The medial septum controls hippocampal supra-theta oscillations.

Hippocampal theta oscillations orchestrate faster beta-to-gamma oscillations facilitating the segmentation of neural representations during navigation and episodic memory. Supra-theta rhythms of hippocampal CA1 are coordinated by local interactions as well as inputs from the entorhinal cortex (EC) and CA3 inputs. However, theta-nested gamma-band activity in the medial septum (MS) suggests that the MS may control supra-theta CA1 oscillations. To address this, we performed multi-electrode recordings of MS and CA1 activity in rodents and found that MS neuron firing showed strong phase-coupling to theta-nested supra-theta episodes and predicted changes in CA1 beta-to-gamma oscillations on a cycle-by-cycle basis. Unique coupling patterns of anatomically defined MS cell types suggested that indirect MS-to-CA1 pathways via the EC and CA3 mediate distinct CA1 gamma-band oscillations. Optogenetic activation of MS parvalbumin-expressing neurons elicited theta-nested beta-to-gamma oscillations in CA1. Thus, the MS orchestrates hippocampal network activity at multiple temporal scales to mediate memory encoding and retrieval.

Huygens synchronization of medial septal pacemaker neurons generates hippocampal theta oscillation.

Episodic learning and memory retrieval are dependent on hippocampal theta oscillation, thought to rely on the GABAergic network of the medial septum (MS). To test how this network achieves theta synchrony, we recorded MS neurons and hippocampal local field potential simultaneously in anesthetized and awake mice and rats. We show that MS pacemakers synchronize their individual rhythmicity frequencies, akin to coupled pendulum clocks as observed by Huygens. We optogenetically identified them as parvalbumin-expressing GABAergic neurons, while MS glutamatergic neurons provide tonic excitation sufficient to induce theta. In accordance, waxing and waning tonic excitation is sufficient to toggle between theta and non-theta states in a network model of single-compartment inhibitory pacemaker neurons. These results provide experimental and theoretical support to a frequency-synchronization mechanism for pacing hippocampal theta, which may serve as an inspirational prototype for synchronization processes in the central nervous system from Nematoda to Arthropoda to Chordate and Vertebrate phyla.

Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings.

Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

Infrared neural stimulation and inhibition using an implantable silicon photonic microdevice.

Brain is one of the most temperature sensitive organs. Besides the fundamental role of temperature in cellular metabolism, thermal response of neuronal populations is also significant during the evolution of various neurodegenerative diseases. For such critical environmental factor, thorough mapping of cellular response to variations in temperature is desired in the living brain. So far, limited efforts have been made to create complex devices that are able to modulate temperature, and concurrently record multiple features of the stimulated region. In our work, the in vivo application of a multimodal photonic neural probe is demonstrated. Optical, thermal, and electrophysiological functions are monolithically integrated in a single device. The system facilitates spatial and temporal control of temperature distribution at high precision in the deep brain tissue through an embedded infrared waveguide, while it provides recording of the artefact-free electrical response of individual cells at multiple locations along the probe shaft. Spatial distribution of the optically induced temperature changes is evaluated through in vitro measurements and a validated multi-physical model. The operation of the multimodal microdevice is demonstrated in the rat neocortex and in the hippocampus to increase or suppress firing rate of stimulated neurons in a reversible manner using continuous wave infrared light (λ = 1550 nm). Our approach is envisioned to be a promising candidate as an advanced experimental toolset to reveal thermally evoked responses in the deep neural tissue.

Dynamics of sleep oscillations is coupled to brain temperature on multiple scales.

KEY POINTS: Sleep spindle frequency positively, duration negatively correlates with brain temperature. Local heating of the thalamus produces similar effects in the heated area. Thalamic network model corroborates temperature dependence of sleep spindle frequency. Brain temperature shows spontaneous microfluctuations during both anesthesia and natural sleep. Larger fluctuations are associated with epochs of REM sleep. Smaller fluctuations correspond to the alteration of spindling and delta epochs of infra-slow oscillation. ABSTRACT: Every form of neural activity depends on temperature, yet its relationship to brain rhythms is poorly understood. In this work we examined how sleep spindles are influenced by changing brain temperatures and how brain temperature is influenced by sleep oscillations. We employed a novel thermoelectrode designed for measuring temperature while recording neural activity. We found that spindle frequency is positively correlated and duration negatively correlated with brain temperature. Local heating of the thalamus replicated the temperature dependence of spindle parameters in the heated area only, suggesting biophysical rather than global modulatory mechanisms, a finding also supported by a thalamic network model. Finally, we show that switches between oscillatory states also influence brain temperature on a shorter and smaller scale. Epochs of paradoxical sleep as well as the infra-slow oscillation were associated with brain temperature fluctuations below 0.2°C. Our results highlight that brain temperature is massively intertwined with sleep oscillations on various time scales.

A highly collateralized thalamic cell type with arousal-predicting activity serves as a key hub for graded state transitions in the forebrain.

Sleep cycles consist of rapid alterations between arousal states, including transient perturbation of sleep rhythms, microarousals, and full-blown awake states. Here we demonstrate that the calretinin (CR)-containing neurons in the dorsal medial thalamus (DMT) constitute a key diencephalic node that mediates distinct levels of forebrain arousal. Cell-type-specific activation of DMT/CR+ cells elicited active locomotion lasting for minutes, stereotyped microarousals, or transient disruption of sleep rhythms, depending on the parameters of the stimulation. State transitions could be induced in both slow-wave and rapid eye-movement sleep. The DMT/CR+ cells displayed elevated activity before arousal, received selective subcortical inputs, and innervated several forebrain sites via highly branched axons. Together, these features enable DMT/CR+ cells to summate subcortical arousal information and effectively transfer it as a rapid, synchronous signal to several forebrain regions to modulate the level of arousal.

UP-DOWN cortical dynamics reflect state transitions in a bistable network.

In the idling brain, neuronal circuits transition between periods of sustained firing (UP state) and quiescence (DOWN state), a pattern the mechanisms of which remain unclear. Here we analyzed spontaneous cortical population activity from anesthetized rats and found that UP and DOWN durations were highly variable and that population rates showed no significant decay during UP periods. We built a network rate model with excitatory (E) and inhibitory (I) populations exhibiting a novel bistable regime between a quiescent and an inhibition-stabilized state of arbitrarily low rate. Fluctuations triggered state transitions, while adaptation in E cells paradoxically caused a marginal decay of E-rate but a marked decay of I-rate in UP periods, a prediction that we validated experimentally. A spiking network implementation further predicted that DOWN-to-UP transitions must be caused by synchronous high-amplitude events. Our findings provide evidence of bistable cortical networks that exhibit non-rhythmic state transitions when the brain rests.

Hybrid intracerebral probe with integrated bare LED chips for optogenetic studies.

This article reports on the development, i.e., the design, fabrication, and validation of an implantable optical neural probes designed for in vivo experiments relying on optogenetics. The probes comprise an array of ten bare light-emitting diode (LED) chips emitting at a wavelength of 460 nm and integrated along a flexible polyimide-based substrate stiffened using a micromachined ladder-like silicon structure. The resulting mechanical stiffness of the slender, 250-µm-wide, 65-µm-thick, and 5- and 8-mm-long probe shank facilitates its implantation into neural tissue. The LEDs are encapsulated by a fluropolymer coating protecting the implant against the physiological conditions in the brain. The electrical interface to the external control unit is provided by 10-µm-thick, highly flexible polyimide cables making the probes suitable for both acute and chronic in vivo experiments. Optical and electrical properties of the probes are reported, as well as their in vivo validation in acute optogenetic studies in transgenic mice. The depth-dependent optical stimulation of both excitatory and inhibitory neurons is demonstrated by altering the brain activity in the cortex and the thalamus. Local network responses elicited by 20-ms-long light pulses of different optical power (20 µW and 1 mW), as well as local modulation of single unit neuronal activity to 1-s-long light pulses with low optical intensity (17 µW) are presented. The ability to modulate neural activity makes these devices suitable for a broad variety of optogenetic experiments.

Inhibitory control of correlated intrinsic variability in cortical networks.

Cortical networks exhibit intrinsic dynamics that drive coordinated, large-scale fluctuations across neuronal populations and create noise correlations that impact sensory coding. To investigate the network-level mechanisms that underlie these dynamics, we developed novel computational techniques to fit a deterministic spiking network model directly to multi-neuron recordings from different rodent species, sensory modalities, and behavioral states. The model generated correlated variability without external noise and accurately reproduced the diverse activity patterns in our recordings. Analysis of the model parameters suggested that differences in noise correlations across recordings were due primarily to differences in the strength of feedback inhibition. Further analysis of our recordings confirmed that putative inhibitory neurons were indeed more active during desynchronized cortical states with weak noise correlations. Our results demonstrate that network models with intrinsically-generated variability can accurately reproduce the activity patterns observed in multi-neuron recordings and suggest that inhibition modulates the interactions between intrinsic dynamics and sensory inputs to control the strength of noise correlations.

Diverse coupling of neurons to populations in sensory cortex.

A large population of neurons can, in principle, produce an astronomical number of distinct firing patterns. In cortex, however, these patterns lie in a space of lower dimension, as if individual neurons were "obedient members of a huge orchestra". Here we use recordings from the visual cortex of mouse (Mus musculus) and monkey (Macaca mulatta) to investigate the relationship between individual neurons and the population, and to establish the underlying circuit mechanisms. We show that neighbouring neurons can differ in their coupling to the overall firing of the population, ranging from strongly coupled 'choristers' to weakly coupled 'soloists'. Population coupling is largely independent of sensory preferences, and it is a fixed cellular attribute, invariant to stimulus conditions. Neurons with high population coupling are more strongly affected by non-sensory behavioural variables such as motor intention. Population coupling reflects a causal relationship, predicting the response of a neuron to optogenetically driven increases in local activity. Moreover, population coupling indicates synaptic connectivity; the population coupling of a neuron, measured in vivo, predicted subsequent in vitro estimates of the number of synapses received from its neighbours. Finally, population coupling provides a compact summary of population activity; knowledge of the population couplings of n neurons predicts a substantial portion of their n(2) pairwise correlations. Population coupling therefore represents a novel, simple measure that characterizes the relationship of each neuron to a larger population, explaining seemingly complex network firing patterns in terms of basic circuit variables.

Optogenetic activation of septal cholinergic neurons suppresses sharp wave ripples and enhances theta oscillations in the hippocampus.

Theta oscillations in the limbic system depend on the integrity of the medial septum. The different populations of medial septal neurons (cholinergic and GABAergic) are assumed to affect different aspects of theta oscillations. Using optogenetic stimulation of cholinergic neurons in ChAT-Cre mice, we investigated their effects on hippocampal local field potentials in both anesthetized and behaving mice. Cholinergic stimulation completely blocked sharp wave ripples and strongly suppressed the power of both slow oscillations (0.5-2 Hz in anesthetized, 0.5-4 Hz in behaving animals) and supratheta (6-10 Hz in anesthetized, 10-25 Hz in behaving animals) bands. The same stimulation robustly increased both the power and coherence of theta oscillations (2-6 Hz) in urethane-anesthetized mice. In behaving mice, cholinergic stimulation was less effective in the theta (4-10 Hz) band yet it also increased the ratio of theta/slow oscillation and theta coherence. The effects on gamma oscillations largely mirrored those of theta. These findings show that medial septal cholinergic activation can both enhance theta rhythm and suppress peri-theta frequency bands, allowing theta oscillations to dominate.

Ongoing network state controls the length of sleep spindles via inhibitory activity.

Sleep spindles are major transient oscillations of the mammalian brain. Spindles are generated in the thalamus; however, what determines their duration is presently unclear. Here, we measured somatic activity of excitatory thalamocortical (TC) cells together with axonal activity of reciprocally coupled inhibitory reticular thalamic cells (nRTs) and quantified cycle-by-cycle alterations in their firing in vivo. We found that spindles with different durations were paralleled by distinct nRT activity, and nRT firing sharply dropped before the termination of all spindles. Both initial nRT and TC activity was correlated with spindle length, but nRT correlation was more robust. Analysis of spindles evoked by optogenetic activation of nRT showed that spindle probability, but not spindle length, was determined by the strength of the light stimulus. Our data indicate that during natural sleep a dynamically fluctuating thalamocortical network controls the duration of sleep spindles via the major inhibitory element of the circuits, the nRT.

Phasic, nonsynaptic GABA-A receptor-mediated inhibition entrains thalamocortical oscillations.

GABA-A receptors (GABA-ARs) are typically expressed at synaptic or nonsynaptic sites mediating phasic and tonic inhibition, respectively. These two forms of inhibition conjointly control various network oscillations. To disentangle their roles in thalamocortical rhythms, we focally deleted synaptic, γ2 subunit-containing GABA-ARs in the thalamus using viral intervention in mice. After successful removal of γ2 subunit clusters, spontaneous and evoked GABAergic synaptic currents disappeared in thalamocortical cells when the presynaptic, reticular thalamic (nRT) neurons fired in tonic mode. However, when nRT cells fired in burst mode, slow phasic GABA-AR-mediated events persisted, indicating a dynamic, burst-specific recruitment of nonsynaptic GABA-ARs. In vivo, removal of synaptic GABA-ARs reduced the firing of individual thalamocortical cells but did not abolish slow oscillations or sleep spindles. We conclude that nonsynaptic GABA-ARs are recruited in a phasic manner specifically during burst firing of nRT cells and provide sufficient GABA-AR activation to control major thalamocortical oscillations.

Formation and reverberation of sequential neural activity patterns evoked by sensory stimulation are enhanced during cortical desynchronization.

Memory formation is hypothesized to involve the generation of event-specific neural activity patterns during learning and the subsequent spontaneous reactivation of these patterns. Here, we present evidence that these processes can also be observed in urethane-anesthetized rats and are enhanced by desynchronized brain state evoked by tail pinch, subcortical carbachol infusion, or systemic amphetamine administration. During desynchronization, we found that repeated tactile or auditory stimulation evoked unique sequential patterns of neural firing in somatosensory and auditory cortex and that these patterns then reoccurred during subsequent spontaneous activity, similar to what we have observed in awake animals. Furthermore, the formation of these patterns was blocked by an NMDA receptor antagonist, suggesting that the phenomenon depends on synaptic plasticity. These results suggest that anesthetized animals with a desynchronized brain state could serve as a convenient model for studying stimulus-induced plasticity to improve our understanding of memory formation and replay in the brain.

Gating of sensory input by spontaneous cortical activity.

The activity of neural populations is determined not only by sensory inputs but also by internally generated patterns. During quiet wakefulness, the brain produces spontaneous firing events that can spread over large areas of cortex and have been suggested to underlie processes such as memory recall and consolidation. Here we demonstrate a different role for spontaneous activity in sensory cortex: gating of sensory inputs. We show that population activity in rat auditory cortex is composed of transient 50-100 ms packets of spiking activity that occur irregularly during silence and sustained tone stimuli, but reliably at tone onset. Population activity within these packets had broadly consistent spatiotemporal structure, but the rate and also precise relative timing of action potentials varied between stimuli. Packet frequency varied with cortical state, with desynchronized state activity consistent with superposition of multiple overlapping packets. We suggest that such packets reflect the sporadic opening of a "gate" that allows auditory cortex to broadcast a representation of external sounds to other brain regions.

Consistent sequential activity across diverse forms of UP states under ketamine anesthesia.

During slow-wave sleep, the neocortex shows complex, self-organized spontaneous activity. Similar slow-wave oscillations are present under anesthesia where massive, persistent network activity (UP states) alternates with periods of generalized neural silence (DOWN states). To investigate the neuronal activity patterns occurring during UP states, we recorded simultaneously from populations of cells in neocortical layer V of ketamine/xylazine-anesthetized rats. UP states formed a diverse class. In particular, simultaneous-onset UP states were typically accompanied by sharp field potentials and 10-14 Hz modulation, and were often grouped in a 3 Hz ('delta') pattern. Longer, slow-onset UP states did not exhibit 10-14 Hz modulation, and showed a slow propagation across recording electrodes ('traveling waves'). Despite this diversity, the temporal patterns of spiking activity were similar across different UP state types. Analysis of cross-correlograms revealed conserved temporal relationships among neurons, with each neuron having specific timing during UP states. As a group, putative interneurons were most active at the beginning of UP states and putative pyramidal cells were active uniformly throughout the duration of UP states. These results show that UP states under ketamine anesthesia have a stable, fine-structured firing pattern despite a large variability in global structure.

How do neurons work together? Lessons from auditory cortex.

Recordings of single neurons have yielded great insights into the way acoustic stimuli are represented in auditory cortex. However, any one neuron functions as part of a population whose combined activity underlies cortical information processing. Here we review some results obtained by recording simultaneously from auditory cortical populations and individual morphologically identified neurons, in urethane-anesthetized and unanesthetized passively listening rats. Auditory cortical populations produced structured activity patterns both in response to acoustic stimuli, and spontaneously without sensory input. Population spike time patterns were broadly conserved across multiple sensory stimuli and spontaneous events, exhibiting a generally conserved sequential organization lasting approximately 100 ms. Both spontaneous and evoked events exhibited sparse, spatially localized activity in layer 2/3 pyramidal cells, and densely distributed activity in larger layer 5 pyramidal cells and putative interneurons. Laminar propagation differed however, with spontaneous activity spreading upward from deep layers and slowly across columns, but sensory responses initiating in presumptive thalamorecipient layers, spreading rapidly across columns. In both unanesthetized and urethanized rats, global activity fluctuated between "desynchronized" state characterized by low amplitude, high-frequency local field potentials and a "synchronized" state of larger, lower-frequency waves. Computational studies suggested that responses could be predicted by a simple dynamical system model fitted to the spontaneous activity immediately preceding stimulus presentation. Fitting this model to the data yielded a nonlinear self-exciting system model in synchronized states and an approximately linear system in desynchronized states. We comment on the significance of these results for auditory cortical processing of acoustic and non-acoustic information.

The asynchronous state in cortical circuits.

Correlated spiking is often observed in cortical circuits, but its functional role is controversial. It is believed that correlations are a consequence of shared inputs between nearby neurons and could severely constrain information decoding. Here we show theoretically that recurrent neural networks can generate an asynchronous state characterized by arbitrarily low mean spiking correlations despite substantial amounts of shared input. In this state, spontaneous fluctuations in the activity of excitatory and inhibitory populations accurately track each other, generating negative correlations in synaptic currents which cancel the effect of shared input. Near-zero mean correlations were seen experimentally in recordings from rodent neocortex in vivo. Our results suggest a reexamination of the sources underlying observed correlations and their functional consequences for information processing.