Spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity.

Understanding the functional connectivity between brain regions and its emergent dynamics is a central challenge. Here we present a theory-experiment hybrid approach involving iteration between a minimal computational model and in vivo electrophysiological measurements. Our model not only predicted spontaneous persistent activity (SPA) during Up-Down-State oscillations, but also inactivity (SPI), which has never been reported. These were confirmed in vivo in the membrane potential of neurons, especially from layer 3 of the medial and lateral entorhinal cortices. The data was then used to constrain two free parameters, yielding a unique, experimentally determined model for each neuron. Analytic and computational analysis of the model generated a dozen quantitative predictions about network dynamics, which were all confirmed in vivo to high accuracy. Our technique predicted functional connectivity; e. g. the recurrent excitation is stronger in the medial than lateral entorhinal cortex. This too was confirmed with connectomics data. This technique uncovers how differential cortico-entorhinal dialogue generates SPA and SPI, which could form an energetically efficient working-memory substrate and influence the consolidation of memories during sleep. More broadly, our procedure can reveal the functional connectivity of large networks and a theory of their emergent dynamics.

Moving bar of light evokes vectorial spatial selectivity in the immobile rat hippocampus.

Visual cortical neurons encode the position and motion direction of specific stimuli retrospectively, without any locomotion or task demand1. The hippocampus, which is a part of the visual system, is hypothesized to require self-motion or a cognitive task to generate allocentric spatial selectivity that is scalar, abstract2,3 and prospective4-7. Here we measured rodent hippocampal selectivity to a moving bar of light in a body-fixed rat to bridge these seeming disparities. About 70% of dorsal CA1 neurons showed stable activity modulation as a function of the angular position of the bar, independent of behaviour and rewards. One-third of tuned cells also encoded the direction of revolution. In other experiments, neurons encoded the distance of the bar, with preference for approaching motion. Collectively, these demonstrate visually evoked vectorial selectivity (VEVS). Unlike place cells, VEVS was retrospective. Changes in the visual stimulus or its predictability did not cause remapping but only caused gradual changes. Most VEVS-tuned neurons behaved like place cells during spatial exploration and the two selectivities were correlated. Thus, VEVS could form the basic building block of hippocampal activity. When combined with self-motion, reward or multisensory stimuli8, it can generate the complexity of prospective representations including allocentric space9, time10,11 and episodes12.

Linking hippocampal multiplexed tuning, Hebbian plasticity and navigation.

Three major pillars of hippocampal function are spatial navigation1, Hebbian synaptic plasticity2 and spatial selectivity3. The hippocampus is also implicated in episodic memory4, but the precise link between these four functions is missing. Here we report the multiplexed selectivity of dorsal CA1 neurons while rats performed a virtual navigation task using only distal visual cues5, similar to the standard water maze test of spatial memory1. Neural responses primarily encoded path distance from the start point and the head angle of rats, with a weak allocentric spatial component similar to that in primates but substantially weaker than in rodents in the real world. Often, the same cells multiplexed and encoded path distance, angle and allocentric position in a sequence, thus encoding a journey-specific episode. The strength of neural activity and tuning strongly correlated with performance, with a temporal relationship indicating neural responses influencing behaviour and vice versa. Consistent with computational models of associative and causal Hebbian learning6,7, neural responses showed increasing clustering8 and became better predictors of behaviourally relevant variables, with the average neurometric curves exceeding and converging to psychometric curves. Thus, hippocampal neurons multiplex and exhibit highly plastic, task- and experience-dependent tuning to path-centric and allocentric variables to form episodic sequences supporting navigation.

Enhanced hippocampal theta rhythmicity and emergence of eta oscillation in virtual reality.

Hippocampal theta rhythm is a therapeutic target because of its vital role in neuroplasticity, learning and memory. Curiously, theta differs across species. Here we show that theta rhythmicity is greatly amplified when rats run in virtual reality. A novel eta rhythm emerged in the CA1 cell layer, primarily in interneurons. Thus, multisensory experience governs hippocampal rhythms. Virtual reality can be used to boost or control brain rhythms and to alter neural dynamics, wiring and plasticity.

Dynamics of cortical dendritic membrane potential and spikes in freely behaving rats.

Neural activity in vivo is primarily measured using extracellular somatic spikes, which provide limited information about neural computation. Hence, it is necessary to record from neuronal dendrites, which can generate dendritic action potentials (DAPs) in vitro, which can profoundly influence neural computation and plasticity. We measured neocortical sub- and suprathreshold dendritic membrane potential (DMP) from putative distal-most dendrites using tetrodes in freely behaving rats over multiple days with a high degree of stability and submillisecond temporal resolution. DAP firing rates were several-fold larger than somatic rates. DAP rates were also modulated by subthreshold DMP fluctuations, which were far larger than DAP amplitude, indicating hybrid, analog-digital coding in the dendrites. Parietal DAP and DMP exhibited egocentric spatial maps comparable to pyramidal neurons. These results have important implications for neural coding and plasticity.

Causal Influence of Visual Cues on Hippocampal Directional Selectivity.

Hippocampal neurons show selectivity with respect to visual cues in primates, including humans, but this has never been found in rodents. To address this long-standing discrepancy, we measured hippocampal activity from rodents during real-world random foraging. Surprisingly, ∼ 25% of neurons exhibited significant directional modulation with respect to visual cues. To dissociate the contributions of visual and vestibular cues, we made similar measurements in virtual reality, in which only visual cues were informative. Here, we found significant directional modulation despite the severe loss of vestibular information, challenging prevailing theories of directionality. Changes in the amount of angular information in visual cues induced corresponding changes in head-directional modulation at the neuronal and population levels. Thus, visual cues are sufficient for-and play a predictable, causal role in-generating directionally selective hippocampal responses. These results dissociate hippocampal directional and spatial selectivity and bridge the gap between primate and rodent studies.

From synaptic plasticity to spatial maps and sequence learning.

The entorhinal-hippocampal circuit is crucial for several forms of learning and memory, especially sequence learning, including spatial navigation. The challenge is to understand the underlying mechanisms. Pioneering discoveries of spatial selectivity in this circuit, i.e. place cells and grid cells, provided a major step forward in tackling this challenge. Considerable research has also shown that sequence learning relies on synaptic plasticity, especially the Hebbian or the NMDAR-dependent synaptic plasticity. This raises several questions: Are spatial maps plastic? If so, what is the contribution of Hebbian plasticity to spatial map plasticity? How does the spatial map plasticity contribute to sequence learning? A combination of computational and experimental studies has shown that NMDAR-mediated plasticity and theta rhythm can have specific effects on the formation and experiential modification of spatial maps to facilitate predictive coding. Advances in transgenic techniques have provided further support for these mechanisms. Although many exciting challenges remain, these findings have brought us closer to solving the puzzle of how the hippocampal system contributes to spatial memory, and point to a way forward.

Impaired spatial selectivity and intact phase precession in two-dimensional virtual reality.

During real-world (RW) exploration, rodent hippocampal activity shows robust spatial selectivity, which is hypothesized to be governed largely by distal visual cues, although other sensory-motor cues also contribute. Indeed, hippocampal spatial selectivity is weak in primate and human studies that use only visual cues. To determine the contribution of distal visual cues only, we measured hippocampal activity from body-fixed rodents exploring a two-dimensional virtual reality (VR). Compared to that in RW, spatial selectivity was markedly reduced during random foraging and goal-directed tasks in VR. Instead we found small but significant selectivity to distance traveled. Despite impaired spatial selectivity in VR, most spikes occurred within ∼2-s-long hippocampal motifs in both RW and VR that had similar structure, including phase precession within motif fields. Selectivity to space and distance traveled were greatly enhanced in VR tasks with stereotypical trajectories. Thus, distal visual cues alone are insufficient to generate a robust hippocampal rate code for space but are sufficient for a temporal code.

Multisensory control of multimodal behavior: do the legs know what the tongue is doing?

Understanding of adaptive behavior requires the precisely controlled presentation of multisensory stimuli combined with simultaneous measurement of multiple behavioral modalities. Hence, we developed a virtual reality apparatus that allows for simultaneous measurement of reward checking, a commonly used measure in associative learning paradigms, and navigational behavior, along with precisely controlled presentation of visual, auditory and reward stimuli. Rats performed a virtual spatial navigation task analogous to the Morris maze where only distal visual or auditory cues provided spatial information. Spatial navigation and reward checking maps showed experience-dependent learning and were in register for distal visual cues. However, they showed a dissociation, whereby distal auditory cues failed to support spatial navigation but did support spatially localized reward checking. These findings indicate that rats can navigate in virtual space with only distal visual cues, without significant vestibular or other sensory inputs. Furthermore, they reveal the simultaneous dissociation between two reward-driven behaviors.

Multisensory control of hippocampal spatiotemporal selectivity.

The hippocampal cognitive map is thought to be driven by distal visual cues and self-motion cues. However, other sensory cues also influence place cells. Hence, we measured rat hippocampal activity in virtual reality (VR), where only distal visual and nonvestibular self-motion cues provided spatial information, and in the real world (RW). In VR, place cells showed robust spatial selectivity; however, only 20% were track active, compared with 45% in the RW. This indicates that distal visual and nonvestibular self-motion cues are sufficient to provide selectivity, but vestibular and other sensory cues present in RW are necessary to fully activate the place-cell population. In addition, bidirectional cells preferentially encoded distance along the track in VR, while encoding absolute position in RW. Taken together, these results suggest the differential contributions of these sensory cues in shaping the hippocampal population code. Theta frequency was reduced, and its speed dependence was abolished in VR, but phase precession was unaffected, constraining mechanisms governing both hippocampal theta oscillations and temporal coding. These results reveal cooperative and competitive interactions between sensory cues for control over hippocampal spatiotemporal selectivity and theta rhythm.

Spontaneous persistent activity in entorhinal cortex modulates cortico-hippocampal interaction in vivo.

Persistent activity is thought to mediate working memory during behavior. Can it also occur during sleep? We found that the membrane potential of medial entorhinal cortex layer III (MECIII) neurons, a gateway between neocortex and hippocampus, showed spontaneous, stochastic persistent activity in vivo in mice during Up-Down state oscillations (UDS). This persistent activity was locked to the neocortical Up states with a short delay, but persisted over several cortical UDS cycles. Lateral entorhinal neurons did not show substantial persistence, and current injections similar to those used in vitro failed to elicit persistence in vivo, implicating network mechanisms. Hippocampal CA1 neurons' spiking activity was reduced during neocortical Up states, but was increased during MECIII persistent states. These results provide, to the best of our knowledge, the first direct evidence for persistent activity in MECIII neurons in vivo and reveal its contribution to cortico-hippocampal interaction that could be involved in working memory and learning of long behavioral sequences during behavior, and memory consolidation during sleep.

The effects of GluA1 deletion on the hippocampal population code for position.

The GluA1 subunit of AMPA receptors (AMPARs) is critical for hippocampal synaptic transmission and plasticity. Here, we measured the activity of single units from the CA1 region of the hippocampus while GluA1 knock-out (GluA1⁻/⁻) and wild-type (WT) mice traversed a linear track. Although overall firing rates were similar, GluA1⁻/⁻ neurons were more likely to spike in bursts, but at lower burst frequencies, compared with WT neurons. GluA1⁻/⁻ neurons showed large reductions in all measures of spatial and directional selectivity compared with WT neurons. Consistent with these alterations of single-neuron properties, the accuracy of the population code for position was substantially reduced in GluA1⁻/⁻, yet it is predicted to approach the accuracy of WT with increasing population size. The absolute representation of space, independent of movement direction, was greatly diminished in GluA1⁻/⁻ mice and is predicted to remain reduced even for larger populations. Finally, we found that the rate maps of GluA1⁻/⁻ neurons showed increased trial-by-trial variability but reduced experiential plasticity compared with the WT. These results reveal the critical contribution of GluA1-containing AMPARs to individual place cells and the hippocampal population code for space, which could explain the selective behavioral impairments observed in these mice.

Running speed alters the frequency of hippocampal gamma oscillations.

Successful spatial navigation is thought to employ a combination of at least two strategies: the following of landmark cues and path integration. Path integration requires that the brain use the speed and direction of movement in a meaningful way to continuously compute the position of the animal. Indeed, the running speed of rats modulates both the firing rate of neurons and the spectral properties of low frequency, theta oscillations seen in the local field potential (LFP) of the hippocampus, a region important for spatial memory formation. Higher frequency, gamma-band LFP oscillations are usually associated with decision-making, increased attention, and improved reaction times. Here, we show that increased running speed is accompanied by large, systematic increases in the frequency of hippocampal CA1 network oscillations spanning the entire gamma range (30-120 Hz) and beyond. These speed-dependent changes in frequency are seen on both linear tracks and two-dimensional platforms, and are thus independent of the behavioral task. Synchrony between anatomically distant CA1 regions also shifts to higher gamma frequencies as running speed increases. The changes in frequency are strongly correlated with changes in the firing rates of individual interneurons, consistent with models of gamma generation. Our results suggest that as a rat runs faster, there are faster gamma frequency transitions between sequential place cell-assemblies. This may help to preserve the spatial specificity of place cells and spatial memories at vastly different running speeds.

Contribution of Ih to LTP, place cells, and grid cells.

The brain's grid and place cells, which contribute to spatial representations of the external environment, are thought to be modulated by the hyperpolarization-activated cation current (I(h)). Giocomo et al. and Hussaini et al. now provide new insights into these cells' unique activity patterns by studying transgenic mice lacking I(h).

Frequency-Dependent Changes in NMDAR-Dependent Synaptic Plasticity.

The NMDAR-dependent synaptic plasticity is thought to mediate several forms of learning, and can be induced by spike trains containing a small number of spikes occurring with varying rates and timing, as well as with oscillations. We computed the influence of these variables on the plasticity induced at a single NMDAR containing synapse using a reduced model that was analytically tractable, and these findings were confirmed using detailed, multi-compartment model. In addition to explaining diverse experimental results about the rate and timing dependence of synaptic plasticity, the model made several novel and testable predictions. We found that there was a preferred frequency for inducing long-term potentiation (LTP) such that higher frequency stimuli induced lesser LTP, decreasing as 1/f when the number of spikes in the stimulus was kept fixed. Among other things, the preferred frequency for inducing LTP varied as a function of the distance of the synapse from the soma. In fact, same stimulation frequencies could induce LTP or long-term depression depending on the dendritic location of the synapse. Next, we found that rhythmic stimuli induced greater plasticity then irregular stimuli. Furthermore, brief bursts of spikes significantly expanded the timing dependence of plasticity. Finally, we found that in the ∼5-15-Hz frequency range both rate- and timing-dependent plasticity mechanisms work synergistically to render the synaptic plasticity most sensitive to spike timing. These findings provide computational evidence that oscillations can have a profound influence on the plasticity of an NMDAR-dependent synapse, and show a novel role for the dendritic morphology in this process.

Speed controls the amplitude and timing of the hippocampal gamma rhythm.

Cortical and hippocampal gamma oscillations have been implicated in many behavioral tasks. The hippocampus is required for spatial navigation where animals run at varying speeds. Hence we tested the hypothesis that the gamma rhythm could encode the running speed of mice. We found that the amplitude of slow (20-45 Hz) and fast (45-120 Hz) gamma rhythms in the hippocampal local field potential (LFP) increased with running speed. The speed-dependence of gamma amplitude was restricted to a narrow range of theta phases where gamma amplitude was maximal, called the preferred theta phase of gamma. The preferred phase of slow gamma precessed to lower values with increasing running speed. While maximal fast and slow gamma occurred at coincident phases of theta at low speeds, they became progressively more theta-phase separated with increasing speed. These results demonstrate a novel influence of speed on the amplitude and timing of the hippocampal gamma rhythm which could contribute to learning of temporal sequences and navigation.

Explicit-duration hidden Markov model inference of UP-DOWN states from continuous signals.

Neocortical neurons show UP-DOWN state (UDS) oscillations under a variety of conditions. These UDS have been extensively studied because of the insight they can yield into the functioning of cortical networks, and their proposed role in putative memory formation. A key element in these studies is determining the precise duration and timing of the UDS. These states are typically determined from the membrane potential of one or a small number of cells, which is often not sufficient to reliably estimate the state of an ensemble of neocortical neurons. The local field potential (LFP) provides an attractive method for determining the state of a patch of cortex with high spatio-temporal resolution; however current methods for inferring UDS from LFP signals lack the robustness and flexibility to be applicable when UDS properties may vary substantially within and across experiments. Here we present an explicit-duration hidden Markov model (EDHMM) framework that is sufficiently general to allow statistically principled inference of UDS from different types of signals (membrane potential, LFP, EEG), combinations of signals (e.g., multichannel LFP recordings) and signal features over long recordings where substantial non-stationarities are present. Using cortical LFPs recorded from urethane-anesthetized mice, we demonstrate that the proposed method allows robust inference of UDS. To illustrate the flexibility of the algorithm we show that it performs well on EEG recordings as well. We then validate these results using simultaneous recordings of the LFP and membrane potential (MP) of nearby cortical neurons, showing that our method offers significant improvements over standard methods. These results could be useful for determining functional connectivity of different brain regions, as well as understanding network dynamics.

The hippocampal rate code: anatomy, physiology and theory.

Since the days of Cajal, the CA1 pyramidal cell has arguably received more attention than any other neuron in the mammalian brain. Hippocampal CA1 pyramidal cells fire spikes with remarkable spatial and temporal precision, giving rise to the hippocampal rate and temporal codes. However, little is known about how different inputs interact during spatial behavior to generate such robust firing patterns. Here, we review the properties of the rodent hippocampal rate code and synthesize work from several disciplines to understand the functional anatomy and excitation-inhibition balance that can produce the rate-coded outputs of the CA1 pyramidal cell. We argue that both CA3 and entorhinal inputs are crucial for the formation of sharp, sparse CA1 place fields and that precisely timed and dominant inhibition is an equally important factor.

Differential responses of hippocampal subfields to cortical up-down states.

The connectivity of the hippocampal trisynaptic circuit, formed by the dentate gyrus, the CA3 and the CA1 region, is well characterized anatomically and functionally in vitro. The functional connectivity of this circuit in vivo remains to be understood. Toward this goal, we investigated the influence of the spontaneous, synchronized oscillations in the neocortical local field potential, reflecting up-down states (UDS) of cortical neurons, on the hippocampus. We simultaneously measured the extracellular local field potential in association cortex and the membrane potential of identified hippocampal excitatory neurons in anesthetized mice. Dentate gyrus granule cells showed clear UDS modulation that was phase locked to cortical UDS with a short delay. In contrast, CA3 pyramidal neurons showed mixed UDS modulation, such that some cells were depolarized during the cortical up state and others were hyperpolarized. CA1 pyramidal neurons, located farther downstream, showed consistent UDS modulation, such that when the cortical and dentate gyrus neurons were depolarized, the CA1 pyramidal cells were hyperpolarized. These results demonstrate the differential functional connectivity between neocortex and hippocampal subfields during UDS oscillations.