vision to survive and thrive. Cichlids therefore are a unique model for exploring how visual systems evolve in a changing world.

Dysregulation of emotional processing and its integration with cognitive functions are central features of many mental/emotional disorders associated both with externalizing problems (aggressive, antisocial behaviors) and internalizing problems (anxiety, depression). As Dr. Joseph LeDoux, our invited speaker of this program, wrote in his famous book “Synaptic self: How Our Brains Become Who We Are”—the brain’s synapses—are the channels through which we think, act, imagine, feel, and remember. Synapses encode the essence of personality, enabling each of us to function as a distinctive, integrated individual from moment to moment. Thus, exploring the functioning of synapses leads to the understanding of the mechanism of (patho)physiological function of our brain. In this context, we have investigated the pathophysiology of psychiatric disorders, with particular emphasis on the synaptic function of model mice of various psychiatric disorders such as schizophrenia, autism, depression, and PTSD. Our current interest is how synaptic inputs are integrated to generate the action potential. Because the spatiotemporal organization of neuronal firing is crucial for information processing, but how thousands of inputs to the dendritic spines drive the firing remains a central question in neuroscience. We identified a distinct pattern of synaptic integration in the disease-related models, in which extra-large (XL) spines generate NMDA spikes within these spines, which was sufficient to drive neuronal firing. We experimentally and theoretically observed that XL spines negatively correlated with working memory. Our work offers a whole new concept for dendritic computation and network dynamics, and the understanding of psychiatric research will be greatly reconsidered. The second half of my talk is the development of a novel synaptic tool. Because, no matter how beautifully we can illuminate the spine morphology and how accurately we can quantify the synaptic integration, the links between synapse and brain function remain correlational. In order to challenge the causal relationship between synapse and brain function, we established AS-PaRac1, which is unique not only because it can specifically label and manipulate the recently potentiated dendritic spine (Hayashi-Takagi et al, 2015, Nature). With use of AS-PaRac1, we developed an activity-dependent simultaneous labeling of the presynaptic bouton and the potentiated spines to establish “functional connectomics” in a synaptic resolution. When we apply this new imaging method for PTSD model mice, we identified a completely new functional neural circuit of brain region A→B→C with a very strong S/N in the PTSD model mice. This novel tool of “functional connectomics” and its photo-manipulation could open up new areas of emotional/psychiatric research, and by extension, shed light on the neural networks that determine who we are.

Maintaining average activity level within a set-point range constitutes a fundamental property of central neural circuits. Accumulated evidence suggests that firing rate distributions and their means represent physiological variables regulated by homeostatic systems during sleep-wake cycle in central neural circuits. While intracellular Ca2+ has long been hypothesized as a feedback control signal, the source of Ca2+ and the molecular machinery enabling network-wide homeostatic responses remain largely unknown. I will present our hypothesis and framework on identifying homeostatic regulators in neural circuits. Next, I will show our new results on the role of mitochondria in the regulation of activity set-points and feedback responses. Finally, I will provide an evidence on state-dependent dysregulation of activity set-points at the presymptomatic disease stage in familial Alzheimer’s models.

In the past several years, I have been involved in building a biologically realistic model of the monkey visual cortex. Work on one of the input layers (4Ca) of the primary visual cortex (V1) is now nearly complete, and I would like to share some of what I have learned with the community. After a brief overview of the model and its capabilities, I would like to focus on three sets of results that represent three different aspects of the modeling. They are: (i) emergent E-I dynamics in local circuits; (ii) how visual cortical neurons acquire their ability to detect edges and directions of motion, and (iii) a view across the cortical surface: nonequilibrium steady states (in analogy with statistical mechanics) and beyond.

Stereopsis – deriving information about distance by comparing views from two eyes – is widespread in vertebrates but so far known in only class of invertebrates, the praying mantids. Understanding stereopsis which has evolved independently in such a different nervous system promises to shed light on the constraints governing any stereo system. Behavioral experiments indicate that insect stereopsis is functionally very different from that studied in vertebrates. Vertebrate stereopsis depends on matching up the pattern of contrast in the two eyes; it works in static scenes, and may have evolved in order to break camouflage rather than to detect distances. Insect stereopsis matches up regions of the image where the luminance is changing; it is insensitive to the detailed pattern of contrast and operates to detect the distance to a moving target. Work from my lab has revealed a network of neurons within the mantis brain which are tuned to binocular disparity, including some that project to early visual areas. This is in contrast to previous theories which postulated that disparity was computed only at a single, late stage, where visual information is passed down to motor neurons. Thus, despite their very different properties, the underlying neural mechanisms supporting vertebrate and insect stereopsis may be computationally more similar than has been assumed.

We have long known that rod and cone signals interact within the retina and can even contribute to color vision, but the extent of these influences has remained unclear. New results with more powerful methods of RNA expression profiling, specific cell labeling, and single-cell recording have provided greater clarity and are showing that rod and cone signals can mix at virtually every level of signal processing. These interactions influence the integration of retinal signals and make an important contribution to visual perception.

Sensory experience and perceptual learning changes receptive field properties of cortical pyramidal neurons possibly mediated by long-term potentiation (LTP) of synapses. We have previously shown in the mouse somatosensory cortex (S1) that sensory-driven LTP in layer (L) 2/3 pyramidal neurons is dependent on higher order thalamic feedback from the posteromedial nucleus (POm), which is thought to convey contextual information from various cortical regions integrated with sensory input. We have followed up on this work by dissecting the cortical microcircuitry that underlies this form of LTP. We found that repeated pairing of Pom thalamocortical and intracortical pathway activity in brain slices induces NMDAr-dependent LTP of the L2/3 synapses that are driven by the intracortical pathway. Repeated pairing also recruits activity of vasoactive intestinal peptide (VIP) interneurons, whereas it reduces the activity of somatostatin (SST) interneurons. VIP interneuron-mediated inhibition of SST interneurons has been established as a motif for the disinhibition of pyramidal neurons. By chemogenetic interrogation we found that activation of this disinhibitory microcircuit motif by higher-order thalamic feedback is indispensable for eliciting LTP. Preliminary results in vivo suggest that VIP neuron activity also increases during sensory-evoked LTP. Together, this suggests that the higherorder thalamocortical feedback may help modifying the strength of synaptic circuits that process first-order sensory information in S1. To start characterizing the relationship between higher-order feedback and cortical plasticity during learning in vivo, we adapted a perceptual learning paradigm in which head-fixed mice have to discriminate two types of textures in order to obtain a reward. POm axons or L2/3 pyramidal neurons labeled with the genetically encoded calcium indicator GCaMP6s were imaged during the acquisition of this task as well as the subsequent learning of a new discrimination rule. We found that a subpopulation of the POm axons and L2/3 neurons dynamically represent textures. Moreover, upon a change in reward contingencies, a fraction of the L2/3 neurons re-tune their selectivity to the texture that is newly associated with the reward. Altogether, our data indicates that higher-order thalamic feedback can facilitate synaptic plasticity and may be implicated in dynamic sensory stimulus representations in S1, which depends on higher-order features that are associated with the stimuli.

PIEZO ion channels detect force in cellular membranes. They are expressed in a wide variety of mammalian tissues, including the vasculature, lymphatic system, and the nervous system. We have found that PIEZO2 in sensory neurons is required for the mechanical senses of touch and proprioception, but our understanding of internal organ sensing, interoception, is far behind. I will describe our findings on the role of PIEZO ion channels in the lesser-known interoceptive senses in multiple organ systems.

Arguably one of the biggest mysteries in neuroscience is how the brain stores long-term memories. The major challenge for investigating the neural circuit underlying memory formation in the neocortex is the distributed nature of the resulting memory trace throughout the cortex. Here, we used a new behavioral paradigm that enabled us to generate memory traces in a specific cortical location and to specifically examine the mechanisms of memory formation in that region. We found that medial-temporal inputs arrive in neocortical layer 1 where the apical dendrites of cortical pyramidal neurons predominate. These dendrites have active properties that make them sensitive to contextual inputs from other areas that also send axons to layer 1 around the cortex. Blocking the influence of these medial-temporal inputs prevented learning and suppressed resulting dendritic activity. We conclude that layer 1 is the locus for hippocampal-dependent memory formation in the neocortex and propose that this process enhances the sensitivity of the tuft dendrites to contextual inputs.

The long-term goal of my research is to study the mammalian retina as a model for the central nervous system (CNS) -- to understand how it functions in physiological conditions, how it is formed, how it breaks down in pathological conditions, and how it can be repaired. I have focused on two research themes: 1) Photoreceptor structure, synapse, circuits, and development, 2) Hibernation and metabolic adaptations in the retina and beyond. As the first neuron of the visual system, photoreceptors are vital for photoreception and transmission of visual signals. I am particularly interested in cone photoreceptors, as they mediate our daylight vision with high resolution color information. Diseases affecting cone photoreceptors compromise visual functions in the central macular area of the human retina and are thus most detrimental to our vision. However, because cones are much less abundant compared to rods in most mammals, they are less well studied. We have used the ground squirrel (GS) as a model system to study cone vision, taking advantage of their unique cone-dominant retina. In particular, we have focused on short-wavelength sensitive cones (S-cones), which are not only essential for color vision, but are also an important origin of signals for biological rhythm, mood and cognitive functions, and the growth of the eye during development. We are studying critical cone synaptic structures – synaptic ribbons, the synaptic connections of S-cones, and the development of S-cones with regard to their specific connections. These works will provide knowledge of normal retinal development and function, which can also be extended to the rest of CNS; for example, the mechanisms of synaptic targeting during development. In addition, such knowledge will benefit the development of optimal therapeutic strategies for regeneration and repair in cases of retinal degenerative disease. Many neurodegenerative diseases, including retinal diseases, are rooted in metabolic stress in neurons and/or glial cells. Using the same GS model, we aim to learn from this hibernating mammal, which possesses an amazing capability to adapt to the extreme metabolic conditions during hibernation. By exploring the mechanisms of such adaptation, we hope to discover novel therapeutic tactics for neurodegenerative diseases.

Marmosets (Callithrix jacchus) are small South American monkeys which are being increasingly becoming adopted as animal models in neuroscience. Knowledge about the marmoset visual system has developed rapidly over the last decade. But what are the comparative advantages, and disadvantages involved in adopting this emerging model, as opposed to the more traditionally used macaque monkey? In this talk I will present case studies where the simpler brain morphology and short developmental cycle of the marmoset have been key factors in facilitating discoveries about the anatomy and physiology of the visual system. Although no single species provides the “ideal” animal model for invasive studies of the neural bases of visual processing, I argue that the development of robust methodologies for the study of the marmoset brain provides exciting opportunities to address long-standing problems in neuroscience.

Vision starts in the retina where images are transformed and coded into neuronal activity relevant for the brain. These coding steps function optimally over a wide range of conditions: from bright day on the beach to a moonless night. Under these very different conditions, specific retinal mechanisms continue to select relevant aspects of the visual world and send this information to the brain. We are studying the neuronal processing involved in these selection and adaptation processes. This knowledge is essential for understanding how the visual system works and forms the basis for research dedicated to restoring vision in blind people.

Eric Verdin examines advances in the biology of aging and their potential application to human health. The lecture distinguishes lifespan from healthspan and considers how research on aging mechanisms can inform the diagnosis and treatment of chronic diseases associated with getting older. Against the background of aging populations, Verdin explores the underlying causes of biological aging, the contributions of genetics and lifestyle, and approaches being investigated to extend healthy longevity. The discussion connects mechanistic research with the question of how a longer life can include more years of good health.

Organisms sense light for purposes that range from recognizing objects to synchronizing activity with environmental cycles. What mechanisms serve these diverse tasks? This seminar will examine the specializations of two cell types. First are the foveal cone photoreceptors. These neurons are used by primates to see far greater detail than other mammals, which lack them. How do the biophysical properties of foveal cones support high-acuity vision? Second are the melanopsin retinal ganglion cells, which are conserved among mammals and essential for processes that include regulation of the circadian clock, sleep, and hormone levels. How do these neurons encode light, and is encoding customized for animals of different niches? In pursuing these questions, a broad goal is to learn how various levels of biological organization are shaped to behavioural needs.

The Ca2+ modulated pulsatile secretions of glucagon and insulin by pancreatic α and β cells play a key role in glucose metabolism and homeostasis. However, how different types of cells in the islet couple and coordinate to give rise to various Ca2+ oscillation patterns and how these patterns are being tuned by paracrine regulation are still elusive. Here we developed a microfluidic device to facilitate long-term recording of islet Ca2+ activity at single cell level and found that islets show heterogeneous but intrinsic oscillation patterns. The α and β cells in an islet oscillate in antiphase and are globally phase locked to display a variety of oscillation modes. A mathematical model of islet oscillation maps out the dependence of the oscillation modes on the paracrine interactions between α and β cells. Our study reveals the origin of the islet oscillation patterns and highlights the role of paracrine regulation in tuning them.

Synaptic scaling is a homeostatic normalization mechanism that preserves relative synaptic strengths by adjusting them with a common factor. This multiplicative change is believed to be critical, since synaptic strengths are involved in learning and memory retention. Further, this homeostatic process is thought to be crucial for neuronal stability, playing a stabilizing role in otherwise runaway Hebbian plasticity [1-3]. Synaptic scaling requires a mechanism to sense total neuron activity and globally adjust synapses to achieve some activity set-point [4]. This process is relatively slow, which places limits on its ability to stabilize network activity [5]. Here we show that this slow response is inevitable in realistic neuronal morphologies. Furthermore, we reveal that global scaling can in fact be a source of instability unless responsiveness or scaling accuracy are sacrificed." "A neuron with tens of thousands of synapses must regulate its own excitability to compensate for changes in input. The time requirement for global feedback can introduce critical phase lags in a neuron’s response to perturbation. The severity of phase lag increases with neuron size. Further, a more expansive morphology worsens cell responsiveness and scaling accuracy, especially in distal regions of the neuron. Local pools of reserve receptors improve efficiency, potentiation, and scaling, but this comes at a cost. Trafficking large quantities of receptors requires time, exacerbating the phase lag and instability. Local homeostatic feedback mitigates instability, but this too comes at the cost of reducing scaling accuracy." "Realization of the phase lag instability requires a unified model of synaptic scaling, regulation, and transport. We present such a model with global and local feedback in realistic neuron morphologies (Fig. 1). This combined model shows that neurons face a tradeoff between stability, accuracy, and efficiency. Global feedback is required for synaptic scaling but favors either system stability or efficiency. Large receptor pools improve scaling accuracy in large morphologies but worsen both stability and efficiency. Local feedback improves the stability-efficiency tradeoff at the cost of scaling accuracy. This project introduces unexplored constraints on neuron size, morphology, and synaptic scaling that are weakened by an interplay between global and local feedback.

Popular notions of how the retina encodes visual stimuli typically focus on the center-surround receptive fields of retinal ganglion cells, the output neurons of the retina. In this view, the receptive field acts as a linear filter on the visual stimulus, highlighting spatial contrast and providing efficient representations of natural images. Yet, we also know that many ganglion cells respond vigorously to fine spatial gratings that should not activate the linear filter of the receptive field. Thus, ganglion cells may integrate visual signals nonlinearly across space. In this talk, I will discuss how these (and other) nonlinearities relate to the encoding of natural visual stimuli in the retina. Based on electrophysiological recordings of ganglion and bipolar cells from mouse and salamander retina, I will present methods for assessing nonlinear processing in different cell types and examine their importance and potential function under natural stimulation.