UP-DOWN states and ripples differentially modulate membrane potential dynamics across DG, CA3, and CA1 in awake mice.

Hippocampal ripples are transient population bursts that structure cortico-hippocampal communication and play a central role in memory processing. However, the mechanisms controlling ripple initiation in behaving animals remain poorly understood. Here we combine multisite extracellular and whole-cell recordings in awake mice to contrast the brain state and ripple modulation of subthreshold dynamics across hippocampal subfields. We find that entorhinal input to the dentate gyrus (DG) exhibits UP and DOWN dynamics with ripples occurring exclusively in UP states. While elevated cortical input in UP states generates depolarization in DG and CA1, it produces persistent hyperpolarization in CA3 neurons. Furthermore, growing inhibition is evident in CA3 throughout the course of the ripple buildup, while DG and CA1 neurons exhibit depolarization transients 100 ms before and during ripples. These observations highlight the importance of CA3 inhibition for ripple generation, while pre-ripple responses indicate a long and orchestrated ripple initiation process in the awake state.

Model-based spike sorting with a mixture of drifting t-distributions.

BACKGROUND: Chronic extracellular recordings are a powerful tool for systems neuroscience, but spike sorting remains a challenge. A common approach is to fit a generative model, such as a mixture of Gaussians, to the observed spike data. Even if non-parametric methods are used for spike sorting, such generative models provide a quantitative measure of unit isolation quality, which is crucial for subsequent interpretation of the sorted spike trains. NEW METHOD: We present a spike sorting strategy that models the data as a mixture of drifting t-distributions. This model captures two important features of chronic extracellular recordings-cluster drift over time and heavy tails in the distribution of spikes-and offers improved robustness to outliers. RESULTS: We evaluate this model on several thousand hours of chronic tetrode recordings and show that it fits the empirical data substantially better than a mixture of Gaussians. We also provide a software implementation that can re-fit long datasets in a few seconds, enabling interactive clustering of chronic recordings. COMPARISON WITH EXISTING METHODS: We identify three common failure modes of spike sorting methods that assume stationarity and evaluate their impact given the empirically-observed cluster drift in chronic recordings. Using hybrid ground truth datasets, we also demonstrate that our model-based estimate of misclassification error is more accurate than previous unit isolation metrics. CONCLUSIONS: The mixture of drifting t-distributions model enables efficient spike sorting of long datasets and provides an accurate measure of unit isolation quality over a wide range of conditions.

Brain State Dependence of Hippocampal Subthreshold Activity in Awake Mice.

Monitoring the membrane potential of individual neurons has uncovered how single-cell properties contribute to network processing across different brain states in neocortex. In contrast, the subthreshold modulation of hippocampal neurons by brain state has not been systematically characterized. To address this, we combined whole-cell recordings from dentate granule cells and CA1 pyramidal neurons with multisite extracellular recordings and behavioral measurements in awake mice. We show that the average membrane potential, amplitude of subthreshold fluctuations, and distance to spike threshold are all modulated by brain state. Furthermore, even within individual states, rapid variations in arousal are reflected in membrane potential fluctuations. These factors produce depolarizing ramps in the membrane potential of hippocampal neurons that precede ripples and mirror transitions to a network regime conducive for ripple generation. These results suggest that there are coordinated shifts in the subthreshold dynamics of individual neurons that underlie the transitions between distinct modes of hippocampal processing.

Nanofabricated Neural Probes for Dense 3-D Recordings of Brain Activity.

Computations in brain circuits involve the coordinated activation of large populations of neurons distributed across brain areas. However, monitoring neuronal activity in the brain of intact animals with high temporal and spatial resolution has remained a technological challenge. Here we address this challenge by developing dense, three-dimensional (3-D) electrode arrays for electrophysiology. The 3-D arrays constitute the front-end of a modular and configurable system architecture that enables monitoring neuronal activity with unprecedented scale and resolution.

Spatial tuning and brain state account for dorsal hippocampal CA1 activity in a non-spatial learning task.

The hippocampus is a brain area crucial for episodic memory in humans. In contrast, studies in rodents have highlighted its role in spatial learning, supported by the discovery of place cells. Efforts to reconcile these views have found neurons in the rodent hippocampus that respond to non-spatial events but have not unequivocally dissociated the spatial and non-spatial influences on these cells. To disentangle these influences, we trained freely moving rats in trace eyeblink conditioning, a hippocampally dependent task in which the animal learns to blink in response to a tone. We show that dorsal CA1 pyramidal neurons are all place cells, and do not respond to the tone when the animal is moving. When the animal is inactive, the apparent tone-evoked responses reflect an arousal-mediated resumption of place-specific firing. These results suggest that one of the main output stages of the hippocampus transmits only spatial information, even in this non-spatial task.

Membrane Potential Dynamics of CA1 Pyramidal Neurons during Hippocampal Ripples in Awake Mice.

Ripples are high-frequency oscillations associated with population bursts in area CA1 of the hippocampus that play a prominent role in theories of memory consolidation. While spiking during ripples has been extensively studied, our understanding of the subthreshold behavior of hippocampal neurons during these events remains incomplete. Here, we combine in vivo whole-cell and multisite extracellular recordings to characterize the membrane potential dynamics of identified CA1 pyramidal neurons during ripples. We find that the subthreshold depolarization during ripples is uncorrelated with the net excitatory input to CA1, while the post-ripple hyperpolarization varies proportionately. This clarifies the circuit mechanism keeping most neurons silent during ripples. On a finer timescale, the phase delay between intracellular and extracellular ripple oscillations varies systematically with membrane potential. Such smoothly varying delays are inconsistent with models of intracellular ripple generation involving perisomatic inhibition alone. Instead, they suggest that ripple-frequency excitation leading inhibition shapes intracellular ripple oscillations.

Structured Variability in Purkinje Cell Activity during Locomotion.

The cerebellum is a prominent vertebrate brain structure that is critically involved in sensorimotor function. During locomotion, cerebellar Purkinje cells are rhythmically active, shaping descending signals and coordinating commands from higher brain areas with the step cycle. However, the variation in this activity across steps has not been studied, and its statistical structure, afferent mechanisms, and relationship to behavior remain unknown. Here, using multi-electrode recordings in freely moving rats, we show that behavioral variables systematically influence the shape of the step-locked firing rate. This effect depends strongly on the phase of the step cycle and reveals a functional clustering of Purkinje cells. Furthermore, we find a pronounced disassociation between patterns of variability driven by the parallel and climbing fibers. These results suggest that Purkinje cell activity not only represents step phase within each cycle but also is shaped by behavior across steps, facilitating control of movement under dynamic conditions.

A wireless multi-channel neural amplifier for freely moving animals.

Conventional neural recording systems restrict behavioral experiments to a flat indoor environment compatible with the cable that tethers the subject to recording instruments. To overcome these constraints, we developed a wireless multi-channel system for recording neural signals from rats. The device takes up to 64 voltage signals from implanted electrodes, samples each at 20 kHz, time-division multiplexes them into one signal and transmits that output by radio frequency to a receiver up to 60 m away. The system introduces <4 µV of electrode-referred noise, comparable to wired recording systems, and outperforms existing rodent telemetry systems in channel count, weight and transmission range. This allows effective recording of brain signals in freely behaving animals. We report measurements of neural population activity taken outdoors and in tunnels. Neural firing in the visual cortex was relatively sparse, correlated even across large distances and was strongly influenced by locomotor activity.

Hippocampal theta oscillations are travelling waves.

Theta oscillations clock hippocampal activity during awake behaviour and rapid eye movement (REM) sleep. These oscillations are prominent in the local field potential, and they also reflect the subthreshold membrane potential and strongly modulate the spiking of hippocampal neurons. The prevailing view is that theta oscillations are synchronized throughout the hippocampus, despite the lack of conclusive experimental evidence. In contrast, here we show that in freely behaving rats, theta oscillations in area CA1 are travelling waves that propagate roughly along the septotemporal axis of the hippocampus. Furthermore, we find that spiking in the CA1 pyramidal cell layer is modulated in a consistent travelling wave pattern. Our results demonstrate that theta oscillations pattern hippocampal activity not only in time, but also across anatomical space. The presence of travelling waves indicates that the instantaneous output of the hippocampus is topographically organized and represents a segment, rather than a point, of physical space.

Dopamine signaling differences in the nucleus accumbens and dorsal striatum exploited by nicotine.

The dorsal striatum and the nucleus accumbens (NAc) shell of the ventral striatum have similar cellular components and are both richly innervated by dopamine neurons. Despite similarities that extend throughout the striatum, only the NAc shell has a conspicuous increase in basal dopamine upon the initial administration of psychostimulant drugs such as nicotine. As measured by microdialysis, the elevated dopamine in the NAc shell is considered an identifying functional characteristic of addictive drugs. To examine this general functional difference between nicotine's action on the dorsolateral striatum and NAc shell, we directly monitored dopamine release in rat striatal slices using fast-scan cyclic voltammetry. In addition, we separately monitored the in vivo unit firing activity of putative midbrain dopamine neurons from freely moving rats using chronic multiple tetrodes. Nicotine administration increased the firing frequency of dopamine neurons and specifically increased the number and the length of phasic burst firing. The frequency dependence for dopamine release in the dorsolateral striatum and NAc shell is fundamentally different, enabling mainly the NAc shell to capitalize on the nicotine-induced phasic burst firing by dopamine neurons. Although nicotine decreased low-frequency (tonic) dopamine release in both areas, the increased ratio of phasic bursts relative to tonic firing caused by nicotine boosted the basal dopamine concentration predominantly in the NAc shell. By favoring release from bursts while depressing release from tonic signals, nicotine spreads the range of dopamine signaling and effectively increases the signal-to-noise relationship along dopamine afferents.

State-dependent spike-timing relationships between hippocampal and prefrontal circuits during sleep.

Cortico-hippocampal interactions during sleep are believed to reorganize neural circuits in support of memory consolidation. However, spike-timing relationships across cortico-hippocampal networks-key determinants of synaptic changes-are poorly understood. Here we show that cells in prefrontal cortex fire consistently within 100 ms after hippocampal cells in naturally sleeping animals. This provides evidence at the single cell-pair level for highly consistent directional interactions between these areas within the window of plasticity. Moreover, these interactions are state dependent: they are driven by hippocampal sharp-wave/ripple (SWR) bursts in slow-wave sleep (SWS) and are sharply reduced during REM sleep. Finally, prefrontal responses are nonlinear: as the strength of hippocampal bursts rises, short-latency prefrontal responses are augmented by increased spindle band activity and a secondary peak approximately 100 ms later. These findings suggest that SWR events are atomic units of hippocampal-prefrontal communication during SWS and that the coupling between these areas is highly attenuated during REM sleep.

Decoupling through synchrony in neuronal circuits with propagation delays.

The level of synchronization in distributed systems is often controlled by the strength of the interactions between individual elements. In brain circuits the connection strengths between neurons are modified under the influence of spike-timing-dependent plasticity (STDP) rules. Here we show that when recurrent networks with conduction delays exhibit population bursts, STDP rules exert a strong decoupling force that desynchronizes activity. Conversely, when activity in the network is random, the same rules can have a coupling and synchronizing influence. The presence of these opposing forces promotes the self-organization of spontaneously active neuronal networks to a state at the border between randomness and synchrony. The decoupling force of STDP may be engaged by the synchronous bursts occurring in the hippocampus during slow-wave sleep, leading to the selective erasure of information from hippocampal circuits as memories are established in neocortical areas.

Recording chronically from the same neurons in awake, behaving primates.

Understanding the mechanisms of learning requires characterizing how the response properties of individual neurons and interactions across populations of neurons change over time. To study learning in vivo, we need the ability to track an electrophysiological signature that uniquely identifies each recorded neuron for extended periods of time. We have identified such an extracellular signature using a statistical framework that allows quantification of the accuracy by which stable neurons can be identified across successive recording sessions. Our statistical framework uses spike waveform information recorded on a tetrode's four channels to define a measure of similarity between neurons recorded across time. We use this framework to quantitatively demonstrate for the first time the ability to record from the same neurons across multiple consecutive days and weeks. The chronic recording techniques and methods of analyses we report can be used to characterize the changes in brain circuits due to learning.

Prefrontal phase locking to hippocampal theta oscillations.

The interactions between cortical and hippocampal circuits are critical for memory formation, yet their basic organization at the neuronal network level is not well understood. Here, we demonstrate that a significant portion of neurons in the medial prefrontal cortex of freely behaving rats are phase locked to the hippocampal theta rhythm. In addition, we show that prefrontal neurons phase lock best to theta oscillations delayed by approximately 50 ms and confirm this hippocampo-prefrontal directionality and timing at the level of correlations between single cells. Finally, we find that phase locking of prefrontal cells is predicted by the presence of significant correlations with hippocampal cells at positive delays up to 150 ms. The theta-entrained activity across cortico-hippocampal circuits described here may be important for gating information flow and guiding the plastic changes that are believed to underlie the storage of information across these networks.