The sodium-potassium ATPase (i.e., the "sodium pump") plays a central role in maintaining ionic homeostasis in all cells. Although the sodium pump is intrinsically electrogenic and responsive to dynamic changes in intracellular sodium concentration, its role in regulating neuronal excitability remains unclear. Here we describe a physiological role for the sodium pump in regulating the excitability of mouse neocortical layer 5 and hippocampal CA1 pyramidal neurons. Trains of action potentials produced long-lasting (ϳ20 s) afterhyperpolarizations (AHPs) that were insensitive to blockade of voltage-gated calcium channels or chelation of intracellular calcium, but were blocked by tetrodotoxin, ouabain, or the removal of extracellular potassium. Correspondingly, the AHP time course was similar to the decay of activity-induced increases in intracellular sodium, whereas intracellular calcium decayed at much faster rates. To determine whether physiological patterns of activity engage the sodium pump, we replayed in vitro a place-specific burst of 15 action potentials recorded originally in vivo in a CA1 "place cell" as the animal traversed the associated place field. In both layer 5 and CA1 pyramidal neurons, this "place cell train" generated small, long-lasting AHPs capable of reducing neuronal excitability for many seconds. Placecell-train-induced AHPs were blocked by ouabain or removal of extracellular potassium, but not by intracellular calcium chelation. Finally, we found calcium contributions to the AHP to be temperature dependent: prominent at room temperature, but largely absent at 35°C. Our results demonstrate a previously unappreciated role for the sodium-potassium ATPase in regulating the excitability of neocortical and hippocampal pyramidal neurons.

The corticogeniculate (CG) pathway connects the visual cortex with the visual thalamus (LGN) in the feedback direction and enables the cortex to directly influence its own input. Despite numerous investigations, the role of this feedback circuit in visual perception remained elusive. To probe the function of CG feedback in a causal manner, we selectively and reversibly manipulated the activity of CG neurons in anesthetized ferrets in vivo using a combined viral-infection and optogenetics approach to drive expression of channelrhodopsin2 (ChR2) in CG neurons. We observed significant increases in temporal precision and spatial resolution of LGN neuronal responses to drifting grating and white noise stimuli when CG neurons expressing ChR2 were light activated. Enhancing CG feedback reduced visually evoked response latencies, increased spike-timing precision, and reduced classical receptive field size. Increased precision among LGN neurons led to increased spike-timing precision among granular layer V1 neurons as well. Together, our findings suggest that the function of CG feedback is to control the timing and precision of thalamic responses to incoming visual signals.T he feedforward progression of sensory information from peripheral receptors through nuclei in the sensory thalamus to the primary sensory cortex is well understood. For example, much is known about how neurons in the primary sensory cortex represent elementary sensory features based on the inputs they receive from peripheral and thalamic neurons with well-defined receptive field properties. In addition to these feedforward circuits, mammalian sensory systems include a substantial feedback projection from the primary sensory cortex to the sensory thalamus (1). Despite a rich history of investigation, the functional role of corticothalamic feedback circuits in sensory perception remains a fundamental mystery in neuroscience.Our goal was to determine the functional contribution of corticothalamic feedback to vision. Corticogeniculate (CG) circuits link the primary visual cortex (V1) with the lateral geniculate nucleus of the thalamus (LGN) and constitute the first cortical feedback connection in the visual processing hierarchy (2). CG axons target LGN relay neurons, local interneurons within the LGN, and neurons in the visual portion of the thalamic reticular nucleus (TRN) that inhibit LGN relay neurons (3-5) (Fig. 1A). Based on this pattern of axonal innervation, CG modulation of LGN neurons could include both monosynaptic excitation and disynaptic inhibition of LGN relay neurons via TRN and/or local LGN inhibitory circuitry. The CG circuit is anatomically robust-cortical synapses onto LGN relay neurons far outnumber retinal synapses (4); however, the receptive fields of LGN relay neurons reflect their retinal and not their cortical inputs (6). In part due to its subtle influence on LGN responses, the function of CG feedback has remained elusive.There have been numerous experimental examinations of CG function-using methods with varying degrees of sele...

The corticogeniculate (CG) pathway links the visual cortex with the lateral geniculate nucleus (LGN) of the thalamus and is the first feedback connection in the mammalian visual system. Whether functional connections between CG neurons and LGN relay neurons obey or ignore the separation of feedforward visual signals into parallel processing streams is not known. Accordingly, there is some debate about whether CG neurons are morphologically heterogeneous or homogenous. Here we characterized the morphology of CG neurons in the ferret, a visual carnivore with distinct feedforward parallel processing streams, and compared the morphology of ferret CG neurons with CG neuronal morphology previously described in macaque monkeys [Briggs et al. (2016) Neuron, 90, 388]. We used a G-deleted rabies virus as a retrograde tracer to label CG neurons in adult ferrets. We then reconstructed complete dendritic morphologies for a large sample of virus-labeled CG neurons. Quantification of CG morphology revealed three distinct CG neuronal subtypes with striking similarities to the CG neuronal subtypes observed in macaques. These findings suggest that CG neurons may be morphologically diverse in a variety of highly visual mammals in which feedforward visual pathways are organized into parallel processing streams. Accordingly, these results provide support for the notion that CG feedback is functionally parallel stream-specific in ferrets and macaques.

This work is focused on streaming particle filter registration of surface models such as homogeneous triangle meshes and point clouds. Part of the approach is a streaming curvature feature calculation. The investigated approach utilizes a particle filter to incrementally update pose estimates during data acquisition. The method is evaluated in real data experiments with a high-precision laser striper system attached to an industrial robot. During the laser scan, the data is integrated on-the-fly in order to calculate features and based on these to estimate the object's pose. Experiments show the method's competitiveness in accuracy and reliability compared to state-ofthe-art offline algorithms.