Publications by authors named "Rieke F"

Article Synopsis
  • The study challenges the traditional view of retinal ganglion cells (RGCs) in the retina functioning mainly through simple center-surround spatial filtering, revealing instead a much higher functional diversity in primate RGC types, particularly in macaques and humans.
  • Researchers identified 18-27 functional RGC types in primates, along with surprising non-classical receptive field structures and distinct responses to visual stimuli like natural movies.
  • These findings suggest that these diverse RGC types have specialized roles in vision rather than just proportioning visual information at varying spatial scales.
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Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations.

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Article Synopsis
  • Adaptation is essential for neural systems to adjust to varying sensory inputs efficiently, but traditional artificial neural networks (ANNs) struggle with this flexibility.
  • A new deep learning model for the retina was developed, integrating photoreceptor adaptation into convolutional neural networks (CNNs), enhancing their predictive capabilities.
  • This approach, which builds on previous models of retinal ganglion cell activity, shows improved accuracy in forecasting responses to complex visual stimuli, demonstrating the value of mimicking neural adaptation in AI systems.
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Article Synopsis
  • The study aims to connect neural activity in the retina to human behavior, specifically how we perceive flickering lights, which is complicated by differences between human and animal behaviors.
  • Researchers investigate how signals from rod and cone cells in the retina are processed and how this affects our ability to perceive high contrast flickering lights under certain conditions.
  • Using both electrophysiological recordings and perceptual tests, the team develops a predictive model that explains why we often struggle to notice flickering lights despite the signals received by our retina.
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How the spike output of the retina enables human visual perception is not fully understood. Here, we address this at the sensitivity limit of vision by correlating human visual perception with the spike outputs of primate ON and OFF parasol (magnocellular) retinal ganglion cells in tightly matching stimulus conditions. We show that human vision at its ultimate sensitivity limit depends on the spike output of the ON but not the OFF retinal pathway.

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Vertebrates rely on rod photoreceptors for vision in low-light conditions. The specialized downstream circuit for rod signalling, called the primary rod pathway, is well characterized in mammals, but circuitry for rod signalling in non-mammals is largely unknown. Here we demonstrate that the mammalian primary rod pathway is conserved in zebrafish, which diverged from extant mammals ~400 million years ago.

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In mammals, loss of retinal cells due to disease or trauma is an irreversible process that can lead to blindness. Interestingly, regeneration of retinal neurons is a well established process in some non-mammalian vertebrates and is driven by the Müller glia (MG), which are able to re-enter the cell cycle and reprogram into neurogenic progenitors upon retinal injury or disease. Progress has been made to restore this mechanism in mammals to promote retinal regeneration: MG can be stimulated to generate new neurons in vivo in the adult mouse retina after the over-expression of the pro-neural transcription factor Ascl1.

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Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations.

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Vertebrates rely on rod photoreceptors for vision in low-light conditions. Mammals have a specialized downstream circuit for rod signaling called the primary rod pathway, which comprises specific cell types and wiring patterns that are thought to be unique to this lineage. Thus, it has been long assumed that the primary rod pathway evolved in mammals.

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Vertebrates rely on rod photoreceptors for vision in low-light conditions. Mammals have a specialized downstream circuit for rod signaling called the primary rod pathway, which comprises specific cell types and wiring patterns that are thought to be unique to this lineage. Thus, it has been long assumed that the primary rod pathway evolved in mammals.

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Some visual properties are consistent across a wide range of environments, while other properties are more labile. The efficient coding hypothesis states that many of these regularities in the environment can be discarded from neural representations, thus allocating more of the brain's dynamic range to properties that are likely to vary. This paradigm is less clear about how the visual system prioritizes different pieces of information that vary across visual environments.

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The sensitivity of retinal cells is altered in background light to optimize the detection of contrast. For scotopic (rod) vision, substantial adaptation occurs in the first two cells, the rods and rod bipolar cells (RBCs), through sensitivity adjustments in rods and postsynaptic modulation of the transduction cascade in RBCs. To study the mechanisms mediating these components of adaptation, we made whole-cell, voltage-clamp recordings from retinal slices of mice from both sexes.

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Many neurodegenerative diseases cause degeneration of specific types of neurons. For example, glaucoma leads to death of retinal ganglion cells, leaving other neurons intact. Neurons are not regenerated in the adult mammalian central nervous system.

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The mammalian retina engages a broad array of linear and nonlinear circuit mechanisms to convert natural scenes into retinal ganglion cell (RGC) spike outputs. Although many individual integration mechanisms are well understood, we know less about how multiple mechanisms interact to encode the complex spatial features present in natural inputs. Here, we identified key spatial features in natural scenes that shape encoding by primate parasol RGCs.

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The development and connectivity of retinal ganglion cells (RGCs), the retina's sole output neurons, are patterned by activity-independent transcriptional programs and activity-dependent remodeling. To inventory the molecular correlates of these influences, we applied high-throughput single-cell RNA sequencing (scRNA-seq) to mouse RGCs at six embryonic and postnatal ages. We identified temporally regulated modules of genes that correlate with, and likely regulate, multiple phases of RGC development, ranging from differentiation and axon guidance to synaptic recognition and refinement.

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The detection of motion direction is a fundamental visual function and a classic model for neural computation. In the non-primate retina, direction selectivity arises in starburst amacrine cell (SAC) dendrites, which provide selective inhibition to direction-selective retinal ganglion cells (dsRGCs). Although SACs are present in primates, their connectivity and the existence of dsRGCs remain open questions.

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Neural circuits are constructed from nonlinear building blocks, and not surprisingly overall circuit behavior is often strongly nonlinear. But neural circuits can also behave near linearly, and some circuits shift from linear to nonlinear behavior depending on stimulus conditions. Such control of nonlinear circuit behavior is fundamental to neural computation.

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Primates explore their visual environment by making frequent saccades, discrete and ballistic eye movements that direct the fovea to specific regions of interest. Saccades produce large and rapid changes in input. The magnitude of these changes and the limited signaling range of visual neurons mean that effective encoding requires rapid adaptation.

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The morphology of retinal neurons strongly influences their physiological function. Ganglion cell (GC) dendrites ramify in distinct strata of the inner plexiform layer (IPL) so that GCs responding to light increments (ON) or decrements (OFF) receive appropriate excitatory inputs. This vertical stratification prescribes response polarity and ensures consistent connectivity between cell types, whereas the lateral extent of GC dendritic arbors typically dictates receptive field (RF) size.

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Regenerative neuroscience aims to stimulate endogenous repair in the nervous system to replace neurons lost from degenerative diseases. Recently, we reported that overexpressing the transcription factor Ascl1 in Müller glia (MG) is sufficient to stimulate MG to regenerate functional neurons in the adult mouse retina. However, this process is inefficient, and only a third of the Ascl1-expressing MG generate new neurons.

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Developing neural circuits, including GABAergic circuits, switch receptor types. But the role of early GABA receptor expression for establishment of functional inhibitory circuits remains unclear. Tracking the development of GABAergic synapses across axon terminals of retinal bipolar cells (BCs), we uncovered a crucial role of early GABA receptor expression for the formation and function of presynaptic inhibitory synapses.

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Predictive motion encoding is an important aspect of visually guided behavior that allows animals to estimate the trajectory of moving objects. Motion prediction is understood primarily in the context of translational motion, but the environment contains other types of behaviorally salient motion correlation such as those produced by approaching or receding objects. However, the neural mechanisms that detect and predictively encode these correlations remain unclear.

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Most models of neural responses are constructed to reproduce the average response to inputs but lack the flexibility to capture observed variability in responses. The origins and structure of this variability have significant implications for how information is encoded and processed in the nervous system, both by limiting information that can be conveyed and by determining processing strategies that are favorable for minimizing its negative effects. Here, we present a new modeling framework that incorporates multiple sources of noise to better capture observed features of neural response variability across stimulus conditions.

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Amacrine cells are interneurons composing the most diverse cell class in the mammalian retina. They help encode visual features, such as edges or directed motion, by mediating excitatory and inhibitory interactions between input (i.e.

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