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• W3084283750 abstract "•A speed-coding multisynaptic circuit connects PPN to MEC via HDB•Each level of the PPN-HDB-MEC pathway contains cells with linear speed coding•Optogenetic stimulation of PPN elicits activity in HDB and MEC speed cells•In MEC, locomotor inputs from PPN mainly target speed-modulated interneurons Locomotion activates an array of sensory inputs that may help build the self-position map of the medial entorhinal cortex (MEC). In this map, speed-coding neurons are thought to dynamically update representations of the animal’s position. A possible origin for the entorhinal speed signal is the mesencephalic locomotor region (MLR), which is critically involved in the activation of locomotor programs. Here, we describe, in rats, a circuit connecting the pedunculopontine tegmental nucleus (PPN) of the MLR to the MEC via the horizontal limb of the diagonal band of Broca (HDB). At each level of this pathway, locomotion speed is linearly encoded in neuronal firing rates. Optogenetic activation of PPN cells drives locomotion and modulates activity of speed-modulated neurons in HDB and MEC. Our results provide evidence for a pathway by which brainstem speed signals can reach cortical structures implicated in navigation and higher-order dynamic representations of space. Locomotion activates an array of sensory inputs that may help build the self-position map of the medial entorhinal cortex (MEC). In this map, speed-coding neurons are thought to dynamically update representations of the animal’s position. A possible origin for the entorhinal speed signal is the mesencephalic locomotor region (MLR), which is critically involved in the activation of locomotor programs. Here, we describe, in rats, a circuit connecting the pedunculopontine tegmental nucleus (PPN) of the MLR to the MEC via the horizontal limb of the diagonal band of Broca (HDB). At each level of this pathway, locomotion speed is linearly encoded in neuronal firing rates. Optogenetic activation of PPN cells drives locomotion and modulates activity of speed-modulated neurons in HDB and MEC. Our results provide evidence for a pathway by which brainstem speed signals can reach cortical structures implicated in navigation and higher-order dynamic representations of space. In the mammalian brain, the medial entorhinal cortex (MEC) and the hippocampus are part of a dedicated neuronal network that allows an animal to create an internal representation of its current position by continuously integrating self-motion cues as the animal traverses the environment (McNaughton et al., 1996McNaughton B.L. Barnes C.A. Gerrard J.L. Gothard K. Jung M.W. Knierim J.J. Kudrimoti H. Qin Y. Skaggs W.E. Suster M. Weaver K.L. Deciphering the hippocampal polyglot: the hippocampus as a path integration system.J. Exp. Biol. 1996; 199: 173-185PubMed Google Scholar; McNaughton et al., 2006McNaughton B.L. Battaglia F.P. Jensen O. Moser E.I. Moser M.B. Path integration and the neural basis of the ‘cognitive map’.Nat. Rev. Neurosci. 2006; 7: 663-678Crossref PubMed Scopus (1180) Google Scholar; Moser et al., 2014Moser E.I. Roudi Y. Witter M.P. Kentros C. Bonhoeffer T. Moser M.B. Grid cells and cortical representation.Nat. Rev. Neurosci. 2014; 15: 466-481Crossref PubMed Scopus (174) Google Scholar). This process, known as path integration (Mittelstaedt and Mittelstaedt, 1980Mittelstaedt M.L. Mittelstaedt H. Homing by path integration in a mammal.Naturwissenschaften. 1980; 67: 566-567Crossref Scopus (460) Google Scholar; Gallistel, 1990Gallistel C.R. The Organization of Learning. Bradford Books/MIT Press, 1990Google Scholar; Etienne and Jeffery, 2004Etienne A.S. Jeffery K.J. Path integration in mammals.Hippocampus. 2004; 14: 180-192Crossref PubMed Scopus (430) Google Scholar), provides a mechanism for translating activity across the internal spatial representation in accordance with the animal’s changing location. A key component of this self-position system is the network of grid cells in the MEC (Fyhn et al., 2004Fyhn M. Molden S. Witter M.P. Moser E.I. Moser M.B. Spatial representation in the entorhinal cortex.Science. 2004; 305: 1258-1264Crossref PubMed Scopus (833) Google Scholar; Hafting et al., 2005Hafting T. Fyhn M. Molden S. Moser M.B. Moser E.I. Microstructure of a spatial map in the entorhinal cortex.Nature. 2005; 436: 801-806Crossref PubMed Scopus (2183) Google Scholar), whose multiple spatially confined firing fields form a hexagonal lattice across the entire environment. Because the relative position of firing fields of different grid cells is maintained across environments and behavioral tasks (Fyhn et al., 2007Fyhn M. Hafting T. Treves A. Moser M.B. Moser E.I. Hippocampal remapping and grid realignment in entorhinal cortex.Nature. 2007; 446: 190-194Crossref PubMed Scopus (435) Google Scholar; Yoon et al., 2013Yoon K. Buice M.A. Barry C. Hayman R. Burgess N. Fiete I.R. Specific evidence of low-dimensional continuous attractor dynamics in grid cells.Nat. Neurosci. 2013; 16: 1077-1084Crossref PubMed Scopus (134) Google Scholar), self-motion, rather than external sensory inputs, may determine grid cell firing in moving animals (McNaughton et al., 2006McNaughton B.L. Battaglia F.P. Jensen O. Moser E.I. Moser M.B. Path integration and the neural basis of the ‘cognitive map’.Nat. Rev. Neurosci. 2006; 7: 663-678Crossref PubMed Scopus (1180) Google Scholar; Moser et al., 2014Moser E.I. Roudi Y. Witter M.P. Kentros C. Bonhoeffer T. Moser M.B. Grid cells and cortical representation.Nat. Rev. Neurosci. 2014; 15: 466-481Crossref PubMed Scopus (174) Google Scholar). A path integration-based mechanism for translation is further supported by the fact that passive transport disrupts the spatial regularity of grid cells (Winter et al., 2015bWinter S.S. Mehlman M.L. Clark B.J. Taube J.S. Passive transport disrupts grid signals in the parahippocampal cortex.Curr. Biol. 2015; 25: 2493-2502Abstract Full Text Full Text PDF PubMed Scopus (52) Google Scholar), whereas in virtual environments, grid cells respond to changes in the gain between locomotion and translation of the visual scene (Campbell et al., 2018Campbell M.G. Ocko S.A. Mallory C.S. Low I.I.C. Ganguli S. Giocomo L.M. Principles governing the integration of landmark and self-motion cues in entorhinal cortical codes for navigation.Nat. Neurosci. 2018; 21: 1096-1106Crossref PubMed Scopus (53) Google Scholar). Similarly, in place cells, the firing fields are often controlled by the animal’s movement when translocation is decoupled from the animal’s ambulation (Gothard et al., 1996Gothard K.M. Skaggs W.E. McNaughton B.L. Dynamics of mismatch correction in the hippocampal ensemble code for space: interaction between path integration and environmental cues.J. Neurosci. 1996; 16: 8027-8040Crossref PubMed Google Scholar; Czurkó et al., 1999Czurkó A. Hirase H. Csicsvari J. Buzsáki G. Sustained activation of hippocampal pyramidal cells by ‘space clamping’ in a running wheel.Eur. J. Neurosci. 1999; 11: 344-352Crossref PubMed Scopus (227) Google Scholar; Redish et al., 2000Redish A.D. Rosenzweig E.S. Bohanick J.D. McNaughton B.L. Barnes C.A. Dynamics of hippocampal ensemble activity realignment: time versus space.J. Neurosci. 2000; 20: 9298-9309Crossref PubMed Google Scholar; Terrazas et al., 2005Terrazas A. Krause M. Lipa P. Gothard K.M. Barnes C.A. McNaughton B.L. Self-motion and the hippocampal spatial metric.J. Neurosci. 2005; 25: 8085-8096Crossref PubMed Scopus (149) Google Scholar; Chen et al., 2013Chen G. King J.A. Burgess N. O’Keefe J. How vision and movement combine in the hippocampal place code.Proc. Natl. Acad. Sci. U S A. 2013; 110: 378-383Crossref PubMed Scopus (180) Google Scholar; Ravassard et al., 2013Ravassard P. Kees A. Willers B. Ho D. Aharoni D.A. Cushman J. Aghajan Z.M. Mehta M.R. Multisensory control of hippocampal spatiotemporal selectivity.Science. 2013; 340: 1342-1346Crossref PubMed Scopus (174) Google Scholar). These observations support the notion that active self-motion is necessary for spatially responsive cells in MEC and hippocampus to keep track of the animal’s location (McNaughton et al., 1996McNaughton B.L. Barnes C.A. Gerrard J.L. Gothard K. Jung M.W. Knierim J.J. Kudrimoti H. Qin Y. Skaggs W.E. Suster M. Weaver K.L. Deciphering the hippocampal polyglot: the hippocampus as a path integration system.J. Exp. Biol. 1996; 199: 173-185PubMed Google Scholar, McNaughton et al., 2006McNaughton B.L. Battaglia F.P. Jensen O. Moser E.I. Moser M.B. Path integration and the neural basis of the ‘cognitive map’.Nat. Rev. Neurosci. 2006; 7: 663-678Crossref PubMed Scopus (1180) Google Scholar; Fuhs and Touretzky, 2006Fuhs M.C. Touretzky D.S. A spin glass model of path integration in rat medial entorhinal cortex.J. Neurosci. 2006; 26: 4266-4276Crossref PubMed Scopus (405) Google Scholar; Burgess et al., 2007Burgess N. Barry C. O’Keefe J. An oscillatory interference model of grid cell firing.Hippocampus. 2007; 17: 801-812Crossref PubMed Scopus (469) Google Scholar; Hasselmo et al., 2007Hasselmo M.E. Giocomo L.M. Zilli E.A. Grid cell firing may arise from interference of theta frequency membrane potential oscillations in single neurons.Hippocampus. 2007; 17: 1252-1271Crossref PubMed Scopus (188) Google Scholar; Burak and Fiete, 2009Burak Y. Fiete I.R. Accurate path integration in continuous attractor network models of grid cells.PLoS Comput. Biol. 2009; 5: e1000291Crossref PubMed Scopus (367) Google Scholar). Path integration requires information about the animal’s ongoing speed. Such information is expressed in specialized MEC cells referred to as speed cells (Kropff et al., 2015Kropff E. Carmichael J.E. Moser M.B. Moser E.I. Speed cells in the medial entorhinal cortex.Nature. 2015; 523: 419-424Crossref PubMed Scopus (295) Google Scholar; Ye et al., 2018Ye J. Witter M.P. Moser M.B. Moser E.I. Entorhinal fast-spiking speed cells project to the hippocampus.Proc. Natl. Acad. Sci. U S A. 2018; 115: E1627-E1636Crossref PubMed Scopus (18) Google Scholar), although some cells also encode speed conjunctively with positional or directional correlates (Sargolini et al., 2006Sargolini F. Fyhn M. Hafting T. McNaughton B.L. Witter M.P. Moser M.B. Moser E.I. Conjunctive representation of position, direction, and velocity in entorhinal cortex.Science. 2006; 312: 758-762Crossref PubMed Scopus (856) Google Scholar; Hinman et al., 2016Hinman J.R. Brandon M.P. Climer J.R. Chapman G.W. Hasselmo M.E. Multiple Running Speed Signals in Medial Entorhinal Cortex.Neuron. 2016; 91: 666-679Abstract Full Text Full Text PDF PubMed Scopus (76) Google Scholar; Hardcastle et al., 2017Hardcastle K. Maheswaranathan N. Ganguli S. Giocomo L.M. A multiplexed, heterogeneous, and adaptive code for navigation in medial entorhinal cortex.Neuron. 2017; 94: 375-387.e7Abstract Full Text Full Text PDF PubMed Scopus (88) Google Scholar). Speed is also expressed in place cells of the hippocampus (McNaughton et al., 1983McNaughton B.L. Barnes C.A. O’Keefe J. The contributions of position, direction, and velocity to single unit activity in the hippocampus of freely-moving rats.Exp. Brain Res. 1983; 52: 41-49Crossref PubMed Scopus (703) Google Scholar; Wiener et al., 1989Wiener S.I. Paul C.A. Eichenbaum H. Spatial and behavioral correlates of hippocampal neuronal activity.J. Neurosci. 1989; 9: 2737-2763Crossref PubMed Google Scholar; Czurkó et al., 1999Czurkó A. Hirase H. Csicsvari J. Buzsáki G. Sustained activation of hippocampal pyramidal cells by ‘space clamping’ in a running wheel.Eur. J. Neurosci. 1999; 11: 344-352Crossref PubMed Scopus (227) Google Scholar). The linear relationship between speed and the firing rate of most MEC speed cells allows direct temporal integration of the animal’s displacement and so provides a self-motion-derived signal that dynamically updates firing in grid cells (Kropff et al., 2015Kropff E. Carmichael J.E. Moser M.B. Moser E.I. Speed cells in the medial entorhinal cortex.Nature. 2015; 523: 419-424Crossref PubMed Scopus (295) Google Scholar). However, locomotor speed may also be encoded non-linearly in some MEC cells (Hinman et al., 2016Hinman J.R. Brandon M.P. Climer J.R. Chapman G.W. Hasselmo M.E. Multiple Running Speed Signals in Medial Entorhinal Cortex.Neuron. 2016; 91: 666-679Abstract Full Text Full Text PDF PubMed Scopus (76) Google Scholar). The emergence of the speed cell signal in MEC remains poorly understood, although several studies have pointed to a subcortical origin. Speed-correlated firing may reflect the activity of neurons in the medial septum and diagonal band of Broca (MSDB), a brain region that sends strong direct projections to both hippocampus and MEC (Amaral and Kurz, 1985Amaral D.G. Kurz J. An analysis of the origins of the cholinergic and noncholinergic septal projections to the hippocampal formation of the rat.J. Comp. Neurol. 1985; 240: 37-59Crossref PubMed Scopus (577) Google Scholar; Gaykema et al., 1990Gaykema R.P. Luiten P.G. Nyakas C. Traber J. Cortical projection patterns of the medial septum-diagonal band complex.J. Comp. Neurol. 1990; 293: 103-124Crossref PubMed Scopus (315) Google Scholar; Unal et al., 2015Unal G. Joshi A. Viney T.J. Kis V. Somogyi P. Synaptic targets of medial septal projections in the hippocampus and extrahippocampal cortices of the mouse.J. Neurosci. 2015; 35: 15812-15826Crossref PubMed Scopus (68) Google Scholar; Fuchs et al., 2016Fuchs E.C. Neitz A. Pinna R. Melzer S. Caputi A. Monyer H. Local and distant input controlling excitation in layer II of the medial entorhinal cortex.Neuron. 2016; 89: 194-208Abstract Full Text Full Text PDF PubMed Scopus (76) Google Scholar) and that controls the dynamics of place cells in the hippocampus (Buzsáki, 2002Buzsáki G. Theta oscillations in the hippocampus.Neuron. 2002; 33: 325-340Abstract Full Text Full Text PDF PubMed Scopus (2056) Google Scholar; Colgin, 2016Colgin L.L. Rhythms of the hippocampal network.Nat. Rev. Neurosci. 2016; 17: 239-249Crossref PubMed Scopus (252) Google Scholar) and grid cells in the MEC (Brandon et al., 2011Brandon M.P. Bogaard A.R. Libby C.P. Connerney M.A. Gupta K. Hasselmo M.E. Reduction of theta rhythm dissociates grid cell spatial periodicity from directional tuning.Science. 2011; 332: 595-599Crossref PubMed Scopus (282) Google Scholar; Koenig et al., 2011Koenig J. Linder A.N. Leutgeb J.K. Leutgeb S. The spatial periodicity of grid cells is not sustained during reduced theta oscillations.Science. 2011; 332: 592-595Crossref PubMed Scopus (276) Google Scholar) during active exploration. Because MSDB neurons with projections to MEC and CA1 are modulated by running speed (King et al., 1998King C. Recce M. O’Keefe J. The rhythmicity of cells of the medial septum/diagonal band of Broca in the awake freely moving rat: relationships with behaviour and hippocampal theta.Eur. J. Neurosci. 1998; 10: 464-477Crossref PubMed Scopus (141) Google Scholar; Fuhrmann et al., 2015Fuhrmann F. Justus D. Sosulina L. Kaneko H. Beutel T. Friedrichs D. Schoch S. Schwarz M.K. Fuhrmann M. Remy S. Locomotion, theta oscillations, and the speed-correlated firing of hippocampal neurons are controlled by a medial septal glutamatergic circuit.Neuron. 2015; 86: 1253-1264Abstract Full Text Full Text PDF PubMed Scopus (163) Google Scholar; Justus et al., 2017Justus D. Dalügge D. Bothe S. Fuhrmann F. Hannes C. Kaneko H. Friedrichs D. Sosulina L. Schwarz I. Elliott D.A. et al.Glutamatergic synaptic integration of locomotion speed via septoentorhinal projections.Nat. Neurosci. 2017; 20: 16-19Crossref PubMed Scopus (43) Google Scholar), MSDB may play a role in implementing path integration in these target regions (Martin et al., 2007Martin M.M. Horn K.L. Kusman K.J. Wallace D.G. Medial septum lesions disrupt exploratory trip organization: evidence for septohippocampal involvement in dead reckoning.Physiol. Behav. 2007; 90: 412-424Crossref PubMed Scopus (30) Google Scholar; Jacob et al., 2017Jacob P.Y. Gordillo-Salas M. Facchini J. Poucet B. Save E. Sargolini F. Medial entorhinal cortex and medial septum contribute to self-motion-based linear distance estimation.Brain Struct. Funct. 2017; 222: 2727-2742Crossref PubMed Scopus (22) Google Scholar). However, the importance that active locomotion plays in the generation of stable and regular spatial codes in hippocampus and MEC suggests the need for these regions to be linked to brain circuits that directly participate in the onset of locomotor programs. Early studies of the mammalian brainstem showed that electrical stimulation of the mesencephalic locomotor region (MLR), a region composed of the cuneiform and the pedunculopontine nuclei (CnF and PPN, respectively), can elicit progressively faster gaits in a frequency-dependent manner (Shik et al., 1969Shik M.L. Severin F.V. Orlovsky G.N. Control of walking and running by means of electrical stimulation of the mesencephalon.Electroencephalogr. Clin. Neurophysiol. 1969; 26: 549PubMed Google Scholar; Skinner and Garcia-Rill, 1984Skinner R.D. Garcia-Rill E. The mesencephalic locomotor region (MLR) in the rat.Brain Res. 1984; 323: 385-389Crossref PubMed Scopus (213) Google Scholar; Garcia-Rill et al., 1987Garcia-Rill E. Houser C.R. Skinner R.D. Smith W. Woodward D.J. Locomotion-inducing sites in the vicinity of the pedunculopontine nucleus.Brain Res. Bull. 1987; 18: 731-738Crossref PubMed Scopus (187) Google Scholar). More recently, optogenetic studies have shown that the locomotion-inducing role of MLR is under bidirectional control of basal ganglia output pathways and linked to activation of glutamatergic neurons in both CnF and PPN (Lee et al., 2014Lee A.M. Hoy J.L. Bonci A. Wilbrecht L. Stryker M.P. Niell C.M. Identification of a brainstem circuit regulating visual cortical state in parallel with locomotion.Neuron. 2014; 83: 455-466Abstract Full Text Full Text PDF PubMed Scopus (145) Google Scholar; Roseberry et al., 2016Roseberry T.K. Lee A.M. Lalive A.L. Wilbrecht L. Bonci A. Kreitzer A.C. Cell-type-specific control of brainstem locomotor circuits by basal ganglia.Cell. 2016; 164: 526-537Abstract Full Text Full Text PDF PubMed Scopus (169) Google Scholar; Caggiano et al., 2018Caggiano V. Leiras R. Goñi-Erro H. Masini D. Bellardita C. Bouvier J. Caldeira V. Fisone G. Kiehn O. Midbrain circuits that set locomotor speed and gait selection.Nature. 2018; 553: 455-460Crossref PubMed Scopus (147) Google Scholar; Josset et al., 2018Josset N. Roussel M. Lemieux M. Lafrance-Zoubga D. Rastqar A. Bretzner F. Distinct contributions of mesencephalic locomotor region nuclei to locomotor control in the freely behaving mouse.Curr. Biol. 2018; 28: 884-901.e3Abstract Full Text Full Text PDF PubMed Scopus (67) Google Scholar). Interestingly, different elements of the MLR circuit are tuned to different behavioral contexts, with CnF involved in escape responses and PPN implicated in exploratory behaviors (Caggiano et al., 2018Caggiano V. Leiras R. Goñi-Erro H. Masini D. Bellardita C. Bouvier J. Caldeira V. Fisone G. Kiehn O. Midbrain circuits that set locomotor speed and gait selection.Nature. 2018; 553: 455-460Crossref PubMed Scopus (147) Google Scholar). In addition to descending projections to spinal regions, the MLR sends widespread ascending projections to several thalamic, basal ganglia, and forebrain targets (Woolf and Butcher, 1986Woolf N.J. Butcher L.L. Cholinergic systems in the rat brain: III. Projections from the pontomesencephalic tegmentum to the thalamus, tectum, basal ganglia, and basal forebrain.Brain Res. Bull. 1986; 16: 603-637Crossref PubMed Scopus (558) Google Scholar; Losier and Semba, 1993Losier B.J. Semba K. Dual projections of single cholinergic and aminergic brainstem neurons to the thalamus and basal forebrain in the rat.Brain Res. 1993; 604: 41-52Crossref PubMed Scopus (97) Google Scholar; Martinez-Gonzalez et al., 2011Martinez-Gonzalez C. Bolam J.P. Mena-Segovia J. Topographical organization of the pedunculopontine nucleus.Front. Neuroanat. 2011; 5: 22Crossref PubMed Google Scholar; Ryczko and Dubuc, 2013Ryczko D. Dubuc R. The multifunctional mesencephalic locomotor region.Curr. Pharm. Des. 2013; 19: 4448-4470Crossref PubMed Scopus (98) Google Scholar; Mena-Segovia and Bolam, 2017Mena-Segovia J. Bolam J.P. Rethinking the pedunculopontine nucleus: from cellular organization to function.Neuron. 2017; 94: 7-18Abstract Full Text Full Text PDF PubMed Scopus (84) Google Scholar), with PPN serving as one of the main sources of projections to the MSDB area (Hallanger and Wainer, 1988Hallanger A.E. Wainer B.H. Ascending projections from the pedunculopontine tegmental nucleus and the adjacent mesopontine tegmentum in the rat.J. Comp. Neurol. 1988; 274: 483-515Crossref PubMed Scopus (300) Google Scholar). Activation of ascending MLR projections in cholinergic basal forebrain regions, including MSDB, has been shown to replicate activity states in primary visual cortex that are linked to locomotion, even in the absence of movement (Lee et al., 2014Lee A.M. Hoy J.L. Bonci A. Wilbrecht L. Stryker M.P. Niell C.M. Identification of a brainstem circuit regulating visual cortical state in parallel with locomotion.Neuron. 2014; 83: 455-466Abstract Full Text Full Text PDF PubMed Scopus (145) Google Scholar). Taken together, these findings point to the MLR as a possible modulator of locomotor-dependent cortical activity by way of its projections through the basal forebrain. Here, we hypothesized that the MLR, and more specifically the PPN, serves as a brainstem source of locomotor-derived speed inputs that modulate the neuronal encoding of speed in MEC during exploration. Using a combination of anatomical tracing, in vivo single-unit recordings, and optogenetic stimulation, we describe here a neuronal circuit in the rat brain that by way of connections from PPN to the horizontal limb of the diagonal band of Broca (HDB), and further from HDB to MEC, controls the activity of speed cells in the MEC. To determine whether and how locomotion-related activity in MLR might influence speed coding in MEC, we started out by mapping the anatomical connections between these regions using neuronal tracers (Figure 1). We performed simultaneous injections of the retrograde tracer fast blue (FB) in dorsal MEC (n = 4 rats; Figure 1A; Figure S1A) and the anterograde tracer biotinylated dextran amine (BDA) in MLR, specifically targeting PPN (n = 4 rats; Figure 1B). No FB-labeled neurons were identified in PPN, suggesting an absence of monosynaptic projections from PPN to MEC (Figure 1B). A subsequent brain-wide tracer labeling analysis allowed us to identify several brain areas where it was possible to observe the co-occurrence of BDA-labeled axonal projections from PPN and FB-labeled neurons projecting to MEC. Such labeling was prominent in HDB and the border region between horizontal and vertical limbs of the diagonal band (Figures 1C and 1D). Even without direct evidence for monosynaptic connections between PPN and HDB, this result points to HDB as one of several potential relays for communication between PPN and MEC. Additional double labeling of BDA and FB was observed in the medial septum (MS; Figure 1D), supramammillary nucleus (SuM; Figure 1E), and nucleus reuniens (Re; Figure 1F), opening the possibility for multiple parallel pathways connecting PPN to MEC. In addition to identifying the HDB region as a major convergence site between PPN and MEC, we sought to identify the source of HDB afferents from the nuclei within the MLR, specifically the CnF and the PPN (Ryczko and Dubuc, 2013Ryczko D. Dubuc R. The multifunctional mesencephalic locomotor region.Curr. Pharm. Des. 2013; 19: 4448-4470Crossref PubMed Scopus (98) Google Scholar), as this region is known to send projections to MSDB targets (Woolf and Butcher, 1986Woolf N.J. Butcher L.L. Cholinergic systems in the rat brain: III. Projections from the pontomesencephalic tegmentum to the thalamus, tectum, basal ganglia, and basal forebrain.Brain Res. Bull. 1986; 16: 603-637Crossref PubMed Scopus (558) Google Scholar; Hallanger and Wainer, 1988Hallanger A.E. Wainer B.H. Ascending projections from the pedunculopontine tegmental nucleus and the adjacent mesopontine tegmentum in the rat.J. Comp. Neurol. 1988; 274: 483-515Crossref PubMed Scopus (300) Google Scholar). We performed a FB injection in HDB (Figure S1B; n = 1 rat) and observed that within MLR, a substantial population of FB-labeled neurons was present in PPN (Figure S1C), validating this brain area as the main source of MLR monosynaptic projections to HDB. We then asked whether locomotion speed was encoded at each step of the PPN-HDB-MEC pathway. Rats were implanted with tetrodes to target PPN (n = 12 rats), HDB (n = 20 rats), and MEC (n = 35 rats) (Figures 2A–2C; Figure S2). We performed single-unit recordings from these brain regions while the animals foraged for food crumbles in an open-field arena. On the basis of post hoc anatomical reconstruction of recording sites, we selected 1,890 units (PPN, n = 260 cells; HDB, n = 308 cells; MEC, n = 1,322 cells). In each area, we observed units where spike activity co-varied with the animal’s running speed (Figures 2D–2F), most often by increasing or decreasing linearly with speed (Figures 2G–2I). For every single unit in each area, we calculated a speed score—Pearson’s correlation between the unit firing rate and the animal’s running speed, considering only periods when running speed was between 6 cm/s and the mean value of the last 10 cm/s speed bin in which the animal had spent more than 30 s—and we classified units as negative or positive speed cells if their speed scores were lower than the 1st or higher than the 99th percentile of a shuffled distribution of observed speed versus rate values, respectively (Figures 2J–2L; Kropff et al., 2015Kropff E. Carmichael J.E. Moser M.B. Moser E.I. Speed cells in the medial entorhinal cortex.Nature. 2015; 523: 419-424Crossref PubMed Scopus (295) Google Scholar). The speed threshold, modified from a previous report (Kropff et al., 2015Kropff E. Carmichael J.E. Moser M.B. Moser E.I. Speed cells in the medial entorhinal cortex.Nature. 2015; 523: 419-424Crossref PubMed Scopus (295) Google Scholar), was chosen empirically to represent the approximate transition between discrete neural firing regimes in MEC (Figure S3A). At low speeds, from 0 to 6 cm/s, the firing rates of MEC cells increased sharply, likely as a result of network state changes following locomotor onset. Above 6 cm/s, firing increased with increasing locomotor speed in an apparently linear manner. The presence of two discrete firing regimes was also observed in PPN and HDB (Figure S3A), allowing us to remove from our further analyses in each brain region any behavioral-state effects associated with locomotor onset or arrest. During running, a linear speed cell signal in MEC, with monotonically increasing or decreasing speed tuning curves, may provide a more robust moment-by-moment account of the animal’s running speed as required for path integration (Fuhs and Touretzky, 2006Fuhs M.C. Touretzky D.S. A spin glass model of path integration in rat medial entorhinal cortex.J. Neurosci. 2006; 26: 4266-4276Crossref PubMed Scopus (405) Google Scholar; McNaughton et al., 2006McNaughton B.L. Battaglia F.P. Jensen O. Moser E.I. Moser M.B. Path integration and the neural basis of the ‘cognitive map’.Nat. Rev. Neurosci. 2006; 7: 663-678Crossref PubMed Scopus (1180) Google Scholar; Burgess et al., 2007Burgess N. Barry C. O’Keefe J. An oscillatory interference model of grid cell firing.Hippocampus. 2007; 17: 801-812Crossref PubMed Scopus (469) Google Scholar; Hasselmo et al., 2007Hasselmo M.E. Giocomo L.M. Zilli E.A. Grid cell firing may arise from interference of theta frequency membrane potential oscillations in single neurons.Hippocampus. 2007; 17: 1252-1271Crossref PubMed Scopus (188) Google Scholar; Burak and Fiete, 2009Burak Y. Fiete I.R. Accurate path integration in continuous attractor network models of grid cells.PLoS Comput. Biol. 2009; 5: e1000291Crossref PubMed Scopus (367) Google Scholar). However, by classifying speed cells according to a linear model, we may undermine the identification of non-linear speed signals present in MEC (Hinman et al., 2016Hinman J.R. Brandon M.P. Climer J.R. Chapman G.W. Hasselmo M.E. Multiple Running Speed Signals in Medial Entorhinal Cortex.Neuron. 2016; 91: 666-679Abstract Full Text Full Text PDF PubMed Scopus (76) Google Scholar; Hardcastle et al., 2017Hardcastle K. Maheswaranathan N. Ganguli S. Giocomo L.M. A multiplexed, heterogeneous, and adaptive code for navigation in medial entorhinal cortex.Neuron. 2017; 94: 375-387.e7Abstract Full Text Full Text PDF PubMed Scopus (88) Google Scholar) but also within MSDB (Zhou et al., 1999Zhou T.L. Tamura R. Kuriwaki J. Ono T. Comparison of medial and lateral septal neuron activity during performance of spatial tasks in rats.Hippocampus. 1999; 9: 220-234Crossref PubMed Scopus (37) Google Scholar) and PPN (Caggiano et al., 2018Caggiano V. Leiras R. Goñi-Erro H. Masini D. Bellardita C. Bouvier J. Caldeira V. Fisone G. Kiehn O. Midbrain circuits that set locomotor speed and gait selection.Nature. 2018; 553: 455-460Crossref PubMed Scopus (147) Google Scholar). We therefore compared speed cell classification with linear and non-linear correlation measures (Pearson’s and Spearman’s correlations, respectively). With a 6 cm/s speed threshold, the two approaches revealed largely overlapping populations of speed cells in each brain region (PPN, 100 of 124 [81%]; HDB, 108 of 127 [85%]; MEC, 311 of 489 [64%]), suggesting that the vast majority of speed cells have a significant linear relationship to speed, although not excluding additional nonlinear components (see legend of Figure 3SB). In PPN, 43 cells (16.5%) were classified as negative speed cells and 76 (29.2%) as positive speed cells. In HDB, 47 cells (15.3%) were classified as negative speed cells and 77 (25.0%) as pos" @default.
• W3084283750 created "2020-09-14" @default.
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• W3084283750 date "2020-09-01" @default.
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• W3084283750 title "A Brainstem Locomotor Circuit Drives the Activity of Speed Cells in the Medial Entorhinal Cortex" @default.
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• W3084283750 doi "https://doi.org/10.1016/j.celrep.2020.108123" @default.
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